Intelligent socket safety monitoring and centralized management system and method

Abstract

The application provides a kind of intelligent socket safety monitoring and centralized management system and method;System includes intelligent socket terminal, cloud server and centralized management platform;Intelligent socket terminal is equipped with temperature sensor directly contacted with terminal contact point, and its microcontroller is configured to: collect current data and perform edge computing locally, identify current mutation, trend anomaly and fluctuation anomaly;While monitoring terminal temperature, according to preset threshold value, perform hierarchical alarm and countdown power-off control;Intelligent socket terminal adopts local high-frequency sampling and characteristic value upload combined data reporting strategy;Centralized management platform provides web access interface, supports multi-tenant data isolation and operation log audit;The application solves the problem that the prior art cannot effectively prevent electrical fire caused by poor contact, response delay and low efficiency of batch equipment monitoring, realizes the real-time, traceability and low-cost large-scale deployment of power safety monitoring.

Description

Technical Field

[0001] This invention relates to the field of smart socket technology, specifically to a smart socket safety monitoring and centralized management system and method. It is applicable to unattended or centralized management scenarios requiring remote status monitoring, fault early warning, and automated control of a large number of electrical devices, such as internet cafes, vending machines, data center computer rooms, and industrial automation equipment. Background Technology

[0002] Smart sockets, serving as the interface between electrical appliances and the power grid, are widely used in homes, offices, and commercial spaces. Current smart socket technologies typically integrate remote control, electricity metering, and overload protection functions.

[0003] For example, users can remotely control the on / off state of a socket (such as the Sunflower C4 smart socket) via a mobile application (APP), or collect current and voltage data through a built-in metering chip to calculate electricity consumption. In commercial and industrial scenarios that require monitoring a large number of devices, existing technologies have also proposed centralized management solutions, such as patent CN209992842U, which uses a concentrator to communicate with multiple smart sockets to achieve remote on / off control of a batch of devices.

[0004] However, analysis reveals that the existing technology has at least the following technical shortcomings: 1. Lack of monitoring capabilities for poor terminal contact, a major cause of electrical fires.

[0005] Current smart sockets only offer overload protection against excessive power consumption. When the internal terminals of the socket experience increased contact resistance due to loosening, oxidation, or other reasons, the contact points will continuously heat up, but the circuit current I may not change significantly. Existing technology cannot accurately detect this type of localized heating, making it difficult to prevent electrical fires caused by poor contact. Although some existing technologies (such as CN204214560U) incorporate temperature sensors at the wires, they detect the overall temperature of the wires and cannot accurately pinpoint the core location of the fault—the terminal contact point.

[0006] 2. Lacks the ability to identify signs of equipment failure and can only respond after the fact.

[0007] Most existing technologies only provide power-off protection after a fault occurs (such as overload or short circuit), and cannot identify progressive faults such as equipment aging or power supply performance degradation by analyzing changes in current characteristics. For example, when a computer power supply ages, its operating current may slowly increase or exhibit abnormal fluctuations. Existing sockets cannot recognize these early signs, causing equipment to continue operating with defects until a substantial failure occurs, increasing the risk of unplanned downtime.

[0008] 3. The mobile APP management mode is difficult to meet the centralized monitoring needs of a large number of devices.

[0009] When monitoring dozens or even hundreds of devices simultaneously, the management model centered on a mobile app has significant shortcomings, such as limited information displayed on a single screen, difficulty in comparing data from multiple devices, inconvenience in analyzing historical data, and the potential for alarm messages to be buried. For scenarios requiring efficient centralized monitoring, such as internet cafes and self-service equipment operators, existing solutions fall short in terms of monitoring efficiency and ease of management.

[0010] 4. Reliance on cloud-based decision-making leads to response delays and offline risks.

[0011] Existing technologies mostly adopt a cloud-based decision-making model of "device data collection - cloud-based judgment - command issuance". In this model, when there is network latency or interruption, the device will lose its real-time monitoring and automatic protection capabilities, and the response time from the occurrence of an anomaly to the execution of power cut is greatly affected by network conditions, making it difficult to meet the needs of rapid response in emergency situations.

[0012] 5. Lack of data storage and accountability mechanisms.

