Intelligent distribution box system based on embedded control and control method thereof

Abstract

The application discloses an intelligent distribution box system and a control method based on embedded control, and particularly adapts to the distribution box and the control system of the existing public building digital management and low-carbon upgrading; the scheme relies on the embedded development control module to realize the edge local computing power support, and fuses multi-source sensing collection, LORA wireless communication, intelligent control algorithm, edge memory learning and video image recognition technology, so that the global energy consumption digital management and control can be completed by only replacing the building 2 or 3 level distribution box; the scheme has the functions of light weight and low cost reconstruction, low construction influence, scene energy-saving linkage, multi-dimensional safety early warning, remote intelligent operation and maintenance and the like, can accurately match the relevant policy requirements of the public institution energy-saving and carbon-reducing assessment, and is particularly suitable for the non-destructive upgrading of the existing public building at night.

Description

Technical Field

[0001] This invention relates to the fields of intelligent control of distribution boxes, digital management of building energy consumption, embedded module development and wireless sensor communication technology, and in particular to a smart distribution box system based on embedded control and its control method. Background Technology

[0003] Currently, most building distribution boxes in China only possess basic functions such as circuit overload protection, short-circuit protection, and basic power supply for circuit switching. They lack dedicated data acquisition units and intelligent control units, making it impossible to collect power parameters of each power supply circuit in real time. This hinders independent energy consumption statistics and refined control of specific energy-consuming circuits such as lighting, sockets, and air conditioning. Furthermore, the switching of distribution circuits relies entirely on manual operation, lacking automatic control and remote management capabilities. Their level of intelligence is extremely low, failing to meet the refined energy consumption digital assessment and intelligent management requirements of modern smart and low-carbon buildings. To address the functional shortcomings of traditional distribution boxes, a small number of intelligent distribution box products and related research solutions have gradually emerged on the market. However, existing intelligent power distribution technologies generally suffer from fragmented functions and significant technical shortcomings, making it difficult to meet the core needs of dual-carbon management and intelligent operation and maintenance in public buildings in terms of overall adaptability and practicality. From the perspective of existing publicly available patent technologies, various similar technical solutions have limited functions and significant application limitations. For example, patent CN202610388466.6 only focuses on power distribution fault self-healing, fault isolation, and power supply restoration, only conducts edge computing on the power fault dimension, and only optimizes power supply reliability, without any energy-saving and carbon-reduction related functions; patent CN202610388974.4 only realizes automatic phase sequence identification and correction and phase loss protection of three-phase circuits, only serving the power supply protection of power equipment, and does not have the ability of multi-source sensing acquisition, intelligent energy control, and energy consumption statistics; patent CN202610253040.X can only collect some power and environmental parameters inside the distribution box, and only relies on the Internet of Things to realize equipment fault early warning, without involving the collection of full-domain data such as building indoor environment and personnel status, and cannot realize scenario-based energy-saving linkage; patent CN202610160968.3 focuses on power distribution... The internal temperature field reconstruction and hotspot fault location of the electrical box only solve the problem of equipment thermal failure, and do not involve the core functions of building terminal energy control and energy consumption statistics; the patent CN202512019285.4 only focuses on the separate management of lighting equipment, and the system architecture is independent, which cannot realize the linkage management of multiple power circuits and the comprehensive power distribution operation and maintenance; in addition, many patents such as CN202511473171.0, CN202411312989.X, and CN202410472958.4 only focus on electrical fault diagnosis and safety protection, and lack the core modules of energy-saving linkage and policy-adaptive energy consumption statistics; while the intelligent distribution box patents such as CN202211545829.0 and CN201911011826.7 only realize basic power data visualization and simple remote on / off functions, mostly adopting wired communication mode, with low level of intelligence and high difficulty in transformation.From the perspective of academic research results, existing related studies also suffer from poor scenario adaptability and incomplete functions. The "Tunnel Distribution Box Dynamic Environment Monitoring and Dehumidification System Based on LoRa Technology" only focuses on internal environmental monitoring and dehumidification operation and maintenance of tunnel distribution boxes, and does not design energy-saving control and multi-circuit statistical functions for indoor terminal electrical equipment in public buildings. The "Research on Intelligent Monitoring System of Temporary Distribution Box for Power Construction Sites Integrating ZigBee and Edge Computing" only focuses on the safety protection of temporary power use on construction sites, and does not adapt to the specific needs of public building office scenarios such as human-sensor linkage, adaptive energy saving, and dual-carbon energy consumption statistics.

