Emergency lighting intelligent starting and switching system and method

Abstract

The invention relates to the technical field of emergency lighting, in particular to an emergency lighting intelligent starting and switching method, which comprises the following steps of: completing module initialization by adopting an embedded controller, establishing a communication network, calibrating a sensor, and monitoring the voltage of a main power supply and the residual electric quantity of a lithium battery in real time; through triggering in three modes of fire alarm linkage, power failure self-inspection and manual emergency button, personnel evacuation simulation software is combined with a fire spreading model, a three-level power supply architecture of commercial power, a diesel generator and a lithium battery is adopted, a time-sharing charging strategy and battery health management are adopted, and through simulation of commercial power interruption test and annual sensor calibration, the safety of a power supply system is improved. And the fault rate and the response time of the module are optimized to obtain long-term stable operation guarantee. According to the invention, the problems of high system failure rate, untimely response and poor operation stability caused by single traditional emergency lighting starting mode and lack of an effective self-checking test mechanism are solved.

Description

Technical Field

[0001] This invention belongs to the field of emergency lighting technology, specifically relating to an intelligent emergency lighting start-up and switching system and method. Background Technology

[0002] In various public places, such as shopping malls, office buildings, and underground parking lots, emergency lighting systems are crucial facilities for ensuring safe evacuation and firefighting operations. Traditional emergency lighting systems have numerous drawbacks and fail to meet the safety requirements of modern buildings. Traditional emergency lighting relies on a single power fault detection method, which cannot respond promptly to emergencies such as fires, failing to activate quickly in the early stages of a fire to buy valuable time for evacuation. Furthermore, its fixed lighting guidance method cannot provide precise escape route guidance based on the dynamic changes in the fire scene, such as the location of the fire and the direction of smoke, easily leading to people falling into danger due to blind escape. In terms of energy utilization, traditional emergency lighting systems have an unreasonable power supply architecture and lack effective energy management strategies. The charging process lacks scientific planning, easily leading to energy waste, and the lack of battery health management results in short battery life and increased maintenance costs. In addition, the stability and reliability of traditional emergency lighting systems are difficult to guarantee. The lack of regular simulation testing and effective self-checking mechanisms makes it impossible to detect potential faults in time. In emergencies such as power outages, there may be problems with delayed response or even failure to activate, seriously threatening the safety of people.

[0003] Existing technologies suffer from problems such as a single start-up method, inability to dynamically guide lighting based on fire conditions, lack of scientific management of energy use leading to waste and poor battery maintenance, and lack of effective self-testing mechanisms resulting in insufficient system stability and reliability. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides an intelligent emergency lighting activation and switching system and method. This system solves the problems of traditional emergency lighting, such as a single activation method, inability to dynamically adjust evacuation guidance based on fire conditions, unreasonable energy utilization and poor battery maintenance, high system failure rate due to a lack of effective self-testing mechanisms, untimely response, and poor operational stability. To achieve the above objectives, this invention adopts the following technical solution: The intelligent start-up and switching method for emergency lighting includes the following steps: Initializing the module using an embedded controller, establishing a communication network and calibrating sensors; acquiring backup power capacity and main power status data by real-time monitoring of main power voltage and remaining lithium battery power to obtain initial operating parameters for the module; triggering the module through three methods—fire alarm linkage, power fault self-check, and manual emergency button—to extract fire alarm signals, voltage anomaly data, and manual commands, switching the emergency lighting module to working state, and obtaining emergency start-up response results; using personnel evacuation simulation software combined with a fire spread model, extracting escape path data by real-time analysis of fire location and smoke direction, and dynamically adjusting the brightness and direction of evacuation indicator lights to obtain an intelligent guidance lighting scheme; employing a three-level power supply architecture of mains power, diesel generator, and lithium battery, using a time-sharing charging strategy and battery health management, extracting grid load data and battery internal resistance changes, optimizing charging power and maintenance cycles to obtain efficient energy utilization results; and through simulated mains power outage testing and annual sensor calibration, using an automatic reset process to restore the module to standby state, extracting self-check data and maintenance records, optimizing module failure rate and response time to ensure long-term stable operation.