[0013] Most existing smart sockets only provide real-time data viewing and lack traceable historical data storage capabilities. In the event of accidents such as electrical fires, they cannot provide equipment operation records as objective evidence for accident cause analysis and liability determination.

[0014] In summary, to address the problems existing in the prior art, there is an urgent need for a smart socket safety monitoring and centralized management system and method that can achieve accurate terminal temperature monitoring, equipment fault symptom identification, centralized monitoring of batch equipment, real-time edge computing response, and data traceability. Summary of the Invention

[0015] The purpose of this invention is to provide a smart socket safety monitoring and centralized management system and method to solve the technical problems in the prior art, such as the inability to accurately monitor terminal temperature, the inability to identify early signs of equipment failure, low efficiency in monitoring batch equipment, response delays caused by cloud reliance, and untraceable data.

[0016] To achieve the above objectives, the present invention provides the following technical solutions.

[0017] A smart socket safety monitoring and centralized management system, such as Figure 1 As shown, it includes: At least one smart socket terminal, and each smart socket terminal is connected to a corresponding electrical device; The cloud server is communicatively connected to the smart socket terminal. A centralized management platform, deployed on a cloud server or local server, provides a web-based access interface.

[0018] Among them, such as Figure 2 As shown, the smart socket terminal includes: Current sampling module and voltage sampling module are used to collect current and voltage signals in the circuit; Terminal temperature sensor, such as Figure 3 As shown, it is located at the point where the copper plate terminal and the wire are crimped inside the socket, and is in direct contact with the contact point to collect the temperature of the terminal contact point; Microcontroller (MCU) serves as the core of local processing; The communication module is used for data interaction with the cloud server; Relays and drive circuits are used to control the on / off state of sockets; Local storage unit, used to store high-frequency sampling data.

[0019] The core of this invention lies in the fact that the microcontroller is configured to execute edge computing logic, that is, to process and analyze data locally in real time: Current data is collected at the first frequency, and the current change rate, current trend, and current fluctuation characteristics are calculated locally.

[0020] like Figure 5 As shown, when the current data is detected to meet the preset abnormal conditions (such as sudden current change, slow rise, abnormal fluctuation), the abnormal alarm information is immediately uploaded through the communication module.

[0021] At the same time, monitor the terminal temperature, such as Figure 4 As shown, when the temperature exceeds the preset first threshold, an early warning message is uploaded; when the temperature exceeds the higher second threshold, a countdown begins and an alarm message is uploaded; if the countdown ends or the temperature exceeds the third threshold, the relay is immediately controlled to disconnect, achieving local autonomous power cut-off.

[0022] Furthermore, the present invention also provides a method for security monitoring and centralized management of smart sockets based on the above system, comprising the following steps: S1: The smart socket terminal collects current data at the first frequency and terminal temperature at the fourth frequency.

[0023] S2: The microcontroller determines locally whether the current data meets the abnormal conditions. If it does, it immediately uploads the abnormal alarm information.

[0024] S3: The microcontroller determines locally whether the terminal temperature exceeds the threshold. If it exceeds the first threshold, it uploads a warning message. If it exceeds the second threshold, it starts a countdown and uploads an alarm message. If the countdown ends or the temperature exceeds the third threshold, it controls the relay to disconnect.

[0025] S4: The microcontroller reports normal data (such as the average value over the past 15 minutes) to the cloud server at a second frequency to reduce communication traffic. Its reporting strategy is as follows: Figure 6 As shown.

[0026] S5: After receiving data, the cloud server stores it in the database and displays it on the front end of the centralized management platform.

[0027] S6: The centralized management platform isolates data from different tenants based on their tenant IDs, such as... Figure 8 As shown, only the device information of the current tenant is displayed.

[0028] Compared with the prior art, the present invention has the following beneficial effects: (1) Accurately monitor terminal temperature to prevent electrical fires: By placing the temperature sensor directly on the terminal contact point, it can accurately detect temperature abnormalities caused by poor contact, provide early warning when there is no significant change in current, and automatically cut off power when the dangerous temperature is reached, thus eliminating the potential for electrical fires from the source.

