Fire-fighting equipment availability monitoring and intelligent three-dimensional warehouse storage management system

Abstract

The invention discloses a fire-fighting equipment availability monitoring and intelligent three-dimensional warehouse storage management system, and relates to the technical field of warehouse management, and the system comprises an intelligent three-dimensional warehouse storage module which is used for storing fire-fighting equipment and carrying out the access management of the fire-fighting equipment based on an automatic access system and a robot scheduling system. The intelligent three-dimensional warehouse storage module comprises a fire-fighting equipment pre-distribution mechanism based on dynamic storage optimization, and the fire-fighting equipment pre-distribution mechanism based on dynamic storage optimization is combined with fire risk analysis, historical fire-fighting equipment use data and fire-fighting equipment service life prediction data to dynamically adjust the storage position of fire-fighting equipment. The fire-fighting equipment availability monitoring module is designed, so that the functions of real-time monitoring and fault prediction of the fire-fighting equipment are realized, the problem of equipment failure caused by long-time non-use or equipment aging is solved, the availability and reliability of the equipment are improved, and fire emergency work is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and particularly to a fire fighting equipment availability monitoring and intelligent automated storage and retrieval system Background Technique

[0002] With the continuous acceleration of the urbanization and industrialization processes, fire safety has become the focus of attention of all sectors of society. The traditional fire fighting equipment management mode has problems such as long manual inspection cycles, slow emergency response speeds, and incomplete equipment status monitoring, making it difficult to meet the requirements of modern large buildings, industrial parks, and public places for the rapid, accurate dispatching and intelligent maintenance of fire fighting equipment.

[0003] Patent document CN117893385B discloses a fire fighting early warning method and system for ensuring warehouse safety. The above patent realizes the prediction of related facilities by integrating relevant fire alarm sensors, enhances the correlation between various fire fighting facilities, and can better conduct early fire fighting warnings to reduce losses.

[0004] In summary, the above patent uses real-time data and a trained fire fighting early warning model to achieve fire fighting early warnings, but there is room for optimization and improvement in the availability monitoring of fire fighting equipment. To solve the problem of intelligent monitoring of the availability of fire fighting equipment, this application makes optimizations and improvements thereto; Therefore, this application proposes a fire fighting equipment availability monitoring and intelligent automated storage and retrieval system that can monitor the status of fire fighting equipment and automatically predict failure risks. Summary of the Invention

[0005] The purpose of the present invention is to provide a fire fighting equipment availability monitoring and intelligent automated storage and retrieval system to solve the technical problems of long manual inspection cycles, slow emergency response speeds, and incomplete equipment status monitoring mentioned in the above background technique.

[0006] To achieve the above object, the present invention provides the following technical solutions: A fire fighting equipment availability monitoring and intelligent vertical warehouse storage management system, including an intelligent vertical warehouse storage module, which is used to store fire fighting equipment and manage the access of fire fighting equipment based on an automated access system and a robot scheduling system. The intelligent vertical warehouse storage module includes a pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization. The pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization combines fire risk analysis, historical fire fighting equipment usage data, and fire fighting equipment life prediction data to dynamically adjust the storage location of fire fighting equipment, so that high-demand fire fighting equipment is stored in an easily accessible location. The pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization optimizes the layout of fire fighting equipment based on the regional fire risk level. When the fire risk of a certain area increases, the management system automatically moves key fire fighting equipment to the vertical warehouse unit close to that area, reducing the fire fighting equipment extraction time and improving the emergency response efficiency.

[0007] Preferably, the intelligent vertical warehouse storage module includes a high-density storage rack, an automatic access manipulator, an orbital conveying system, and an NFC identification device. The identity of the fire fighting equipment is identified through a two-dimensional code, and the storage and retrieval operations are performed by the automatic access manipulator.

