Iot data fusion and collaborative control management system based on edge computing gateway

Abstract

The application discloses an Internet of Things data fusion and cooperative control management system based on an edge computing gateway, relates to the technical field of edge computing, and sets a data collection module to monitor illegal behaviors of red light running and overspeeding in road traffic in real time; and saves the monitoring picture in an edge data storage module of each region; sets an edge data processing module to identify human feature data and vehicle feature data in illegal behaviors; sets a regional data storage module to pre-save identity information and vehicle information of permanent urban residents; and sets a regional data query module to query real identities of personnel corresponding to the human feature data and the vehicle feature data in the city or across cities; and the problems of slow processing speed caused by large processing amount of traffic illegal data are solved.

Description

Technical Field

[0001] This invention belongs to the field of edge computing and relates to data management technology, specifically an IoT data fusion and collaborative control management system based on an edge computing gateway. Background Technology

[0002] This refers to an open platform that integrates core capabilities such as networking, computing, storage, and applications, located closer to the source of the data or object, to provide services at the nearest edge. Its applications are initiated at the edge, resulting in faster network service responses and meeting the industry's basic needs in areas such as real-time business operations, application intelligence, security, and privacy protection.

[0003] Due to the vast geographical coverage of traffic road data and the strong demand for timely data processing, edge computing has become an important technical means to solve the problem of timely traffic violation processing. However, current road edge computing systems do not yet have the means to process individual traffic violations, and the use of a unified query method for querying violators and vehicles results in low efficiency.

[0004] To address this, an IoT data fusion and collaborative control management system based on edge computing gateways is proposed. Summary of the Invention

[0005] This invention aims to address at least one of the technical problems existing in the prior art. To this end, this invention proposes an IoT data fusion and collaborative control management system based on an edge computing gateway. This system includes a data collection module that monitors red-light running and speeding violations in real time; it stores the monitoring footage in edge data storage modules for each area; an edge data processing module that identifies human and vehicle characteristic data in the violations; an area data storage module that pre-stores the identity information of the city's permanent residents and vehicle information; and an area data query module that queries the real identities of individuals corresponding to human and vehicle characteristic data within the city or across cities. This solves the problem of slow processing speed caused by the massive volume of traffic violation data.

[0006] To achieve the above objectives, an IoT data fusion and collaborative control management system based on an edge computing gateway is proposed according to an embodiment of the first aspect of the present invention, including a data collection module, an edge data storage module, an edge data processing module, a regional data storage module, and a regional data query module; wherein the data collection module, the edge data storage module, the edge data processing module, the regional data storage module, and the regional data query module are connected wirelessly and / or electrically.

[0007] The data collection module is mainly used to acquire real-time image data of pedestrians and vehicles walking or driving on traffic roads.

[0008] The data collection module includes image capture devices and electronic speed measurement devices used in urban road traffic. The image capture devices on traffic light poles are electrically connected to the traffic lights. When the traffic light is red, they capture real-time image data of pedestrians and vehicles at the intersection. The image capture devices installed on the street light poles are electrically connected to the electronic speed measurement devices. The electronic speed measurement devices calculate the speed of passing vehicles in real time, while the image capture devices connected to the electronic speed measuring devices capture the characteristic data of passing vehicles simultaneously. Each image capture device and electronic speed measurement device has a unique physical number.

[0009] The data collection module sends human feature data, vehicle feature data, and vehicle speed acquired by the image capture device and electronic speed measuring device to the edge data storage module in real time.

[0010] Edge computing involves placing a separate computing center in different areas of a city. Each computing center includes data processing equipment and data storage equipment to store the data to be processed. The location of each computing center is determined based on the actual traffic data volume in each area of ​​the city. Furthermore, the computing power and storage capacity of the data processing equipment and data storage equipment in each computing center are determined based on the actual traffic data volume in the area where the computing center is located.

[0011] The edge data storage module is a data storage device for each computing center;

[0012] The edge data storage module receives road images and vehicle speed data sent by the data collection module in the area in real time; the edge data storage module also stores the physical number of each image capture device and electronic speed measuring device in the area, as well as the road segment corresponding to each physical number; the edge data storage module saves the road images and vehicle speed data in the data storage device in order of time and road segment; the edge data storage module sends the data to the edge data processing module for processing in real time;

[0013] The edge data processing module is a data processing device in each computing center;

[0014] In a preferred embodiment, the edge data processing module processes the road surface images and vehicle speed data sent in real time by the data storage module; specifically, it includes the following steps:

[0015] Step S1: For the road image captured by the image capture device corresponding to the traffic light, the edge data processing module uses an image target recognition algorithm to obtain pedestrians and vehicles in the image, and determines whether the pedestrians and vehicles are in the road; if they are in the road, proceed to step S2; otherwise, no processing is performed.