[0029] (2) Achieve equipment fault sign identification and predictive maintenance: By analyzing multi-dimensional parameters such as current change rate, ramp-up trend and fluctuation characteristics through edge computing, it is possible to identify progressive fault signs such as aging and instability before the equipment experiences a substantial fault, notify users to perform maintenance in advance, and effectively reduce unplanned downtime losses.

[0030] (3) Reduce response latency and ensure offline availability: The core fault judgment logic is executed on the device side. In an emergency, the device can automatically shut down without waiting for the cloud response, reducing the response time from seconds to milliseconds. Moreover, the device can still independently complete temperature monitoring and abnormal power-off functions when the network is interrupted.

[0031] (4) Improve the efficiency of centralized monitoring of batch devices: Provide a web-based centralized management platform that supports functions such as one-screen overview of all device status, multi-device data comparison, historical trend analysis and report export, which significantly improves the management efficiency for large-scale devices.

[0032] (5) Effective control of communication and operation costs: The edge computing reporting strategy of "local judgment + feature value upload" is adopted. Only necessary data and abnormal events are uploaded. The monthly traffic of a single device can be controlled at a very low level (such as within 5MB), which solves the traffic cost problem of high-frequency sampling data in large-scale deployment.

[0033] (6) Enables data traceability and provides a basis for liability determination: The equipment stores high-frequency sampling data locally, and alarm records and user operation logs are centrally stored in the cloud, forming a complete chain of evidence. In the event of an electrical accident, objective historical data can be provided as a basis for liability determination.

[0034] Other features and advantages of the invention will be set forth in the following description or may be learned by practicing the invention. Attached Figure Description

[0035] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0036] Figure 1 This is a system architecture diagram of the present invention; Figure 2 This is a block diagram of the smart socket terminal structure; Figure 3 A schematic diagram (cross-sectional view) of the terminal temperature sensor installation location; Figure 4 Flowchart for temperature-grade alarm and power-off control; Figure 5 Here is a flowchart of the current anomaly diagnosis method; Figure 6 Flowchart of data reporting strategy; Figure 7 This is a schematic diagram of the centralized management platform interface; Figure 8 This is a diagram illustrating a multi-tenant data isolation mechanism. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below with reference to specific embodiments. It should be noted that these embodiments are only used to explain this invention and do not constitute a limitation on the scope of protection of this invention.

[0038] Example 1, such as Figure 2 As shown, the hardware implementation of the smart socket terminal is as follows: This embodiment provides a hardware implementation scheme for a smart socket terminal suitable for scenarios such as internet cafes, vending machines, and computer rooms.

[0039] Microcontroller (MCU): The STM32F103C8T6 from STMicroelectronics is used. This chip is based on the ARM Cortex-M3 core, with a main frequency of 72MHz, 64KB Flash and 20KB RAM, and has sufficient processing power to perform edge computing tasks such as current trend analysis and temperature monitoring.

[0040] Energy metering: The ATT7022B energy metering chip from Juquan Optoelectronics is used. This chip communicates with the MCU via the SPI interface and can simultaneously collect parameters such as current, voltage, active power, and reactive power. The measurement accuracy is better than 0.5 class, providing high-precision raw data for current characteristic analysis.

[0041] Terminal temperature monitoring: such as Figure 3As shown, an NTC thermistor (model: MF52-103F3435, resistance 10kΩ at 25℃) is used. During manufacturing, this thermistor is tightly fitted to the copper terminal and wire crimping point inside the socket. The resistance change is converted into a voltage signal by a voltage divider circuit, which is acquired by the MCU's analog-to-digital converter (ADC), and the voltage value is converted into a precise temperature value using a lookup table method.

[0042] Communication Module: Utilizing Quectel's EC800M 4G Cat.1 module, it communicates with the MCU via a UART interface. This module supports the MQTT protocol for establishing long-lived connections and exchanging data with the cloud server, ensuring stable network connectivity in various scenarios.

[0043] Local storage: Utilizes Winbond Electronics' W25Q64 64M-bit (8MB) SPI Flash chip. This chip stores data in a circular buffer, such as high-frequency current sampling data from the most recent hour, as well as device configuration parameters, providing data support for incident tracing and local decision-making.

