A property management system based on edge computing

Abstract

This invention relates to the fields of edge computing, property management, and the Internet of Things (IoT), and provides a property management system based on edge computing. By setting up a multi-meter edge computing concentrator and a cloud server, the concentrator includes an edge computing motherboard, a built-in power supply, and multiple communication interfaces for connecting and communicating with various smart meters. The built-in power supply provides power to the multiple communication interfaces through the edge computing motherboard, and each powered communication interface provides communication power to a different smart meter. The edge computing motherboard reads the metering data from the smart meters connected to the corresponding communication interfaces through these interfaces and performs edge computing on the data to obtain various metering results. The cloud server acquires the various metering results calculated by the edge computing motherboard in real time and displays them on the system interface of the property management system, thereby reducing the difficulty and cost of remote property management.

Description

Technical Field

[0001] This invention relates to the fields of edge computing, property management, Internet of Things, and more particularly to a property management system based on edge computing. Background Technology

[0002] In property management systems, it is often necessary to collect and upload data from various meters such as electricity meters, water meters, and gas meters to the cloud to achieve remote property management. Currently, data collection from various meters is generally processed using two methods: centralized processing and edge computing. Centralized processing is a cloud-based collaborative solution between meters and cloud servers. In this solution, meter data is directly uploaded to the cloud server, which calculates the uploaded data to obtain the metering result data and then controls the real-time display of the metering result data on the property management system's interface. Edge computing involves meters transmitting data to an edge computing concentrator. The edge computing concentrator performs edge computing on the uploaded data, obtains the metering result data, and then uploads it to the cloud server for real-time display on the property management system's interface. Compared to centralized processing, which involves direct cloud upload, edge computing not only has advantages in data security, but it can also handle the computation of large amounts of process data to obtain the result data for uploading to the cloud server, thereby significantly reducing the computing pressure and resource consumption of the cloud server. However, in existing property management systems, a single edge computing concentrator can only be adapted to one type of meter and resolve one corresponding communication protocol. For example, a water meter corresponds to a water meter edge computing concentrator, and an electricity meter corresponds to an electricity meter edge computing concentrator. This makes remote property management difficult and costly. Moreover, each type of meter requires a separate external power supply to provide communication power to both the edge computing concentrator and the meter, significantly increasing the cost of remote property management.

[0003] In summary, existing edge computing-based property management technologies suffer from technical challenges such as difficulty in remote management and high costs. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, this invention provides a property management system based on edge computing to reduce the difficulty and cost of remote property management.

[0005] This invention provides a property management system based on edge computing, comprising: A multi-meter edge computing concentrator includes an edge computing motherboard, a built-in power supply, and multiple communication interfaces for connecting and communicating with various smart meters. The built-in power supply is electrically connected to the edge computing motherboard and supplies power to the multiple communication interfaces through the edge computing motherboard. The multiple powered communication interfaces provide communication power to the various smart meters. The edge computing motherboard reads the metering data from the smart meters connected to the corresponding communication interfaces through the multiple communication interfaces and performs edge computing on the metering data to obtain various metering result data. The cloud server is connected and communicates with the multi-meter edge computing concentrator to obtain the various metering result data calculated by the edge computing motherboard in real time, so as to display them on the system interface of the property management system.

[0006] Compared with the prior art, the beneficial effects of this invention are as follows: This invention provides a property management system based on edge computing. It involves setting up a multi-meter edge computing concentrator and a cloud server. The multi-meter edge computing concentrator includes an edge computing motherboard, a built-in power supply, and multiple communication interfaces for connecting and communicating with various smart meters. The built-in power supply is electrically connected to the edge computing motherboard and supplies power to the multiple communication interfaces. Each powered communication interface provides communication power to the various smart meters. The edge computing motherboard reads metering data from the smart meters connected to the corresponding communication interface and performs edge computing on the metering data to obtain various metering results. The cloud server communicates with the multi-meter edge computing concentrator and acquires the various metering results calculated by the edge computing motherboard in real time for display on the system interface of the property management system, thereby reducing the difficulty and cost of remote property management. Attached Figure Description