[0004] In summary, existing intelligent distribution box technologies generally suffer from several core technical deficiencies. First, their data acquisition dimensions are limited, only collecting basic electrical parameters such as voltage and current, without integrating multi-dimensional data such as building environment, human perception, video images, and historical energy consumption, thus failing to support scenario-based energy-saving linkage control. Second, their intelligent control capabilities are weak, with rigid control logic and simple control modes, supporting only threshold alarms and basic remote switching operations, lacking advanced intelligent functions such as adaptive scenario-based linkage control and user energy consumption habit memory optimization, resulting in a severe lack of precision in energy management. Third, their adaptability to retrofitting is poor, with existing products mostly employing wired communication and requiring complete equipment replacement for retrofitting. The existing technologies suffer from several drawbacks. First, they are incompatible with current policies. They lack localized edge computing capabilities, relying entirely on cloud servers for data processing and command issuance. This results in high wiring costs, long renovation cycles, and significant construction impacts, easily disrupting the normal operation of existing public buildings and hindering lightweight, low-impact upgrades. Second, they are not policy-compatible, failing to meet the stringent energy conservation and carbon reduction requirements of public institutions. Third, they suffer from poor system architecture stability. Most products lack localized edge computing capabilities, with all data processing and command issuance dependent on cloud servers, leading to high data response latency and complete system failure offline, making them unsuitable for complex public building power distribution scenarios. Currently, the industry lacks a dedicated smart distribution box solution integrating multi-source full-domain sensing, wireless networking, edge intelligent computing, AI security identification, multi-circuit refined control, policy-adaptive energy consumption statistics, and lightweight, low-cost renovation. This makes it difficult to address the industry pain points of intelligent and low-carbon renovation of existing public buildings and to meet the needs of refined energy consumption management and digital assessment under the dual-carbon policy. Summary of the Invention

[0005] The purpose of this invention is to provide a smart distribution box system and its control method based on embedded control to address the above-mentioned shortcomings, thereby solving the industry pain points of low intelligence level of existing traditional distribution boxes, high difficulty in building intelligent transformation, single management and control dimension, inability to adapt to dual-carbon policies, and high cost of existing building renovation.

[0006] This invention is achieved through the following scheme: A smart distribution box system based on embedded control includes a multi-source sensing and acquisition unit, a LoRa wireless communication unit, an edge data storage unit, an embedded development and control module, an execution output unit, and a remote operation and maintenance platform. The multi-source sensing and acquisition unit and the remote operation and maintenance platform are both connected to the edge data storage unit via the LoRa wireless communication unit. The edge data storage unit is connected to the embedded development and control module, and the embedded development and control module is connected to the execution output unit via the LoRa wireless communication unit. The execution output unit is integrated into the embedded development and control module.

[0007] Based on the aforementioned smart distribution box system with embedded control, the multi-source sensing and acquisition unit includes eight categories of data acquisition units: power, environment, human body, video, time, permissions, historical data, and equipment and circuit status. The multi-source sensing and acquisition unit provides the system with full-dimensional input data, and all sensing and acquisition devices communicate with the embedded development control module through the LoRa wireless network.

[0008] Based on the above-mentioned intelligent distribution box system based on embedded control, the power parameter acquisition specifically involves: configuring a dual-coil acquisition device consisting of a current transformer and a voltage transformer in each power supply circuit of the distribution box to collect basic power parameters such as instantaneous current, voltage, power supply frequency, active power, and reactive power of each circuit in real time, and accurately dividing the power data of each circuit for lighting, sockets, air conditioning, and power equipment. The environmental parameter collection process involves using existing air conditioning system panels and smart lighting panels to collect temperature, humidity, and illuminance data via compatible communication protocols. This data serves as the core basis for the adaptive control of air conditioning and lighting circuits. The human presence detection specifically involves: deploying millimeter-wave radar indoors to replace traditional infrared sensors, accurately identifying the static and dynamic state of people, avoiding interference from ambient temperature, and determining the presence, departure, and lingering status of people. The video image acquisition process involves: using a communication protocol compatible with existing surveillance cameras in the building area to acquire real-time video image data, which is then used by the embedded module to perform edge-end image recognition and analysis. The time signal specifically includes: a built-in high-precision clock module that synchronously acquires Beijing time, holiday information, and working / non-working time period tags; The historical energy consumption data specifically includes: retrieving historical energy consumption data for each circuit, equipment start-up and shutdown records, and user control operation records stored locally at the edge. The remote permission signal specifically refers to receiving advanced permission control signals issued by the remote operation and maintenance platform, including instructions for remote forced on / off, parameter threshold modification, time period locking, and permission allocation. The specific equipment and circuit status signals are: collecting the internal communication protocol of the equipment and the real-time on / off status, fault alarm status, and fault alarm type of each circuit's intelligent circuit breaker.

[0009] Based on the aforementioned intelligent power distribution box system with embedded control, the embedded development control module is equipped with an embedded main control chip and is matched with an edge data storage unit. It has five major capabilities: multi-source data parsing, intelligent linkage control, edge memory learning, edge image recognition, and data classification and statistics. It is the core computing power hub of the system. All data processing and instruction decisions are completed locally at the edge first, reducing the dependence on remote operation and maintenance platforms.

