U.S. patent application number 17/545210 was filed with the patent office on 2022-03-31 for multi-stage object detection and categorization of antenna mount locations.
This patent application is currently assigned to AT&T Intellectual Property I, L.P.. The applicant listed for this patent is AT&T Intellectual Property I, L.P.. Invention is credited to Arun Jotshi, Suchitra Krishnaswamy, Shang Li, Kathleen Meier-Hellstern, Amit Rathod, Manish Shah, Martin Suchara, Gaurav Thakur.
Application Number | 20220104029 17/545210 |
Document ID | / |
Family ID | 1000006013490 |
Filed Date | 2022-03-31 |
United States Patent
Application |
20220104029 |
Kind Code |
A1 |
Jotshi; Arun ; et
al. |
March 31, 2022 |
MULTI-STAGE OBJECT DETECTION AND CATEGORIZATION OF ANTENNA MOUNT
LOCATIONS
Abstract
Aspects of the disclosure include determining that a first
instance of a first object is present in a first image in
accordance with an execution of a first image processing algorithm,
generating a first bounding region that at least partially
surrounds the first instance of the first object in the first
image, determining that the first instance of the first object in
the first image has a first attribute in accordance with an
execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object and/or a second instance of the
first object to receive a deployment of a network resource in
accordance with the determining that the first instance of the
first object in the first image has the first attribute. Other
aspects are disclosed.
Inventors: |
Jotshi; Arun; (Parsippany,
NJ) ; Rathod; Amit; (Hillsborough, NJ) ;
Thakur; Gaurav; (Matawan, NJ) ; Krishnaswamy;
Suchitra; (San Ramon, CA) ; Li; Shang;
(Aberdeen, NJ) ; Meier-Hellstern; Kathleen;
(Cranbury, NJ) ; Shah; Manish; (Hillsborough,
NJ) ; Suchara; Martin; (Woodridge, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AT&T Intellectual Property I, L.P. |
Atlanta |
GA |
US |
|
|
Assignee: |
AT&T Intellectual Property I,
L.P.
Atlanta
GA
|
Family ID: |
1000006013490 |
Appl. No.: |
17/545210 |
Filed: |
December 8, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16893479 |
Jun 5, 2020 |
11228920 |
|
|
17545210 |
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|
16427760 |
May 31, 2019 |
10728769 |
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16893479 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 16/18 20130101;
G06K 9/6215 20130101; H04B 17/27 20150115; G06V 10/44 20220101 |
International
Class: |
H04W 16/18 20060101
H04W016/18; G06K 9/62 20060101 G06K009/62; G06K 9/46 20060101
G06K009/46; H04B 17/27 20060101 H04B017/27 |
Claims
1. A device, comprising: a processing system including a processor;
and a memory that stores executable instructions that, when
executed by the processing system, facilitate performance of
operations, the operations comprising: identifying a first object
of a plurality of objects as being present in an image in
accordance with a comparison of a first plurality of
characteristics identified in the image to a second plurality of
characteristics associated with the plurality of objects;
identifying a third plurality of characteristics in the image based
on a processing of the image in accordance with a first bounding
region that at least partially surrounds the first object in the
image; identifying a first attribute of a plurality of attributes
as being present in the first object in accordance with a
comparison of the third plurality of characteristics to the
plurality of attributes; and generating an instruction for placing
a resource on or about the first object in accordance with the
identifying of the first object and the identifying of the first
attribute.
2. The device of claim 1, wherein the resource comprises a
transmitter, a receiver, and an antenna.
3. The device of claim 1, wherein the image is sourced from a first
image captured by a fixed-wing aircraft and a second image captured
by a satellite.
4. The device of claim 3, wherein the image comprises a composite
of the first image and the second image.
5. The device of claim 1, wherein the plurality of objects
comprises a streetlight, a utility pole, an ornate pole, a tower,
and a structure of a building.
6. The device of claim 1, wherein the plurality of attributes
comprises a dimension, a material, a utility equipment, a road
sign, a traffic signal, and an attachment mechanism.
7. The device of claim 1, wherein the comparison of the first
plurality of characteristics to the second plurality of
characteristics generates a first score, and wherein the operations
further comprise: responsive to a determination that a first match
exists in accordance with a comparison of the first score to a
first threshold, identifying a second object as being present in
the image.
8. The device of claim 1, wherein the operations further comprise:
scheduling a maintenance activity with respect to at least one of
the first object, a second object, the resource, or a combination
thereof, in accordance with the first attribute, wherein the
scheduling comprises an identification of personnel to perform the
maintenance activity and equipment needed to perform the
maintenance activity.
9. The device of claim 1, wherein the operations further comprise:
selecting an operating parameter for the resource in accordance
with the first attribute.
10. The device of claim 9, wherein the operating parameter
comprises a transmission power level, a frequency band, a
modulation scheme, a demodulation scheme, an encoding scheme, a
decoding scheme, an encryption scheme, a decryption scheme, or a
combination thereof.
11. The device of claim 1, wherein the instruction comprises
driving directions to a geographic location where the first object
is located, an identification of the resource by a part number, or
a video tutorial that includes an indication of where the resource
is to be mounted about the first object.
12. The device of claim 1, wherein the generating the instruction
is further in accordance with a specification of a restriction
imposed by a jurisdiction, a governmental entity, or a private
party with respect to a placement of the resource on or about the
first object.
13. A non-transitory machine-readable medium, comprising executable
instructions that, when executed by a processing system including a
processor, facilitate performance of operations, the operations
comprising: identifying a first object, a second object, or a
combination thereof, as being present in a first plurality of
images in accordance with a comparison of a first plurality of
characteristics identified in the first plurality of images to a
second plurality of characteristics associated with a plurality of
objects, resulting in at least one identified object; identifying a
third plurality of characteristics in the first plurality of images
based on a processing of the first plurality of images in
accordance with a bounding region that at least partially surrounds
the at least one identified object; identifying a first attribute
of a plurality of attributes as being present in the at least one
identified object in accordance with a comparison of the third
plurality of characteristics to the plurality of attributes; and
generating a direction for deployment of at least a first resource
for the at least one identified object in accordance with the
identifying of the at least one identified object and the
identifying of the first attribute.
14. The non-transitory machine-readable medium of claim 13, wherein
the first attribute comprises a geographic location of the at least
one identified object.
15. The non-transitory machine-readable medium of claim 13, wherein
the at least one identified object comprises a streetlight, a
utility pole, an ornate pole, a tower, a structure of a building,
or any combination thereof.
16. The non-transitory machine-readable medium of claim 15, wherein
the operations further comprise: modifying a model of a
communication system subsequent to the deployment of the at least a
first resource for the at least one identified object to generate a
modified model, wherein the modified model is based on an operating
parameter of the at least a first resource.
17. The non-transitory machine-readable medium of claim 13, wherein
the generating the direction is further in accordance with a
specification of a restriction imposed by a jurisdiction, a
governmental entity, a private party, or any combination thereof
with respect to a placement of the at least a first resource for
the at least one identified object.
18. A method, comprising: determining, by a processing system
including a processor, that a first instance of a first object
present in a first image has a first attribute, in accordance with
a first execution of an image processing algorithm for the first
image; determining, by the processing system, that a second
instance of the first object is present in the first image, a
second image, or a combination thereof, wherein the second instance
of the first object is different from the first instance of the
first object; responsive to the determining that the second
instance of the first object is present in the first image, the
second image, or the combination thereof, generating, by the
processing system, a bounding region that at least partially
surrounds the second instance of the first object in the first
image, the second image, or the combination thereof; responsive to
the generating of the bounding region, determining, by the
processing system, that the second instance of the first object has
a second attribute that is different from the first attribute, in
accordance with a second execution of the image processing
algorithm for the first image, the second image, or the combination
thereof; and generating, by the processing system, an instruction
for positioning a resource in accordance with the determining that
the first instance of the first object in the first image has the
first attribute and in accordance with the determining that the
second instance of the first object has the second attribute.
19. The method of claim 18, wherein the generating the instruction
is further in accordance with a specification of a restriction
imposed by a jurisdiction, a governmental entity, a private party,
or any combination thereof with respect to a placement of the
resource.
20. The method of claim 18, further comprising: appending, by the
processing system, the first attribute to a profile for the first
instance of the first object responsive to the determining that the
first instance of the first object in the first image has the first
attribute.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 16/893,479, filed on Jun. 5, 2020, which is a
continuation of U.S. patent application Ser. No. 16/427,760 filed
on May 31, 2019 (now U.S. Pat. No. 10,728,769). The contents of
each of the foregoing are hereby incorporated by reference into
this application as if set forth herein in full.
FIELD OF THE DISCLOSURE
[0002] The subject disclosure relates to a multi-stage object
detection and categorization of antenna mount locations.
BACKGROUND
[0003] As the world continues to become increasingly connected over
vast/various communication networks, network/service
operators/providers are continuously confronted with the challenge
of providing efficient, high-quality service to users/devices. For
example, as a network/service operator seeks to implement
additional resources to support an existing network, or is
providing resources in the first instance (such as during an
initial deployment of a given, new network), technicians/site
surveyors are dispatched to identify candidate locations/objects
(e.g., utility poles) that will best serve as a host site of the
resources. Reports/Data prepared/gathered by the technicians are
subsequently reviewed/analyzed by, e.g., engineers to ultimately
select a location/object from the candidate locations/objects.
Thus, the identification/selection of a location/object is time and
labor intensive and is susceptible to error (e.g., is susceptible
to misinterpretation or miscommunication between technicians and
engineers), potentially resulting in costly rework and increased
product/service development cycle times. Still further, the
reports/data may potentially miss/overlook/ignore information, such
that a selected candidate location might not be the optimum
location. As a result, the service that is obtained/provided by the
resources when deployed/implemented may be sub-optimal in some
instances.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] Reference will now be made to the accompanying drawings,
which are not necessarily drawn to scale, and wherein:
[0005] FIG. 1 is a block diagram illustrating an exemplary,
non-limiting embodiment of a communications network in accordance
with various aspects described herein.
[0006] FIG. 2A is a block diagram illustrating an example,
non-limiting embodiment of a system functioning within the
communication network of FIG. 1 in accordance with various aspects
described herein.
[0007] FIG. 2B depicts an illustrative embodiment of a method in
accordance with various aspects described herein.
[0008] FIG. 2C depicts an example of an image that is processed to
identify objects and attributes of the objects in accordance with
various aspects described herein.
[0009] FIG. 2D depicts an illustrative embodiment of a method in
accordance with various aspects described herein.
[0010] FIG. 2E depicts a deployment of a resource about an object
in accordance with various aspects described herein.
[0011] FIG. 3 is a block diagram illustrating an example,
non-limiting embodiment of a virtualized communication network in
accordance with various aspects described herein.
[0012] FIG. 4 is a block diagram of an example, non-limiting
embodiment of a computing environment in accordance with various
aspects described herein.
[0013] FIG. 5 is a block diagram of an example, non-limiting
embodiment of a mobile network platform in accordance with various
aspects described herein.