[0007] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. Some specific embodiments of the invention will be described in detail below with reference to the accompanying drawings in an exemplary and non-limiting manner. The same reference numerals in the drawings designate the same or similar parts or components. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a schematic diagram of an architecture of a property management system based on edge computing according to an embodiment of the present invention; Figure 2 This is a schematic diagram of an architecture of a property management system based on edge computing, according to an embodiment of the present invention, which embodies plug-and-play edge computing. Figure 3 This is a schematic diagram of an architecture of a property management system based on edge computing based on RS485 interface, according to an embodiment of the present invention. Figure 4 This is a schematic diagram of an architecture of a property management system based on edge computing, which embodies edge computing in parking management according to an embodiment of the present invention. Figure 5 This is a schematic diagram of an architecture of a property management system based on edge computing, which embodies edge computing for charging pile management, according to an embodiment of the present invention. Figure 6 This is a schematic diagram of an architecture for a property management system based on edge computing, which embodies edge computing in car wash management, according to an embodiment of the present invention. Detailed Implementation

[0008] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are merely 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 should fall within the scope of protection of the present invention.

[0009] See Figures 1-6 This invention provides a property management system based on edge computing, comprising: A multi-meter edge computing concentrator includes an edge computing motherboard, a built-in power supply, and multiple communication interfaces for connecting and communicating with various smart meters. The built-in power supply is electrically connected to the edge computing motherboard and supplies power to the multiple communication interfaces through the edge computing motherboard. The multiple powered communication interfaces provide communication power to the various smart meters. The edge computing motherboard reads the metering data from the smart meters connected to the corresponding communication interfaces through the multiple communication interfaces and performs edge computing on the metering data to obtain various metering result data. The cloud server is connected and communicates with the multi-meter edge computing concentrator to obtain the various metering result data calculated by the edge computing motherboard in real time, so as to display them on the system interface of the property management system.

[0010] It should be noted that in this embodiment, by integrating the edge computing motherboard, built-in power supply, and multi-protocol communication interfaces within the same hardware unit (multi-meter edge computing concentrator), not only are the technical problems of existing systems, such as the large number of meters deployed, complex wiring, and high costs due to the single meter box, solved, but the built-in power supply is also centrally powered by the motherboard, which then provides communication power to each communication interface and meter, avoiding the extensive configuration and maintenance of external power adapters. Furthermore, the edge computing motherboard locally parses multiple communication protocols and executes metering algorithms, moving a large amount of process calculations that would otherwise be completed in the cloud to the site, thereby significantly reducing the CPU and bandwidth pressure on the cloud server and improving data security and real-time performance. The metering result data, containing only the summarized results, is then uploaded to the cloud server, reducing the latency of the property management system interface's visual refresh and simultaneously lowering maintenance costs, achieving the technical effects of easy remote management, low overall cost, high real-time performance, and good security.

[0011] Furthermore, when the built-in power supply powers multiple communication interfaces through the edge computing motherboard, the edge computing motherboard monitors the power requirements of the various smart meters and controls the built-in power supply to power each communication interface to adapt to the power requirements of different smart meters. It should be noted that in multi-meter edge computing concentrators, smart meters, water meters, and gas meters from different manufacturers or using different protocols have significant differences in the voltage levels (e.g., 5V, 9V, 12V) and peak current for communication power supply. If a single, fixed-output built-in power supply is used, problems such as some meters experiencing undervoltage disconnection or the overall power supply overheating due to prolonged overload can easily occur. Moreover, on-site technicians need to use jumpers to meet the needs of individual meters, increasing deployment complexity and maintenance costs. In this embodiment, the edge computing motherboard monitors the power requirements of the communication power supply of the various smart meters and controls the built-in power supply to power each communication interface to adapt to the power requirements of different smart meters. This effectively solves the technical problems of the unified power supply being incompatible with the power consumption of heterogeneous meters and the cumbersome and error-prone manual configuration. It enables multiple meters to truly achieve plug-and-play functionality and on-demand power allocation, providing flexible expansion capabilities for subsequent additions of meter models. This further reduces the cost of remote property management and improves system reliability and security.