[0010] Based on the above-mentioned intelligent distribution box system based on embedded control, the data parsing specifically includes: decoding and standardizing various sensor signals, video signals, and power signals, unifying data formats, and storing them in categories; The intelligent linkage control algorithm consists of four major modules: scene linkage sub-algorithm, energy consumption optimization and adjustment sub-algorithm, time period control sub-algorithm, and fault diagnosis sub-algorithm. It issues execution instructions based on multi-source input signals. The edge memory learning function specifically involves collecting and recording data on users' daily air conditioning temperature settings, lighting usage times, socket power consumption habits, device start / stop preferences, and device failure frequency and type through machine learning algorithms. This data is then used to automatically generate personalized optimal energy consumption and operation switching strategies without the need for manual reconfiguration. The edge image recognition function is as follows: It has a built-in lightweight AI recognition model, which can complete personnel fall detection, early fire smoke recognition, and area personnel density statistics locally without uploading the original video to the cloud. When an anomaly is triggered, it can simultaneously perform alarm, power cut-off and linkage operations. The data classification and statistics function specifically includes: automatically calculating data on lighting energy consumption, air conditioning energy consumption, socket energy consumption, and power equipment energy consumption from multiple dimensions such as circuit, energy type, time period, and region, generating standardized energy consumption reports to meet the reporting requirements of dual-carbon assessment data.

[0011] Based on the aforementioned smart distribution box system with embedded control, the LORA wireless communication unit specifically adopts LORA low-power wide area network as the core communication method, taking into account communication distance, anti-interference capability, and low power consumption characteristics, and adapting to the complex power distribution environment of large public buildings with multiple walls obstructing the view; at the same time, it reserves 4G / 5G and WiFi communication expansion interfaces to achieve redundancy backup; all data interaction and command issuance between input sensors, actuators, embedded modules, and remote platforms are completed through the wireless network.

[0012] Based on the above-mentioned intelligent power distribution box system based on embedded control, the execution output unit receives instructions from the embedded control module to complete the operation of power distribution circuit on / off control, equipment start / stop and output adjustment, status data feedback, sub-item energy consumption output, and remote fault inspection.

[0013] Based on the above-mentioned intelligent distribution box system based on embedded control, the circuit on / off control specifically involves: directly controlling the intelligent circuit breakers of each circuit in the distribution box to realize the automatic / remote on / off of lighting circuits, socket circuits, air conditioning circuits, and power circuits; The specific start-up, shutdown, and output adjustment of the equipment are as follows: In places without refined energy-saving requirements, the start-up and shutdown control of the equipment on the circuit can be achieved by controlling the on / off state of the intelligent circuit breakers of each circuit; In places with refined energy-saving requirements, matching active power regulation modules or variable frequency speed control drivers are installed in each circuit to dynamically adjust the lighting output power, air conditioning operating frequency, and output of pumps and fans according to ambient illuminance, indoor temperature and humidity, and equipment load requirements, thereby achieving refined energy saving; Specifically, the status data feedback involves uploading the on / off status of each smart circuit breaker and the operating status of the equipment to the embedded module and the remote platform in real time. The specific energy consumption output includes: statistically analyzing and outputting the daily / weekly / monthly / annual energy consumption of each circuit, distinguishing between working hours and non-working hours, and completing the energy consumption classification and grading statistics for the corresponding area of ​​each circuit; Remote fault inspection specifically includes: supporting remote reading of fault codes, overload records, and leakage data of circuits and equipment; automatically locating fault points such as short circuits, leakage, overloads, and undervoltage; and outputting fault inspection results to the remote operation and maintenance platform to achieve unmanned remote fault inspection and fault early warning.

[0014] Based on the above-mentioned intelligent distribution box system with embedded control, the embedded development control module adopts an integrated modular design and is directly integrated into the standard distribution box; the current transformer + voltage transformer dual coil acquisition device is snap-on installed on the main line of each circuit; the intelligent circuit breaker adopts the national standard universal size and directly replaces the original ordinary circuit breaker; the communication layer adopts LORA networking throughout the entire domain.

