U.S. patent application number 16/053878 was filed with the patent office on 2019-02-07 for parking management system.
The applicant listed for this patent is BlitzIt, Inc.. Invention is credited to Jessica Ornstein, Jonathan Ornstein, Nishit Rathod.
Application Number | 20190043082 16/053878 |
Document ID | / |
Family ID | 63371774 |
Filed Date | 2019-02-07 |
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United States Patent
Application |
20190043082 |
Kind Code |
A1 |
Ornstein; Jonathan ; et
al. |
February 7, 2019 |
PARKING MANAGEMENT SYSTEM
Abstract
Disclosed is a parking management system that includes a central
database in communication with a server, at least one user device,
at least one merchant console, and a parking gate controller device
over a network. The central database is provided to receive and
store data from a plurality of parking systems. A processor is
provided for analyzing the data received by the central database. A
dynamic data engine is provided for analyzing the data from the
plurality of parking systems and generating dynamic pricing data. A
targeted promotion engine is provided for analyzing user data and
generating a targeted promotion. The dynamic pricing data may be
provided to the user device to allow a user to book a parking space
from one of the parking systems. The targeted promotion may be
provided to the user device to allow the user to select a promotion
offered from a merchant.
Inventors: |
Ornstein; Jonathan;
(Phoenix, AZ) ; Ornstein; Jessica; (Phoenix,
AZ) ; Rathod; Nishit; (Phoenix, AZ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
BlitzIt, Inc. |
Phoenix |
AZ |
US |
|
|
Family ID: |
63371774 |
Appl. No.: |
16/053878 |
Filed: |
August 3, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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62540649 |
Aug 3, 2017 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/02 20130101;
G06Q 2240/00 20130101; G06Q 30/0223 20130101; G06Q 30/0251
20130101; G06Q 10/04 20130101; G06Q 30/0284 20130101 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02 |
Claims
1. A parking management system comprising: a central database in
operative communication with at least one user device, and at least
one merchant console of at least one parking system, wherein the
central database operatively receives and stores data from the at
least one merchant counsel, and wherein the central database
comprises: a processor and a memory storing instructions that, when
executed by the processors, cause the processors to execute
computer executable engines stored in the memory, the engines
comprising: a dynamic data engine that operatively analyzes the
data from the at least one parking systems and generates dynamic
pricing data for the at least one parking systems; and a targeted
promotion engine that operatively generates a targeted promotion
based on the user data, wherein the targeted promotion is to be
sent to the at least one user device.
2. The parking management system of claim 1, wherein the dynamic
pricing data includes a plurality of prices for reserving parking
spaces at the at least one parking systems.
3. The parking management system of claim 2, wherein the dynamic
data engine generates the dynamic pricing data based on at least
one of a date, time, price, utilization, weather, competitive data,
foot traffic, number of guests, and scheduled events.
4. The parking management system of claim 1, wherein said dynamic
data engine generates a forecasted price for a parking space based
on an input of date and time.
5. The parking management system of claim 1, wherein the dynamic
data engine executes a staging phase to generate a baseline for
price sensitivity as a function of historic price change data
associated with the at least one parking systems.
6. The parking management system of claim 1, wherein the dynamic
data engine receives a price increase granularity for the at least
one parking systems and generates the dynamic pricing data as a
function of the price increase granularity.
7. The parking management system of claim 1, wherein the data from
the at least one parking systems stored in the central database
includes at least one of usage date, usage time, parking price,
utilization rate, weather information, competitive pricing, and
foot traffic.
8. The parking management system of claim 1, wherein the dynamic
data engine operatively generates the dynamic pricing data based on
a predefined interval of time.
9. The parking management system of claim 1, wherein the dynamic
data engine operatively generates the dynamic pricing data in time
real time.
10. The parking management system of claim 1, wherein the targeted
promotions includes offers, messages, or notifications based on the
input preferences set up by the merchants.
11. The parking management system of claim 1, wherein said targeted
promotion engine generates and sends the target promotions based on
information associated with the user device.
12. The parking management system of claim 11, wherein the
information associated with the user device includes an indication
of a user entering or exiting a parking system.
13. The parking management system of claim 1, wherein the dynamic
pricing data includes a plurality of prices for parking spaces at
the at least one parking systems for use by a user in an unreserved
scenario.
14. The parking management system of claim 1, wherein the targeting
promotion engine captures feedback data from one or more user
devices and determines a user affinity for the targeted promotion
and provide the feedback information to the database.
15. A parking management system comprising, one or more parking
system devices each associated with a parking system; one or more
processors in communication with the one or more parking system
devices and one or more memory resources storing instructions that,
when executed by the one or more processors, cause the one or more
processors to: receive and store pricing and utilization data from
one or more parking system devices in a database; generating a
pricing and utilization model for the one or more parking systems
based on the received pricing and utilization data; creating a list
of price-utilization options based on the pricing and utilization
model for selection by a user; and receiving a selection of a
price-utilization option from the list.
16. The parking management system of claim 15, wherein the
processor further receives optimization criteria and generates one
or more optimization options for the list of price-utilization
options.
17. The parking management system of claim 16, wherein the
optimization criteria includes at least one of revenue optimization
or utilization optimization.
18. The parking management system of claim 16, wherein the one or
more parking system devices includes an input device that receives
information from a user device as a user enters or exits the
parking system.
19. The parking management system of claim 18, wherein the
information from the user device comprises a scannable image.
20. A method for a parking management system, comprising:
generating a baseline sensitivity for a parking system based on a
history of price changes and utilization associated with the price
changes; creating a model for price and utilization of the parking
system based on the baseline sensitivity; receiving information
associated with at least one of foot traffic, events, weather
information, or user preferences; and utilizing the model and the
received information to determine dynamic price adjustments for a
predefined time interval.