[0014] FIG. 6 is a block diagram of an example, non-limiting
embodiment of a communication device in accordance with various
aspects described herein.
DETAILED DESCRIPTION
[0015] The subject disclosure describes, among other things,
illustrative embodiments for selecting an object for receiving a
deployment of a resource in accordance with a processing of one or
more images. Other embodiments are described in the subject
disclosure.
[0016] One or more aspects of the subject disclosure include
obtaining an image that is sourced from a vehicle, identifying a
first plurality of characteristics in the image, comparing the
first plurality of characteristics to a second plurality of
characteristics associated with a plurality of objects to generate
a first score, determining that a first match exists based on a
comparison of the first score to a first threshold, responsive to
the determining that the first match exists, identifying a first
object of the plurality of objects as being present in the image,
identifying a third plurality of characteristics in the image based
on a processing of the image in accordance with a first bounding
region that surrounds the first object in the image, comparing the
third plurality of characteristics to a plurality of attributes to
generate a second score, determining that a second match exists
based on a comparison of the second score to a second threshold,
responsive to the determining that the second match exists,
identifying a first attribute of the plurality of attributes as
being present in the first object, and selecting the first object
or a second object of the plurality of objects to receive a
deployment of a communication network resource in accordance with
the identifying of the first object and the identifying of the
first attribute.
[0017] One or more aspects of the subject disclosure include
obtaining a first plurality of images, identifying a first
plurality of characteristics in the first plurality of images,
determining that a first match exists based on a comparison of the
first plurality of characteristics to a second plurality of
characteristics associated with a plurality of objects, responsive
to the determining that the first match exists, identifying a first
object, a second object, or a combination thereof, as being present
in the first plurality of images, resulting in at least one
identified object, identifying a third plurality of characteristics
in the first plurality of images based on a processing of the first
plurality of images in accordance with a bounding region that at
least partially surrounds the at least one identified object,
determining that a second match exists based on a comparison of the
third plurality of characteristics to a plurality of attributes,
responsive to the determining that the second match exists,
identifying a first attribute of the plurality of attributes as
being present in the at least one identified object, and selecting
the at least one identified object to receive a deployment of a
first resource in accordance with the identifying of the at least
one identified object and the identifying of the first
attribute.
[0018] One or more aspects of the subject disclosure include
determining that a first instance of a first object is present in a
first image in accordance with an execution of a first image
processing algorithm, responsive to the determining that the first
instance of the first object is present in the first image,
generating a first bounding region that at least partially
surrounds the first instance of the first object in the first
image, determining that the first instance of the first object in
the first image has a first attribute in accordance with an
execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object, a second instance of the first
object, or a combination thereof, to receive a deployment of a
network resource in accordance with the determining that the first
instance of the first object in the first image has the first
attribute.
[0019] Referring now to FIG. 1, a block diagram is shown
illustrating an example, non-limiting embodiment of a
communications network 100 in accordance with various aspects
described herein. For example, communications network 100 can
facilitate in whole or in part obtaining an image that is sourced
from a vehicle, identifying a first plurality of characteristics in
the image, comparing the first plurality of characteristics to a
second plurality of characteristics associated with a plurality of
objects to generate a first score, determining that a first match
exists based on a comparison of the first score to a first
threshold, responsive to the determining that the first match
exists, identifying a first object of the plurality of objects as
being present in the image, identifying a third plurality of
characteristics in the image based on a processing of the image in
accordance with a first bounding region that surrounds the first
object in the image, comparing the third plurality of
characteristics to a plurality of attributes to generate a second
score, determining that a second match exists based on a comparison
of the second score to a second threshold, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the
first object, and selecting the first object or a second object of
the plurality of objects to receive a deployment of a communication
network resource in accordance with the identifying of the first
object and the identifying of the first attribute. Communications
network 100 can facilitate in whole or in part obtaining a first
plurality of images, identifying a first plurality of
characteristics in the first plurality of images, determining that
a first match exists based on a comparison of the first plurality
of characteristics to a second plurality of characteristics
associated with a plurality of objects, responsive to the
determining that the first match exists, identifying a first
object, a second object, or a combination thereof, as being present
in the first plurality of images, resulting in at least one
identified object, identifying a third plurality of characteristics
in the first plurality of images based on a processing of the first
plurality of images in accordance with a bounding region that at
least partially surrounds the at least one identified object,
determining that a second match exists based on a comparison of the
third plurality of characteristics to a plurality of attributes,
responsive to the determining that the second match exists,
identifying a first attribute of the plurality of attributes as
being present in the at least one identified object, and selecting
the at least one identified object to receive a deployment of a
first resource in accordance with the identifying of the at least
one identified object and the identifying of the first attribute.
Communications network 100 can facilitate in whole or in part
determining that a first instance of a first object is present in a
first image in accordance with an execution of a first image
processing algorithm, responsive to the determining that the first
instance of the first object is present in the first image,
generating a first bounding region that at least partially
surrounds the first instance of the first object in the first
image, determining that the first instance of the first object in
the first image has a first attribute in accordance with an
execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object, a second instance of the first
object, or a combination thereof, to receive a deployment of a
network resource in accordance with the determining that the first
instance of the first object in the first image has the first
attribute.
[0020] In particular, in FIG. 1 a communications network 125 is
presented for providing broadband access 110 to a plurality of data
terminals 114 via access terminal 112, wireless access 120 to a
plurality of mobile devices 124 and vehicle 126 via base station or
access point 122, voice access 130 to a plurality of telephony
devices 134, via switching device 132 and/or media access 140 to a
plurality of audio/video display devices 144 via media terminal
142. In addition, communication network 125 is coupled to one or
more content sources 175 of audio, video, graphics, text and/or
other media. While broadband access 110, wireless access 120, voice
access 130 and media access 140 are shown separately, one or more
of these forms of access can be combined to provide multiple access
services to a single client device (e.g., mobile devices 124 can
receive media content via media terminal 142, data terminal 114 can
be provided voice access via switching device 132, and so on).
[0021] The communications network 125 includes a plurality of
network elements (NE) 150, 152, 154, 156, etc. for facilitating the
broadband access 110, wireless access 120, voice access 130, media
access 140 and/or the distribution of content from content sources
175. The communications network 125 can include a circuit switched
or packet switched network, a voice over Internet protocol (VoIP)
network, Internet protocol (IP) network, a cable network, a passive
or active optical network, a 4G, 5G, or higher generation wireless
access network, WIMAX network, UltraWideband network, personal area
network or other wireless access network, a broadcast satellite
network and/or other communications network.
[0022] In various embodiments, the access terminal 112 can include
a digital subscriber line access multiplexer (DSLAM), cable modem
termination system (CMTS), optical line terminal (OLT) and/or other
access terminal. The data terminals 114 can include personal
computers, laptop computers, netbook computers, tablets or other
computing devices along with digital subscriber line (DSL) modems,
data over coax service interface specification (DOCSIS) modems or
other cable modems, a wireless modem such as a 4G, 5G, or higher
generation modem, an optical modem and/or other access devices.
[0023] In various embodiments, the base station or access point 122
can include a 4G, 5G, or higher generation base station, an access
point that operates via an 802.11 standard such as 802.11n,
802.11ac or other wireless access terminal. The mobile devices 124
can include mobile phones, e-readers, tablets, phablets, wireless
modems, and/or other mobile computing devices.
[0024] In various embodiments, the switching device 132 can include
a private branch exchange or central office switch, a media
services gateway, VoIP gateway or other gateway device and/or other
switching device. The telephony devices 134 can include traditional
telephones (with or without a terminal adapter), VoIP telephones
and/or other telephony devices.
[0025] In various embodiments, the media terminal 142 can include a
cable head-end or other TV head-end, a satellite receiver, gateway
or other media terminal 142. The display devices 144 can include
televisions with or without a set top box, personal computers
and/or other display devices.
[0026] In various embodiments, the content sources 175 include
broadcast television and radio sources, video on demand platforms
and streaming video and audio services platforms, one or more
content data networks, data servers, web servers and other content
servers, and/or other sources of media.
[0027] In various embodiments, the communications network 125 can
include wired, optical and/or wireless links and the network
elements 150, 152, 154, 156, etc. can include service switching
points, signal transfer points, service control points, network
gateways, media distribution hubs, servers, firewalls, routers,
edge devices, switches and other network nodes for routing and
controlling communications traffic over wired, optical and wireless
links as part of the Internet and other public networks as well as
one or more private networks, for managing subscriber access, for
billing and network management and for supporting other network
functions.
[0028] FIG. 2A is a block diagram illustrating an example,
non-limiting embodiment of a system 200a functioning within, or
operatively overlaid upon, the communication network 100 of FIG. 1
in accordance with various aspects described herein. In some
embodiments, aspects of the system 200a may be at least partially
implemented in hardware, software, firmware, or any combination
thereof. As described in further detail below, the system 200a may
be implemented/utilized to identify mount locations for
receiving/deploying/placing one or more resources, such as for
example communication network resources.
[0029] The system 200a may incorporate various types/kinds of image
capture equipment, illustratively depicted as a camera 204a in FIG.
2A. For example, the image capture equipment 204a may include a
vehicle, such as an aircraft (e.g., fixed-wing aircraft, rotary
aircraft, etc.), a spacecraft (e.g., satellites), a motor vehicle
(e.g., a car, a truck, a bus, an all-terrain vehicle etc.), a
train/railcar/locomotive, a marine craft (e.g., a boat, a ship, a
ferry, a yacht, etc.), a bicycle, etc. In some embodiments, the
image capture equipment 204a may include user equipment (UE)/client
devices, such as for example handheld cameras, mobile devices
(e.g., smartphones), etc.
[0030] As depicted via reference character/block 254a, one or more
images may be obtained from the image capture equipment 204a. For
example, as part of block 254a, the images may be obtained directly
from the image capture equipment 204a and/or may be obtained
indirectly from the image capture equipment 204a via one or more
third-party sites/service/devices. In the context of the vehicular
image capture equipment described above, the images may be captured
when the vehicle is at rest/on the ground and/or when the vehicle
is in operation/deployed (e.g., in motion). The images may be
captured/oriented at various angles or perspectives, such as for
example an overhead perspective, a street-side or street-view
perspective, etc.
[0031] Once the images are obtained (block 254a), the images may be
processed to identify one or more potential/candidate
locations/objects for receiving/deploying/placing/mounting one or
more resources as represented by block 258a. For example, the
processing of the images may be performed in accordance with one or
more algorithms. The algorithms may include one or more image
processing algorithms. The algorithms may incorporate aspects of
machine learning (ML), artificial intelligence (AI), and/or deep
learning (DL). To facilitate an execution of the algorithms, data
may be sourced/obtained from a data storage 208a (e.g., a
computer-readable medium, a memory, a database, etc.).
[0032] The data included in the data storage 208a may correspond to
a profile or specification of known objects that may be used for
mounting resources, such as for example streetlights,
utility/telephone poles, ornate/decorative/historical poles, towers
(e.g., communication towers), structures of buildings (e.g.,
trusses, pilings, etc.), etc. In this respect, the processing
performed as part of block 258a (which may incorporate aspects of
the method 258b of FIG. 2B) may include identifying
characteristics/parameters of/in the images of block 254a (see FIG.