[0008] Preferably, the fire fighting equipment availability monitoring module includes an embedded intelligent sensor. The embedded intelligent sensor includes a pressure sensor, a temperature and humidity sensor, a gas leakage sensor, a battery power monitoring module, and an intelligent tag. The pressure sensor is used to detect the pressure of fire extinguishers or gas cylinders. The temperature and humidity sensor is used to monitor the storage environment of fire fighting equipment. The gas leakage sensor is used to detect the leakage of gas fire extinguishers. The battery power monitoring module is used to monitor the remaining power of battery-powered equipment. The intelligent tag communicates with the gateway to realize remote monitoring data transmission. The fire fighting equipment availability monitoring module further includes an intelligent self-check unit. The intelligent self-check unit periodically self-checks fire extinguishers, respirators, and battery-powered equipment through the embedded intelligent sensor, and analyzes the fault trend of the equipment based on the AI diagnosis algorithm to predict the fault occurrence time. When the fire fighting equipment has not been used for a long time, the intelligent self-check unit regularly performs self-check operations in the minimum power consumption mode, and automatically generates a maintenance work order and sends it to the intelligent scheduling and operation and maintenance management module when the equipment failure is approaching.

[0009] Preferably, the intelligent scheduling and operation and maintenance management module further includes an AI analysis unit, which analyzes the health status, service life, and maintenance cycle of fire fighting equipment through a deep learning model, and predicts the equipment failure risk based on historical data to specify a maintenance plan in advance.

[0010] Preferably, the automatic inventory unit uses AI vision recognition technology combined with RFID batch scanning technology to perform automatic inventory periodically, and automatically alarms when fire fighting equipment is missing, the equipment is aging or damaged.

[0011] Preferably, the management system further includes an emergency linkage module which communicates with the fire alarm system in real time. When a fire alarm is triggered, the management system automatically calculates the types and quantities of required fire-fighting equipment, controls the intelligent automated storage and retrieval module to retrieve the fire-fighting equipment, and quickly distributes it to the designated emergency area through an AGV or a rail transportation system.

[0012] Preferably, the management system further includes a cloud and edge computing architecture, which includes edge computing devices and cloud servers. The edge computing devices are responsible for locally and real-time processing the monitoring data of fire-fighting equipment, reducing data latency. The cloud servers are used to store historical data and perform big data analysis to optimize the management strategy of fire-fighting equipment. The management system further has a remote operation and maintenance function. Operation and maintenance personnel can remotely query the status of fire-fighting equipment, receive fault alarms and perform remote management operations through a mobile APP or a web platform. The management system further has an abnormal status warning mechanism. When a fire-fighting equipment fails, exceeds the storage temperature and humidity threshold, the battery power is lower than the set value, or the equipment has not been used for a long time, the management system automatically sends a warning notice and recommends a maintenance treatment plan.

[0013] Preferably, the intelligent automated storage and retrieval module further includes a fire-fighting equipment availability monitoring module, which includes multiple sensor units and data acquisition devices for real-time monitoring of the health status of fire-fighting equipment, including pressure, temperature and humidity, battery power and gas leakage, and sending the monitoring data to the data processing center. The intelligent scheduling and operation and maintenance management module includes an AI analysis unit and an automatic inventory unit for predictive maintenance based on the usage frequency, health status and environmental impact of fire-fighting equipment, and automatically checking the status of the in-stock fire-fighting equipment; The fire-fighting equipment availability monitoring module monitors the status of fire-fighting equipment through embedded intelligent sensors and uploads the collected data to the intelligent scheduling and operation and maintenance management module for real-time analysis. The intelligent scheduling and operation and maintenance management module evaluates the health status of fire-fighting equipment by combining AI algorithms based on the data collected by the fire-fighting equipment availability monitoring module, generates maintenance suggestions or automatically triggers maintenance tasks, and simultaneously synchronizes the fire-fighting equipment status data to the cloud and edge computing architecture for long-term storage and trend analysis.