21. The method of claim 20, further comprising receiving flight
information describing at least one of a number of flights or
number of passengers, and wherein utilizing the model further
comprises utilizing the flight information and the received
information to determine the dynamic price adjustments
Description
FIELD OF THE INVENTION
[0001] The present invention is generally related to a system and
method for efficiently managing parking systems. More particularly,
this disclosure is related to a parking management system for
dynamically tracking and determining parking data for a variety of
parking systems.
BACKGROUND
[0002] The parking systems such as garages and lots are generally
subject to passive management. Various techniques have been
developed to reduce operating cost and to increase revenue and
utilization. These available techniques utilize parking management
systems that include a combination of software and hardware
implemented by a program over a network. These systems are
disclosed by various published patent documents such as, for
example, U.S. Patent Publication 2017/0098374 to Sullivan et al
which teaches a parking data aggregation and distribution system.
However, these types of systems are disclosed for tracking parking
related data, such as yield and amount a parking system charges its
customers.
[0003] Yield management systems have been implemented to enhance
utilization in various industries with similar dynamics to parking
systems such as with airlines, hotels, and rental cars. Whether
airline "seats" or parking "spots", yield management systems
attempt to generate additional revenue and maximize utilization.
However, existing yield management systems for parking facilities
may not generate efficient utilization rates due to varying demand
and other conditions that are specific to parking systems. These
parking systems generally rely on limited data to manage
utilization of their facilities.
[0004] Thus, there may be a need to provide an improved yield
management system for parking systems to increase utilization and
improve revenue generation. There may also be a need to allow users
to customize a parking management system to individually determine
their goals for operating a parking system
SUMMARY
[0005] Disclosed is a parking management system that includes a
central database in communication with a server, at least one user
device, at least one merchant console, and a parking gate
controller device over a network. The central database is provided
to receive and store data from a plurality of parking systems. A
processor is provided for analyzing the data received by the
central database. A dynamic data engine is provided for analyzing
the data from the plurality of parking systems and generating
dynamic pricing data. A targeted promotion engine is provided for
analyzing user data and generating a targeted promotion. The
dynamic pricing data may be provided to the user device to allow a
user to book a parking space from one of the parking systems. The
targeted promotion may be provided to the user device to allow the
user to select a promotion offered from a merchant.
[0006] The dynamic data engine may generate the dynamic pricing
data which includes a plurality of prices for reserving parking
spaces at a plurality of parking systems. The dynamic data engine
may process date, time, price, utilization, weather, competitive
data, foot traffic, number of guests, and scheduled events to
generate the dynamic pricing data. The dynamic data engine may
generate a forecasted price for a parking space based on an input
of date and time as desired by the user. The dynamic data engine
may be programmed to generate various price granularities for a
plurality of parking systems. The data from the plurality of
parking systems includes usage date, usage time, parking price,
utilization rate, weather information, competitive pricing, and
foot traffic.
[0007] The targeted promotion engine may generate and send targeted
promotions to the user. The targeted promotions include offers,
messages, or notifications based on the input preferences set up by
the merchants
[0008] Also described is a parking management system comprising a
central database in operative communication with at least one user
device, and at least one merchant console of at least one parking
systems, wherein the central database operatively receives and
stores data from the at least one merchant counsel. The central
database may comprise a processor and a memory storing instructions
that, when executed by the processors, cause the processors to
execute computer executable engines stored in the memory. The
engines may comprise a dynamic data engine that operatively
analyzes the data from the at least one parking systems and
generates dynamic pricing data for the at least one parking
systems, and a targeted promotion engine that operatively generates
a targeted promotion based on the user data, wherein the targeted
promotion is to be sent to the at least one user device. The
dynamic pricing data includes a plurality of prices for reserving
parking spaces at the at least one parking systems. In another
aspect, the dynamic data engine generates the dynamic pricing data
based on at least one of a date, time, price, utilization, weather,
competitive data, foot traffic, number of guests, and scheduled
events. It is noted that said dynamic data engine may generate a
forecasted price for a parking space based on an input of date and
time. Moreover, the dynamic data engine may execute a staging phase
to generate a baseline for price sensitivity as a function of
historic price change data associated with the at least one parking
systems. The dynamic data engine may receive a price increase
granularity for the at least one parking systems and generate the
dynamic pricing data as a function of the price increase
granularity. The data from the at least one parking systems stored
in the central database includes at least one of usage date, usage
time, parking price, utilization rate, weather information,
competitive pricing, and foot traffic. In examples, the dynamic
data engine operatively generates the dynamic pricing data based on
a predefined interval of time, and in other examples, the dynamic
data engine operatively generates the dynamic pricing data in time
real time. The targeted promotions may include offers, messages, or
notifications based on the input preferences set up by the
merchants. The targeted promotion engine generates and sends the
target promotions based on information associated with the user
device. The information associated with the user device includes an
indication of a user entering or exiting a parking system. The
dynamic pricing data includes a plurality of prices for parking
spaces at the at least one parking systems for use by a user in an
unreserved scenario. The targeting promotion engine captures
feedback data from one or more user devices and determines a user
affinity for the targeted promotion and provide the feedback
information to the database.
[0009] Another example includes a parking management system
comprising one or more parking system devices each associated with
a parking system, one or more processors in communication with the
one or more parking system devices and one or more memory resources
storing instructions that, when executed by the one or more
processors, cause the one or more processors to, receive and store
pricing and utilization data from one or more parking system
devices in a database, generating a pricing and utilization model
for the one or more parking systems based on the received pricing
and utilization data, creating a list of price-utilization options
based on the pricing and utilization model for selection by a user,
and receiving a selection of a price-utilization option from the
list. The processor further receives optimization criteria and
generates one or more optimization options for the list of
price-utilization options. The optimization criteria include at
least one of revenue optimization or utilization optimization. The
one or more parking system devices include an input device that
receives information from a user device as a user enters or exits
the parking system. The information from the user device comprises
a scannable image.