2B: block 258b-1), and then comparing the identified
characteristics/parameters with characteristic/parameters of the
objects represented by the data of the data storage 208a (see FIG.
2B: block 258b-5).
[0033] In some embodiments, as part of block 258a of FIG. 2A (see
FIG. 2B: block 258b-5), one or more scores may be generated. The
scores may be representative of the degree/extent to which an
object included in the images of block 254a match the
profile/specification of the objects represented in the data of the
data storage 208a in accordance with the comparison. As an
illustrative example, on a scale of 0.00 to 1.00 a score of 1.00
may represent an exact match, whereas a score of 0.00 may represent
a complete lack of a match. Other scoring scales/rankings may be
used in some embodiments. A threshold may be generated/established
as part of identifying whether a match exists (e.g., the "yes" path
out of block 258b-7 of FIG. 2B). To continue the above example
incorporating scoring on a scale from 0.00 to 1.00, and assuming
that a threshold of 0.90 is used, scores (equal to or) above 0.90
may be declared a match, whereas scores (equal to or) less than
0.90 may be declared as not being a match (e.g., may be declared as
a lack of a match).
[0034] If the comparison yields an exact match or a similar match
(e.g., a match in an amount that is greater than a threshold) (see
FIG. 2B: block 258b-7), then the characteristics of the images may
be identified/declared as the object represented by the data of the
data storage 208a (see FIG. 2B: block 258b-9). On the other hand,
if there is no such match based on the comparison, the
characteristics of the images may be ignored and/or subjected to
additional processing as needed/desired (see FIG. 2B: block
258b-11).
[0035] As part of block 258b-9 of FIG. 2B, one or more profiles may
be established/generated for the identified/declared objects. Such
profiles may be stored in/by, e.g., the data storage 208a of FIG.
2A.
[0036] In some embodiments, the processing performed as part of
block 258a may be based on (e.g., may be supplemented via)
geo-tagged coordinates (e.g., latitude and longitude). For example,
metadata appended to the images of block 254a may include an
identification of a geographical location of the subject matter of
the images. In this respect, the data of the data storage 208a may
identify objects on the basis of geographical data. Thus, in some
embodiments the comparison described above in conjunction with,
e.g., block 258b-5 of FIG. 2B may be based on location/coordinate
data/characteristics. For example, the comparison may entail
looking up an identification of an object in a look-up table stored
by the data storage 208a, where the location/coordinate data
specified by the metadata of the images may serve as an index into
the look-up table.
[0037] Referring now to FIG. 2C, an example of an image 254c (which
may be included as part of the images of block 254a of FIG. 2A) is
shown. The processing of the image 254c in accordance with the
description set forth above (e.g., in accordance with block 258a of
FIGS. 2A-2B) may serve to identify two potential/candidate objects
for mounting a resource--namely, a first object 204c-1 (e.g., a
first pole) and a second object 204c-2 (e.g., a second pole). As
shown in FIG. 2C (see also FIG. 2B: block 258b-13), the first
object 204c-1 and the second object 204c-2 may be
included/contained within a first bounding region 208c-1 and a
second bounding region 208c-2, respectively.
[0038] While the bounding regions 208c-1 and 208c-2 are shown in
FIG. 2C as being (substantially) box-like or rectangular in shape,
other shapes (e.g., regular shapes and/or irregular shapes) may be
used in some embodiments. Use of regular shapes may simplify
subsequent processing discussed below, at the potential expense of
including extraneous/unnecessary detail. Accordingly, one skilled
in the art will appreciate that trade-offs may be made in
accordance with one or more application requirements.
[0039] In some embodiments, the scores of, e.g., block 258b-5 of
FIG. 2B may influence a shape and/or size of the bounding regions
208c-1 and 208c-2. For example, if the score is indicative of a
close/strong match, the bounding region may be made smaller and
conform more closely to the profile of the respective object than
if the score is indicative of a far/weak match.
[0040] The bounding regions 208c-1 and 208c-2 may be
identified/generated as a result of the processing of block 258a of
FIG. 2A. For reasons that will become clearer in the description
below, the identification/recognition of the objects 204c-1 and
204c-2 and/or the identification/generation of the bounding regions
208c-1 and 208c-2 may serve as a first-stage of a filter with
respect to the image 254c.
[0041] Having identified the candidate objects (e.g., objects
204c-1 and 204c-2 of FIG. 2C) (and respective bounding regions
[e.g., bounding regions 208c-1 and 208c-2 of FIG. 2C]) for
receiving/mounting a resource in conjunction with the processing of
block 258a described above, additional processing may be performed
with respect to such candidate objects/bounding regions as
represented by block 262a of FIG. 2A. As the nomenclature implies,
the processing of block 262a may be bounded by/limited to the
bounding regions, which is to say that the processing of block 262a
may effectively ignore/discard of image data that is outside
of/external to the bounding regions. Ignoring/discarding of such
data may help to eliminate noise that may be present in an image
(e.g., the image 254c of FIG. 2C). Referring to FIG. 2A and FIG.
2C, and in view of the disclosure above, the processing performed
in block 262a may represent a second-stage of the filter with
respect to the image 254c.
[0042] The processing of block 262a may be performed in accordance
with one or more algorithms, such as for example one or more image
processing algorithms. The processing/algorithms of block 262a may
incorporate aspects of ML, AI, and/or DL. The processing of block
262a may serve to identify attributes of the candidate objects, in
accordance with data contained within/stored by a data storage
212a. The data storage 212a may correspond to the data storage
208a, which is to say that a common housing/storage device may be
used in some embodiments.
[0043] Referring to FIG. 2A and FIG. 2D, the processing performed
as part of block 262a may incorporate aspects of the method 262d.
In block 262d-1, characteristics in/of/associated with an object in
an image may be identified. To demonstrate, and taking the object
204c-1 of FIG. 2C as an example, a dimension (e.g., a height, a
diameter, a circumference, etc.) of the object 204c-1 may be
identified. If the image 254c contains/exhibits a sharp contrast
(e.g., a large gradient) proximate to the object 204c-1 (e.g.,
within a threshold distance of the object 204c-1), such a condition
may be noted as part of block 262d-1; this condition may be
indicative of a large amount of light (e.g., sunlight) reflecting
off of the object 204c-1, such that it may be inferred that the
object 204c-1 is made of metal. Conversely, the lack of such a
sharp contrast/gradient proximate the object 204c-1 in the image
254c may be indicative of the object 204c-1 absorbing a large
portion of the light--e.g., not being made of metal (e.g., being
made of wood). Still further, a sharp gradient (or lack thereof)
may be indicative of equipment (e.g., utility equipment), signage
(e.g., road/highway signs), traffic signals (e.g., traffic lights,
cross-walk signals), etc., such as for example an attachment
mechanism 212c-1 of FIG. 2C, that may be present on the object
204c-1. Whether a particular gradient is sharp or not may be based
on a comparison with one or more thresholds.
[0044] In block 262d-5, the characteristics identified in block
262d-1 may be compared with known attributes (as represented by the
data in the data storage 212a). To continue the above example, the
height of the object 204c-1 identified as part of block 262d-1 may
indicate that the object 204c-1 is likely a pole. The
characteristics of the image described above in terms of, e.g.,
sharpness of gradient may be compared with known characteristics in
relation to the same to identify, e.g., one or more dimensions,
materials, equipment, signage, traffic signals, etc., with a given
likelihood/probability. One or more scores may be generated as part
of block 262d-5 to indicate the extent/degree to which the
comparison yields a match (e.g., an exact match, a substantial
match, a lack of a match, etc.).
[0045] As described above, the comparison of block 262d-5 may yield
a determination of whether a match exists (e.g., an exact match or
a match in an amount greater than a threshold) in block 262d-7. If
so (e.g., the "yes" path is taken from block 262d-7), flow may
proceed to block 262d-9; otherwise (e.g., the "no" path is taken
from block 262d-7), flow may proceed to block 262d-11. In block
262d-11, the characteristics of the objects may be ignored and/or
subjected to additional processing as needed/desired.
[0046] In block 262d-9, the attributes represented in the data of
the data storage 212a may be identified/declared as corresponding
to the characteristics identified in block 262d-1. As part of block
262d-9, the attributes may be appended to a profile for the object
204c-1 (where the profile for the object 204c-1 may be stored as
data in, e.g., the data storage 208a as set forth above).
[0047] While the processing of block 262a (e.g., the execution of
the method 262d) was described above in relation to the object
204c-1 (or, analogously, the bounding region 208c-1), the
processing/execution may be applied in respect of the object 204c-2
(or, analogously, the bounding region 208c-2). For example, the
processing/execution as applied to the object 204c-2 may serve to
identify the attachment mechanism 212c-2 and a power-head
216c-2.
[0048] The power-head 216c-2 may correspond to a section of the
object 204c-2 that may be reserved for power/electrical equipment
(e.g., a transformer) as provided by a power/electrical generating
operator/service provider. In this respect, a resource that may be
deployed/mounted to the object 204c-2 may be required to maintain a
sufficient (e.g., minimum) clearance relative to the power-head
216c-2. In some instances, the inclusion of the power-head 216c-2
may even eliminate the object 204c-2 from serving as a candidate
for receiving the resource.
[0049] Having identified the candidate objects in conjunction with
block 258a, and having identified attributes associated with the
candidate objects in conjunction with block 262a, additional
processing may be performed as represented by block 266a. The
processing of block 266a may be performed in accordance with one or
more algorithms. The processing/algorithms of block 266a may
incorporate aspects of ML, AI, and/or DL. The processing of block
266a may serve to select one or more mounting/mount objects to
receive the resource(s), in accordance with data contained
within/stored by a data storage 216a. The data storage 216a may
correspond to the data storage 208a and/or the data storage 212a,
which is to say that a common housing/storage device may be used in
some embodiments.
[0050] The data of the data storage 216a may include/identify
restrictions/limitations in respect of one or more of the candidate
objects and/or one or more of the attributes associated therewith.
For example, and as described above, the power-head 216c-2
associated with the object 204c-2 may represent a restriction in
terms of where on the object 204c-2 the resource may be located (if
at all). Similarly, the data of the data storage 216a may
include/identify preferences in respect of one or more of the
candidate objects and/or one or more of the attributes associated
therewith. Such preferences may be specified in accordance with one
or more terms/conditions. For example, a preference may be
established on the basis of a technical specification/value (e.g.,
maintaining/reducing signal interference in a communication system
in/to an amount less than a threshold), a business goal/objective
(e.g., generate at least `X` amount of revenue/profit per quarter),
etc. The restrictions/limitations and/or preferences may be
established by one or more entities, such as for example a given
jurisdiction, a governmental entity (e.g., a local or regional
board of officials), a private party, etc.