[0012] Furthermore, the edge computing motherboard is equipped with a signal strength detection module, a power monitoring module, and a power distribution control module. The signal strength detection module is used to detect the instantaneous amplitude, average amplitude, or signal-to-noise ratio of the signal transmitted on the communication interface in real time when the smart meters of each property interact with data through the corresponding communication interface, so as to generate signal strength data representing the communication quality. The power monitoring module is used to monitor the current output voltage, output current, and power demand parameters of each communication interface in real time. The power distribution control module is communicatively connected to the signal strength detection module and the power monitoring module, and is used to dynamically adjust the output voltage level and current limit of the programmable DC-DC converter corresponding to the communication interface channel in the built-in power supply according to the signal strength data, the output voltage, the output current, and the power demand parameters. When the signal strength of a certain communication interface is detected to be lower than a set first threshold and the power margin is sufficient, the power supply voltage or maximum output current of the communication interface with the signal strength lower than the set first threshold is increased. When the signal strength of a certain communication interface is detected to be higher than a set second threshold or the interface is idle, the output power of the communication interface with the signal strength higher than the set second threshold is reduced. It should be noted that in field environments with multiple protocols, varying line lengths, and combined power supply and communication, the voltage drop and electromagnetic interference levels of the lines where different meters are located vary. This can cause edge value jitter, CRC retransmissions, or even disconnections in weak signal links under fixed power supply mode. In addition, if all links are preset with maximum power redundancy, most links with already good signal quality will be over-powered for extended periods, leading to increased energy consumption and power supply thermal load. In this embodiment, the power distribution control module is communicatively connected to the signal strength detection module and the power monitoring module. It is used to dynamically adjust the output voltage level and current limit of the programmable DC-DC converter corresponding to the communication interface channel in the built-in power supply according to the signal strength data, the output voltage, the output current, and the power demand parameters. When the signal strength of a certain communication interface is detected to be lower than a set first threshold and the power margin is sufficient, the power supply voltage or maximum output current of the communication interface with the signal strength lower than the set first threshold is increased. When the signal strength of a certain communication interface is detected to be higher than a set second threshold or the interface is idle, the output power of the communication interface with the signal strength higher than the set second threshold is reduced. This significantly reduces the bit error rate of weak signal links and improves the online rate, thereby reducing the average temperature rise of the built-in power supply and improving the conversion efficiency, further reducing the operation and maintenance costs and risks of remote property management.

[0013] Furthermore, the signal strength detection module includes: a high-impedance analog front-end, an analog-to-digital converter, and a digital filtering unit connected in parallel with the data lines of each communication interface. The high-impedance analog front-end is used to non-intrusively sample the differential voltage on the communication data lines. The analog-to-digital converter converts the sampled signal into a digital signal and sends it to the digital filtering unit. The digital filtering unit uses an algorithm combining sliding window averaging and peak hold to output real-time signal strength values, thereby generating signal strength data representing communication quality. It should be noted that common meter communication buses such as RS-485 and M-Bus require differential lines to be unaffected by external loads and are highly sensitive to instantaneous level fluctuations. In this embodiment, the parallel sampling using a high-impedance analog front-end ensures that the input impedance to the differential signal reaches hundreds of kiloohms or more, without additionally reducing the bus drive capability. By digitizing the sampled waveform using an analog-to-digital converter, and then using a sliding window to average out short-term spike noise and supplementing it with peak hold to capture occasional deep attenuation, accurate, smooth signal strength values ​​that are sensitive to sudden attenuation can be generated in milliseconds. This enables low-intrusion, high-precision, and real-time communication quality measurement, providing a reliable basis for subsequent power distribution control and significantly improving system transmission stability and energy efficiency.