[0010] Described is a method for a parking management system,
comprising generating a baseline sensitivity for a parking system
based on a history of price changes and utilization associated with
the price changes, creating a model for price and utilization of
the parking system based on the baseline sensitivity, receiving
information associated with at least one of foot traffic, events,
weather information, or user preferences, and utilizing the model
and the received information to determine dynamic price adjustments
for a predefined time interval. The method may further comprise
receiving flight information describing at least one of a number of
flights or number of passengers, and wherein utilizing the model
further comprises utilizing the flight information and the received
information to determine the dynamic price adjustments
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The disclosed method and system may be better understood by
reference to the following detailed description taken in connection
with the following illustrations, wherein:
[0012] FIG. 1 is a conceptual overview of a parking management
system for managing the operation of a parking system in accordance
with the present disclosure;
[0013] FIG. 2 illustrates a block diagram of an embodiment of the
parking management system in accordance with the present
disclosure;
[0014] FIG. 3 is a diagram of an embodiment of the parking
management system in accordance with the present disclosure;
[0015] FIGS. 4 and 5 illustrate a mobile device displaying a
portion of the parking management system thereon;
[0016] FIG. 6 illustrates a mobile device displaying a QR code in
accordance with one aspect of the present disclosure;
[0017] FIGS. 7 and 8 illustrate a gate of a parking system in
accordance with one aspect of the present disclosure;
[0018] FIGS. 9-24 illustrate images displayed on a graphical user
interface of a user device of the present disclosure; and
[0019] FIGS. 25-28 illustrate images displayed on a graphical user
interface of a merchant dashboard of the present disclosure.
DETAILED DESCRIPTION
[0020] Reference will now be made in detail to exemplary
embodiments of the present invention, examples of which are
illustrated in the accompanying drawings. It is to be understood
that other embodiments may be utilized and structural and
functional changes may be made without departing from the
respective scope of the invention. Moreover, features of the
various embodiments may be combined or altered without departing
from the scope of the invention. As such, the following description
is presented by way of illustration only and should not limit in
any way the various alternatives and modifications that may be made
to the illustrated embodiments and still be within the spirit and
scope of the invention.
[0021] The present disclosure provides a parking management system
100 that may collect, analyze, and generate predictive information
to assist with managing a parking system. The parking management
system 100 may collect and analyze various parking data such as
occupancy and turnover data related to utilization of parking
spaces from a particular parking system. The system may also
collect data from various other sources and generate predictive
information related to the management of the parking facility or
system. The collected data and generated prediction information may
be processed and provided to computing devices utilized by any of
parking operators, consumers, and merchants. The term "parking
system" may be used herein to describe a physical building, garage,
or facility containing many parking spaces, but may also refer to a
flat parking lot, a group of metered parking spaces on a street,
underground lot, or any group of parking spaces managed by a
parking operator or the ownership.
[0022] Embodiments described herein may generate prediction or
forecasting models for dynamic management of parking systems. The
models may be a function of user defined parameters or predefined
parameters. The parameters may include date/time, price,
utilization of available parking spots, weather information (e.g.,
average temperature, minimum/maximum temperature, precipitation,
etc.), competitive pricing information, foot traffic (e.g., number
of guests, number of flights or passengers, number of tickets sold
to an event, etc.), events (e.g., performances, sports events,
promotions at a mall, holidays, etc.), customer history, customer
preferences, or the like. It is noted that embodiments may include
a staging process or phase wherein historical information of price
changes are analyzed to establish a baseline of price sensitivity.
The historical information may additionally be utilized for model
generation. In some examples, an operator may not have a history of
price changes as there may have been a flat rate. As such, the
prices may be systematically adjusted and described systems may
establish a baseline for price sensitivity utilizing information
gathered during the adjustments.
[0023] Moreover, described embodiments may include a dynamic data
or pricing engine. The dynamic data engine may determine pricing
changes for a particular parking system. It is noted that different
parking systems may comprise different preferences in terms of
granularity (e.g., an airport may decide to adjust prices on a
weekly or monthly basis, whereas a mall may prefer price changes on
a daily basis or at peak times). In some embodiments, the dynamic
data engine may receive input or user preferences regarding the
granularity, acceptable price ranges (e.g., upper threshold, lower
threshold, unit step (e.g., increase or decrease by x units, where
x is a number and units is a unit of currency), optimization
criteria (e.g., revenue, utilization, etc.), or the like. Described
dynamic data engines may utilize these and other inputs to generate
models. The models may be updated via a feedback loop in real-time,
daily, or another time period based on historical information
(e.g., actual weather, actual utilization, actual revenue, etc.).
The models may predict utilization, revenue, or other metrics for a
particular date, time, and price based on parameters such as
weather forecasts, events, foot traffic, or other parameters
described herein. The models may select or provide an operator with
options for selection of a price level for a desired amount of
revenue or utilization. In some embodiments, the models may select
a price level based on optimization criteria selected by a
user.
[0024] In instances prices are updated at predefined intervals and
an operator approval of price changes may be required. In such
described systems, models may be updated using collected data from
a timer interval that has ended (e.g., past day, etc.). A
price-utilization list or options may then be generated as
described herein. This price-utilization list, and other additional
or optional information, may be presented to an operator and the
operator may select a price level for the next interval of time. In
some embodiments, a system may allow for reservations to be made in
advance by drivers. These reservations may be utilized in
generation of the price-utilization list for future time
intervals.