[0051] Once the object(s) for receiving the resource(s) are
selected from the pool of candidate objects, the processing of
block 266a may cause the resource(s) to be deployed on/about the
selected objects. For example, as part of block 266a, directions
may be generated and presented in conjunction with a presentation
device (e.g., a display device, a speaker, a print-out, etc.). The
directions may advise a technician/operator of a geographical
location where the selected object(s) is/are located relative to a
current location of the technician/operator (e.g., driving
directions to a site of the selected object(s) may be provided).
The directions may identify a resource (e.g., resource 200e of FIG.
2E) by a part number. The directions may provide an indication
(e.g., a visual indication) of where the resource is to be placed
on/about the selected object(s), potentially in accordance with the
attributes identified as part of block 262a. In some embodiments,
the directions may include a video tutorial.
[0052] The deployment of the resource(s) about the object(s) in
conjunction with block 266a may result in attributes of the
resource(s) being appended to one or more profiles for the
object(s).
[0053] Referring to FIG. 2E, a network resource 200e is shown as
being placed on/about an object 204e (where the object 204e may
correspond to one of the objects 204c-1 through 204c-2 of FIG. 2C).
In an illustrative embodiment, the object 204e may correspond to a
utility pole coupled to a second utility pole 214e via a
transmission medium 224e. In the example of FIG. 2E, the resource
200e may include an antenna 200e-1, a transmitter (TX) 200e-2,
and/or a receiver 200e-3. Other types of resources may be deployed
as part of, e.g., block 266a of FIG. 2A in some embodiments.
[0054] While for purposes of simplicity of explanation, the
respective methodological operations/processes are shown and
described as a series of blocks in FIGS. 2A, 2B, and 2D, it is to
be understood and appreciated that the claimed subject matter is
not limited by the order of the blocks, as some blocks may occur in
different orders and/or concurrently with other blocks from what is
depicted and described herein. Moreover, not all illustrated blocks
may be required to implement the methods described herein.
[0055] In some embodiments, aspects of the methods described herein
may be executed iteratively/repeatedly. To demonstrate, while
aspects of an implementation of the system 200a (e.g., the
processing associated with the blocks 258a and 262a) were described
above as implementing a two-stage filter, in some embodiments
additional stages may be included/incorporated. For example, if
based on an initial analysis it is unclear whether a given
(candidate) object of a particular type/kind is included in an
image (see FIG. 2A: block 258a; see also FIG. 2B: blocks 258b-7 and
blocks 258b-11), additional images may be requested/obtained in an
effort to clarify the state of the given (candidate) object. As
another example, if a particular attribute of interest is
identified in relation to a (candidate) object (see FIG. 2A: block
262a; see also FIG. 2D), additional bounding boxes may be
generated/defined to focus analysis on that attribute. In this
respect, analyses of objects and/or attributes may occur in
accordance with various levels of detail/specificity.
[0056] In some embodiments, aspects of the disclosure may provide
for a detection/identification of objects or attributes using one
or more neural networks. For example, one or more convolutional
neural networks may be incorporated to identify objects or
attributes.
[0057] Aspects of the disclosure may be used to streamline the
development, deployment, and/or maintenance of a network (e.g., a
communication network). For example, aspects of the disclosure may
reduce (e.g., minimize) the number of site visits that may be
required of technicians to determine whether objects are present at
a given location, and if so, whether those objects are suitable
candidates for receiving/deploying a resource. Still further,
aspects of the disclosure may be used to identify opportunities
(e.g., locations/objects) for a deployment of resources that
otherwise may have been overlooked/missed.
[0058] Aspects of the disclosure may leverage pre-existing image
capture equipment (e.g., image capture equipment 204a of FIG. 2A)
and/or images (e.g., images 254a of FIG. 2A) (which may be stored
in, and may be accessible via, one or more data stores) to identify
and/or select one or more locations/objects for receiving network
resources (e.g., network infrastructure). Stated slightly
differently, aspects of this disclosure may be facilitated via a
use of legacy/pre-existing equipment (which may initially have been
deployed for reasons unrelated to network resource
deployment/management), such that aspects of the disclosure may be
implemented with little-to-no additional cost/overhead.
[0059] Aspects of the disclosure may be used to enrich a database
of data regarding locations/objects for receiving network
resources. In some embodiments, locations/objects that have
demonstrated poor performance (e.g., performance that is less than
a metric/threshold) may be removed/banned from serving as a
candidate location/object in future deployments/implementations. In
this respect, a log/history of locations/objects may assist a
network/service operator/provider from incurring costly
mistakes/rework.
[0060] In some embodiments, models (e.g., communication
system/network models) may be executed/exercised to identify/assess
a prospective performance of network resources when
deployed/implemented at a given location/object. While aspects of
such model execution may provide insight into the performance of a
specific network resource at the given location, the execution of
the model may also identify the impact of one or more operations of
the resource on other resources (at the same location and/or at
other locations). For example, while a first resource may
operate/function as intended at a first location, the first
resource may negatively impact (e.g., may cause
signal/message/communication interference in relation to) a second
resource (at the first location or at a second location). In this
regard, an execution of one or more models may assist
engineers/technicians in identifying an impact of a deployment of a
first resource on one or more additional resources. In this
respect, aspects of the disclosure may facilitate a decision-making
procedure at both the device/component level and the system/network
level. The models may be modified in accordance with a deployment
of one or more resources, thereby resulting in modified models.
[0061] Aspects of this disclosure may facilitate an
identification/selection of objects or locations for
receiving/placing/mounting resources. Additionally, aspects of the
disclosure may facilitate a maintenance of such objects, locations,
and/or resources by proactively identifying when such maintenance
should be performed (e.g., relative to a probability of
inoperability of a resource exceeding a threshold), as well as
identifying equipment and/or personnel needed to perform such
maintenance. For example, in relation to the resource 200e of FIG.
2E, a frequency band of communication associated with a transmitter
(e.g., TX 200e-2) may be adjusted to account for an aging/drift of
a first oscillator of the transmitter over time. A technician may
be dispatched to the site of the transmitter if, e.g., the first
oscillator needs to be replaced. The technician may be instructed
to bring a second/replacement oscillator.
[0062] Aspects of the disclosure may be used to recommend and/or
identify/select one or more operating parameters (e.g., a
transmission power level, a frequency band, a
modulation/demodulation scheme, an encoding/decoding scheme, an
encryption/decryption scheme) of a network resource(s). The
operating parameter(s) may be selected based on an identification
of one or more objects and/or one or more attributes as identified
in accordance with various aspects of this disclosure.
[0063] In accordance with aspects of the disclosure, a selection of
one or more objects to receive a deployment of one or more
resources may be based on data associated with a communication
system. For example, such data may be obtained and analyzed as part
of the selection. The data may refer to at least one signal quality
parameter/metric, such as for example a received signal strength,
interference, noise, or any combination thereof.
[0064] Aspects of the disclosure may facilitate a selection of an
object to receive a deployment of a resource in accordance with one
or more attributes. For example, an object having/possessing a
given attribute may make it more likely that the object will
receive the deployment of the resource than if the object did not
possess the given attribute. In this regard, aspects of the
disclosure may identify attributes that an object has, as well as
identify attributes that an object lacks.
[0065] Referring now to FIG. 3, a block diagram 300 is shown
illustrating an example, non-limiting embodiment of a virtualized
communication network in accordance with various aspects described
herein. In particular a virtualized communication network is
presented that can be used to implement some or all of the
subsystems and functions of communication network 100, the
subsystems and functions of system 200a, method 258b, and method
262d presented in FIGS. 1, 2A, 2B, and 2D. For example, virtualized
communication network 300 can facilitate in whole or in part
obtaining an image that is sourced from a vehicle, identifying a
first plurality of characteristics in the image, comparing the
first plurality of characteristics to a second plurality of
characteristics associated with a plurality of objects to generate
a first score, determining that a first match exists based on a
comparison of the first score to a first threshold, responsive to
the determining that the first match exists, identifying a first
object of the plurality of objects as being present in the image,
identifying a third plurality of characteristics in the image based
on a processing of the image in accordance with a first bounding
region that surrounds the first object in the image, comparing the
third plurality of characteristics to a plurality of attributes to
generate a second score, determining that a second match exists
based on a comparison of the second score to a second threshold,
responsive to the determining that the second match exists,
identifying a first attribute of the plurality of attributes as
being present in the first object, and selecting the first object
or a second object of the plurality of objects to receive a
deployment of a communication network resource in accordance with
the identifying of the first object and the identifying of the
first attribute. Virtualized communication network 300 can
facilitate in whole or in part obtaining a first plurality of
images, identifying a first plurality of characteristics in the
first plurality of images, determining that a first match exists
based on a comparison of the first plurality of characteristics to
a second plurality of characteristics associated with a plurality
of objects, responsive to the determining that the first match
exists, identifying a first object, a second object, or a
combination thereof, as being present in the first plurality of
images, resulting in at least one identified object, identifying a
third plurality of characteristics in the first plurality of images
based on a processing of the first plurality of images in
accordance with a bounding region that at least partially surrounds
the at least one identified object, determining that a second match
exists based on a comparison of the third plurality of
characteristics to a plurality of attributes, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the at
least one identified object, and selecting the at least one
identified object to receive a deployment of a first resource in
accordance with the identifying of the at least one identified
object and the identifying of the first attribute. Virtualized
communication network 300 can facilitate in whole or in part
determining that a first instance of a first object is present in a
first image in accordance with an execution of a first image
processing algorithm, responsive to the determining that the first
instance of the first object is present in the first image,
generating a first bounding region that at least partially
surrounds the first instance of the first object in the first
image, determining that the first instance of the first object in
the first image has a first attribute in accordance with an
execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object, a second instance of the first
object, or a combination thereof, to receive a deployment of a
network resource in accordance with the determining that the first
instance of the first object in the first image has the first
attribute.
[0066] In particular, a cloud networking architecture is shown that
leverages cloud technologies and supports rapid innovation and
scalability via a transport layer 350, a virtualized network
function cloud 325 and/or one or more cloud computing environments
375. In various embodiments, this cloud networking architecture is
an open architecture that leverages application programming
interfaces (APIs); reduces complexity from services and operations;
supports more nimble business models; and rapidly and seamlessly
scales to meet evolving customer requirements including traffic
growth, diversity of traffic types, and diversity of performance
and reliability expectations.
[0067] In contrast to traditional network elements--which are
typically integrated to perform a single function, the virtualized
communication network employs virtual network elements (VNEs) 330,
332, 334, etc. that perform some or all of the functions of network
elements 150, 152, 154, 156, etc. For example, the network
architecture can provide a substrate of networking capability,
often called Network Function Virtualization Infrastructure (NFVI)
or simply infrastructure that is capable of being directed with
software and Software Defined Networking (SDN) protocols to perform
a broad variety of network functions and services. This
infrastructure can include several types of substrates. The most
typical type of substrate being servers that support Network
Function Virtualization (NFV), followed by packet forwarding
capabilities based on generic computing resources, with specialized
network technologies brought to bear when general purpose
processors or general purpose integrated circuit devices offered by
merchants (referred to herein as merchant silicon) are not
appropriate. In this case, communication services can be
implemented as cloud-centric workloads.