[0005] Furthermore, the module initialization using an embedded controller, the establishment of a communication network, and the calibration of sensors, along with the acquisition of backup power capacity and main power status data through real-time monitoring of the main power voltage and remaining lithium battery power, yields the initial operating parameters of the module. This process includes the following steps: using an embedded controller as the core control unit to initialize and configure the power management module, sensor module, and communication module, ensuring the hardware units are in standby mode; establishing an RS-485 communication network to enable data interaction between the controller and the fire alarm module and lithium battery monitoring unit, real-time acquisition of main power voltage fluctuation data and lithium battery voltage and current parameters, and extraction of valid values; calculating the remaining backup power capacity using a built-in algorithm, obtaining the main power abnormal status flag, and integrating the voltage fluctuation data and lithium battery voltage and current parameters into a structured parameter set to obtain the initial operating parameters of the module.

[0006] Furthermore, the emergency lighting module is switched to working state through three triggering methods: fire alarm linkage, power fault self-check, and manual emergency button. This process extracts fire alarm signals, voltage anomaly data, and manual commands, resulting in an emergency start response. The steps include: employing a multi-mode triggering mechanism to activate the emergency lighting, utilizing the linkage signal transmitted in real-time by the fire alarm module and the main power voltage fluctuation data collected by the power monitoring module; assigning manual emergency button input commands and extracting three types of information: fire alarm location code, voltage anomaly amplitude, and manual triggering identifier; processing these three types of information signals through a logic judgment unit to generate an emergency start control command, driving the lighting module to switch from standby to full power output, thus obtaining the emergency start response result.

[0007] Furthermore, the method of using personnel evacuation simulation software combined with a fire spread model to extract escape path data by analyzing the fire location and smoke direction in real time, and dynamically adjusting the brightness and direction of evacuation indicator lights to obtain an intelligent guidance lighting scheme, includes the following steps: using an intelligent analysis platform that integrates personnel evacuation simulation algorithms and fire dynamic spread models, and accessing the fire source coordinates fed back by fire detectors and the diffusion direction data collected by smoke sensors in real time; using a path optimization algorithm to extract information on unobstructed, low-smoke escape routes, and converting the extracted path data into a spatial coordinate sequence; and using a controller to process and generate dynamic adjustment commands to drive the evacuation indicator lights to complete brightness level enhancement and real-time directional arrow turning, outputting an intelligent guidance lighting scheme that includes path visualization, light intensity distribution, and personnel diversion strategies.

[0008] Furthermore, the three-tiered power supply architecture of mains power, diesel generator, and lithium battery, employing a time-sharing charging strategy and battery health management, extracts grid load data and battery internal resistance changes, optimizes charging power and maintenance cycles, and achieves efficient energy utilization results. This includes the following steps: Constructing an energy security system using a three-tiered power supply architecture with mains power, diesel generator backup, and lithium battery emergency power; collecting grid load peak and valley data in real time using smart meters; extracting electricity demand characteristics and battery health status parameters for different time periods by combining the lithium battery internal resistance growth trend monitored by the battery management module; inputting the collected data into an optimization algorithm model to dynamically adjust the lithium battery charging power and maintenance cycle, outputting a tiered charging scheme and preventative maintenance strategy that matches electricity consumption patterns, using a 0.2C charging rate during off-peak periods, and triggering equalization maintenance when internal resistance exceeds the standard, thus achieving efficient energy utilization results.

[0009] Furthermore, the method of simulating mains power outage tests and annual sensor calibration, using an automatic reset process to restore the module to standby state, extracting self-test data and maintenance records, and optimizing the module failure rate and response time to achieve long-term stable operation assurance includes the following steps: employing a periodic simulated mains power outage test and annual sensor accuracy calibration mechanism, triggering an emergency power supply mode by cutting off the mains power input, and simultaneously recording module switching time and power stability data; using calibration equipment to perform zero-point drift correction and range calibration on smoke and voltage sensors, extracting fault codes, response delay parameters, and calibrated sensor error values ​​from the tests; inputting the data into a fault prediction model to generate a maintenance strategy, and by repairing high-frequency fault points and optimizing switching logic circuits, extending the module's average fault interval to over 5000 hours, thus obtaining a long-term stable operation assurance system that meets fire safety regulations.