[0015] This solution also discloses a control method for a smart distribution box system based on embedded control, including the following control methods: human body linkage energy-saving control, environmental adaptive regulation, edge memory optimization, and AI safety intelligent recognition; The human-linked energy-saving control specifically involves: millimeter-wave radar monitoring the status of people indoors in real time; when someone is detected indoors, it automatically triggers the corresponding area lighting circuit to turn on and the air conditioning circuit to start, and retrieves the user's historical habits to automatically match parameters; when no one is detected indoors and the preset time is maintained, it automatically turns off the lighting, air conditioning and unnecessary socket circuits to eliminate ineffective energy consumption. The environmental adaptive control is specifically as follows: the illuminance sensor collects ambient light data in real time, and the embedded algorithm dynamically adjusts the output power of the lighting circuit. When the light is sufficient, the lighting power is reduced, and when the light is insufficient, the power is increased to balance lighting comfort and energy consumption; the temperature and humidity sensor is linked to the air conditioning circuit to automatically adjust the air conditioning set temperature and operating mode, while locking the air conditioning operation permission during non-office hours to prevent invalid operation. The edge memory optimization specifically involves: the module continuously collects user energy consumption behavior and optimizes the control strategy through algorithm iteration, such as automatically memorizing the air conditioner set temperature in different seasons, the preferred brightness of lighting at different times, and the start and stop times of commonly used sockets, and actively adapting to user habits. AI-powered safety intelligent recognition specifically includes: relying on surveillance video image data to locally identify people falling, triggering an alarm and sending a notification to management personnel; identifying early-stage smoke and open flame characteristics of a fire, immediately cutting off the power supply to the corresponding hazardous circuit, and linking the fire alarm system. In summary, due to the adoption of the above technical solution, the beneficial effects of this solution are: 1. Multi-source fusion for precise control: It innovatively integrates multi-dimensional input signals from electricity, environment, human body, video, and historical data, and relies on embedded intelligent algorithms to achieve scenario-based linkage and adaptive power adjustment. Compared with traditional intelligent distribution boxes, the precision of control is effectively improved. 2. High stability of edge computing: It adopts a localized data processing architecture at the edge, eliminating the dependence on servers and enabling all management and control functions to be completed independently in an offline environment; 3. Easy deployment of wireless networking: The entire area adopts LORA low-power wireless communication, which eliminates the need for wiring construction, adapts to complex building power distribution environments, and solves the technical problems of difficult construction and poor adaptability of traditional wired transformation. 4. Multifunctional integration: It integrates six major functions: energy consumption statistics, scene energy saving, habit memory, AI safety recognition, remote fault inspection, and intelligent circuit breaker management. The integrated module replaces multiple independent devices, simplifying the power distribution system architecture.

[0016] 5. Low retrofit cost: Only 1-3 level distribution boxes and supporting sensors and actuators need to be upgraded, without the need for a complete overhaul of the building's power distribution system, which greatly reduces hardware procurement and construction costs; lightweight construction at night with no downtime losses indirectly reduces hidden retrofit costs. 6. Energy consumption reduction and efficiency improvement: Through energy-saving strategies such as human body linkage, environmental adaptation, and locking during non-working hours, the ineffective energy consumption of public buildings can be reduced, saving public institutions electricity consumption expenditure in the long term; 7. Reduced operation and maintenance costs: Relying on remote fault inspection and automatic fault early warning functions, the frequency of manual on-site inspections is reduced, thereby reducing the labor costs of power distribution system operation and maintenance, and at the same time reducing the repair costs caused by equipment failures.

[0017] 8. Precisely Adapted to Dual Carbon Policies: The system's segmented and time-period-based energy consumption statistics function fully matches the assessment requirements of the two energy conservation and carbon reduction policies issued by the General Office of the CPC Central Committee and the General Office of the State Council in 2026, helping public institutions to quickly complete the quantitative assessment of carbon emissions and energy consumption and avoid assessment risks. 9. Adapting to existing building renovation: Specifically addressing the industry pain points of difficult and impactful intelligent upgrades of existing public buildings, providing standardized, lightweight, and replicable power distribution energy-saving renovation solutions to help public institutions promote energy conservation and carbon reduction on a large scale; 10. Enhance electrical safety: Relying on AI fire detection, fall warning, and automatic power fault diagnosis functions, comprehensively improve the electrical safety level of public buildings and reduce the incidence of electrical fires, electric shocks, equipment damage, and other safety accidents. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall principle architecture of the present invention; Figure 2 This is a diagram of the embedded control smart power distribution box in Example 2; Detailed Implementation All features disclosed in this specification, or steps in all methods or processes disclosed herein, may be combined in any way, except for mutually exclusive features and / or steps.

[0019] Any feature disclosed in this specification (including any appended claims and abstract) may be replaced by other equivalent or similar features, unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is merely one example of a series of equivalent or similar features.

[0020] In the description of this invention, it should be understood that the terms "upper," "lower," "left," "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a predetermined orientation, or be constructed and operated in a predetermined orientation. Therefore, they should not be construed as limitations on this invention.

[0021] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature.

[0022] Example 1 like Figure 1 As shown, the present invention provides a technical solution: A smart distribution box system based on embedded control includes a multi-source sensing and acquisition unit, a LoRa wireless communication unit, an edge data storage unit, an embedded development and control module, an execution output unit, and a remote operation and maintenance platform. The multi-source sensing and acquisition unit and the remote operation and maintenance platform are both connected to the edge data storage unit via the LoRa wireless communication unit. The edge data storage unit is connected to the embedded development and control module, and the embedded development and control module is connected to the execution output unit via the LoRa wireless communication unit. The execution output unit is integrated into the embedded development and control module.