[0025] Some embodiments may utilize targeted campaigns, as
described here as well as elsewhere in the specification. In these
campaigns, described systems may generate notifications (e.g.,
promotional offers, messages, surveys, or the like) to drivers who
are entering or exiting a parking system, are near a parking
system, have recently entered or exited a parking system, or the
like. The notifications may be based on campaigns set up by an
entity (e.g., retail store, gas station, etc.) located at or near
the parking system. However, entities may utilize campaigns
regardless of their location. It is noted that notifications may be
generated via campaigns set by businesses or third parties (e.g.,
retail stores near a parking garage), customer information (e.g.,
demographic information, flight information, user preferences, user
feedback, etc.), time/day, events, or the like.
[0026] In at least one example, a driver may enter into a parking
lot and may utilize a user device to enter through a gate or notify
the system of their arrival. The system may record a time of entry
and may generate notifications to be sent to the user at i minutes
after entry, where i is a number. In some instances, a user may not
utilize a user device when entering a parking system. As such, the
user device's GPS, Wi-Fi connectivity status, or other location
information may alert the systems that the user has entered the
garage and a notification may be generated. In another aspect, the
user may receive a notification when within a specified range of a
business. The user's location may be determined based on GPS
information, Wi-Fi connectivity, beacons sending proximity, or the
like.
[0027] FIG. 1 illustrates a conceptual overview of an embodiment of
the parking management system 100. The system 100 may include a
management server 102, a parking system operator console 104, a
merchant console 106, signage 108, a parking gate control device
110, and a user device 120. The user device 120 may be a cell phone
72, lap top 74, tablet, deck top, or other device that may access
the network. Each of these devices may communicate through a
network 124 wherein the network 124 may include the internet,
cloud, Wi-Fi, radio transmission, or other medium as is generally
known in the art. Additionally, the architecture of the system 100
allows each of the devices to communicate with one another such
that information can be communicated and stored via the server 102
or other peripheral device. These devices of the parking management
system 100 track user data, generate dynamic pricing data, and
generate targeted promotions as to be described more fully
below.
[0028] A plurality of parking garage users 70 may access a user
facing portion of the parking management system through the user
device 120. FIGS. 9-24 illustrate dashboard views of the user
device application. A merchant 60 may operate the merchant console
106. FIGS. 25-29 illustrate dashboard views of the merchant console
application. A parking garage operator 50 may operate the parking
garage operator console 104 and may be associated with one or more
parking systems. The parking management system 100 may be
implemented over the server 102 or any one of the consoles 104, 106
and user device 120 to allow the operator 50, merchant 60 and users
70 to access particular applications of the system. The operator 50
may access both the merchant console application and the user
device application while the merchant may access the merchant
console application and the user may access the user device
application. The merchant console application may display different
information and include different functionality than the user
device application. Further, the system 100 may display information
on signage 108 via the network 124.
[0029] Such networks 124 may include wired and wireless networks,
including, but not limited to, a cellular network, a wide area
network (WAN) or a local area network (LAN). For example, the one
or more user device 120 may communicate with the server 102 using
virtually any desired wired or wireless technology, including but
not limited to: wireless fidelity (Wi-Fi), global system for mobile
communications (GSM), third generation partnership project (3GPP)
long term evolution (LTE), Zigbee, 802.XX wireless technologies,
legacy telecommunication technologies, BLUETOOTH.RTM., and
ultra-wideband (UWB) standard protocol technologies.
[0030] Aspects of the parking management system 100 may be
implemented by machine-executable components embodied within a
computer system in which a set of instructions can cause to execute
a device to perform any one or more aspects of the present
disclosure. The components described are examples only and do not
limit the scope of use or functionality of any hardware, software,
embedded logic component, or a combination of these components. As
illustrated by FIG. 1, each of the described consoles or devices
may include a processor, a memory, and a storage that communicate
with each other, and with other components. These consoles or
devices may also link a display, input devices, output devices,
storage devices and may interface various other components as is
known in the art. Each computer or component device may have any
suitable physical form, including but not limited to one or more
integrated circuits, printed circuit boards, laptop or notebook
computers, distributed computer systems, or mobile handheld
devices. Processors may contain a cache memory unit for temporary
storage of instructions, computer addresses, or data. Processors
may be configured to assist in execution of computer readable
instructions. The processors may execute non-transitory,
processor-executable instructions embodied in one or more tangible
computer-readable media such as storage devices or memory
medium.
[0031] The architecture of the system 100 may be implemented
through any of the devices identified in FIG. 1 but, in one
embodiment, may be located on the server 102. Referring to FIG. 2,
the parking management system 102 may include a processor 210 in
communication with storage 212, memory 214 and a central database
220. The central database 220 may receive and store a variety of
data as it relates to the parking systems. For example, the central
database 220 may include data such as the usage date 161, usage
time 162, parking price 163, utilization rate 164, weather
information 165 (e.g., precipitation metrics, temperature metrics,
weather forecasts, etc.), competitive pricing 166, foot traffic
167, and customer information 169 (e.g., customer preferences,
customer history, etc.). It is noted that the central database may
include other information that may be utilized to, for example,
determine dynamic pricing or promotions. For instance, the data may
include a number of flights/passengers at an airport/terminal, the
number of guests at events, holiday schedules, GPS information from
user devices, traffic information, construction information, or
customized data fields based on a specific region or entities.
Events may include sporting events, concerts, gatherings, or
promotions at shopping facilities. Further, the database 220 may
include a filter 190 that allows the database to be programmed to
sift through various ranges of data that may be collected by the
system 100. Each device may be configured to provide input data 230
that may be communicated to the processor 210 and central database
220. Additionally, each device is configured to receive output data
240 from the central database 220 and the processor 210. The output
data 240 may include a dynamic pricing data 242 and a targeted
promotion data 244 as will be described more fully herein.