[0016] Step S2: The edge data processing module obtains human feature data and vehicle feature data of pedestrians and vehicles in the road from the image; wherein, human feature data may be face data; vehicle feature data may be vehicle license plate number;

[0017] Step S3: The edge data processing module sends human feature data and vehicle feature data to the regional data query module;

[0018] Step S4: For the road surface image captured by the image capture device corresponding to the electronic speed measuring device, the data processing module searches for data in the data measured by the electronic speed measuring device that the vehicle speed is greater than the vehicle speed threshold v; and obtains the speed measurement time; obtains the road surface image at the corresponding time according to the speed measurement time of the electronic speed measuring data; and obtains the vehicle feature data of the passing vehicles from the road surface image at that time.

[0019] Step S5: The edge data processing module sends the vehicle feature data and the corresponding vehicle speed to the regional data query module;

[0020] The regional data storage module is mainly used to store population information and vehicle registration information for each city.

[0021] A secondary edge computing network is set up in each city; the secondary edge computing network includes data storage devices and data processing programs with data query functions; the secondary edge computing network is connected to the computing center in each region of the city via a wireless network; and the secondary edge computing networks between different cities are also connected via a wireless network.

[0022] The regional data storage module is a data storage device in a secondary edge computing network;

[0023] The regional data storage module pre-stores the human characteristic data and vehicle characteristic data of the permanent residents of the city. Specifically, each regional data storage module pre-collects the human characteristic data, real names, and real mobile phone numbers of the city's population. At the same time, each regional data storage module pre-collects the vehicle characteristic data of the city's vehicles, as well as the real names and real mobile phone numbers of the corresponding drivers. The regional data storage module sends the collected data to the regional data query module.

[0024] The regional data query module is mainly used to query and obtain the real identity and mobile phone number of the corresponding personnel and drivers based on human body feature data and vehicle feature data.

[0025] The regional data query module queries the driver's real identity and mobile phone number through the following steps:

[0026] Step P1: For human feature data, match it with the human feature database stored in the city area data storage module; if a match is found, obtain the real name and real mobile phone number of the corresponding person, and send traffic violation information to the mobile phone number; otherwise, proceed to step P2.

[0027] Step P2: Broadcast the human body feature data to the regional data query modules of all cities. Each city's regional data query module will then match the data with the human body feature database stored in the regional data storage module. If a match is found, the corresponding person's real name and real mobile phone number will be obtained, and traffic violation information will be sent to that mobile phone number.

[0028] Step P3: For vehicle feature data, obtain the city identifier from the vehicle feature data; and send the vehicle feature data to the corresponding city's regional data query module; the corresponding city's regional data query module queries the real name and real mobile phone number of the driver corresponding to the vehicle feature data from the regional data storage module; and sends traffic violation information to the mobile phone number.

[0029] The traffic violation information includes the name of the violator, the reason for the violation, and the section of road where the violation occurred.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] This invention includes a data collection module that monitors red-light running and speeding violations in real time; it stores the monitoring footage in an edge data storage module for each area; an edge data processing module that identifies human and vehicle characteristics in the violations; an area data storage module that pre-stores the identity information of the city's permanent residents and vehicle information; and an area data query module that queries the real identities of individuals corresponding to human and vehicle characteristics within the city or across cities. This invention solves the problem of slow traffic violation data processing speed. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the present invention. Detailed Implementation

[0033] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] like Figure 1 As shown, the IoT data fusion and collaborative control management system based on edge computing gateway includes a data collection module, an edge data storage module, an edge data processing module, a regional data storage module, and a regional data query module; wherein the data collection module, edge data storage module, edge data processing module, regional data storage module, and regional data query module are connected wirelessly and / or electrically.

[0035] The data collection module is mainly used to acquire real-time image data of pedestrians and vehicles walking or driving on traffic roads.

[0036] In a preferred embodiment, the data collection module includes image capture devices and electronic speed measurement devices involved in urban road traffic. The image capture devices can be surveillance cameras installed on streetlights or traffic light poles. The electronic speed measurement devices are installed on both sides of the road. The image capture devices on the traffic light poles are electrically connected to the traffic lights. When the traffic light is red, they capture real-time image data of pedestrians and vehicles at the intersection. The image capture devices installed on the streetlight poles are electrically connected to the electronic speed measurement devices. The electronic speed measurement devices calculate the speed of passing vehicles in real time, and the image capture devices connected to the electronic speedometer simultaneously capture the characteristic data of passing vehicles. The human characteristic data can be facial data; the vehicle characteristic data can be license plate numbers; each image capture device and electronic speed measurement device has a unique physical number.

[0037] The data collection module sends human feature data, vehicle feature data, and vehicle speed acquired by the image capture device and electronic speed measuring device to the edge data storage module in real time.