[0014] Preferably, the intelligent automated storage and retrieval module further includes an energy recovery unit. The energy recovery unit converts the kinetic energy generated during the mechanical movement into electrical energy through the kinetic energy recovery device of the automatic storage and retrieval robotic arm, AGV or rail transportation system, and stores it in the energy management system. The energy recovery unit adopts a combined mode of electromagnetic induction and mechanical energy recovery. During the storage process of fire-fighting equipment, the overall energy consumption of the management system is reduced through regenerative braking technology, improving the energy utilization efficiency of the intelligent automated storage and retrieval system.

[0015] Preferably, the intelligent automated storage module further includes an environmental control unit. The environmental control unit monitors the temperature and humidity of the storage environment in real time and controls air conditioners, dehumidifiers or ventilation equipment to ensure that the environmental condition parameters of the fire fighting equipment storage environment are maintained within the set range, so as to extend the service life of the fire fighting equipment. The environmental control unit performs intelligent environmental adjustment in combination with the type of fire fighting equipment. For dry powder fire extinguishers, gas fire extinguishers and lithium battery-powered equipment, the storage temperature and humidity range is dynamically adjusted to prevent the aging or failure of the fire fighting equipment and reduce the risk of storage accidents.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. By designing a fire fighting equipment availability monitoring module, the present invention realizes the real-time monitoring and fault prediction functions of fire fighting equipment, solves the problem of equipment failure caused by long-term non-use or equipment aging, improves the availability and reliability of the equipment, and ensures fire emergency work; 2. By designing a pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization, the present invention realizes the function of automatically storing high-demand equipment in easily accessible positions according to the risk level and usage frequency, shortens the fire emergency response time, optimizes the use of warehouse space, improves the processing efficiency, and reduces the accident risk; 3. By designing an energy recovery unit, the present invention realizes the function of recovering the energy of equipment deceleration braking, reduces the overall energy consumption, improves the energy utilization rate, increases the fire response speed, and reduces the operation cost; 4. By designing an emergency linkage module and an intelligent scheduling and operation and maintenance management module, the present invention realizes the function of automatically dispatching fire fighting equipment to quickly respond to fire alarms, improves the response speed, reduces manual intervention, improves the accuracy of equipment dispatching, and reduces safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the framework structure of the management system of the present invention; Figure 2 It is a schematic diagram of the fire fighting equipment management process of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] Please refer to Figure 1 and Figure 2, an embodiment provided by the present invention: A fire fighting equipment availability monitoring and intelligent automated storage and retrieval system, including an intelligent automated storage and retrieval module, characterized in that: the intelligent automated storage and retrieval module is used to store fire fighting equipment, and based on an automated storage and retrieval system and a robot scheduling system for the access management of fire fighting equipment. The intelligent automated storage and retrieval module includes a pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization. The pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization combines fire risk analysis, historical fire fighting equipment usage data, and fire fighting equipment life prediction data to dynamically adjust the storage location of fire fighting equipment, so that high-demand fire fighting equipment is stored in an easy-to-store location. The pre-allocation mechanism for fire fighting equipment based on dynamic storage optimization optimizes the layout of fire fighting equipment based on the regional fire risk level. When the fire risk of a certain area increases, the management system automatically moves the key fire fighting equipment to the storage unit near the area, reducing the fire fighting equipment extraction time and improving the emergency response efficiency; Furthermore, in the intelligent automated storage and retrieval module, the storage unit is divided into multiple levels and areas. Among them, the storage locations near the entrance / exit or distribution channels are "easy-to-access" areas, and the deeper storage locations are "low-frequency" areas. The management system inputs the fire risk data, historical usage frequency, and life prediction data into the pre-allocation algorithm to calculate the optimal storage location for various types of fire fighting equipment: For frequently retrieved, high-usage frequency, or critical equipment, the management system stores it in the "easy-to-access" area so that it can be quickly dispatched in case of emergency; When the fire risk of a certain area increases, the management system automatically reallocates the key equipment related to the emergency response of the area to the storage unit near the area, shortening the equipment retrieval path and response time. Through the above dynamic pre-allocation, the key equipment is always in the optimal dispatch state, which can significantly reduce the retrieval time during a fire emergency and improve the response efficiency; At the same time, the storage layout is optimized according to the equipment life prediction, effectively reducing the equipment aging risk and maintenance cost; In the intelligent automated storage and retrieval module, temperature and humidity sensors are evenly deployed to monitor the temperature and humidity of the storage environment in real time. The monitoring data is transmitted to the management system through wired or wireless networks. After receiving the real-time temperature and humidity data of each storage area, the environmental control unit automatically adjusts the relevant equipment according to the preset target parameters: When the detected temperature exceeds the set range, the air conditioning equipment is automatically started for temperature adjustment; When the humidity exceeds the range, the dehumidifier or humidification equipment is controlled to balance the humidity; The environmental control unit not only performs feedback control based on real-time monitoring data, but also makes intelligent adjustments in combination with the type of fire fighting equipment. For example, in the area where lithium battery-powered equipment is stored, when the temperature and humidity fluctuate, it intervenes in the control in advance to reduce the battery degradation risk.