[0068] As an example, a traditional network element 150 (shown in
FIG. 1), such as an edge router can be implemented via a VNE 330
composed of NFV software modules, merchant silicon, and associated
controllers. The software can be written so that increasing
workload consumes incremental resources from a common resource
pool, and moreover so that it's elastic: so the resources are only
consumed when needed. In a similar fashion, other network elements
such as other routers, switches, edge caches, and middle-boxes are
instantiated from the common resource pool. Such sharing of
infrastructure across a broad set of uses makes planning and
growing infrastructure easier to manage.
[0069] In an embodiment, the transport layer 350 includes fiber,
cable, wired and/or wireless transport elements, network elements
and interfaces to provide broadband access 110, wireless access
120, voice access 130, media access 140 and/or access to content
sources 175 for distribution of content to any or all of the access
technologies. In particular, in some cases a network element needs
to be positioned at a specific place, and this allows for less
sharing of common infrastructure. Other times, the network elements
have specific physical layer adapters that cannot be abstracted or
virtualized, and might require special DSP code and analog
front-ends (AFEs) that do not lend themselves to implementation as
VNEs 330, 332 or 334. These network elements can be included in
transport layer 350.
[0070] The virtualized network function cloud 325 interfaces with
the transport layer 350 to provide the VNEs 330, 332, 334, etc. to
provide specific NFVs. In particular, the virtualized network
function cloud 325 leverages cloud operations, applications, and
architectures to support networking workloads. The virtualized
network elements 330, 332 and 334 can employ network function
software that provides either a one-for-one mapping of traditional
network element function or alternately some combination of network
functions designed for cloud computing. For example, VNEs 330, 332
and 334 can include route reflectors, domain name system (DNS)
servers, and dynamic host configuration protocol (DHCP) servers,
system architecture evolution (SAE) and/or mobility management
entity (MME) gateways, broadband network gateways, IP edge routers
for IP-VPN, Ethernet and other services, load balancers,
distributers and other network elements. Because these elements
don't typically need to forward large amounts of traffic, their
workload can be distributed across a number of servers--each of
which adds a portion of the capability, and overall which creates
an elastic function with higher availability than its former
monolithic version. These virtual network elements 330, 332, 334,
etc. can be instantiated and managed using an orchestration
approach similar to those used in cloud compute services.
[0071] The cloud computing environments 375 can interface with the
virtualized network function cloud 325 via APIs that expose
functional capabilities of the VNEs 330, 332, 334, etc. to provide
the flexible and expanded capabilities to the virtualized network
function cloud 325. In particular, network workloads may have
applications distributed across the virtualized network function
cloud 325 and cloud computing environment 375 and in the commercial
cloud, or might simply orchestrate workloads supported entirely in
NFV infrastructure from these third party locations.
[0072] Turning now to FIG. 4, there is illustrated a block diagram
of a computing environment in accordance with various aspects
described herein. In order to provide additional context for
various embodiments of the embodiments described herein, FIG. 4 and
the following discussion are intended to provide a brief, general
description of a suitable computing environment 400 in which the
various embodiments of the subject disclosure can be implemented.
In particular, computing environment 400 can be used in the
implementation of network elements 150, 152, 154, 156, access
terminal 112, base station or access point 122, switching device
132, media terminal 142, and/or VNEs 330, 332, 334, etc. Each of
these devices can be implemented via computer-executable
instructions that can run on one or more computers, and/or in
combination with other program modules and/or as a combination of
hardware and software. For example, computing environment 400 can
facilitate in whole or in part obtaining an image that is sourced
from a vehicle, identifying a first plurality of characteristics in
the image, comparing the first plurality of characteristics to a
second plurality of characteristics associated with a plurality of
objects to generate a first score, determining that a first match
exists based on a comparison of the first score to a first
threshold, responsive to the determining that the first match
exists, identifying a first object of the plurality of objects as
being present in the image, identifying a third plurality of
characteristics in the image based on a processing of the image in
accordance with a first bounding region that surrounds the first
object in the image, comparing the third plurality of
characteristics to a plurality of attributes to generate a second
score, determining that a second match exists based on a comparison
of the second score to a second threshold, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the
first object, and selecting the first object or a second object of
the plurality of objects to receive a deployment of a communication
network resource in accordance with the identifying of the first
object and the identifying of the first attribute. Computing
environment 400 can facilitate in whole or in part obtaining a
first plurality of images, identifying a first plurality of
characteristics in the first plurality of images, determining that
a first match exists based on a comparison of the first plurality
of characteristics to a second plurality of characteristics
associated with a plurality of objects, responsive to the
determining that the first match exists, identifying a first
object, a second object, or a combination thereof, as being present
in the first plurality of images, resulting in at least one
identified object, identifying a third plurality of characteristics
in the first plurality of images based on a processing of the first
plurality of images in accordance with a bounding region that at
least partially surrounds the at least one identified object,
determining that a second match exists based on a comparison of the
third plurality of characteristics to a plurality of attributes,
responsive to the determining that the second match exists,
identifying a first attribute of the plurality of attributes as
being present in the at least one identified object, and selecting
the at least one identified object to receive a deployment of a
first resource in accordance with the identifying of the at least
one identified object and the identifying of the first attribute.
Computing environment 400 can facilitate in whole or in part
determining that a first instance of a first object is present in a
first image in accordance with an execution of a first image
processing algorithm, responsive to the determining that the first
instance of the first object is present in the first image,
generating a first bounding region that at least partially
surrounds the first instance of the first object in the first
image, determining that the first instance of the first object in
the first image has a first attribute in accordance with an
execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object, a second instance of the first
object, or a combination thereof, to receive a deployment of a
network resource in accordance with the determining that the first
instance of the first object in the first image has the first
attribute.
[0073] Generally, program modules comprise routines, programs,
components, data structures, etc., that perform particular tasks or
implement particular abstract data types. Moreover, those skilled
in the art will appreciate that the methods can be practiced with
other computer system configurations, comprising single-processor
or multiprocessor computer systems, minicomputers, mainframe
computers, as well as personal computers, hand-held computing
devices, microprocessor-based or programmable consumer electronics,
and the like, each of which can be operatively coupled to one or
more associated devices.
[0074] As used herein, a processing circuit includes one or more
processors as well as other application specific circuits such as
an application specific integrated circuit, digital logic circuit,
state machine, programmable gate array or other circuit that
processes input signals or data and that produces output signals or
data in response thereto. It should be noted that while any
functions and features described herein in association with the
operation of a processor could likewise be performed by a
processing circuit.
[0075] The illustrated embodiments of the embodiments herein can be
also practiced in distributed computing environments where certain
tasks are performed by remote processing devices that are linked
through a communications network. In a distributed computing
environment, program modules can be located in both local and
remote memory storage devices.
[0076] Computing devices typically comprise a variety of media,
which can comprise computer-readable storage media and/or
communications media, which two terms are used herein differently
from one another as follows. Computer-readable storage media can be
any available storage media that can be accessed by the computer
and comprises both volatile and nonvolatile media, removable and
non-removable media. By way of example, and not limitation,
computer-readable storage media can be implemented in connection
with any method or technology for storage of information such as
computer-readable instructions, program modules, structured data or
unstructured data.
[0077] Computer-readable storage media can comprise, but are not
limited to, random access memory (RAM), read only memory (ROM),
electrically erasable programmable read only memory (EEPROM), flash
memory or other memory technology, compact disk read only memory
(CD-ROM), digital versatile disk (DVD) or other optical disk
storage, magnetic cassettes, magnetic tape, magnetic disk storage
or other magnetic storage devices or other tangible and/or
non-transitory media which can be used to store desired
information. In this regard, the terms "tangible" or
"non-transitory" herein as applied to storage, memory or
computer-readable media, are to be understood to exclude only
propagating transitory signals per se as modifiers and do not
relinquish rights to all standard storage, memory or
computer-readable media that are not only propagating transitory
signals per se.
[0078] Computer-readable storage media can be accessed by one or
more local or remote computing devices, e.g., via access requests,
queries or other data retrieval protocols, for a variety of
operations with respect to the information stored by the
medium.
[0079] Communications media typically embody computer-readable
instructions, data structures, program modules or other structured
or unstructured data in a data signal such as a modulated data
signal, e.g., a carrier wave or other transport mechanism, and
comprises any information delivery or transport media. The term
"modulated data signal" or signals refers to a signal that has one
or more of its characteristics set or changed in such a manner as
to encode information in one or more signals. By way of example,
and not limitation, communication media comprise wired media, such
as a wired network or direct-wired connection, and wireless media
such as acoustic, RF, infrared and other wireless media.
[0080] With reference again to FIG. 4, the example environment can
comprise a computer 402, the computer 402 comprising a processing
unit 404, a system memory 406 and a system bus 408. The system bus
408 couples system components including, but not limited to, the
system memory 406 to the processing unit 404. The processing unit
404 can be any of various commercially available processors. Dual
microprocessors and other multiprocessor architectures can also be
employed as the processing unit 404.
[0081] The system bus 408 can be any of several types of bus
structure that can further interconnect to a memory bus (with or
without a memory controller), a peripheral bus, and a local bus
using any of a variety of commercially available bus architectures.
The system memory 406 comprises ROM 410 and RAM 412. A basic
input/output system (BIOS) can be stored in a non-volatile memory
such as ROM, erasable programmable read only memory (EPROM),
EEPROM, which BIOS contains the basic routines that help to
transfer information between elements within the computer 402, such
as during startup. The RAM 412 can also comprise a high-speed RAM
such as static RAM for caching data.
[0082] The computer 402 further comprises an internal hard disk
drive (HDD) 414 (e.g., EIDE, SATA), which internal HDD 414 can also
be configured for external use in a suitable chassis (not shown), a
magnetic floppy disk drive (FDD) 416, (e.g., to read from or write
to a removable diskette 418) and an optical disk drive 420, (e.g.,
reading a CD-ROM disk 422 or, to read from or write to other high
capacity optical media such as the DVD). The HDD 414, magnetic FDD
416 and optical disk drive 420 can be connected to the system bus
408 by a hard disk drive interface 424, a magnetic disk drive
interface 426 and an optical drive interface 428, respectively. The
hard disk drive interface 424 for external drive implementations
comprises at least one or both of Universal Serial Bus (USB) and
Institute of Electrical and Electronics Engineers (IEEE) 1394
interface technologies. Other external drive connection
technologies are within contemplation of the embodiments described
herein.
[0083] The drives and their associated computer-readable storage
media provide nonvolatile storage of data, data structures,
computer-executable instructions, and so forth. For the computer
402, the drives and storage media accommodate the storage of any
data in a suitable digital format. Although the description of
computer-readable storage media above refers to a hard disk drive
(HDD), a removable magnetic diskette, and a removable optical media
such as a CD or DVD, it should be appreciated by those skilled in
the art that other types of storage media which are readable by a
computer, such as zip drives, magnetic cassettes, flash memory
cards, cartridges, and the like, can also be used in the example
operating environment, and further, that any such storage media can
contain computer-executable instructions for performing the methods
described herein.