[0032] Referring to FIG. 3, the parking management system 100 may
be stored and implemented through the server 102, network 124 and
one or more user devices 120. The server 102 may include various
computer-executable components, including, but not limited to, a
feedback component 300, dynamic data engine 310, targeted promotion
engine 320, and a communication component 304. The server 102 may
also include or otherwise be associated with at least one memory
214 that stores computer-executable components. The processor 210
may execute computer-executable commands stored in the memory 214.
A system bus 306 may couple the various components including, but
not limited to, the feedback component 300, the dynamic data engine
310, the communication component 304, the memory 330 and the
processor 220.
[0033] The communication component 304 may facilitate wireless
communication between the server 102 and the one or more user
devices 120, or between the server 102 and one or more other
external devices (not shown). For example, the communication
component 304 may receive feedback information from one or more
user devices 120 or one or more other devices (e.g., a gate control
device 110 or other sensors or information sources associated with
the user, etc.) and forward the feedback information to the
feedback component 300 for processing.
[0034] The communication component 304 may include hardware (e.g.,
a central processing unit (CPU), a transceiver, a decoder),
software (e.g., a set of threads, a set of processes, software in
execution) or a combination of hardware and software that
facilitates communicating information between the server 102 and
the one or more user devices 120. Further, although the embodiment
of the feedback component 300, the dynamic data engine 310, the
targeted promotion engine 320, and the communication component 304
are provided at the server 102, it should be appreciated that the
architecture of parking management system 100 is not so limited.
For example, one or more of the components included at the server
102 may be located at another device, such as another server
device, an intermediary device between the server device and the
one or more user devices 120, or at the one or more consoles,
etc.
[0035] FIGS. 4 through 6 illustrate a mobile device 72 displaying a
portion of the parking management system thereon. The mobile device
72 may display the user application to allow a user 70 to reserve
and purchase a parking space from a variety of parking systems as
illustrated by FIGS. 4, 5 and 9-18. However, before a user books a
parking space, the parking management system 100 may provide a user
various options based on generating and presenting dynamic pricing
data 242 and targeted promotion 244 by collecting and processing
data from a plurality of sources.
[0036] The dynamic data engine 310 generates the dynamic pricing
data 242 which may include a price presented to the user device 120
for reserving the parking space. Here, the dynamic data engine 310
may process different types and amounts of data available based on
prediction or forecasting models. The dynamic pricing data 242 may
be based on predicted utilization rates at various price levels
that allow the operator of the parking system to meet optimal
revenue versus utilization rates. The parameters that may be
considered by the dynamic data engine 310 includes: date, time of
day, price, utilization, weather, competitive data, foot traffic,
number of guests, and scheduled events. Weather data may be
provided by an available third party weather service. Scheduled
event data may be provided by various known or published calendars
or schedulers. This data may be analyzed to create a forecasted
price for a parking space based on an input of date and time as
desired by the user. The user may also be prompted to set up a user
account and to log into the application. The user may provide input
data 230 representative of a desired date, time, and location to
search for a parking space at a desired location of which multiple
parking systems may be able to provide parking spaces for
reservation. The system may be utilized to reserve a parking space
from a parking system at a future time or may be used during
unreserved scenarios. For example, a user may drive up to a gate at
a parking system and be granted access through pre-issued
credentials, or pull a ticket from the gate, or scan indicia at the
gate through the parking management system 100. In various
embodiments, the user may then be permitted to enter the gate and
park. It is noted that the user device may store information
associated with where the user parks, such as an address, garage
name, parking spot number, parking garage level, or the like. This
information may be entered by a user manual, or a user may scan a
code or other indicia at a particular parking spot.
[0037] According to other embodiments, the user may receive a code
to enter into a gate or point of sale. The code may be periodically
updated or uniquely generated for a particular transaction. For
example, some gates may comprise an interface such as key pads or
touch screens. The user may receive a code and may enter the code
via the interface. In other examples, the user may utilize the user
device 120 to enter the code or click an activation button. The
user devices may transmit this information to a gate directly or
via a server that is in communication with the gate. Moreover,
other embodiments may utilize radio frequency identification (RFID)
devices, BLUETOOTH, Beacon devices, such as Near Field
Communication (NFC) devices. Some embodiments may utilize a radio
access network (RAN), e.g., Wi-Fi, Wi-Fi Direct, global system for
mobile communications, universal mobile telecommunications systems,
worldwide interoperability for microwave access, enhanced general
packet radio service, third generation partnership project long
term evolution (3G LTE), fourth generation long term evolution (4G
LTE), third generation partnership project 2, ultra mobile
broadband, high speed packet access, x.sup.th generation long term
evolution, or another IEEE 802.XX technology. Furthermore,
embodiments may utilize wired communications. In an example, an NFC
device may comprise stored information, such as in a memory (e.g.,
read-only memory (ROM), random access memory (RAM), electrically
erasable programmable read-only memory (EEPROM), or various other
types of memory). In an example, an NFC component may include an
NFC tag and an NFC emitter. The NFC tag and NFC emitter may each
include one or more antennae that may communicate with a reader of
a gate or garage. In one example, the user device 120 may utilize
an NFC device to generate a code or signal that is received by the
gate's reader. The gate verifies that the code is valid and may
allow the user to pass through the gate. Moreover, it is further
noted that stand-alone devices may comprise an NFC component that
may communicate with the gate. For instance, an NFC device may
comprise a plastic housing that houses an NFC antenna and NFC chip.
The stand-alone NFC device may operatively communicate with the
user device 120 to receive a code and may relay this code to a
reader at a gate.
[0038] In a staging phase, the dynamic data engine 310 may analyze
historic data specific to the parking system regarding whether
rates have been flat or have changed and specifically if an
operator of a particular parking system has established a baseline
for price sensitivity.
[0039] In one embodiment, the dynamic data engine 310 may be
programmed to generate various price granularities. For example,
price granularity may include a generated price for a specific
parking system, such as an airport, that modifies prices on a
weekly or monthly basis, whereas another parking system, such as a
shopping mall, may decide to modify prices on a daily basis.