[0020] The dynamic pre-allocation mechanism ensures that high-demand fire-fighting equipment is always stored in easily accessible locations; when the fire risk suddenly increases, key equipment can automatically move closer to high-risk areas, significantly shortening the extraction time; the environmental control unit ensures that different types of fire-fighting equipment are always in suitable storage conditions through real-time monitoring and precise adjustment, effectively preventing equipment aging or failure caused by environmental deterioration.

[0021] Please refer to Figure 1 and Figure 2 , an embodiment provided by the present invention: a fire-fighting equipment availability monitoring and intelligent automated warehouse storage management system, the intelligent automated warehouse storage module further includes a fire-fighting equipment availability monitoring module, the fire-fighting equipment availability monitoring module includes a plurality of sensor units and a data acquisition device, for real-time monitoring of the health status of fire-fighting equipment, including pressure, temperature and humidity, battery power and gas leakage, and sending the monitoring data to the data processing center, the intelligent scheduling and operation and maintenance management module includes an AI analysis unit and an automatic inventory unit, for predictive maintenance based on the usage frequency, health status and environmental impact of fire-fighting equipment, and automatically inventorying the status of the fire-fighting equipment in stock; The fire-fighting equipment availability monitoring module monitors the status of fire-fighting equipment through embedded intelligent sensors, and uploads the collected data to the intelligent scheduling and operation and maintenance management module for real-time analysis. The intelligent scheduling and operation and maintenance management module evaluates the health status of fire-fighting equipment based on the data collected by the fire-fighting equipment availability monitoring module, combines with AI algorithms, and generates maintenance suggestions or automatically triggers maintenance tasks, and at the same time synchronizes the fire-fighting equipment status data to the cloud and edge computing architecture for long-term storage and trend analysis; Furthermore, the inventory task is automatically executed by the intelligent scheduling and operation and maintenance management module according to the set cycle, or is immediately triggered when special situations such as equipment damage or inventory changes occur. After the inventory instruction is issued, the robot scheduling system in the intelligent automated warehouse storage module schedules the robotic arm or AGV to move the storage units to the detection area in turn. High-definition industrial cameras are deployed in the inventory area. Combining with the AI vision analysis algorithm, the appearance of fire-fighting equipment is identified. The vision recognition system uses the feature matching algorithm to judge whether the appearance of the fire-fighting equipment is abnormal, such as damaged labels, abnormal pressure indicating needles of fire extinguishers, damaged nozzles, etc. If an abnormality is found, it is automatically marked as the status to be repaired. If equipment loss or damage is found, the intelligent scheduling and operation and maintenance management module immediately sends a notice to the terminal of the operation and maintenance personnel, and automatically generates maintenance and replenishment tasks. For abnormal equipment, the management system automatically links the intelligent automated warehouse storage module, sends the damaged equipment to the maintenance area, and at the same time schedules spare equipment for replacement to ensure that the fire-fighting equipment is always in a complete and available state; A variety of intelligent sensors are embedded in firefighting equipment, including pressure sensors, temperature and humidity sensors, battery power detection modules, gas leakage monitoring devices, etc. The data is transmitted to the edge computing gateway in real time through LoRa wireless communication. The gateway has a built-in AI algorithm for real-time analysis to filter out equipment data that may be abnormal. The edge computing unit combines historical data analysis to predict the health trend of firefighting equipment. When the predicted life of a certain equipment is about to end, the management system automatically generates a maintenance work order, notifies the maintainer to conduct an inspection, and links the intelligent vertical warehouse storage module to retrieve spare equipment for replacement; By using AI combined with edge computing technology, equipment failures can be predicted in advance, sudden failures can be avoided, and equipment availability can be improved. Without human intervention, the system automatically determines maintenance needs and deploys equipment to improve maintenance efficiency. Predictive maintenance can reduce unnecessary inspections, increase the service life of firefighting equipment, and reduce long-term maintenance costs.