[0023] Based on the above structure, this invention uses an embedded development control module as the core hub to receive input signals from the entire domain, run a built-in dedicated intelligent control algorithm, and output corresponding loop regulation, data statistics, fault inspection, and safety early warning commands. It relies on the LoRa wireless network to complete data interaction and command transmission. The overall architecture adopts an edge computing + lightweight cloud collaborative architecture, capable of independent offline operation and synchronous data upload to a remote platform online. Specifically, this solution relies on the embedded development control module to achieve localized computing power support at the edge, integrating multi-source sensor acquisition, LoRa wireless communication, intelligent control algorithms, edge memory learning, and video image recognition technologies. It only requires replacing the building's level 2 and 3 electrical distribution boxes to achieve full-domain digital energy management. It also considers lightweight, low-cost retrofitting, low construction impact, scenario-based energy-saving linkage, multi-dimensional safety early warning, and remote intelligent operation and maintenance functions, accurately matching the relevant policy requirements for energy conservation and carbon reduction assessments of public institutions, and is particularly suitable for non-destructive nighttime upgrades of existing public buildings.

[0024] As an example, the multi-source sensing and acquisition unit can include eight categories of data acquisition units: power, environment, human body, video, time, permissions, historical data, and device and loop status. The multi-source sensing and acquisition unit provides the system with full-dimensional input data, and all sensing devices and acquisition devices establish communication with the embedded development control module through the LoRa wireless network. Specifically, power parameter acquisition can be achieved by configuring a dual-coil acquisition device consisting of a current transformer (CT) and a voltage transformer (PT) in each power supply circuit of the distribution box to collect real-time power parameters such as instantaneous current, voltage, power supply frequency, active power, and reactive power of each circuit, and accurately classifying the power data of each circuit such as lighting, sockets, air conditioning, and power equipment. Environmental parameter acquisition can specifically involve: prioritizing the use of existing air conditioning system panels, smart lighting panels, etc., and collecting temperature, humidity, illuminance and other parameter data through communication protocols (sensors can also be deployed separately) as the core basis for adaptive control of air conditioning and lighting circuits; Human presence sensing can specifically involve: deploying millimeter-wave radar indoors to replace traditional infrared sensors, accurately identifying static and dynamic human status, avoiding environmental temperature interference, and achieving high-precision determination of human presence, departure, and lingering status. Specifically, video image acquisition can be achieved by using a communication protocol compatible with existing surveillance cameras in the building area to obtain real-time video image data, which is then used by the embedded module to perform edge-end image recognition and analysis. Specifically, the time signal can be: a built-in high-precision clock module that synchronously acquires Beijing time, holiday information, and working / non-working time period tags; Historical energy consumption data can specifically include: retrieving historical energy consumption data for each circuit, equipment start-up and shutdown records, and user control operation records stored locally at the edge. Specifically, remote permission signals can be: receiving advanced permission control signals issued by the remote operation and maintenance platform, including instructions such as remote forced on / off, parameter threshold modification, time period locking, and permission allocation; Specifically, the equipment and circuit status signals can include: collecting the internal communication protocol of the equipment and the real-time on / off status, fault alarm status, and fault alarm type of each circuit's intelligent circuit breaker.

[0025] As an example, the embedded development control module is equipped with an embedded main control chip and is matched with the edge data storage unit. It has five core capabilities: multi-source data parsing, intelligent linkage control, edge memory learning, edge image recognition, and data classification and statistics. It is the core computing power hub of the system. All data processing and instruction decisions are completed locally at the edge first, reducing the dependence on remote operation and maintenance platforms. Specifically, data parsing involves decoding and standardizing various types of sensor signals, video signals, and power signals, unifying data formats, and storing them in categories. The intelligent linkage control algorithm consists of four major modules: scene linkage sub-algorithm, energy consumption optimization and adjustment sub-algorithm, time period control sub-algorithm, and fault diagnosis sub-algorithm. It issues execution instructions based on multi-source input signals. The edge memory learning function specifically involves collecting and recording data such as users' daily air conditioning temperature settings, lighting usage times, socket power consumption habits, device start / stop preferences, and device failure frequency and type through machine learning algorithms. This data is then used to automatically generate personalized optimal energy consumption and operation switching strategies without the need for manual reconfiguration. The edge image recognition function is as follows: It has a built-in lightweight AI recognition model, which can complete personnel fall detection, early fire smoke recognition, and area personnel density statistics locally without uploading the original video to the cloud. When an anomaly is triggered, it can simultaneously perform alarm, power cut-off, and linkage operations. The data classification and statistics function is as follows: it automatically calculates data such as lighting energy consumption, air conditioning energy consumption, socket energy consumption, and power equipment energy consumption by multiple dimensions such as circuit, energy type, time period, and region, and generates standardized energy consumption reports to meet the reporting requirements of dual carbon assessment data. As an example, the LORA wireless communication unit specifically adopts LORA low-power wide area network as the core communication method, which takes into account communication distance, anti-interference ability and low power consumption characteristics, and is suitable for the complex power distribution environment of large public buildings with multiple walls. At the same time, it reserves 4G / 5G and WiFi communication expansion interfaces to achieve redundancy backup. All data interaction and command issuance between input sensors, execution devices, embedded modules and remote platforms are completed through wireless network, eliminating the need to lay communication cables and greatly reducing the difficulty of transformation and construction.