[0044] Relays and Drivers: SRD-05VDC-SL-C relays are used, with a contact capacity of 16A / 250VAC, meeting the needs of most electrical devices. A driver circuit is constructed using an 8050 transistor, and the relay's activation and deactivation are controlled by the MCU's GPIO (General Purpose Input / Output) pins.

[0045] Example 2, as Figure 5 As shown, the current anomaly diagnosis logic in edge computing: This embodiment details a method for diagnosing current anomalies performed locally by a microcontroller.

[0046] Current surge detection: The MCU collects current values ​​at millisecond-level frequency (e.g., every 1 millisecond). When a current change exceeding a preset threshold (e.g., 10A) is detected within 1 millisecond, the program determines that a short circuit or a sudden serious equipment failure may have occurred. At this time, the MCU immediately uploads a "short circuit / surge alarm" via the communication module and simultaneously triggers the relay drive circuit to perform a power-off operation locally. The entire process can be completed within milliseconds, which is much faster than cloud-based decision-making.

[0047] Current trend detection: The MCU calculates the average current over the past 30 seconds every 30 seconds and records it within a sliding time window (e.g., 30 minutes). The program uses linear regression or a simple comparison algorithm to detect whether the average current within this window shows a continuous upward trend. When the detected increase exceeds a preset percentage (e.g., 30%), it is determined that the equipment is aging or overheating abnormally, generating a "trend alarm" and uploading it to prompt the user to perform preventative maintenance.

[0048] Current fluctuation detection: The MCU calculates the variance of the current data over the past 5 minutes in real time (measuring the degree of fluctuation). This value is compared with the "historical baseline variance" (representing the fluctuation level when the device is working normally) learned and stored by the system. When the current variance exceeds a preset multiple (e.g., 3 times) of the historical baseline variance, it is determined that the power supply or device is unstable, and an "abnormal fluctuation alarm" is generated and uploaded.

[0049] Example 3: Software implementation and data isolation of the centralized management platform: This embodiment describes a specific implementation of a centralized management platform.

[0050] Technology Stack: The backend uses the Spring Boot framework in Java to build RESTful API interfaces. The database uses MySQL to store user information, basic device information, and alarm records, and TDengine time-series database is used for efficient storage and querying of massive amounts of historical current, voltage, and temperature time-series data. The frontend uses the Vue.js framework and ECharts charting library to build interactive web interfaces.

[0051] Multi-tenant isolation: such as Figure 8 As shown, key data tables in the platform's database design (such as the device table and alarm record table) all include a "tenant ID" field. Each registered user corresponds to a unique tenant ID. When a user logs in, the system stores the tenant ID in the session or generates a token containing the tenant ID. Subsequently, before executing any data query interface, the tenant ID is automatically parsed from the session or token and appended as an implicit query condition to the SQL statement (e.g., SELECT * FROM device WHERE tenant_id = ?). This ensures that the data of different tenants is logically completely isolated and invisible to each other.

[0052] Operation Log Auditing: The platform features an operation log table to record all critical user operations, including but not limited to: user login (recording account, time, and IP address), device control (recording operator, time, device ID, and command), alarm confirmation (recording confirmer, time, and alarm ID), and configuration modification (recording modifier, time, and modified content). Once written, all log records are unmodifiable at the user interface level and can be retrieved and exported based on conditions, providing objective evidence for incident tracing and liability determination.

[0053] Example 4: Application in the vending machine operator scenario: This embodiment demonstrates the application effect of the present invention in unattended batch equipment management scenarios.

[0054] A vending machine operator deployed 50 vending machines in multiple shopping malls, each equipped with one of the smart sockets described in this invention. Operators accessed a centralized management platform via computer from their office.

[0055] Overview monitoring: such as Figure 7 As shown, the platform's main interface displays the real-time status of all 50 devices in a list or grid format on a single screen, sorted by temperature level or alarm severity. Operators can quickly locate devices with abnormal status.

[0056] Fault Warning and Handling: The compressor of a vending machine began to show signs of failure due to aging, with abnormal fluctuations in its current waveform. Upon detecting this fluctuation, the MCU of the smart socket terminal immediately reported an "abnormal fluctuation alarm" to the cloud platform. After receiving the alarm, the platform prominently displayed it in the alarm center and could also send notifications to operations personnel via SMS or WeChat official account.