[0022] See also Figure 1 and Figure 2 , an embodiment provided by the present invention: a fire equipment availability monitoring and intelligent vertical warehouse storage management system, the intelligent vertical warehouse storage module includes a high-density storage rack, an automatic storage and retrieval robot arm, a track conveying system and an NFC identification device, which identifies the identity of the fire equipment through a QR code, and performs storage and retrieval operations through the automatic storage and retrieval robot arm; The intelligent scheduling and operation and maintenance management module further includes an AI analysis unit, which analyzes the health status, service life and maintenance cycle of firefighting equipment through a deep learning model, predicts the risk of equipment failure based on historical data, and specifies maintenance plans in advance; Furthermore, each piece of firefighting equipment is equipped with a QR code and an NFC electronic tag. The QR code contains the equipment number, manufacturer, production date, maintenance record, etc. The NFC electronic tag is used for remote data interaction. Before the equipment is put into storage, the staff registers their identity through the NFC recognition device, or the automatic storage robot automatically reads the equipment information through the QR code scanning system. After reading, the system uploads the equipment information to the intelligent scheduling and operation and maintenance management module, and matches it with the database to ensure that the equipment information is complete and correct. The AI ​​analysis unit selects the optimal storage location based on the equipment category, frequency of use, and storage environment requirements. After receiving the command, the automatic storage and retrieval robot takes the equipment from the conveying system and stores it in the designated cargo location according to the optimized path. After storage, the location information of the equipment is synchronized to the database, and the RFID or NFC tag records the current location of the equipment to achieve precise management. The fire-fighting equipment availability monitoring module collects equipment status data through embedded intelligent sensors. The collected data is transmitted to the intelligent scheduling and operation and maintenance management module through NFC or LoRa wireless communication modules. The AI analysis unit uses deep learning models such as the LSTM prediction model, which is trained based on the following data sets: the usage frequency and maintenance records of the equipment in the past 3 years, sensor data, and equipment aging curves in different environments. The LSTM prediction model automatically analyzes the health status of the equipment, calculates the failure risk score. When the AI analysis unit predicts that a certain fire-fighting equipment may fail, the system automatically generates a maintenance task and sends it to the management terminal. Through AI predictive maintenance, the failure risk of equipment can be identified in advance, sudden equipment failures can be reduced, and the reliability of fire-fighting response can be improved.