[0026] As an example, the execution output unit receives instructions from the embedded control module to complete operations such as power distribution circuit on / off control, equipment start / stop and output adjustment, status data feedback, sub-item energy consumption output, and remote fault inspection. The specific output content includes the following five categories. The circuit on / off control specifically involves directly controlling the intelligent circuit breakers of each circuit in the distribution box to achieve automatic / remote on / off of lighting circuits, socket circuits, air conditioning circuits, and power circuits; The specific start-up, shutdown, and output adjustment of the equipment are as follows: In places without refined energy-saving requirements, the start-up and shutdown control of the equipment on the circuit can be achieved by controlling the on / off state of the intelligent circuit breakers of each circuit; In places with refined energy-saving requirements, matching active power regulation modules or variable frequency speed control drivers are installed in each circuit, which can dynamically adjust the lighting output power, air conditioning operating frequency, pump and fan output, etc., according to the ambient illuminance, indoor temperature and humidity, and equipment load requirements, to achieve refined energy saving; Specifically, the status data feedback involves uploading the on / off status of each smart circuit breaker and the operating status of the equipment to the embedded module and the remote platform in real time. The specific energy consumption output includes: statistically analyzing and outputting the daily / weekly / monthly / annual energy consumption of each circuit, distinguishing between working hours and non-working hours, and completing the energy consumption classification and grading statistics for the corresponding area of ​​each circuit; Remote fault inspection specifically includes: supporting remote reading of fault codes, overload records, and leakage data of circuits and equipment; automatically locating fault points such as short circuits, leakage, overloads, and undervoltage; and outputting fault inspection results to the remote operation and maintenance platform to achieve unmanned remote fault inspection and fault early warning.

[0027] Example 2 In the preferred design, the embedded development control module adopts an integrated modular design, which can be directly integrated into the standard distribution box; the CT+PT dual-coil acquisition device is snap-fitted onto the main line of each circuit; the intelligent circuit breaker adopts a national standard universal size, directly replacing the original ordinary circuit breaker; the communication layer adopts LORA networking throughout, adapting to low-impact construction modes at night. Embedded control intelligent distribution box design. Figure 2 As shown.

[0028] Example 3 like Figure 1As shown, the present invention provides a technical solution: A control method for a smart distribution box system based on embedded control includes the following control methods: human body linkage energy-saving control, environmental adaptive regulation, edge memory optimization, and AI safety intelligent recognition. The human-linked energy-saving control specifically involves: millimeter-wave radar monitoring the status of people indoors in real time; when someone is detected indoors, it automatically triggers the corresponding area lighting circuit to turn on and the air conditioning circuit to start, and retrieves the user's historical habits to automatically match the optimal parameters; when no one is detected indoors and this continues for a preset time, it automatically turns off the lighting, air conditioning and unnecessary socket circuits to eliminate ineffective energy consumption. The environmental adaptive control specifically involves: an illuminance sensor collecting ambient light data in real time, and an embedded algorithm dynamically adjusting the output power of the lighting circuit, reducing the lighting power when there is sufficient light and increasing the power when there is insufficient light, thus balancing lighting comfort and energy consumption; and a temperature and humidity sensor linking with the air conditioning circuit to automatically adjust the air conditioning set temperature and operating mode, while also locking the air conditioning operation permission during non-office hours to prevent invalid operation. The edge memory optimization specifically involves: the module continuously collects user energy consumption behavior and optimizes the control strategy through algorithm iteration, such as automatically memorizing the optimal set temperature of the air conditioner in different seasons, the preferred brightness of lighting at different times, and the start and stop times of commonly used sockets, and actively adapting to user habits. AI-powered safety intelligent recognition specifically involves: relying on surveillance video image data to locally identify people falling, triggering an alarm and sending a notification to management personnel; identifying early-stage smoke and open flame characteristics of a fire, immediately cutting off the power supply to the corresponding dangerous circuit, and linking the fire alarm system.