[0040] In one embodiment, the dynamic data engine 310 may be
programmable by the operator of the parking system to account for
granularity, range of minimum and maximum price range, unit step
increase or decrease, and optimization criteria. The optimization
criteria allow an operator or garage owner to specify criteria for
setting prices dynamically. As an example, an operator may specify
one or more aspects to which price optimization should utilize. In
some embodiments, an owner may wish to maximize revenue or maximize
utilization. Maximizing revenue may set prices irrespective of how
much or how little a parking lot is utilized. Maximizing
utilization may set prices to increase utilization, which may
require reduce prices and revenue.
[0041] It is noted that the operator may choose desired revenue
ranges, utilization ranges, or the like, rather than picking to
maximize on a particular optimization criteria. The dynamic data
engine 310 may generate one or more options to achieve results
within the selected ranges, and may present the options to the
user. The user may select an option or may allow the dynamic data
engine 310 to automatically select an option.
[0042] Additionally or alternatively, the operator may select to
alter optimization criteria based on dates, times, utilization
(e.g., maximize utilization until 80% of spots are full, then
switch to maximization of revenue), or the like. For instance, the
operator may select to optimize utilization during a particular
time or date (e.g., weekends, weekdays, nights, mornings, etc.) and
optimize revenue a different time or date. Moreover, the operator
may select to override or opt out of dynamic prices for a given
time period, may provide early bird special rates, or the like.
[0043] The optimization criteria may be different for each operator
of each parking system. An operator's preferred optimization
criteria may be selected by the operator of the specified parking
system. The dynamic data engine 310 may generate a predictive
profile that establishes an optimal price at a particular time for
a selected parking system to facilitate an acceptable level of
parking space utilization, revenue generation, or other
optimization metric that may be specified by a user. The historic
predictive profile may be recorded. Based on inputs provided by the
operator of the parking system, the dynamic data engine may operate
in a real-time mode as follows: [0044] a. The dynamic data engine
310 generates a price-utilization list that includes information
reflective of a lowest acceptable price to a highest acceptable
price based on unit step increments. [0045] b. The dynamic data
engine 310 may predict the utilization (amount of parking spaces
occupied) based on its analysis of historical data collected and
stored in the memory. These predictions may incorporate weather
data and event data from third party sources. [0046] c. The
utilization prediction for a current price level may be recorded.
[0047] d. A price profile is selected by the operator from the
price-utilization list that meets the optimization criteria. [0048]
e. The dynamic data engine 310 is updated by the feed back
component 300 which incorporates real time data to update the
price-utilization list and/or the optimization criteria. The
real-time mode of the dynamic pricing engine may continually track
this information for a parking price for each of the unit step
increment amounts set between the lowest acceptable price and the
highest acceptable price. [0049] f. A user may order a parking
space for a selected date and time in a desired area. [0050] g. The
user application may offer dynamic pricing data 242 to the user.
The dynamic pricing data 242 generated by the dynamic data engine
310 as selected by the operator from the price-utilization list and
as updated by the feedback component 300 for a plurality of parking
systems in a desired area. [0051] h. The user may select a parking
space from the dynamic pricing data 242 to reserve a parking
space.
[0052] In another embodiment, the dynamic data engine 310 may
operate in a predefined interval mode where parking space prices
may be updated at predefined intervals of time or where an operator
may approve a generated price change before it is offered by the
parking management system 100 to the user device 120. Based on
inputs provided by the operator of the parking system, the dynamic
data engine may operate in the interval mode as follows: [0053] a.
The dynamic data engine 310 processes the data collected and
records parking space pricing and utilization data for a specified
interval of time. [0054] b. The dynamic data engine 310 generates a
price-utilization list that includes information by starting with a
lowest acceptable price to a highest acceptable price based on unit
step increments. [0055] c. For a desired date and time, the dynamic
data engine 310 may predict a range of prices or a price level
profile for parking spaces for the specified parking system. These
predictions may incorporate weather data and event data from third
party sources. The range of prices may be presented to the operator
for selection of the price level or price level profile for the
next interval. [0056] d. For cases where a user may make a
reservation in advance, the selected price level or price level
profile may be made for subsequent time intervals (e.g. for the
next 12 months, or a time period established by the operator.).
[0057] e. A user may order a parking space for a selected date and
time in a desired area. [0058] f. The user application may offer
dynamic pricing data 242 to the user. The dynamic pricing data 242
generated by the dynamic data engine 310 as selected by the
operator from the price-utilization list for a plurality of parking
systems in a desired area. [0059] g. The user may select a parking
space from the dynamic pricing data 242 to reserve a parking
space.
[0060] In an aspect, dynamic data engine 310 may utilize artificial
intelligence, statistical models, or other processes and/or
algorithms. In embodiments, dynamic data engine 310 may utilize
classifiers that map an attribute vector to a confidence that the
attribute belongs to a class. For instance, dynamic data engine 310
may input attribute vector, x=(x1, x2, x3, x4, xn) mapped to
f(x)=confidence(class). Such classification can employ a
probabilistic and/or statistical based analysis (e.g., factoring
into the analysis affinities and revenue or utilization attributes)
to infer an action that a user desires to be automatically
performed, adjustments to be made, or the like. In various
embodiments, dynamic data engine 310 may utilize other directed and
undirected model classification. Such approaches include, e.g.,
naive Bayes, Bayesian networks, decision trees, neural networks,
fuzzy logic models, and probabilistic classification models
providing different patterns of independence. Classification may
also include statistical regression that is utilized to develop
models of priority. Further still, classification may also include
data derived from another system, such as cameras, point of sales
systems, GPS systems, or the like.