[0038] It is understandable that edge computing involves placing a separate computing center in different areas of a city. Each computing center includes data processing equipment and data storage equipment to store the data to be processed. The data processing equipment is pre-installed with data processing programs to process the IoT data of the area. The location of each computing center is determined based on the actual traffic data volume in each area of ​​the city. Furthermore, the computing power and storage capacity of the data processing equipment and data storage equipment in each computing center are determined based on the actual traffic data volume in the area where the computing center is located.

[0039] The edge data storage module is a data storage device for each computing center;

[0040] In a preferred embodiment, the edge data storage module receives road surface images and vehicle speed data sent by the data collection module in the area in real time; the edge data storage module also stores the physical number of each image capture device and electronic speed measuring device in the area, as well as the road segment corresponding to each physical number; the edge data storage module saves the road surface images and vehicle speed data in the data storage device in order of time and road segment; the edge data storage module sends the data to the edge data processing module for processing in real time;

[0041] The edge data processing module is a data processing device in each computing center;

[0042] In a preferred embodiment, the edge data processing module processes the road surface images and vehicle speed data sent in real time by the data storage module; specifically, it includes the following steps:

[0043] Step S1: For the road image captured by the image capture device corresponding to the traffic light, the edge data processing module uses an image target recognition algorithm to obtain pedestrians and vehicles in the image, and determines whether the pedestrians and vehicles are in the road; if they are in the road, proceed to step S2; otherwise, no processing is performed.

[0044] Step S2: The edge data processing module obtains human feature data and vehicle feature data of pedestrians and vehicles in the road from the image; wherein, human feature data may be face data; vehicle feature data may be vehicle license plate number;

[0045] Step S3: The edge data processing module sends human feature data and vehicle feature data to the regional data query module;

[0046] Step S4: For the road surface image captured by the image capture device corresponding to the electronic speed measuring device, the data processing module searches for data in the data measured by the electronic speed measuring device that the vehicle speed is greater than the vehicle speed threshold v; and obtains the speed measurement time; obtains the road surface image at the corresponding time according to the speed measurement time of the electronic speed measuring data; and obtains the vehicle feature data of the passing vehicles from the road surface image at that time.

[0047] Step S5: The edge data processing module sends the vehicle feature data and the corresponding vehicle speed to the regional data query module;

[0048] The regional data storage module is mainly used to store population information and vehicle registration information for each city.

[0049] Understandably, given the large national population, storing all national data in a single database would inevitably lead to slow query speeds and excessively long data transmission times. Therefore, it is considered to set up a secondary edge computing network in each city. This secondary edge computing network includes data storage devices and data processing programs with data query capabilities. The secondary edge computing network is connected to the computing center in each region of the city via a wireless network. Furthermore, the secondary edge computing networks between different cities are also connected via a wireless network.

[0050] The regional data storage module is a data storage device in a secondary edge computing network;

[0051] In a preferred embodiment, the regional data storage module pre-stores the anthropometric data and vehicle characteristic data of the permanent residents of the city; specifically, each regional data storage module pre-collects the anthropometric data, real names, and real mobile phone numbers of the city's residents; simultaneously, each regional data storage module pre-collects the vehicle characteristic data and the real names and real mobile phone numbers of the corresponding drivers of the city's vehicles; the regional data storage module sends the collected data to the regional data query module;

[0052] The regional data query module is mainly used to query and obtain the real identity and mobile phone number of the corresponding personnel and drivers based on human body feature data and vehicle feature data.

[0053] In a preferred embodiment, the regional data query module queries the driver's real identity and mobile phone number by including the following steps:

[0054] Step P1: For human feature data, match it with the human feature database stored in the city area data storage module; if a match is found, obtain the real name and real mobile phone number of the corresponding person, and send traffic violation information to the mobile phone number; otherwise, proceed to step P2.

[0055] Step P2: Broadcast the human body feature data to the regional data query modules of all cities. Each city's regional data query module will then match the data with the human body feature database stored in the regional data storage module. If a match is found, the corresponding person's real name and real mobile phone number will be obtained, and traffic violation information will be sent to that mobile phone number.

[0056] Step P3: For vehicle feature data, obtain the city identifier from the vehicle feature data; and send the vehicle feature data to the corresponding city's regional data query module; the corresponding city's regional data query module queries the real name and real mobile phone number of the driver corresponding to the vehicle feature data from the regional data storage module; and sends traffic violation information to the mobile phone number.

[0057] The traffic violation information includes the name of the violator, the reason for the violation, and the section of road where the violation occurred.