[0014] In some preferred embodiments, the edge computing-based property management system further includes a plug-and-play edge computing box. This box includes a communication slot, which is connected to the communication slot of a single smart meter to secure it to the meter. It should be noted that in this embodiment, a standardized communication slot is designed on the edge computing box itself, and it is directly plugged into and fixed to a single smart meter with a communication slot of the same specification. This effectively meets the metering requirements of a single meter. Using mechanical plug-in locking instead of screws or rails significantly shortens installation time and avoids additional wiring errors and potential waterproofing and dustproofing hazards. After plugging in, the plug-and-play edge computing box forms a tightly integrated structure with the meter, facilitating later maintenance and replacement. This achieves low cost, rapid deployment, and minimal space occupation, thereby improving the economy and convenience of small-scale renovations or upgrades of old meters.

[0015] In some preferred embodiments, the plug-and-play edge computing box, plugged into the communication slot, is powered by the single smart meter with the communication slot and reads the single-meter metering data of the single smart meter with the communication slot in real time. Edge computing is then performed on the single-meter metering data to obtain the single-meter metering result data. The cloud server communicates with the plug-and-play edge computing box and obtains the single-meter metering result data calculated by the plug-and-play edge computing box in real time for display on the system interface of the property management system. It should be noted that in this embodiment, the power supply port of the plugged-in meter can be used for power supply, thereby solving the problems of inconsistent external power supply and insufficient on-site power interfaces. Simultaneously, after the plug-and-play edge computing box completes the parsing and calculation of the original baud rate data stream of the single meter, it only uploads the single-meter metering result data. This allows existing meters to have edge intelligence functions without upgrades, thereby reducing the complexity of low-voltage power distribution transformation, improving data security and real-time performance, avoiding additional wiring, and further reducing overall operation and maintenance costs.

[0016] In some preferred embodiments, the edge computing-based property management system further includes an RS485 interface edge computing box. The RS485 interface edge computing box includes an RS485 interface, which is connected to a smart meter supporting RS485 communication via an RS485 communication bus. The main body of the RS485 interface edge computing box is fixed to the housing of the smart meter supporting RS485 communication by adhesive or locking, or fixed to other carriers other than the smart meter supporting RS485 communication by adhesive or locking. It should be noted that there is a huge demand for retrofitting existing RS485 smart meters in practice. In this embodiment, the edge computing box can be reserved with 3-wire or 4-wire RS485 interfaces, and can be directly fixed to the meter housing or adjacent carrier by adhesive or locking. This ensures hardware compatibility with mainstream 485 protocols such as IEC-62056, DL, or T645, effectively solving the problems of lack of expansion space and inconsistent screw hole positions in old meters, which lead to difficult retrofitting. It also provides flexible options for non-standard installation environments, realizes low-cost intelligent upgrade of old RS485 systems, and ensures the mechanical and electrical safety of the edge box and the meter.

[0017] In some preferred embodiments, the RS485 interface edge computing box, connected to a smart meter supporting RS485 communication, is powered by the smart meter and reads the individual metering data of the smart meter in real time. Edge computing is then performed on this individual metering data to obtain the individual metering result data. The cloud server communicates with the RS485 interface edge computing box to obtain the individual metering result data calculated by the edge computing box in real time, which is then displayed on the system interface of the property management system. It should be noted that existing buildings contain a large number of RS48 smart meters with complex wiring environments. Traditional methods often require laying a separate 220V adapter or low-voltage DC power supply line for each meter and continuously uploading the complete original message to the cloud for centralized parsing, causing the following problems: inconsistent power supply ports, limited on-site sockets, and high difficulty in renovation; low serial bus baud rate and large data volume, with long links requiring full cloud uploading and being susceptible to interference; and high computation and storage costs for the cloud to perform rate, demand, or anomaly analysis on high-frequency instantaneous data. In this embodiment, the edge box is powered by the 12V or 24V auxiliary power supply or bus power supply pin reserved on the meter. Combined with the low-power SoC, power bootstrap circuit, and thermal protection inside the edge box, power can be obtained simply by plugging in, without the need for an external power adapter or additional wiring, ensuring electrical safety while reducing installation costs. The edge box's mainboard can integrate protocol stacks such as DL / T645 and IEC62056 to parse raw messages such as current, voltage, and active / reactive power in real time. It can also locally execute algorithms for rate segmentation, frozen curves, and abnormal fluctuation detection, generating only single meter readings and handling a large amount of process data. The edge box can push meter readings to a cloud server via MQTT / HTTPS, allowing the cloud to handle only aggregation, billing, and visualization rendering. This reduces the computational burden on the central server and avoids latency and packet loss caused by repeated retransmissions over long distances.