[0061] In accordance with various aspects of the subject
disclosure, an example embodiment may employ classifiers that are
explicitly trained (e.g., via a generic training data) as well as
implicitly trained (e.g., via observing a user's behavior, user
preferences, historical information, receiving extrinsic
information). For example, support vector machines may be
configured via a learning or training phase within a classifier
constructor and feature selection module. Thus, the classifier(s)
may be used to automatically learn and perform a number of
functions, including but not limited to determining dynamic price
adjustments, price adjustments based on environmental or external
factors (e.g., weather, traffic, events, etc.), targeted
advertising parameters, or the like. This learning may be on an
individual basis, i.e., based solely on a single user, or may apply
across a set of or the entirety of the user base. Information from
the users may be aggregated and the classifier(s) may be used to
automatically learn and perform a number of functions based on this
aggregated information. The information may be dynamically
distributed, such as through an automatic update, a notification,
or any other method or means, to the entire user base, a subset
thereof, or to an individual user.
[0062] In one embodiment, the targeted promotion engine 320 may
identify, generate and send targeted promotions including offers,
messages and/or notifications to the user device based on the input
preferences set up by the merchants. The merchants may be located
on or adjacent to premises of the parking system but this
disclosure does not limit the location of the merchants as any
merchant may be contemplated herein, for example, online retailers,
or other remotely located businesses interested in offering
promotions to targeted customers. In particular, a targeted
promotion may be presented to the user via the user device 120 as
the user enters the parking system, is approaching the parking
system, or is in a defined area proximate to the parking system.
FIGS. 19 and 20 illustrate a user application that has been
provided targeted promotions from company 1, company 2, and company
3.
[0063] Because the user accesses the application program via the
user device 120 to enter the parking system, the parking management
system 100 may receive the time and date of entry. The user may
receive targeted promotion notifications within a predetermined
time after their entry into the parking garage. Alternatively, GPS
functionality built into the user's smartphone or other proximity
sensing technologies may be used to determine whether the user has
entered into the parking system, is approaching, or adjacent to the
parking system.
[0064] Once the user enters within the range of the merchants on
premises, the user may further receive the targeted promotion data.
This may be done by using the GPS functionality built into the
user's smartphones, or other proximity sensing technology. The
targeted promotion comprises an offer, messages, or notification
sent to user devices 120 that are associated with the parking
management system 100 to park a vehicle in a space of a parking
system.
[0065] In one embodiment, the targeted promotion engine 320 may be
programmable by the merchants with access to merchant consoles. The
merchants may typically be located on the premises of the parking
system or in proximity thereto. The targeted promotion engine 320
may analyze data from user devices and the central database 220 to
generate targeted promotions 244. FIGS. 25-29 illustrate a
dashboard for a merchant application that has been implemented to
be accessed by the merchant at the merchant console. The targeted
promotion 244 may be based on various user data including the time
of the day, weather, location, date or other parameter such as a
demographic of the user, flight information, booking information,
and user preferences.
[0066] The parking management system 100 may be employed to use
hardware and/or software to solve problems that are highly
technical in nature, that are not abstract and that may not be
performed as a set of mental acts by a human. For example, the
parking management system 100 may be employed to use hardware
and/or software to perform operations including affective computing
related to automatically detecting and recognizing user
information, correlating the user information with parking data
(e.g. price) associated with a specific price sensitivity of the
user, and automatically selecting and providing targeted promotion
for the user. Further, some of the processes performed may be
performed by the dynamic data engine 310 and targeted promotion
engine 320 which are specialized computers for carrying out defined
tasks. These tasks facilitate receiving and correlating user
interaction information with a respective merchant to automatically
determine merchants of the targeted promotion that may be
considered effective. The parking management system 100 may further
provide technical improvements to live and internet based learning
systems, such as artificial intelligence, by improving processing
efficiency among processing components associated with selecting
and providing dynamic pricing data and targeted promotion data
associated with an advertisement in real-time based on a user's
current price sensitivity and preferences.
[0067] In various embodiments, the server 102 and the one or more
user devices 120 may operate in a server/client relationship
wherein a targeted promotion associated with an advertisement or
marketing deal is provided to the one or more user devices 120. The
targeted promotion may be generated from feedback information
regarding the location, history, and preferences for a product
offered by a merchant in proximity to a selected parking system.
The feedback information may also be generated from a survey
procured by the system prompting the user to respond to various
questions regarding preference.
[0068] The one or more user devices 120 may receive the dynamic
price data and the targeted promotion provided by the server 102.
In some implementations, the one or more user devices 120 may also
facilitate capturing feedback information regarding the respective
users' need or desire for the targeted promotion and provide the
feedback information to the server 102.
[0069] In at least one embodiment, the server 102 may initiate an
exit survey or promotion process via the user devices 120. It is
noted, however, that user devices 120 may initiate the exit survey
or promotional process and may send results or other information to
the server 102. As an example, a user may exit a parking garage and
utilize a bar code, NFC, or the like at an exit point. The user
device 120 may identify that the user is exiting and may generate a
notification or alert. The notification may comprise audio, video,
tactile, or other notifications. In an embodiment, the notification
may comprise an exit survey that prompts the user for feedback
regarding satisfaction, improvements, suggestions, ratings, or the
like. The survey may prompt the user to provide information
regarding airlines, an airport, the parking facility, retail
stores, restaurants or other food vendors, or the like. It is noted
that the system may provide an incentive to the user to complete
the survey, such as promotional codes, discounts, or the like. In
some examples, the notifications or surveys may be provided on
behalf of third parties, such as airlines, airports, retailers, or
restaurants.