[0058] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An IoT data fusion and collaborative control management system based on an edge computing gateway, characterized in that, It includes a data collection module, an edge data storage module, an edge data processing module, a regional data storage module, and a regional data query module; the modules are connected wirelessly and / or electrically. The data collection module is used to acquire real-time image data of pedestrians and vehicles walking or driving on traffic roads; the data collection module sends the collected data to the edge data storage module in real time. The edge data storage module is a data storage device for each computing center; the edge data storage module sends data to the edge data processing module for processing in real time. The edge data processing module is a data processing device for each computing center; the edge data processing module processes the road surface images and vehicle speed data sent in real time by the data storage module; A secondary edge computing network is set up in each city. The secondary edge computing network is connected to the computing center in each region of the city via a wireless network. The secondary edge computing networks between different cities are also connected via a wireless network. The regional data storage module is a data storage device in the secondary edge computing network; the regional data storage module is used to store population information and vehicle registration information for each city; the regional data storage module sends the collected data to the regional data query module; The regional data query module is used to query and obtain the real identity and mobile phone number of the corresponding person and driver based on human feature data and vehicle feature data. The query of the regional data query module includes the following steps: For human feature data, it is matched with the human feature database stored in the city area data storage module; if a match is found, the real name and real mobile phone number of the corresponding person are obtained; otherwise, the human feature data is broadcast to the area data query module of all cities for matching. For vehicle feature data, obtain the city identifier from the vehicle feature data; and send the vehicle feature data to the corresponding city's regional data query module for querying.

2. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, The data collection module includes image capture devices and electronic speed measurement devices used in urban road traffic; the image capture devices on traffic light poles are electrically connected to the traffic lights; when the traffic lights are red, they capture real-time image data of pedestrians and vehicles at the intersection; the image capture devices installed on the street light poles are electrically connected to the electronic speed measurement devices; the electronic speed measurement devices calculate the speed of passing vehicles in real time, and the image capture devices connected to the electronic speed measuring devices capture the characteristic data of passing vehicles synchronously; each image capture device and electronic speed measurement device has a unique physical number.

3. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, Edge computing involves placing a separate computing center in different areas of a city. Each computing center includes data processing equipment and data storage equipment to store the data to be processed. The location of each computing center is determined based on the actual traffic data volume in each area of ​​the city. Furthermore, the computing power and storage capacity of the data processing equipment and data storage equipment in each computing center are determined based on the actual traffic data volume in the area where the computing center is located.

4. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, The edge data storage module receives road images and vehicle speed data sent by the data collection module in the area in real time; the edge data storage module also stores the physical number of each image capture device and electronic speed measuring device in the area, as well as the road segment corresponding to each physical number. The edge data storage module stores road surface images and vehicle speed data in the data storage device according to time and road segment order; The edge data storage module sends data to the edge data processing module in real time for processing.

5. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, The edge data processing module processes the data stored in the data storage module through the following steps: Step S1: For the road image captured by the image capture device corresponding to the traffic light, the edge data processing module uses an image target recognition algorithm to obtain pedestrians and vehicles in the image, and determines whether the pedestrians and vehicles are in the road; if they are in the road, proceed to step S2; otherwise, no processing is performed. Step S2: The edge data processing module obtains human feature data and vehicle feature data of pedestrians and vehicles in the road from the image; wherein, the human feature data is face data; and the vehicle feature data is the license plate number of the vehicle. Step S3: The edge data processing module sends human feature data and vehicle feature data to the regional data query module; Step S4: For the road surface image captured by the image capture device corresponding to the electronic speed measuring device, the data processing module searches for data in the data measured by the electronic speed measuring device that the vehicle speed is greater than the vehicle speed threshold v; and obtains the speed measurement time; obtains the road surface image at the corresponding time according to the speed measurement time of the electronic speed measuring data; and obtains the vehicle feature data of the passing vehicles from the road surface image at that time. Step S5: The edge data processing module sends the vehicle feature data and the corresponding vehicle speed to the regional data query module.

6. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, The regional data storage module pre-stores the human characteristic data and vehicle characteristic data of the permanent residents of the city, as well as the corresponding real identity information and mobile phone numbers of the personnel.

7. The IoT data fusion and collaborative control management system based on an edge computing gateway according to claim 1, characterized in that, The regional data query module queries the driver's real identity and mobile phone number through the following steps: Step P1: For human feature data, match it with the human feature database stored in the city area data storage module; if a match is found, obtain the real name and real mobile phone number of the corresponding person, and send traffic violation information to the mobile phone number; otherwise, proceed to step P2. Step P2: Broadcast the human body feature data to the regional data query modules of all cities. Each city's regional data query module will then match the data with the human body feature database stored in the regional data storage module. If a match is found, the corresponding person's real name and real mobile phone number will be obtained, and traffic violation information will be sent to that mobile phone number. Step P3: For vehicle feature data, obtain the city identifier from the vehicle feature data; and send the vehicle feature data to the corresponding city's regional data query module; the corresponding city's regional data query module queries the real name and real mobile phone number of the driver corresponding to the vehicle feature data from the regional data storage module; and sends traffic violation information to the mobile phone number.

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