[0018] In some preferred embodiments, the edge computing-based property management system further includes a parking management edge computing box. This box communicates with the cloud server and performs edge computing on vehicle parking information in the parking area in real time. The resulting parking information is then transmitted to the cloud server, which displays the parking results in real time on the property management system's interface. It should be noted that, considering the characteristics of parking scenarios involving high-frequency video or geomagnetic data and the large computational load of license plate recognition, this embodiment proposes a dedicated parking edge concentrator. This concentrator first completes the calculation of vehicle parking process information, such as license plate parsing, parking space occupancy judgment, and charging logic, within the local area network. Then, it reports the parking results (such as license plate, parking duration, and fees), avoiding the high bandwidth cost and cloud-side recognition delay associated with directly transmitting parking lot video streams to the cloud.

[0019] In some preferred embodiments, the edge computing-based property management system further includes a charging pile management edge computing box. This box communicates with the cloud server to perform edge computing on vehicle charging information in real time, generating charging result information which is then transmitted to the cloud server. The cloud server displays this charging result information in real time on the property management system's interface. It should be noted that the charging pile service requires real-time calculation of vehicle charging process data, such as charging power curves, billing strategies, and load balancing. In this embodiment, an edge concentrator is used to perform these process data calculations, reducing the computational pressure and resource overhead on the cloud server.

[0020] In some preferred embodiments, the edge computing-based property management system further includes a car wash management edge computing box. This box communicates with the cloud server and performs edge computing on vehicle wash space usage information in real time. The resulting usage information is then transmitted to the cloud server, which displays it in real time on the property management system's interface. In the car wash business scenario, a car wash management edge computing box is configured for each wash space, and a start button is provided on the box's casing. When the start button is activated, the box executes a wash space usage analysis algorithm, uploading only concise usage result information (such as the required car wash fee) to the cloud server, thereby reducing the cloud server's computational load and resource consumption.

[0021] Furthermore, the car wash bay usage analysis algorithm includes: a start button trigger detection module, a vehicle presence verification module, a water flow and power continuity judgment module, an anomaly rollback handling module, and a car wash fee settlement module. Specifically, the start button trigger detection module immediately invokes the vehicle presence verification module when it detects that the start button of the car wash management edge computing box corresponding to the car wash bay has been pressed. The vehicle presence verification module sequentially reads the vehicle presence marker signals output by the piezoelectric weighing sensor installed on the car wash bay floor, the infrared distance sensor set on the car wash arch, and the camera target recognition module. If any vehicle presence marker signal is continuously read within a preset judgment time window ΔT1, the system proceeds to the water flow and power continuity judgment module; otherwise, it triggers the anomaly rollback handling module. The water flow and power continuity judgment module reads the pump motor output power in real time collected by the turbine flow meter connected in series with the high-pressure pump and the power monitoring module inside the edge computing box. If, within a preset time window ΔT2, a continuous data segment with a water flow rate Q ≥ Qmin and a motor power P ≥ Pmin is detected, and its length is not less than Tmin, then an actual car wash is considered to have occurred. The car wash fee is calculated based on the duration of the car wash process or the cumulative water consumption. The car wash fee calculation module uploads the usage result information, including the car wash fee, start and end time, and water consumption, to the cloud server for real-time display. Otherwise, it enters the abnormal rollback processing module. In the abnormal rollback processing module, the algorithm automatically shuts down the high-pressure pump relay, resets the start button state, and records the invalid start event locally. At the same time, it sends abnormal information containing the car wash bay number, abnormal type, and timestamp to the cloud server, thereby avoiding resource waste and incorrect billing caused by accidental touch or malicious operation. While ensuring the simplicity of data upload to the cloud, it solves the technical problem of starting the car but not actually washing it, improving the billing accuracy and resource utilization efficiency of the property management system.