[0010] The second aspect of this invention provides an intelligent emergency lighting start-up and switching system, which includes the following modules: an emergency triggering module, used to trigger the system through three methods: fire alarm linkage, power fault self-check, and manual emergency button; extracting fire alarm signals, voltage anomaly data, and manual commands; switching the emergency lighting module to the working state; obtaining an emergency start-up response result; a lighting adjustment module, used to use personnel evacuation simulation software combined with a fire spread model; by analyzing the fire location and smoke direction in real time, extracting escape path data, and dynamically adjusting the brightness and direction of evacuation indicator lights to obtain an intelligent guidance lighting scheme; a power management module, used to use a three-level power supply architecture of mains power, diesel generator, and lithium battery; employing a time-sharing charging strategy and battery health management; extracting grid load data and battery internal resistance changes; optimizing charging power and maintenance cycle to obtain efficient energy utilization results; and a self-check and maintenance module, used to restore the module to standby state through simulated mains power interruption tests and annual sensor calibration; extracting self-check data and maintenance records; optimizing module failure rate and response time; and ensuring long-term stable operation.

[0011] A third aspect of the present invention provides an intelligent emergency lighting start-up and switching device, the intelligent emergency lighting start-up and switching device comprising a memory and at least one processor, the memory storing instructions; the at least one processor calling the instructions in the memory to cause the intelligent emergency lighting start-up and switching device to perform the steps of the intelligent emergency lighting start-up and switching method as described in any of the preceding claims.

[0012] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions, characterized in that, when executed by a processor, the instructions implement the steps of the emergency lighting intelligent start-up and switching method as described in any one of the preceding claims.

[0013] In the technical solution provided by this invention, an embedded controller is used to complete module initialization, establish a communication network and calibrate sensors. By real-time monitoring of the main power voltage and the remaining power of the lithium battery, the backup power capacity and main power status data are obtained to obtain the initial operating parameters of the module. The module is triggered in three ways: fire alarm linkage, power fault self-test, and manual emergency button. Fire alarm signals, voltage anomaly data and manual commands are extracted to switch the emergency lighting module to the working state, and the emergency start response result is obtained. The personnel evacuation simulation software combined with the fire spread model is used to extract escape path data by analyzing the fire location and smoke direction in real time. The brightness and direction of the evacuation indicator lights are dynamically adjusted to obtain an intelligent guidance lighting scheme. Through a three-level power supply architecture of mains power, diesel generator and lithium battery, a time-sharing charging strategy and battery health management are adopted to extract grid load data and battery internal resistance changes. The charging power and maintenance cycle are optimized to obtain efficient energy utilization results. Through simulated mains power interruption test and annual sensor calibration, an automatic reset process is used to restore the module to standby state. Self-test data and maintenance records are extracted to optimize the module failure rate and response time, and to obtain long-term stable operation guarantee. This invention solves the problems of traditional emergency lighting, such as a single activation method, inability to dynamically adjust evacuation guidance according to the fire situation, unreasonable energy utilization and poor battery maintenance, lack of effective self-testing mechanism leading to high system failure rate, untimely response and poor operational stability. Attached Figure Description

[0014] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0015] Figure 1 This is a schematic diagram of the first embodiment of an intelligent emergency lighting start-up and switching method according to the present invention.

[0016] Figure 2 This is a schematic diagram of a second embodiment of an emergency lighting intelligent start-up and switching method according to an embodiment of the present invention.

[0017] Figure 3 This is a schematic diagram of a third embodiment of an intelligent emergency lighting start-up and switching method according to the present invention.

[0018] Figure 4 This is a schematic diagram of the fourth embodiment of an emergency lighting intelligent start-up and switching method according to the present invention.