[0084] A number of program modules can be stored in the drives and
RAM 412, comprising an operating system 430, one or more
application programs 432, other program modules 434 and program
data 436. All or portions of the operating system, applications,
modules, and/or data can also be cached in the RAM 412. The systems
and methods described herein can be implemented utilizing various
commercially available operating systems or combinations of
operating systems.
[0085] A user can enter commands and information into the computer
402 through one or more wired/wireless input devices, e.g., a
keyboard 438 and a pointing device, such as a mouse 440. Other
input devices (not shown) can comprise a microphone, an infrared
(IR) remote control, a joystick, a game pad, a stylus pen, touch
screen or the like. These and other input devices are often
connected to the processing unit 404 through an input device
interface 442 that can be coupled to the system bus 408, but can be
connected by other interfaces, such as a parallel port, an IEEE
1394 serial port, a game port, a universal serial bus (USB) port,
an IR interface, etc.
[0086] A monitor 444 or other type of display device can be also
connected to the system bus 408 via an interface, such as a video
adapter 446. It will also be appreciated that in alternative
embodiments, a monitor 444 can also be any display device (e.g.,
another computer having a display, a smart phone, a tablet
computer, etc.) for receiving display information associated with
computer 402 via any communication means, including via the
Internet and cloud-based networks. In addition to the monitor 444,
a computer typically comprises other peripheral output devices (not
shown), such as speakers, printers, etc.
[0087] The computer 402 can operate in a networked environment
using logical connections via wired and/or wireless communications
to one or more remote computers, such as a remote computer(s) 448.
The remote computer(s) 448 can be a workstation, a server computer,
a router, a personal computer, portable computer,
microprocessor-based entertainment appliance, a peer device or
other common network node, and typically comprises many or all of
the elements described relative to the computer 402, although, for
purposes of brevity, only a remote memory/storage device 450 is
illustrated. The logical connections depicted comprise
wired/wireless connectivity to a local area network (LAN) 452
and/or larger networks, e.g., a wide area network (WAN) 454. Such
LAN and WAN networking environments are commonplace in offices and
companies, and facilitate enterprise-wide computer networks, such
as intranets, all of which can connect to a global communications
network, e.g., the Internet.
[0088] When used in a LAN networking environment, the computer 402
can be connected to the LAN 452 through a wired and/or wireless
communication network interface or adapter 456. The adapter 456 can
facilitate wired or wireless communication to the LAN 452, which
can also comprise a wireless AP disposed thereon for communicating
with the adapter 456.
[0089] When used in a WAN networking environment, the computer 402
can comprise a modem 458 or can be connected to a communications
server on the WAN 454 or has other means for establishing
communications over the WAN 454, such as by way of the Internet.
The modem 458, which can be internal or external and a wired or
wireless device, can be connected to the system bus 408 via the
input device interface 442. In a networked environment, program
modules depicted relative to the computer 402 or portions thereof,
can be stored in the remote memory/storage device 450. It will be
appreciated that the network connections shown are example and
other means of establishing a communications link between the
computers can be used.
[0090] The computer 402 can be operable to communicate with any
wireless devices or entities operatively disposed in wireless
communication, e.g., a printer, scanner, desktop and/or portable
computer, portable data assistant, communications satellite, any
piece of equipment or location associated with a wirelessly
detectable tag (e.g., a kiosk, news stand, restroom), and
telephone. This can comprise Wireless Fidelity (Wi-Fi) and
BLUETOOTH.RTM. wireless technologies. Thus, the communication can
be a predefined structure as with a conventional network or simply
an ad hoc communication between at least two devices.
[0091] Wi-Fi can allow connection to the Internet from a couch at
home, a bed in a hotel room or a conference room at work, without
wires. Wi-Fi is a wireless technology similar to that used in a
cell phone that enables such devices, e.g., computers, to send and
receive data indoors and out; anywhere within the range of a base
station. Wi-Fi networks use radio technologies called IEEE 802.11
(a, b, g, n, ac, ag, etc.) to provide secure, reliable, fast
wireless connectivity. A Wi-Fi network can be used to connect
computers to each other, to the Internet, and to wired networks
(which can use IEEE 802.3 or Ethernet). Wi-Fi networks operate in
the unlicensed 2.4 and 5 GHz radio bands for example or with
products that contain both bands (dual band), so the networks can
provide real-world performance similar to the basic 10BaseT wired
Ethernet networks used in many offices.
[0092] Turning now to FIG. 5, an embodiment 500 of a mobile network
platform 510 is shown that is an example of network elements 150,
152, 154, 156, and/or VNEs 330, 332, 334, etc. For example,
platform 510 can facilitate in whole or in part obtaining an image
that is sourced from a vehicle, identifying a first plurality of
characteristics in the image, comparing the first plurality of
characteristics to a second plurality of characteristics associated
with a plurality of objects to generate a first score, determining
that a first match exists based on a comparison of the first score
to a first threshold, responsive to the determining that the first
match exists, identifying a first object of the plurality of
objects as being present in the image, identifying a third
plurality of characteristics in the image based on a processing of
the image in accordance with a first bounding region that surrounds
the first object in the image, comparing the third plurality of
characteristics to a plurality of attributes to generate a second
score, determining that a second match exists based on a comparison
of the second score to a second threshold, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the
first object, and selecting the first object or a second object of
the plurality of objects to receive a deployment of a communication
network resource in accordance with the identifying of the first
object and the identifying of the first attribute. Platform 510 can
facilitate in whole or in part obtaining a first plurality of
images, identifying a first plurality of characteristics in the
first plurality of images, determining that a first match exists
based on a comparison of the first plurality of characteristics to
a second plurality of characteristics associated with a plurality
of objects, responsive to the determining that the first match
exists, identifying a first object, a second object, or a
combination thereof, as being present in the first plurality of
images, resulting in at least one identified object, identifying a
third plurality of characteristics in the first plurality of images
based on a processing of the first plurality of images in
accordance with a bounding region that at least partially surrounds
the at least one identified object, determining that a second match
exists based on a comparison of the third plurality of
characteristics to a plurality of attributes, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the at
least one identified object, and selecting the at least one
identified object to receive a deployment of a first resource in
accordance with the identifying of the at least one identified
object and the identifying of the first attribute. Platform 510 can
facilitate in whole or in part determining that a first instance of
a first object is present in a first image in accordance with an
execution of a first image processing algorithm, responsive to the
determining that the first instance of the first object is present
in the first image, generating a first bounding region that at
least partially surrounds the first instance of the first object in
the first image, determining that the first instance of the first
object in the first image has a first attribute in accordance with
an execution of a second image processing algorithm, wherein the
second image processing algorithm is operative on the first image
in accordance with the first bounding region, and selecting the
first instance of the first object, a second instance of the first
object, or a combination thereof, to receive a deployment of a
network resource in accordance with the determining that the first
instance of the first object in the first image has the first
attribute.
[0093] In one or more embodiments, the mobile network platform 510
can generate and receive signals transmitted and received by base
stations or access points such as base station or access point 122.
Generally, mobile network platform 510 can comprise components,
e.g., nodes, gateways, interfaces, servers, or disparate platforms,
that facilitate both packet-switched (PS) (e.g., internet protocol
(IP), frame relay, asynchronous transfer mode (ATM)) and
circuit-switched (CS) traffic (e.g., voice and data), as well as
control generation for networked wireless telecommunication. As a
non-limiting example, mobile network platform 510 can be included
in telecommunications carrier networks, and can be considered
carrier-side components as discussed elsewhere herein. Mobile
network platform 510 comprises CS gateway node(s) 512 which can
interface CS traffic received from legacy networks like telephony
network(s) 540 (e.g., public switched telephone network (PSTN), or
public land mobile network (PLMN)) or a signaling system #7 (SS7)
network 560. CS gateway node(s) 512 can authorize and authenticate
traffic (e.g., voice) arising from such networks. Additionally, CS
gateway node(s) 512 can access mobility, or roaming, data generated
through SS7 network 560; for instance, mobility data stored in a
visited location register (VLR), which can reside in memory 530.
Moreover, CS gateway node(s) 512 interfaces CS-based traffic and
signaling and PS gateway node(s) 518. As an example, in a 3GPP UMTS
network, CS gateway node(s) 512 can be realized at least in part in
gateway GPRS support node(s) (GGSN). It should be appreciated that
functionality and specific operation of CS gateway node(s) 512, PS
gateway node(s) 518, and serving node(s) 516, is provided and
dictated by radio technology(ies) utilized by mobile network
platform 510 for telecommunication over a radio access network 520
with other devices, such as a radiotelephone 575.
[0094] In addition to receiving and processing CS-switched traffic
and signaling, PS gateway node(s) 518 can authorize and
authenticate PS-based data sessions with served mobile devices.
Data sessions can comprise traffic, or content(s), exchanged with
networks external to the mobile network platform 510, like wide
area network(s) (WANs) 550, enterprise network(s) 570, and service
network(s) 580, which can be embodied in local area network(s)
(LANs), can also be interfaced with mobile network platform 510
through PS gateway node(s) 518. It is to be noted that WANs 550 and
enterprise network(s) 570 can embody, at least in part, a service
network(s) like IP multimedia subsystem (IMS). Based on radio
technology layer(s) available in technology resource(s) or radio
access network 520, PS gateway node(s) 518 can generate packet data
protocol contexts when a data session is established; other data
structures that facilitate routing of packetized data also can be
generated. To that end, in an aspect, PS gateway node(s) 518 can
comprise a tunnel interface (e.g., tunnel termination gateway (TTG)
in 3GPP UMTS network(s) (not shown)) which can facilitate
packetized communication with disparate wireless network(s), such
as Wi-Fi networks.
[0095] In embodiment 500, mobile network platform 510 also
comprises serving node(s) 516 that, based upon available radio
technology layer(s) within technology resource(s) in the radio
access network 520, convey the various packetized flows of data
streams received through PS gateway node(s) 518. It is to be noted
that for technology resource(s) that rely primarily on CS
communication, server node(s) can deliver traffic without reliance
on PS gateway node(s) 518; for example, server node(s) can embody
at least in part a mobile switching center. As an example, in a
3GPP UMTS network, serving node(s) 516 can be embodied in serving
GPRS support node(s) (SGSN).
[0096] For radio technologies that exploit packetized
communication, server(s) 514 in mobile network platform 510 can
execute numerous applications that can generate multiple disparate
packetized data streams or flows, and manage (e.g., schedule,
queue, format . . . ) such flows. Such application(s) can comprise
add-on features to standard services (for example, provisioning,
billing, customer support . . . ) provided by mobile network
platform 510. Data streams (e.g., content(s) that are part of a
voice call or data session) can be conveyed to PS gateway node(s)
518 for authorization/authentication and initiation of a data
session, and to serving node(s) 516 for communication thereafter.