[0057] Remote diagnostics and decision-making: After receiving the notification, operators log in to the platform to view detailed historical data curves of the device, including current and temperature changes over the past few days. By comparing with historical baselines, an abnormal trend is confirmed. The platform supports remotely disconnecting the power to the vending machine to await repair, avoiding losses due to product spoilage or equipment downtime caused by complete equipment failure. The entire process from fault discovery and diagnosis to initial handling can be completed efficiently remotely.

[0058] Example 5: Specific process of temperature-graded alarm and power-off control: This embodiment combines Figure 4 The paper details the microcontroller's logic for handling terminal temperatures. Preferably, the first threshold, second threshold, and third threshold are set to 60°C, 80°C, and 90°C, respectively.

[0059] Normal state (T < 60℃): The MCU reports the average temperature as normal data every 15 minutes.

[0060] Warning status (60℃ ≤ T < 80℃): The MCU generates a "warning" event and immediately reports it to the platform, but does not operate the relay, maintains normal power supply to the device, and reminds the user to pay attention to the status of the socket.

[0061] Hazardous Condition (80℃ ≤ T < 90℃): The MCU generates a "hazardous" event and reports it immediately. Simultaneously, a 30-second local countdown timer starts, continuously monitoring the temperature during this period. If the user clicks the "Temporarily Uninterrupt Power" button via the centralized management platform, the platform sends a command, and the MCU stops the countdown upon receiving the command, while the socket remains powered. If no user intervention command is received during the countdown, the MCU controls the relay to disconnect after the countdown ends, de-energizing the socket.

[0062] Emergency State (T ≥ 90℃): Regardless of the current state, once the temperature reaches or exceeds 90℃, the MCU immediately reports an "emergency" event and forces a power-off operation. Simultaneously, it can activate a local buzzer alarm and a rapidly flashing red LED to ensure safety with the highest priority. If the temperature rises to 90℃ during the countdown to the dangerous state, an emergency state will be immediately triggered and a forced power-off will be implemented.

[0063] Example 6, Data Reporting Strategy: This embodiment combines Figure 6 This section details the data reporting logic after the device is powered on. The core mechanism employs a hierarchical reporting mechanism triggered by multiple timers in parallel, with the specific process as follows: The device first performs a power-on initialization operation to complete basic configurations such as hardware, communication, and parameters. After initialization, three independent timers are started, each corresponding to a different reporting scenario, forming three parallel execution branches: A, B, and C.

[0064] Branch A: Periodic heartbeat keep-alive (Timer 1, period 60 seconds): Trigger condition: Triggered every 60 seconds; Action performed: Send a heartbeat packet; Reported content includes the device's unique ID and the current timestamp.

[0065] Branch B: Periodic routine data reporting (Timer 2, period 15 minutes): Trigger condition: Triggered every 15 minutes; Action performed: Upload normal operation data; Reported content includes the average, maximum, and minimum values ​​of key operating parameters such as current, voltage, and temperature.

[0066] Branch C: Real-time reporting of exception events (Timer 3, exception event triggered): Triggering conditions: Not timed triggering, it is triggered immediately only when the device detects an abnormal event (such as parameter over-limit, malfunction, etc.); Action to be taken: Immediately upload abnormal alarm data; Reporting content includes: the type of anomaly, the current value of the parameter when the anomaly occurred, and high-frequency sampling data for 1 second before and after the anomaly occurred.

[0067] Through the aforementioned hierarchical reporting mechanism, this invention effectively controls data flow under normal circumstances while ensuring real-time response to abnormal events, achieving a balance between communication efficiency and real-time monitoring.

[0068] Based on the above strategy, the estimated monthly traffic of a single device can be controlled within 5MB: approximately 50 bytes of periodic routine data reporting every 15 minutes, totaling about 144KB per month; plus heartbeat packets (approximately 20 bytes every 60 seconds, totaling about 86KB per month) and abnormal event reporting (approximately 10 times per month, with each event accounting for about 1KB).