[0019] Figure 5 This is a schematic diagram of the fifth embodiment of an intelligent emergency lighting start-up and switching method according to the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0022] A method for intelligent activation and switching of emergency lighting, such as Figure 1 As shown, the process includes the following steps: First, an embedded controller is used to initialize the module, establish a communication network, and calibrate the sensors. Second, by real-time monitoring of the main power voltage and remaining lithium battery power, backup power capacity and main power status data are obtained to acquire the module's initial operating parameters. Third, the module is triggered through three methods: fire alarm linkage, power fault self-check, and manual emergency button. Fire alarm signals, voltage anomaly data, and manual commands are extracted to switch the emergency lighting module to working status, resulting in an emergency response. Fourth, using personnel evacuation simulation software combined with a fire spread model, real-time analysis of fire location and smoke direction is employed to extract escape path data. The brightness and direction of evacuation indicator lights are dynamically adjusted to obtain an intelligent guidance lighting scheme. Fifth, through a three-tiered power supply architecture of mains power, diesel generator, and lithium battery, a time-sharing charging strategy and battery health management are adopted to extract grid load data and battery internal resistance changes. Charging power and maintenance cycles are optimized to achieve efficient energy utilization. Sixth, through simulated mains power outage testing and annual sensor calibration, an automatic reset process is used to restore the module to standby state. Self-check data and maintenance records are extracted to optimize the module's failure rate and response time, ensuring long-term stable operation.

[0023] like Figure 2 As shown, in this embodiment, an embedded controller is used as the core control unit to initialize and configure the power management module, sensor module, and communication module, ensuring that the hardware units are in standby mode. By establishing an RS-485 communication network, data interaction between the controller and the fire alarm module and lithium battery monitoring unit is realized, real-time collection of main power voltage fluctuation data and lithium battery voltage and current parameters is performed, and effective values ​​are extracted. The remaining capacity of the backup power supply is calculated through the built-in algorithm, the main power abnormal status flag is obtained, and the voltage fluctuation data and lithium battery voltage and current parameters are extracted and integrated into a structured parameter set to obtain the initial operating parameters of the module.

[0024] An embedded controller is used as the core to initialize and configure each hardware module, allowing the system to quickly enter standby mode and laying the foundation for stable operation. An RS-485 communication network is established, enabling efficient data interaction between the controller and multiple modules, and allowing for real-time and accurate acquisition of key parameters of the main power supply and lithium battery. Built-in algorithms accurately calculate the remaining capacity of the backup power supply, obtain main power supply anomaly flags, and integrate the collected data into a structured parameter set to obtain the initial operating parameters of the modules. This provides comprehensive and accurate data support for intelligent startup and switching of emergency lighting, ensuring the system can respond quickly and accurately according to actual conditions.

[0025] like Figure 3 As shown, in this embodiment, a multi-mode triggering mechanism is used to activate emergency lighting. This is achieved through the linkage signal transmitted in real time by the fire alarm module and the main power voltage fluctuation data collected by the power monitoring module. Manual emergency button input commands are deployed, and three types of information are extracted: fire alarm location code, voltage abnormality amplitude, and manual triggering identifier. The three types of information signals are processed by the logic judgment unit to generate an emergency start control command, which drives the lighting module to complete the state switch from standby to full power output, thus obtaining the emergency start response result.

[0026] Employing a multi-mode triggering mechanism, it integrates fire alarm linkage signals, mains voltage fluctuation data, and manual emergency button commands to ensure the timely activation of emergency lighting from multiple dimensions. It can accurately extract three key types of information: fire alarm location code, abnormal voltage amplitude, and manual triggering indicator, providing rich data for accurate assessment of emergency situations. After processing by the logic judgment unit, it generates an emergency start control command, which can quickly drive the lighting module to complete the state switch, achieving a seamless transition from standby to full power output. This effectively shortens emergency response time and ensures that emergency lighting can quickly function in various emergency situations, guaranteeing the safe evacuation of personnel.

[0027] like Figure 4 As shown, in this embodiment, an intelligent analysis platform integrating personnel evacuation simulation algorithm and fire dynamic spread model is adopted. It accesses the fire source coordinates fed back by fire detectors and the diffusion direction data collected by smoke sensors in real time; uses path optimization algorithm to extract information on unobstructed, low-smoke escape routes, and converts the extracted path data into a spatial coordinate sequence; through controller processing, it generates dynamic adjustment commands to drive evacuation indicator lights to complete brightness level enhancement and real-time directional arrow turning, and outputs an intelligent guidance lighting scheme that includes path visualization, light intensity distribution and personnel diversion strategy.

[0028] Leveraging an intelligent analysis platform integrating algorithms and models, real-time access to fire source and smoke data enables precise assessment of the fire situation. Escape route information extracted using path optimization algorithms is transformed into a spatial coordinate sequence, providing a foundation for precise guidance. The controller processes this information to generate dynamic adjustment commands, driving evacuation indicator lights to achieve graded brightness enhancement and real-time directional arrow changes, outputting an intelligent guidance lighting scheme. This scheme not only clearly indicates escape routes to personnel through visual signage and reasonable light intensity distribution but also avoids congestion through personnel diversion strategies.