[0022] It should be noted that the above embodiments are merely preferred embodiments of the present invention, and the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention, and the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An edge-computing based property management system, characterized in that, include A multi-meter edge computing concentrator, comprising an edge computing motherboard, a built-in power supply, and multiple communication interfaces for connecting and communicating with various smart meters in properties; The built-in power supply is electrically connected to the edge computing motherboard, and the edge computing motherboard supplies power to multiple communication interfaces. The multiple communication interfaces that are powered provide communication power to the various smart meters of the property. The edge computing motherboard reads metering data from the smart meters connected to the corresponding communication interfaces through multiple communication interfaces, and performs edge computing on the metering data to obtain various metering result data. The cloud server is connected and communicates with the multi-meter edge computing concentrator to obtain the various metering result data calculated by the edge computing motherboard in real time, so as to display them on the system interface of the property management system. When the built-in power supply powers multiple communication interfaces through the edge computing motherboard, the edge computing motherboard monitors the power requirements of the various smart meters and controls the built-in power supply to power each communication interface to adapt to the power requirements of different smart meters. The edge computing motherboard is equipped with a signal strength detection module, a power monitoring module, and a power distribution control module. The signal strength detection module is used to detect the instantaneous amplitude, average amplitude, or signal-to-noise ratio of the transmitted signal on the communication interface in real time when the smart meters interact with each other through the corresponding communication interface, in order to generate signal strength data representing communication quality. The power monitoring module is used to monitor the current output power of each communication interface in real time. The power distribution control module is communicatively connected to the signal strength detection module and the power monitoring module. It dynamically adjusts the output voltage level and current limit of the programmable DC-DC converter corresponding to the communication interface channel in the built-in power supply based on the signal strength data, the output voltage, the output current, and the power requirement parameters. When the signal strength of a communication interface is detected to be lower than a set first threshold and there is sufficient power margin, the power supply voltage or maximum output current of the communication interface with the signal strength lower than the set first threshold is increased. When the signal strength of a communication interface is detected to be higher than a set second threshold or the interface is idle, the output power of the communication interface with the signal strength higher than the set second threshold is reduced. The signal strength detection module includes: a high-impedance analog front end, an analog-to-digital converter, and a digital filtering unit connected in parallel with the data lines of each communication interface. The high-impedance analog front end is used to non-invasively sample the differential voltage on the communication data lines. The analog-to-digital converter converts the sampled signal into a digital signal and sends it to the digital filtering unit. The digital filtering unit uses an algorithm that combines sliding window averaging and peak holding to output real-time signal strength values ​​to generate signal strength data representing communication quality. The edge computing-based property management system also includes a car wash management edge computing box. This box communicates with the cloud server to perform edge computing on vehicle wash bay usage information in real time, transmitting the resulting information to the cloud server. The cloud server displays this information on the property management system's interface in real time. In the car wash scenario, one car wash management edge computing box is configured for each wash bay, with a start button on its casing. When the start button is activated, the box executes a wash bay usage analysis algorithm, uploading only the usage results to the cloud server. The algorithm includes a start button trigger detection module, a vehicle presence verification module, a water flow and power continuity judgment module, an anomaly rollback handling module, and a car wash fee settlement module. The start button trigger detection module immediately invokes the vehicle presence verification module when it detects the start button of the car wash management edge computing box corresponding to a wash bay being pressed. The vehicle presence verification module sequentially reads the piezoelectric weighing sensor installed on the wash bay floor, and sets... The infrared distance sensor and the vehicle presence marker signal output by the camera target recognition module, which are placed on the car wash arch, will continuously read any vehicle presence marker signal within the preset judgment time window ΔT1. If this signal is continuously read, the system will enter the water flow and power continuity judgment module. Otherwise, the system will trigger the abnormal rollback processing module. The water flow and power continuity judgment module reads the pump motor output power collected in real time by the turbine flow meter connected in series with the high-pressure pump and the power monitoring module inside the edge computing box. If a continuous data segment with water flow rate Q≥Qmin and motor power P≥Pmin is detected within the preset time window ΔT2 and its length is not less than Tmin, the system will determine that the actual car wash has occurred. The car wash fee will be calculated based on the duration of the car wash process or the cumulative water consumption. The car wash fee calculation module will upload the usage result information, including the car wash fee, start and end time, and water consumption, to the cloud server for real-time display. Otherwise, the system will enter the abnormal rollback processing module. In the abnormal rollback processing module, the algorithm will automatically shut down the high-pressure pump relay, reset the start button state, and record the invalid start event locally. At the same time, it will send abnormal information, including the car wash bay number, abnormal type, and timestamp, to the cloud server.