[0023] Please refer to Figure 1 and Figure 2 For an embodiment provided by the present invention: a fire-fighting equipment availability monitoring and intelligent automated storage and retrieval system. The fire-fighting equipment availability monitoring module includes embedded intelligent sensors. The embedded intelligent sensors include a barometric pressure sensor, a temperature and humidity sensor, a gas leakage sensor, a battery power monitoring module, and an intelligent tag. The barometric pressure sensor is used to detect the pressure of fire extinguishers or gas cylinders. The temperature and humidity sensor is used to monitor the storage environment of fire-fighting equipment. The gas leakage sensor is used to detect the leakage of gas fire extinguishers. The battery power monitoring module is used to monitor the remaining power of battery-powered equipment. The intelligent tag communicates with the gateway to achieve remote monitoring data transmission. The fire-fighting equipment availability monitoring module further includes an intelligent self-check unit. The intelligent self-check unit periodically self-checks fire extinguishers, respirators, and battery-powered equipment through the embedded intelligent sensors, and analyzes the fault trend of the equipment based on the AI diagnosis algorithm to predict the time of fault occurrence. When the fire-fighting equipment is in a long-term unused state, the intelligent self-check unit performs self-check operations regularly using the minimum power consumption mode, and automatically generates a maintenance work order and sends it to the intelligent scheduling and operation and maintenance management module when the equipment failure is approaching. Furthermore, the embedded intelligent sensors in each fire-fighting equipment collect the status data of the fire-fighting equipment in real time, and transmit the collected status data to the local gateway and the central data processing center. The AI ​​diagnostic system built into the central data processing center uses deep learning models such as convolutional neural networks to perform trend analysis on the long-term accumulated sensor data. By comparing historical data with current self-test data, the AI ​​model calculates the attenuation trend of various indicators of the equipment. For battery-powered equipment, the model analyzes the battery power decline rate and predicts that the battery may drop to a critical value in the next few days. At the same time, the AI ​​model makes a comprehensive judgment on temperature and humidity data and gas leakage data to evaluate the impact of environmental factors on equipment aging or failure. The AI ​​diagnostic system generates a "fault risk score" for each device based on the analysis results. Once the risk score of a certain device exceeds the preset threshold, the intelligent self-test unit automatically generates a maintenance work order by linking with the intelligent scheduling and operation and maintenance management module. The maintenance work order includes: equipment number, location and detailed identification information; the most recent self-test data and historical trend chart; predicted fault occurrence time and specific abnormal parameters; recommended maintenance or replacement plan; the generated maintenance work order is pushed to relevant maintenance personnel through system messages or emails, and recorded in the management platform for subsequent tracking and processing.

[0024] See also Figure 1 and Figure 2 , an embodiment provided by the present invention: a fire equipment availability monitoring and intelligent vertical warehouse storage management system, the management system further includes an emergency linkage module, the emergency linkage module communicates with the fire alarm system in real time, when the fire alarm is triggered, the management system automatically calculates the type and data of the required fire equipment, controls the intelligent vertical warehouse storage module to retrieve the fire equipment, and quickly delivers it to the designated emergency area through the AGV or rail transportation system; The management system further includes a cloud and edge computing architecture, which includes edge computing devices and cloud servers. The edge computing devices are responsible for local real-time processing of fire equipment monitoring data to reduce data latency. The cloud servers are used to store historical data and perform big data analysis to optimize fire equipment management strategies. The management system further has remote operation and maintenance functions. Operation and maintenance personnel can remotely query the status of fire equipment, receive fault alarms, and perform remote management operations through mobile APP or Web platforms. The management system further has an abnormal status alarm mechanism. When the fire equipment fails, exceeds the storage temperature and humidity threshold, the power is lower than the set value, or the equipment has not been used for a long time, the management system automatically sends an alarm notification and recommends a maintenance solution. Furthermore, when the fire alarm system installed in the park detects the initial stage of a fire, such as a sharp rise in smoke concentration or abnormal temperature, the alarm signal will be transmitted to the emergency linkage module in the management system immediately by wired or wireless means. After receiving the alarm signal, the emergency linkage module immediately calls the preset rules and the on-site risk assessment model, automatically calculates the types and quantities of fire-fighting equipment required at the current fire scene, and according to the calculation results, the emergency linkage module issues an equipment call instruction to the intelligent automated storage and retrieval module. The types, quantities of the required equipment and the specific location information of the target emergency area are clearly marked in the instruction. After receiving the instruction, the intelligent automated storage and retrieval module takes out the equipment through the automatic storage and retrieval robotic arm, and transports the equipment to the designated area through the AGV or the rail conveyor system according to the optimal path algorithm; The management system monitors all key monitoring data in real time, and pre-sets safety thresholds and alarm trigger conditions. Once it detects that a certain indicator exceeds the safe range or the equipment has not been used for a long time, the management system will automatically generate an alarm. The alarm message not only notifies the abnormal situation of the specific equipment, but also recommends a targeted maintenance plan through the built-in AI algorithm to help the operation and maintenance personnel quickly locate and solve the problem. All alarm records and processing results will be uploaded to the cloud server. After big data analysis, it is used to continuously optimize the alarm rules and maintenance strategies of the system, and improve the overall management level of fire-fighting equipment; The edge computing device processes the on-site data in real time to reduce latency; The cloud server stores and analyzes historical data to provide data support for management decisions and optimize future scheduling and maintenance strategies.