[0029] like Figure 5 As shown, in this embodiment, a three-tiered power supply architecture is adopted to construct an energy security system, consisting of main grid power supply, diesel generator backup, and lithium battery emergency power supply. Real-time peak and off-peak load data of the power grid is collected via smart meters. Combined with the lithium battery internal resistance growth trend monitored by the battery management module, the characteristics of electricity demand and battery health status parameters at different times are extracted. The collected data is input into an optimization algorithm model to dynamically adjust the lithium battery charging power and maintenance cycle, outputting a tiered charging scheme and preventative maintenance strategy that matches electricity consumption patterns. Charging at a 0.2C rate is used during off-peak periods, and equalization maintenance is triggered when the internal resistance exceeds the standard, resulting in efficient energy utilization.

[0030] A three-tiered power supply architecture establishes a robust energy security system, with mains power, diesel generators, and lithium batteries working together to ensure stable power supply for emergency lighting under any circumstances. Smart meters collect grid load data in real time, and combined with the battery management module's monitoring of lithium battery internal resistance, accurately extracting power demand and battery health parameters. An optimized algorithm model dynamically adjusts charging power and maintenance cycles accordingly, outputting tiered charging schemes and preventative maintenance strategies. For example, charging at a 0.2C rate during off-peak hours and timely equalization maintenance when internal resistance exceeds limits effectively improves energy utilization efficiency, extends battery life, and reduces operation and maintenance costs.

[0031] In this embodiment, a periodic simulated mains power outage test and annual sensor accuracy calibration mechanism are adopted. By cutting off the main power input, an emergency power supply mode is triggered, and the module switching time and power stability data are recorded simultaneously. Calibration equipment is used to perform zero-point drift correction and range calibration on smoke and voltage sensors, and fault codes, response delay parameters and calibrated sensor error values ​​are extracted from the test. The data is input into a fault prediction model to generate a maintenance strategy. By repairing high-frequency fault points and optimizing the switching logic circuit, the average fault interval of the module is extended to more than 5,000 hours, resulting in a long-term stable operation guarantee system that meets the requirements of fire protection specifications.

[0032] Periodic simulated mains power outage tests and annual sensor accuracy calibration mechanisms comprehensively verify the performance of the emergency lighting system. Disconnecting the mains power triggers an emergency power supply mode and records key data, allowing for precise monitoring of module switching and power stability. Sensor calibration corrects errors, and extracted fault codes and other parameters provide a basis for problem analysis. Data is input into a fault prediction model to generate maintenance strategies, repairing high-frequency fault points and optimizing circuits, significantly extending the mean time between failures (MTBF) to over 5000 hours, effectively improving system reliability.

[0033] This invention also provides an intelligent emergency lighting start-up and switching system, comprising the following modules: an emergency trigger module, used to trigger the system through three methods: fire alarm linkage, power fault self-check, and manual emergency button; extracting fire alarm signals, voltage anomaly data, and manual commands; switching the emergency lighting module to the working state; obtaining emergency start-up response results; a lighting adjustment module, used to use personnel evacuation simulation software combined with a fire spread model; by analyzing the fire location and smoke direction in real time, extracting escape path data, and dynamically adjusting the brightness and direction of evacuation indicator lights to obtain an intelligent guidance lighting scheme; a power management module, used to use a three-level power supply architecture of mains power, diesel generator, and lithium battery; employing a time-sharing charging strategy and battery health management; extracting grid load data and battery internal resistance changes; optimizing charging power and maintenance cycle to obtain efficient energy utilization results; and a self-check and maintenance module, used to restore the module to standby state through simulated mains power interruption tests and annual sensor calibration; extracting self-check data and maintenance records; optimizing module failure rate and response time; and ensuring long-term stable operation.