2. The property management system based on edge computing as described in claim 1, characterized in that, It also includes a plug-and-play edge computing box, which includes a communication card slot. The plug-and-play edge computing box is connected to the communication slot of a single smart meter with a communication slot through the communication card slot to be fixed on the single smart meter.

3. The property management system based on edge computing as described in claim 2, characterized in that, The plug-and-play edge computing box, which is plugged into the communication slot, is powered by the single smart meter with the communication slot and reads the single meter metering data of the single smart meter with the communication slot in real time. It performs edge computing on the single meter metering data to obtain the single meter metering result data.

4. The property management system based on edge computing as described in claim 3, characterized in that, The cloud server connects and communicates with the plug-and-play edge computing box to obtain the single-meter measurement result data calculated by the plug-and-play edge computing box in real time, so as to display it on the system interface of the property management system.

5. The property management system based on edge computing as described in claim 1, characterized in that, It also includes an RS485 interface edge computing box, which includes an RS485 interface. The RS485 interface edge computing box is connected to a smart meter that supports RS485 communication via an RS485 communication bus. The main body structure of the RS485 interface edge computing box is fixed to the housing of the smart meter that supports RS485 communication by adhesive or locking, or fixed to other carriers other than the smart meter that supports RS485 communication by adhesive or locking.

6. The property management system based on edge computing as described in claim 5, characterized in that, The RS485 interface edge computing box, connected to a smart meter that supports RS485 communication, is powered by the smart meter and reads the single meter metering data of the smart meter in real time. It then performs edge computing on the single meter metering data to obtain the single meter metering result data.

7. The property management system based on edge computing as described in claim 6, characterized in that, The cloud server communicates with the RS485 interface edge computing box to obtain the metering result data of the single electricity meter calculated by the RS485 interface edge computing box in real time, and displays it on the system interface of the property management system.

8. The edge computing-based property management system as described in any one of claims 1-7, characterized in that, It also includes a parking management edge computing box, which is connected and communicates with the cloud server to perform edge computing on the vehicle parking information in the parking area in real time, so as to obtain the vehicle parking result information in the parking area and transmit it to the cloud server. The cloud server displays the vehicle parking result information in real time on the system interface of the property management system.

9. The edge computing-based property management system as described in any one of claims 1-7, characterized in that, It also includes a charging pile management edge computing box, which is connected and communicates with the cloud server to perform edge computing on vehicle charging information in real time, so as to obtain vehicle charging result information and transmit it to the cloud server. The cloud server displays the vehicle charging result information in real time on the system interface of the property management system.

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