[0070] Additionally or alternatively, the user devices 120 may
receive or generate notifications regarding promotions or
advertisements for establishments near the parking garage. For
example, when leaving an airport, the user devices 120 may generate
notifications regarding nearby gas stations, convenience stores,
hotels, restaurants, attractions, or the like. It is noted that the
system may utilize a physical proximity of an establishment to the
parking garage to select the establishment for an advertisement or
notification. For example, a list of advertisements may be
generated by the user devices 120. Establishments may be presented
in an order based on proximity the parking garage. In other
examples, the user may define a distance (e.g., establishments
within 10 miles) for which it desires to receive notifications. It
is noted, however, that some embodiments may generate notifications
or advertisements independent of distances.
[0071] Notifications or surveys may be generated at times other
than entry/exit of a garage. For instance, the user device 120 may
generate notifications when a user is not driving, is idle, or upon
request by a user. In an example, the user may be on a return
flight to an airport. When the user arrives at the airport, the
user may utilize the user device 120 to look up a location where
the user parked (e.g., floor, parking spot number, etc.). The user
device 120 may generate notifications or surveys at this time as
the user is not driving.
[0072] Embodiments of the present invention may be a system, a
method, an apparatus and/or a computer program product at any
possible technical detail level of integration. The computer
program product may include a computer readable storage medium (or
merchant) having computer readable program instructions thereon for
causing a processor to carry out aspects of the present invention.
The computer readable storage medium may be a tangible device that
may retain and store instructions for use by an instruction
execution device. The computer readable storage medium may be, for
example, but is not limited to, an electronic storage device, a
magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium may
also include the following: a portable computer diskette, a hard
disk, a random access memory (RAM), a read-only memory (ROM), an
erasable programmable read-only memory (EPROM or Flash memory), a
static random access memory (SRAM), a portable compact disc
read-only memory (CD-ROM), a digital versatile disk (DVD), a memory
stick, a floppy disk, a mechanically encoded device such as
punch-cards or raised structures in a groove having instructions
recorded thereon, and any suitable combination of the foregoing. A
computer readable storage medium, as used herein, is not to be
construed as being transitory signals per se, such as radio waves
or other freely propagating electromagnetic waves, electromagnetic
waves propagating through a waveguide or other transmission
merchant (e.g., light pulses passing through a fiber-optic cable),
or electrical signals transmitted through a wire.
[0073] Computer readable program instructions described herein may
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device. Computer readable program instructions
for carrying out operations of various aspects of the present
invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, configuration data for integrated
circuitry, or either source code or object code written in any
combination of one or more programming languages. The computer
readable program instructions may execute entirely on the user's
computer, partly on the user's computer, as a stand-alone software
package, partly on the user's computer and partly on a remote
computer or entirely on the remote computer or server.
[0074] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, may be implemented by computer readable
program instructions. These computer readable program instructions
may be provided to a processor of a general purpose computer,
special purpose computer, or other programmable data processing
apparatus to produce a machine, such that the instructions, which
execute via the processor of the computer or other programmable
data processing apparatus, create means for implementing the
functions/acts specified in the flowchart and/or block diagram
block or blocks. These computer readable program instructions may
also be stored in a computer readable storage medium that may
direct a computer, a programmable data processing apparatus, and/or
other devices to function in a particular manner, such that the
computer readable storage medium having instructions stored therein
comprises an article of manufacture including instructions which
implement aspects of the function/act specified in the flowchart
and/or block diagram block or blocks.
[0075] Referring to FIGS. 9-24, the parking management system 100
may include dashboard screen shots that are displayed on the user
device 120 of the present disclosure. The app may be downloaded on
the user device as illustrated by FIG. 9 and the user may sign into
the user application as illustrated by FIGS. 10 and 11. FIG. 12
illustrates a desired area to park having displaying dynamic price
data for three parking systems based on the date and time input by
the user. FIG. 13 illustrates a booking confirmation dashboard.
FIGS. 14-15 illustrate payment screens while FIGS. 16 and 17
illustrate confirmations and reservations respectively. FIG. 18
illustrates indicia, in the form of a quick response (QR) code,
that may be presented to the parking gate control device 110 by the
user to access the parking system. See also FIGS. 6-8. FIG. 19
illustrates targeted promotions from various companies that may be
available to the user. FIG. 20 illustrates a selected promotion and
indicia, in the form of a QR code, that may be presented to the
merchant for purchase. The indicia may be a code or other scannable
image such as a bar code (e.g., 2-dimensional, 3-dimensional,
etc.), characters, or numbers and this disclosure is not limited.
FIGS. 21-23 illustrate other screenshots regarding a user's account
and password while FIG. 24 illustrates an application support
screen.
[0076] With respect to FIGS. 25-28, the merchant dashboard is
illustrated that may be accessible by the merchant to provide
various inputs related to the duration and type of promotion that
may be offered. The merchant application may display information
received from the targeted promotion engine 320 and allow the
merchant to review data and provide inputs thereto. The merchant
may schedule a promotion for a specific duration of time as well as
track existing and historical promotions or offer new
promotions.
[0077] The descriptions of the various embodiments have been
presented for purposes of illustration, but are not intended to be
exhaustive or limited to the embodiments disclosed. Many
modifications and variations will be apparent to those of ordinary
skill in the art without departing from the scope and spirit of the
described embodiments. The terminology used herein was chosen to
best explain the principles of the embodiments, the practical
application or technical improvement over technologies found in the
marketplace, or to enable others of ordinary skill in the art to
understand the embodiments disclosed herein.
[0078] Although the embodiments of the present invention have been
illustrated in the accompanying drawings and described in the
foregoing detailed description, it is to be understood that the
present invention is not to be limited to just the embodiments
disclosed, but that the invention described herein is capable of
numerous rearrangements, modifications and substitutions without
departing from the scope of the claims hereafter. The claims as
follows are intended to include all modifications and alterations
insofar as they come within the scope of the claims or the
equivalent thereof.
* * * * *