[0034] The emergency trigger module uses multiple methods to precisely trigger, quickly extract key information, and switch lighting modules to ensure timely activation of emergency lighting. The lighting adjustment module, utilizing software and models, dynamically adjusts evacuation indicator lights to provide clear and accurate escape guidance. The power management module constructs a three-tiered power supply architecture, optimizing charging power and maintenance cycles for efficient energy utilization. The self-testing and maintenance module performs regular testing and calibration, automatically resetting to standby mode, optimizing failure rate and response time. All modules work collaboratively to comprehensively improve the emergency lighting system's response speed, guidance capabilities, energy efficiency, and operational stability.

[0035] This invention also provides an intelligent emergency lighting start-up and switching device. This device may further include one or more power supplies, one or more wired or wireless network interfaces, one or more input / output interfaces, and / or one or more operating systems, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that the structure of the intelligent emergency lighting start-up and switching device does not constitute a limitation on the computer device provided by this invention, and may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0036] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the various steps of the emergency lighting intelligent start-up and switching method provided in the above embodiments.

[0037] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent activation and switching of emergency lighting, characterized in that, The intelligent activation and switching method for emergency lighting includes the following steps: The module initialization is completed by an embedded controller, a communication network is established and the sensors are calibrated. By monitoring the main power voltage and the remaining power of the lithium battery in real time, the backup power capacity and main power status data are obtained to obtain the initial operating parameters of the module. The emergency lighting module is switched to working status by three methods: fire alarm linkage, power fault self-check and manual emergency button. The fire alarm signal, voltage abnormality data and manual command are extracted to obtain the emergency start response result. By combining personnel evacuation simulation software with a fire spread model, and by analyzing the location of the fire and the direction of the smoke in real time, the escape route data is extracted, and the brightness and direction of the evacuation indicator lights are dynamically adjusted to obtain an intelligent guidance lighting solution. By using a three-tier power supply architecture consisting of mains power, diesel generator, and lithium battery, and employing time-sharing charging strategies and battery health management, the grid load data and battery internal resistance changes are extracted to optimize charging power and maintenance cycles, resulting in efficient energy utilization. By simulating mains power outage tests and annual sensor calibration, an automatic reset process is used to restore the module to standby state, extract self-test data and maintenance records, optimize the module failure rate and response time, and ensure long-term stable operation.

2. The method for intelligent activation and switching of emergency lighting according to claim 1, characterized in that, The module initialization is completed using an embedded controller, a communication network is established and sensors are calibrated, and the backup power capacity and main power status data are obtained by real-time monitoring of the main power voltage and the remaining lithium battery power to obtain the initial operating parameters of the module, including the following steps: An embedded controller is used as the core control unit to initialize and configure the power management module, sensor module and communication module to ensure that the hardware unit is in standby mode. By establishing an RS-485 communication network, the controller can interact with the fire alarm module and the lithium battery monitoring unit to collect main power voltage fluctuation data and lithium battery voltage and current parameters in real time and extract effective values. The built-in algorithm calculates the remaining capacity of the backup power supply, obtains the main power abnormal status flag, extracts the effective values ​​of voltage fluctuation data and lithium battery voltage and current parameters, integrates them into a structured parameter set, and obtains the initial operating parameters of the module.

3. The method for intelligent activation and switching of emergency lighting according to claim 1, characterized in that, The emergency lighting module is switched to working status through three triggering methods: fire alarm linkage, power fault self-check, and manual emergency button. This process involves extracting fire alarm signals, voltage anomaly data, and manual commands to obtain the emergency activation response result, including the following steps: Emergency lighting is activated using a multi-mode triggering mechanism, which is achieved through real-time transmission of linkage signals from the fire alarm module and main power voltage fluctuation data collected by the power monitoring module. Manual emergency button input commands were set up, and three types of information were extracted: fire alarm location code, abnormal voltage amplitude, and manual triggering indicator; The three types of information signals are processed by the logic judgment unit to generate an emergency start control command, which drives the lighting module to complete the state switch from standby to full power output, and obtains the emergency start response result.

4. The method for intelligent activation and switching of emergency lighting according to claim 1, characterized in that, The method employs personnel evacuation simulation software combined with a fire spread model. By analyzing the fire location and smoke direction in real time and extracting escape route data, the brightness and direction of evacuation indicator lights are dynamically adjusted to obtain an intelligent guidance lighting scheme, which includes the following steps: An intelligent analysis platform that integrates personnel evacuation simulation algorithms and fire dynamic spread models is used to access the fire source coordinates fed back by fire detectors and the diffusion direction data collected by smoke sensors in real time. The path optimization algorithm is used to extract information on unobstructed escape routes with low smoke concentration, and the extracted path data is converted into a spatial coordinate sequence. The controller processes the data and generates dynamic adjustment commands to drive evacuation indicator lights to achieve brightness level enhancement and real-time directional arrow turning, outputting an intelligent guidance lighting solution that includes path visualization, light intensity distribution, and personnel diversion strategies.