[0069] Those skilled in the art should understand that the above embodiments are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A smart socket safety monitoring and centralized management system, characterized in that, include: At least one smart socket terminal, and each smart socket terminal is connected to a corresponding electrical device; The cloud server is communicatively connected to the smart socket terminal. A centralized management platform, deployed on a cloud server or local server, provides a web-based access interface; The smart socket terminal includes: The current sampling module and voltage sampling module are used to acquire current and voltage signals in the circuit; A terminal temperature sensor is installed inside the socket at the crimping point between the copper terminal and the wire, and is in direct contact with the contact point to collect the temperature of the terminal contact point. The microcontroller serves as the core of local processing. The communication module is used for data interaction with the cloud server; Relays and drive circuits are used to control the on / off state of sockets; Local storage unit, used to store high-frequency sampling data; The microcontroller is configured to: Current data is collected at the first frequency, and the current change rate, current trend and current fluctuation characteristics are calculated locally. When the detected current data meets the preset abnormal conditions, the abnormal alarm information is immediately uploaded through the communication module. Monitor terminal temperature and upload early warning information when the temperature exceeds a preset first threshold; start a countdown and upload alarm information when the temperature exceeds a preset second threshold; if the countdown ends or the temperature exceeds a preset third threshold, immediately control the relay to disconnect.

2. The system according to claim 1, characterized in that, The terminal temperature sensor is an NTC thermistor, which is connected to the analog-to-digital converter interface of the microcontroller through a voltage divider circuit.

3. The system according to claim 1, characterized in that, The preset abnormal conditions include: Abnormal rate of change of current: The current changes beyond the rate of change threshold within a preset time. Abnormal current trend: The average current rises above the proportional threshold within a preset time period; Abnormal current fluctuation: The current variance within the preset time window deviates from the historical baseline by more than a multiple of the threshold.

4. The system according to claim 1, characterized in that, The first threshold is 60°C, the second threshold is 80°C, and the third threshold is 90°C.

5. The system according to claim 1, characterized in that, The microcontroller is also configured to: Normal data is reported to the cloud server at a second frequency, which is lower than the first frequency. The normal data is the average current, average voltage, and average temperature over the past 15 minutes. A heartbeat packet is sent to the cloud server at a third frequency, which is lower than the first frequency.

6. The system according to claim 1, characterized in that, The centralized management platform includes: The device overview dashboard module is used to display the status of all devices on one screen and sort them by the level of abnormality. The historical data query module is used to query the historical current, voltage, and temperature curves of a specified device. The alarm center module is used to record all alarm information and supports confirmation and export. The operation log module is used to record all user operations, including the operator, operation time, and operation content; The multi-tenant isolation module is used to isolate device data from different tenants.

7. A method for intelligent socket security monitoring and centralized management based on the system described in any one of claims 1-6, characterized in that, Includes the following steps: S1: The smart socket terminal collects current data at the first frequency and terminal temperature at the fourth frequency; S2: The microcontroller locally determines whether the current data meets the abnormal conditions. If it does, it immediately uploads the abnormal alarm information. S3: The microcontroller determines locally whether the terminal temperature exceeds the threshold. If it exceeds the first threshold, it uploads a warning message. If it exceeds the second threshold, it starts a countdown and uploads an alarm message. If the countdown ends or the temperature exceeds the third threshold, it controls the relay to disconnect. S4: The microcontroller reports normal data to the cloud server at a second frequency; S5: After receiving data, the cloud server stores it in the database and displays it on the front end of the centralized management platform; S6: The centralized management platform isolates data from different tenants based on their tenant IDs and only displays the device information of the current tenant.

8. The method according to claim 7, characterized in that, The abnormal conditions mentioned in step S2 include: Abnormal rate of change of current: The current changes by more than 10A within 1 millisecond; Abnormal current trend: The average current increases by more than 30% within 30 minutes; Abnormal current fluctuation: The current variance over the current 5 minutes exceeds 3 times the historical baseline variance.

9. The method according to claim 7, characterized in that, In step S3: The first threshold is 60°C, the second threshold is 80°C, and the third threshold is 90°C; When the temperature reaches 80℃, a 30-second countdown begins. If a power-off command is received from the user through the centralized management platform during the countdown, the countdown stops and power is maintained.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 7-9.

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