In addition to application server, server(s) 514 can comprise
utility server(s), a utility server can comprise a provisioning
server, an operations and maintenance server, a security server
that can implement at least in part a certificate authority and
firewalls as well as other security mechanisms, and the like. In an
aspect, security server(s) secure communication served through
mobile network platform 510 to ensure network's operation and data
integrity in addition to authorization and authentication
procedures that CS gateway node(s) 512 and PS gateway node(s) 518
can enact. Moreover, provisioning server(s) can provision services
from external network(s) like networks operated by a disparate
service provider; for instance, WAN 550 or Global Positioning
System (GPS) network(s) (not shown). Provisioning server(s) can
also provision coverage through networks associated to mobile
network platform 510 (e.g., deployed and operated by the same
service provider), such as the distributed antennas networks shown
in FIG. 1(s) that enhance wireless service coverage by providing
more network coverage.
[0097] It is to be noted that server(s) 514 can comprise one or
more processors configured to confer at least in part the
functionality of mobile network platform 510. To that end, the one
or more processor can execute code instructions stored in memory
530, for example. It is should be appreciated that server(s) 514
can comprise a content manager, which operates in substantially the
same manner as described hereinbefore.
[0098] In example embodiment 500, memory 530 can store information
related to operation of mobile network platform 510. Other
operational information can comprise provisioning information of
mobile devices served through mobile network platform 510,
subscriber databases; application intelligence, pricing schemes,
e.g., promotional rates, flat-rate programs, couponing campaigns;
technical specification(s) consistent with telecommunication
protocols for operation of disparate radio, or wireless, technology
layers; and so forth. Memory 530 can also store information from at
least one of telephony network(s) 540, WAN 550, SS7 network 560, or
enterprise network(s) 570. In an aspect, memory 530 can be, for
example, accessed as part of a data store component or as a
remotely connected memory store.
[0099] In order to provide a context for the various aspects of the
disclosed subject matter, FIG. 5, and the following discussion, are
intended to provide a brief, general description of a suitable
environment in which the various aspects of the disclosed subject
matter can be implemented. While the subject matter has been
described above in the general context of computer-executable
instructions of a computer program that runs on a computer and/or
computers, those skilled in the art will recognize that the
disclosed subject matter also can be implemented in combination
with other program modules. Generally, program modules comprise
routines, programs, components, data structures, etc. that perform
particular tasks and/or implement particular abstract data
types.
[0100] Turning now to FIG. 6, an illustrative embodiment of a
communication device 600 is shown. The communication device 600 can
serve as an illustrative embodiment of devices such as data
terminals 114, mobile devices 124, vehicle 126, display devices 144
or other client devices for communication via either communications
network 125. For example, computing device 600 can facilitate in
whole or in part obtaining an image that is sourced from a vehicle,
identifying a first plurality of characteristics in the image,
comparing the first plurality of characteristics to a second
plurality of characteristics associated with a plurality of objects
to generate a first score, determining that a first match exists
based on a comparison of the first score to a first threshold,
responsive to the determining that the first match exists,
identifying a first object of the plurality of objects as being
present in the image, identifying a third plurality of
characteristics in the image based on a processing of the image in
accordance with a first bounding region that surrounds the first
object in the image, comparing the third plurality of
characteristics to a plurality of attributes to generate a second
score, determining that a second match exists based on a comparison
of the second score to a second threshold, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the
first object, and selecting the first object or a second object of
the plurality of objects to receive a deployment of a communication
network resource in accordance with the identifying of the first
object and the identifying of the first attribute. Computing device
600 can facilitate in whole or in part obtaining a first plurality
of images, identifying a first plurality of characteristics in the
first plurality of images, determining that a first match exists
based on a comparison of the first plurality of characteristics to
a second plurality of characteristics associated with a plurality
of objects, responsive to the determining that the first match
exists, identifying a first object, a second object, or a
combination thereof, as being present in the first plurality of
images, resulting in at least one identified object, identifying a
third plurality of characteristics in the first plurality of images
based on a processing of the first plurality of images in
accordance with a bounding region that at least partially surrounds
the at least one identified object, determining that a second match
exists based on a comparison of the third plurality of
characteristics to a plurality of attributes, responsive to the
determining that the second match exists, identifying a first
attribute of the plurality of attributes as being present in the at
least one identified object, and selecting the at least one
identified object to receive a deployment of a first resource in
accordance with the identifying of the at least one identified
object and the identifying of the first attribute. Computing device
600 can facilitate in whole or in part determining that a first
instance of a first object is present in a first image in
accordance with an execution of a first image processing algorithm,
responsive to the determining that the first instance of the first
object is present in the first image, generating a first bounding
region that at least partially surrounds the first instance of the
first object in the first image, determining that the first
instance of the first object in the first image has a first
attribute in accordance with an execution of a second image
processing algorithm, wherein the second image processing algorithm
is operative on the first image in accordance with the first
bounding region, and selecting the first instance of the first
object, a second instance of the first object, or a combination
thereof, to receive a deployment of a network resource in
accordance with the determining that the first instance of the
first object in the first image has the first attribute.
[0101] The communication device 600 can comprise a wireline and/or
wireless transceiver 602 (herein transceiver 602), a user interface
(UI) 604, a power supply 614, a location receiver 616, a motion
sensor 618, an orientation sensor 620, and a controller 606 for
managing operations thereof. The transceiver 602 can support
short-range or long-range wireless access technologies such as
Bluetooth.RTM., ZigBee.RTM., WiFi, DECT, or cellular communication
technologies, just to mention a few (Bluetooth.RTM. and ZigBee.RTM.
are trademarks registered by the Bluetooth.RTM. Special Interest
Group and the ZigBee.RTM. Alliance, respectively). Cellular
technologies can include, for example, CDMA-1X, UMTS/HSDPA,
GSM/GPRS, TDMA/EDGE, EV/DO, WiMAX, SDR, LTE, as well as other next
generation wireless communication technologies as they arise. The
transceiver 602 can also be adapted to support circuit-switched
wireline access technologies (such as PSTN), packet-switched
wireline access technologies (such as TCP/IP, VoIP, etc.), and
combinations thereof.
[0102] The UI 604 can include a depressible or touch-sensitive
keypad 608 with a navigation mechanism such as a roller ball, a
joystick, a mouse, or a navigation disk for manipulating operations
of the communication device 600. The keypad 608 can be an integral
part of a housing assembly of the communication device 600 or an
independent device operably coupled thereto by a tethered wireline
interface (such as a USB cable) or a wireless interface supporting
for example Bluetooth.RTM.. The keypad 608 can represent a numeric
keypad commonly used by phones, and/or a QWERTY keypad with
alphanumeric keys. The UI 604 can further include a display 610
such as monochrome or color LCD (Liquid Crystal Display), OLED
(Organic Light Emitting Diode) or other suitable display technology
for conveying images to an end user of the communication device
600. In an embodiment where the display 610 is touch-sensitive, a
portion or all of the keypad 608 can be presented by way of the
display 610 with navigation features.
[0103] The display 610 can use touch screen technology to also
serve as a user interface for detecting user input. As a touch
screen display, the communication device 600 can be adapted to
present a user interface having graphical user interface (GUI)
elements that can be selected by a user with a touch of a finger.
The display 610 can be equipped with capacitive, resistive or other
forms of sensing technology to detect how much surface area of a
user's finger has been placed on a portion of the touch screen
display. This sensing information can be used to control the
manipulation of the GUI elements or other functions of the user
interface. The display 610 can be an integral part of the housing
assembly of the communication device 600 or an independent device
communicatively coupled thereto by a tethered wireline interface
(such as a cable) or a wireless interface.
[0104] The UI 604 can also include an audio system 612 that
utilizes audio technology for conveying low volume audio (such as
audio heard in proximity of a human ear) and high volume audio
(such as speakerphone for hands free operation). The audio system
612 can further include a microphone for receiving audible signals
of an end user. The audio system 612 can also be used for voice
recognition applications. The UI 604 can further include an image
sensor 613 such as a charged coupled device (CCD) camera for
capturing still or moving images.
[0105] The power supply 614 can utilize common power management
technologies such as replaceable and rechargeable batteries, supply
regulation technologies, and/or charging system technologies for
supplying energy to the components of the communication device 600
to facilitate long-range or short-range portable communications.
Alternatively, or in combination, the charging system can utilize
external power sources such as DC power supplied over a physical
interface such as a USB port or other suitable tethering
technologies.
[0106] The location receiver 616 can utilize location technology
such as a global positioning system (GPS) receiver capable of
assisted GPS for identifying a location of the communication device
600 based on signals generated by a constellation of GPS
satellites, which can be used for facilitating location services
such as navigation. The motion sensor 618 can utilize motion
sensing technology such as an accelerometer, a gyroscope, or other
suitable motion sensing technology to detect motion of the
communication device 600 in three-dimensional space. The
orientation sensor 620 can utilize orientation sensing technology
such as a magnetometer to detect the orientation of the
communication device 600 (north, south, west, and east, as well as
combined orientations in degrees, minutes, or other suitable
orientation metrics).
[0107] The communication device 600 can use the transceiver 602 to
also determine a proximity to a cellular, WiFi, Bluetooth.RTM., or
other wireless access points by sensing techniques such as
utilizing a received signal strength indicator (RSSI) and/or signal
time of arrival (TOA) or time of flight (TOF) measurements. The
controller 606 can utilize computing technologies such as a
microprocessor, a digital signal processor (DSP), programmable gate
arrays, application specific integrated circuits, and/or a video
processor with associated storage memory such as Flash, ROM, RAM,
SRAM, DRAM or other storage technologies for executing computer
instructions, controlling, and processing data supplied by the
aforementioned components of the communication device 600.
[0108] Other components not shown in FIG. 6 can be used in one or
more embodiments of the subject disclosure. For instance, the
communication device 600 can include a slot for adding or removing
an identity module such as a Subscriber Identity Module (SIM) card
or Universal Integrated Circuit Card (UICC). SIM or UICC cards can
be used for identifying subscriber services, executing programs,
storing subscriber data, and so on.
[0109] The terms "first," "second," "third," and so forth, as used
in the claims, unless otherwise clear by context, is for clarity
only and doesn't otherwise indicate or imply any order in time. For
instance, "a first determination," "a second determination," and "a
third determination," does not indicate or imply that the first
determination is to be made before the second determination, or
vice versa, etc.
[0110] In the subject specification, terms such as "store,"
"storage," "data store," data storage," "database," and
substantially any other information storage component relevant to
operation and functionality of a component, refer to "memory
components," or entities embodied in a "memory" or components
comprising the memory. It will be appreciated that the memory
components described herein can be either volatile memory or
nonvolatile memory, or can comprise both volatile and nonvolatile
memory, by way of illustration, and not limitation, volatile
memory, non-volatile memory, disk storage, and memory storage.
Further, nonvolatile memory can be included in read only memory
(ROM), programmable ROM (PROM), electrically programmable ROM
(EPROM), electrically erasable ROM (EEPROM), or flash memory.
Volatile memory can comprise random access memory (RAM), which acts
as external cache memory. By way of illustration and not
limitation, RAM is available in many forms such as synchronous RAM
(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data
rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM
(SLDRAM), and direct Rambus RAM (DRRAM). Additionally, the
disclosed memory components of systems or methods herein are
intended to comprise, without being limited to comprising, these
and any other suitable types of memory.