5. The method for intelligent activation and switching of emergency lighting according to claim 1, characterized in that, The aforementioned three-tier power supply architecture, consisting of mains power, diesel generator, and lithium battery, employs a time-sharing charging strategy and battery health management. It extracts grid load data and battery internal resistance changes, optimizes charging power and maintenance cycles, and achieves high-efficiency energy utilization. The process includes the following steps: An energy security system is constructed using a three-tiered power supply architecture: main grid power supply, diesel generator backup, and lithium battery emergency power supply. Smart meters are used to collect grid load peak and valley data in real time. Based on the lithium battery internal resistance growth trend monitored by the battery management module, the power demand characteristics and battery health status parameters at different time periods are extracted. The collected data is input into the optimization algorithm model to dynamically adjust the lithium battery charging power and maintenance cycle. The output is a graded charging scheme and preventive maintenance strategy that matches the power consumption pattern. During off-peak periods, a 0.2C charging rate is used, and equalization maintenance is triggered when the internal resistance exceeds the standard, resulting in efficient energy utilization.

6. The method for intelligent activation and switching of emergency lighting according to claim 1, characterized in that, The process involves simulating mains power outage tests and annual sensor calibration, using an automatic reset procedure to restore the module to standby state, extracting self-test data and maintenance records, optimizing the module failure rate and response time, and ensuring long-term stable operation. This includes the following steps: The system employs a periodic simulated mains power outage test and an annual sensor accuracy calibration mechanism. By cutting off the mains power input, an emergency power supply mode is triggered, and the module switching time and power stability data are recorded simultaneously. The zero-point drift correction and range calibration of the smoke and voltage sensors were performed using calibration equipment, and the fault codes, response delay parameters and sensor error values ​​after calibration were extracted during the test. By inputting data into the fault prediction model to generate maintenance strategies, and by repairing high-frequency fault points and optimizing switching logic circuits, the average fault interval of the module is extended to more than 5,000 hours, thus obtaining a long-term stable operation guarantee system that meets the requirements of fire protection specifications.

7. An intelligent emergency lighting start-up and switching system, characterized in that, The intelligent emergency lighting activation and switching system includes the following modules: The initialization module is used to complete the module initialization using an embedded controller, establish a communication network and calibrate sensors, and obtain the backup power capacity and main power status data by real-time monitoring of the main power voltage and the remaining power of the lithium battery to obtain the initial operating parameters of the module. The emergency trigger module is used to trigger the emergency lighting module to work through three methods: fire alarm linkage, power fault self-check and manual emergency button. It extracts fire alarm signals, voltage abnormality data and manual commands, and obtains emergency start response results. The lighting adjustment module is used to combine personnel evacuation simulation software with fire spread model, and extract escape path data by analyzing the fire location and smoke direction in real time, and dynamically adjust the brightness and direction of evacuation indicator lights to obtain an intelligent guidance lighting solution. The power management module is used to optimize charging power and maintenance cycle through a three-level power supply architecture of mains power, diesel generator and lithium battery, adopt time-sharing charging strategy and battery health management, extract grid load data and battery internal resistance changes, and obtain efficient energy utilization results. The self-test and maintenance module is used to simulate mains power outage tests and annual sensor calibration, and uses an automatic reset process to restore the module to standby state, extract self-test data and maintenance records, optimize the module failure rate and response time, and ensure long-term stable operation.

8. An intelligent emergency lighting start-up and switching device, characterized in that, The emergency lighting intelligent start-up and switching device includes a memory and at least one processor. The memory stores instructions, and the at least one processor calls the instructions in the memory to cause the emergency lighting intelligent start-up and switching device to perform the steps of the emergency lighting intelligent start-up and switching method as described in any one of claims 1-6.

9. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement each step of the emergency lighting intelligent start-up and switching method as described in any one of claims 1-6.

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