[0029] Meanwhile, this solution replaces all ordinary circuit breakers in traditional distribution boxes with intelligent circuit breakers adapted to this system, supporting local automatic control, remote manual control, and hierarchical access control, thus building a comprehensive intelligent circuit breaker management system. Furthermore, this solution only requires modular upgrades / replacements of the building's primary, secondary, and tertiary distribution boxes, without altering the building's original power supply lines or wall structures, and construction can be completed during nighttime downtime. After the upgrade, the system can automatically generate sub-item energy consumption statistical reports that meet the requirements of the "Comprehensive Evaluation and Assessment Method for Carbon Peaking and Carbon Neutrality" and the "Opinions on Doing a Higher Level and Higher Quality of Energy Conservation and Carbon Reduction Work," thus satisfying the energy conservation and carbon reduction assessment indicators for public institutions.

[0030] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart distribution box system based on embedded control, characterized in that, It includes a multi-source sensing and acquisition unit, a LoRa wireless communication unit, an edge data storage unit, an embedded development and control module, an execution output unit, and a remote operation and maintenance platform; wherein the multi-source sensing and acquisition unit and the remote operation and maintenance platform are both connected to the edge data storage unit through the LoRa wireless communication unit, the edge data storage unit is connected to the embedded development and control module, the embedded development and control module is connected to the execution output unit through the LoRa wireless communication unit; the execution output unit is integrated on the embedded development and control module.

2. The intelligent distribution box system based on embedded control according to claim 1, characterized in that: The multi-source sensing and acquisition unit includes eight categories of data acquisition units: power, environment, human body, video, time, permissions, historical data, and device and circuit status. The multi-source sensing and acquisition unit provides the system with full-dimensional input data, and all sensing devices and acquisition devices establish communication with the embedded development control module through the LoRa wireless network.

3. The intelligent distribution box system based on embedded control according to claim 2, characterized in that: Specifically, the power parameter acquisition involves configuring a dual-coil acquisition device consisting of a current transformer and a voltage transformer in each power supply circuit of the distribution box to collect the basic power parameters of each circuit in real time, including instantaneous current, voltage, power supply frequency, active power, and reactive power, and accurately classifying the power data of each circuit for lighting, sockets, air conditioning, and power equipment. The environmental parameter collection process involves using existing air conditioning system panels and smart lighting panels to collect temperature, humidity, and illuminance data via compatible communication protocols. This data serves as the core basis for the adaptive control of air conditioning and lighting circuits. The human presence detection specifically involves: deploying millimeter-wave radar indoors to replace traditional infrared sensors, accurately identifying the static and dynamic state of people, avoiding interference from ambient temperature, and determining the presence, departure, and lingering status of people. The video image acquisition process involves: using a communication protocol compatible with existing surveillance cameras in the building area to acquire real-time video image data, which is then used by the embedded module to perform edge-end image recognition and analysis. The time signal specifically includes: a built-in high-precision clock module that synchronously acquires Beijing time, holiday information, and working / non-working time period tags; The historical energy consumption data specifically includes: retrieving historical energy consumption data for each circuit, equipment start-up and shutdown records, and user control operation records stored locally at the edge. The remote permission signal specifically refers to receiving advanced permission control signals issued by the remote operation and maintenance platform, including instructions for remote forced on / off, parameter threshold modification, time period locking, and permission allocation. The specific equipment and circuit status signals are: collecting the internal communication protocol of the equipment and the real-time on / off status, fault alarm status, and fault alarm type of each circuit's intelligent circuit breaker.

4. The intelligent distribution box system based on embedded control according to claim 3, characterized in that: The embedded development control module is equipped with an embedded main control chip and is matched with the edge data storage unit. It has five major capabilities: multi-source data parsing, intelligent linkage control, edge memory learning, edge image recognition, and data classification and statistics. It is the core computing power hub of the system. All data processing and instruction decisions are completed locally at the edge first, reducing the dependence on remote operation and maintenance platforms.

5. The intelligent distribution box system based on embedded control according to claim 4, characterized in that: Specifically, data parsing involves decoding and standardizing various types of sensor signals, video signals, and power signals, unifying data formats, and storing them in categories. The intelligent linkage control algorithm consists of four major modules: scene linkage sub-algorithm, energy consumption optimization and adjustment sub-algorithm, time period control sub-algorithm, and fault diagnosis sub-algorithm. It issues execution instructions based on multi-source input signals. The edge memory learning function specifically involves collecting and recording data on users' daily air conditioning temperature settings, lighting usage times, socket power consumption habits, device start / stop preferences, and device failure frequency and type through machine learning algorithms. This data is then used to automatically generate personalized optimal energy consumption and operation switching strategies without the need for manual reconfiguration. The edge image recognition function is as follows: It has a built-in lightweight AI recognition model, which can complete personnel fall detection, early fire smoke recognition, and area personnel density statistics locally without uploading the original video to the cloud. When an anomaly is triggered, it can simultaneously perform alarm, power cut-off and linkage operations. The data classification and statistics function specifically includes: automatically calculating data on lighting energy consumption, air conditioning energy consumption, socket energy consumption, and power equipment energy consumption from multiple dimensions such as circuit, energy type, time period, and region, generating standardized energy consumption reports to meet the reporting requirements of dual-carbon assessment data.