[0111] Moreover, it will be noted that the disclosed subject matter
can be practiced with other computer system configurations,
comprising single-processor or multiprocessor computer systems,
mini-computing devices, mainframe computers, as well as personal
computers, hand-held computing devices (e.g., PDA, phone,
smartphone, watch, tablet computers, netbook computers, etc.),
microprocessor-based or programmable consumer or industrial
electronics, and the like. The illustrated aspects can also be
practiced in distributed computing environments where tasks are
performed by remote processing devices that are linked through a
communications network; however, some if not all aspects of the
subject disclosure can be practiced on stand-alone computers. In a
distributed computing environment, program modules can be located
in both local and remote memory storage devices.
[0112] In one or more embodiments, information regarding use of
services can be generated including services being accessed, media
consumption history, user preferences, and so forth. This
information can be obtained by various methods including user
input, detecting types of communications (e.g., video content vs.
audio content), analysis of content streams, sampling, and so
forth. The generating, obtaining and/or monitoring of this
information can be responsive to an authorization provided by the
user. In one or more embodiments, an analysis of data can be
subject to authorization from user(s) associated with the data,
such as an opt-in, an opt-out, acknowledgement requirements,
notifications, selective authorization based on types of data, and
so forth.
[0113] Some of the embodiments described herein can also employ
artificial intelligence (AI) to facilitate automating one or more
features described herein. The embodiments (e.g., in connection
with automatically identifying acquired cell sites that provide a
maximum value/benefit after addition to an existing communication
network) can employ various AI-based schemes for carrying out
various embodiments thereof. Moreover, the classifier can be
employed to determine a ranking or priority of each cell site of
the acquired network. A classifier is a function that maps an input
attribute vector, x=(x1, x2, x3, x4, . . . , xn), to a confidence
that the input belongs to a class, that is, f(x)=confidence
(class). Such classification can employ a probabilistic and/or
statistical-based analysis (e.g., factoring into the analysis
utilities and costs) to determine or infer an action that a user
desires to be automatically performed. A support vector machine
(SVM) is an example of a classifier that can be employed. The SVM
operates by finding a hypersurface in the space of possible inputs,
which the hypersurface attempts to split the triggering criteria
from the non-triggering events. Intuitively, this makes the
classification correct for testing data that is near, but not
identical to training data. Other directed and undirected model
classification approaches comprise, e.g., naive Bayes, Bayesian
networks, decision trees, neural networks, fuzzy logic models, and
probabilistic classification models providing different patterns of
independence can be employed. Classification as used herein also is
inclusive of statistical regression that is utilized to develop
models of priority.
[0114] As will be readily appreciated, one or more of the
embodiments can employ classifiers that are explicitly trained
(e.g., via a generic training data) as well as implicitly trained
(e.g., via observing UE behavior, operator preferences, historical
information, receiving extrinsic information). For example, SVMs
can be configured via a learning or training phase within a
classifier constructor and feature selection module. Thus, the
classifier(s) can be used to automatically learn and perform a
number of functions, including but not limited to determining
according to predetermined criteria which of the acquired cell
sites will benefit a maximum number of subscribers and/or which of
the acquired cell sites will add minimum value to the existing
communication network coverage, etc.
[0115] As used in some contexts in this application, in some
embodiments, the terms "component," "system" and the like are
intended to refer to, or comprise, a computer-related entity or an
entity related to an operational apparatus with one or more
specific functionalities, wherein the entity can be either
hardware, a combination of hardware and software, software, or
software in execution. As an example, a component may be, but is
not limited to being, a process running on a processor, a
processor, an object, an executable, a thread of execution,
computer-executable instructions, a program, and/or a computer. By
way of illustration and not limitation, both an application running
on a server and the server can be a component. One or more
components may reside within a process and/or thread of execution
and a component may be localized on one computer and/or distributed
between two or more computers. In addition, these components can
execute from various computer readable media having various data
structures stored thereon. The components may communicate via local
and/or remote processes such as in accordance with a signal having
one or more data packets (e.g., data from one component interacting
with another component in a local system, distributed system,
and/or across a network such as the Internet with other systems via
the signal). As another example, a component can be an apparatus
with specific functionality provided by mechanical parts operated
by electric or electronic circuitry, which is operated by a
software or firmware application executed by a processor, wherein
the processor can be internal or external to the apparatus and
executes at least a part of the software or firmware application.
As yet another example, a component can be an apparatus that
provides specific functionality through electronic components
without mechanical parts, the electronic components can comprise a
processor therein to execute software or firmware that confers at
least in part the functionality of the electronic components. While
various components have been illustrated as separate components, it
will be appreciated that multiple components can be implemented as
a single component, or a single component can be implemented as
multiple components, without departing from example
embodiments.
[0116] Further, the various embodiments can be implemented as a
method, apparatus or article of manufacture using standard
programming and/or engineering techniques to produce software,
firmware, hardware or any combination thereof to control a computer
to implement the disclosed subject matter. The term "article of
manufacture" as used herein is intended to encompass a computer
program accessible from any computer-readable device or
computer-readable storage/communications media. For example,
computer readable storage media can include, but are not limited
to, magnetic storage devices (e.g., hard disk, floppy disk,
magnetic strips), optical disks (e.g., compact disk (CD), digital
versatile disk (DVD)), smart cards, and flash memory devices (e.g.,
card, stick, key drive). Of course, those skilled in the art will
recognize many modifications can be made to this configuration
without departing from the scope or spirit of the various
embodiments.
[0117] In addition, the words "example" and "exemplary" are used
herein to mean serving as an instance or illustration. Any
embodiment or design described herein as "example" or "exemplary"
is not necessarily to be construed as preferred or advantageous
over other embodiments or designs. Rather, use of the word example
or exemplary is intended to present concepts in a concrete fashion.
As used in this application, the term "or" is intended to mean an
inclusive "or" rather than an exclusive "or". That is, unless
specified otherwise or clear from context, "X employs A or B" is
intended to mean any of the natural inclusive permutations. That
is, if X employs A; X employs B; or X employs both A and B, then "X
employs A or B" is satisfied under any of the foregoing instances.
In addition, the articles "a" and "an" as used in this application
and the appended claims should generally be construed to mean "one
or more" unless specified otherwise or clear from context to be
directed to a singular form.
[0118] Moreover, terms such as "user equipment," "mobile station,"
"mobile," subscriber station," "access terminal," "terminal,"
"handset," "mobile device" (and/or terms representing similar
terminology) can refer to a wireless device utilized by a
subscriber or user of a wireless communication service to receive
or convey data, control, voice, video, sound, gaming or
substantially any data-stream or signaling-stream. The foregoing
terms are utilized interchangeably herein and with reference to the
related drawings.
[0119] Furthermore, the terms "user," "subscriber," "customer,"
"consumer" and the like are employed interchangeably throughout,
unless context warrants particular distinctions among the terms. It
should be appreciated that such terms can refer to human entities
or automated components supported through artificial intelligence
(e.g., a capacity to make inference based, at least, on complex
mathematical formalisms), which can provide simulated vision, sound
recognition and so forth.
[0120] As employed herein, the term "processor" can refer to
substantially any computing processing unit or device comprising,
but not limited to comprising, single-core processors;
single-processors with software multithread execution capability;
multi-core processors; multi-core processors with software
multithread execution capability; multi-core processors with
hardware multithread technology; parallel platforms; and parallel
platforms with distributed shared memory. Additionally, a processor
can refer to an integrated circuit, an application specific
integrated circuit (ASIC), a digital signal processor (DSP), a
field programmable gate array (FPGA), a programmable logic
controller (PLC), a complex programmable logic device (CPLD), a
discrete gate or transistor logic, discrete hardware components or
any combination thereof designed to perform the functions described
herein. Processors can exploit nano-scale architectures such as,
but not limited to, molecular and quantum-dot based transistors,
switches and gates, in order to optimize space usage or enhance
performance of user equipment. A processor can also be implemented
as a combination of computing processing units.
[0121] As used herein, terms such as "data storage," data storage,"
"database," and substantially any other information storage
component relevant to operation and functionality of a component,
refer to "memory components," or entities embodied in a "memory" or
components comprising the memory. It will be appreciated that the
memory components or computer-readable storage media, described
herein can be either volatile memory or nonvolatile memory or can
include both volatile and nonvolatile memory.
[0122] What has been described above includes mere examples of
various embodiments. It is, of course, not possible to describe
every conceivable combination of components or methodologies for
purposes of describing these examples, but one of ordinary skill in
the art can recognize that many further combinations and
permutations of the present embodiments are possible. Accordingly,
the embodiments disclosed and/or claimed herein are intended to
embrace all such alterations, modifications and variations that
fall within the spirit and scope of the appended claims.
Furthermore, to the extent that the term "includes" is used in
either the detailed description or the claims, such term is
intended to be inclusive in a manner similar to the term
"comprising" as "comprising" is interpreted when employed as a
transitional word in a claim.
[0123] In addition, a flow diagram may include a "start" and/or
"continue" indication. The "start" and "continue" indications
reflect that the steps presented can optionally be incorporated in
or otherwise used in conjunction with other routines. In this
context, "start" indicates the beginning of the first step
presented and may be preceded by other activities not specifically
shown. Further, the "continue" indication reflects that the steps
presented may be performed multiple times and/or may be succeeded
by other activities not specifically shown. Further, while a flow
diagram indicates a particular ordering of steps, other orderings
are likewise possible provided that the principles of causality are
maintained.
[0124] As may also be used herein, the term(s) "operably coupled
to", "coupled to", and/or "coupling" includes direct coupling
between items and/or indirect coupling between items via one or
more intervening items. Such items and intervening items include,
but are not limited to, junctions, communication paths, components,
circuit elements, circuits, functional blocks, and/or devices. As
an example of indirect coupling, a signal conveyed from a first
item to a second item may be modified by one or more intervening
items by modifying the form, nature or format of information in a
signal, while one or more elements of the information in the signal
are nevertheless conveyed in a manner than can be recognized by the
second item. In a further example of indirect coupling, an action
in a first item can cause a reaction on the second item, as a
result of actions and/or reactions in one or more intervening
items.
[0125] Although specific embodiments have been illustrated and
described herein, it should be appreciated that any arrangement
which achieves the same or similar purpose may be substituted for
the embodiments described or shown by the subject disclosure. The
subject disclosure is intended to cover any and all adaptations or
variations of various embodiments. Combinations of the above
embodiments, and other embodiments not specifically described
herein, can be used in the subject disclosure. For instance, one or
more features from one or more embodiments can be combined with one
or more features of one or more other embodiments. In one or more
embodiments, features that are positively recited can also be
negatively recited and excluded from the embodiment with or without
replacement by another structural and/or functional feature. The
steps or functions described with respect to the embodiments of the
subject disclosure can be performed in any order. The steps or
functions described with respect to the embodiments of the subject
disclosure can be performed alone or in combination with other
steps or functions of the subject disclosure, as well as from other
embodiments or from other steps that have not been described in the
subject disclosure. Further, more than or less than all of the
features described with respect to an embodiment can also be
utilized.
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