6. The intelligent distribution box system based on embedded control according to claim 5, characterized in that: The LORA wireless communication unit specifically adopts LORA low-power wide area network as the core communication method, which takes into account communication distance, anti-interference ability and low power consumption characteristics, and is suitable for complex power distribution environment with multiple walls in large public buildings; at the same time, it reserves 4G / 5G and WiFi communication expansion interfaces to achieve redundancy backup; all data interaction and command issuance between input sensors, actuators, embedded modules and remote platforms are completed through wireless network.

7. A smart distribution box system based on embedded control according to claim 6, characterized in that: The execution output unit receives instructions from the embedded control module to complete operations such as power distribution circuit on / off control, equipment start / stop and output adjustment, status data feedback, sub-item energy consumption output, and remote fault inspection.

8. The intelligent distribution box system based on embedded control according to claim 7, characterized in that: The circuit on / off control specifically involves directly controlling the intelligent circuit breakers of each circuit in the distribution box to achieve automatic / remote on / off of lighting circuits, socket circuits, air conditioning circuits, and power circuits; The specific start-up, shutdown, and output adjustment of the equipment are as follows: In places without refined energy-saving requirements, the start-up and shutdown control of the equipment on the circuit can be achieved by controlling the on / off state of the intelligent circuit breakers of each circuit; In places with refined energy-saving requirements, matching active power regulation modules or variable frequency speed control drivers are installed in each circuit to dynamically adjust the lighting output power, air conditioning operating frequency, and output of pumps and fans according to ambient illuminance, indoor temperature and humidity, and equipment load requirements, thereby achieving refined energy saving; Specifically, the status data feedback involves uploading the on / off status of each smart circuit breaker and the operating status of the equipment to the embedded module and the remote platform in real time. The specific energy consumption output includes: statistically analyzing and outputting the daily / weekly / monthly / annual energy consumption of each circuit, distinguishing between working hours and non-working hours, and completing the energy consumption classification and grading statistics for the corresponding area of ​​each circuit; Remote fault inspection specifically includes: supporting remote reading of fault codes, overload records, and leakage data of circuits and equipment; automatically locating fault points such as short circuits, leakage, overloads, and undervoltage; and outputting fault inspection results to the remote operation and maintenance platform to achieve unmanned remote fault inspection and fault early warning.

9. The intelligent distribution box system based on embedded control according to claim 1, characterized in that: The embedded development control module adopts an integrated modular design and is directly integrated into the standard distribution box; the current transformer + voltage transformer dual coil acquisition device is snap-on installed on the main line of each circuit; the intelligent circuit breaker adopts the national standard universal size and directly replaces the original ordinary circuit breaker; the communication layer adopts LORA networking throughout the entire domain.

10. A control method for a smart distribution box system based on embedded control, characterized in that: The control methods include: human body linkage energy-saving control, environmental adaptive regulation, edge memory optimization, and AI safety intelligent recognition. The human-linked energy-saving control specifically involves: millimeter-wave radar monitoring the status of people indoors in real time; when someone is detected indoors, it automatically triggers the corresponding area lighting circuit to turn on and the air conditioning circuit to start, and retrieves the user's historical habits to automatically match parameters; when no one is detected indoors and the preset time is maintained, it automatically turns off the lighting, air conditioning and unnecessary socket circuits to eliminate ineffective energy consumption. The environmental adaptive control is specifically as follows: the illuminance sensor collects ambient light data in real time, and the embedded algorithm dynamically adjusts the output power of the lighting circuit. When the light is sufficient, the lighting power is reduced and when the light is insufficient, the power is increased to balance lighting comfort and energy consumption; the temperature and humidity sensor is linked to the air conditioning circuit to automatically adjust the air conditioning set temperature and operating mode, while locking the air conditioning operation permission during non-office hours to prevent invalid operation. The edge memory optimization specifically involves: the module continuously collects user energy consumption behavior and optimizes the control strategy through algorithm iteration, such as automatically memorizing the air conditioner set temperature in different seasons, the preferred brightness of lighting at different times, and the start and stop times of commonly used sockets, and actively adapting to user habits. AI-powered safety intelligent recognition specifically involves: relying on surveillance video image data to locally identify people falling, triggering an alarm and sending a notification to management personnel; identifying early-stage smoke and open flame characteristics of a fire, immediately cutting off the power supply to the corresponding dangerous circuit, and linking the fire alarm system.

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