[0025] Please refer to Figure 1 and Figure 2 , an embodiment provided by the present invention: A fire-fighting equipment availability monitoring and intelligent automated storage and retrieval management system, the intelligent automated storage and retrieval module further includes an energy recovery unit. The energy recovery unit converts the kinetic energy generated during the mechanical movement into electrical energy through the motion energy recovery device of the automatic storage and retrieval robotic arm, AGV or rail conveyor system, and stores it in the energy management system. The energy recovery unit adopts a combination mode of electromagnetic induction and mechanical energy recovery. During the storage process of fire-fighting equipment, the overall energy consumption of the management system is reduced through the braking energy recovery technology, and the energy utilization efficiency of the intelligent automated storage is improved; Furthermore, when the management system receives the instruction for the fire-fighting equipment to be stored in or taken out of the warehouse, the automatic storage robotic arm starts and moves along a predetermined track, and the AGV or the rail transportation system also starts operating synchronously. At this time, the equipment is driven by an electric motor. When the automatic storage robotic arm, the AGV or the rail transportation system approaches the target access position or changes the direction of movement, the management system activates the braking energy recovery technology. During the deceleration of the equipment, the internal configuration of the motor or the dedicated regenerative braking device consists of a permanent magnet and a stator coil. When the mechanical movement decelerates, the permanent magnet moves relative to the stator coil, generating an alternating current according to Faraday's law of electromagnetic induction. This alternating current is converted into direct current through a rectifier circuit and stabilized through a voltage regulation circuit to ensure that the recovered electric energy meets the requirements of electric energy management; in addition to the electromagnetic induction method, some equipment also adopts a mechanical energy recovery device, such as a gear transmission and a hydraulic recovery system. When the equipment brakes, part of the mechanical energy during the deceleration process is transmitted to the hydraulic recovery device through a precision gear set, and then the hydraulic motor converts the hydraulic energy into electric energy. This mechanical energy recovery method complements the electromagnetic induction to ensure efficient energy recovery under different working conditions; the stored recovered electric energy can be used to supplement the electric energy requirements of other modules in the intelligent storage library, such as sensor power supply, controller operation, and the starting energy of some mechanical equipment, thereby reducing the dependence on external power sources and achieving partial self-powered operation.

[0026] Working principle: The management system monitors the health status of the fire-fighting equipment in real time through a variety of intelligent sensors embedded in the fire-fighting equipment, and the collected data is transmitted to the edge computing device through a wireless module; The edge computing device uploads the real-time data to the cloud server for big data analysis with historical data. Using deep learning models and AI algorithms, the management system conducts intelligent analysis on the service life, fault trend, and environmental factors of the fire-fighting equipment, and automatically generates a predictive maintenance plan. At the same time, through the pre-allocation mechanism of the fire-fighting equipment based on dynamic storage optimization, the system dynamically adjusts the storage location of the equipment according to the fire risk, equipment usage frequency, and life prediction to ensure that high-demand equipment is always in an easily retrievable position; When the fire alarm system triggers a fire signal, the emergency linkage module quickly receives the signal and automatically calculates the types and quantities of the required fire-fighting equipment. The management system uses the automatic storage robotic arm, AGV, and rail transportation system to quickly extract the equipment from the storage library and deliver it to the designated emergency area through the optimal path. At the same time, the management system has the functions of remote operation and maintenance and abnormal alarm, realizing remote monitoring and maintenance of the equipment status to ensure that the equipment is always in the best state and guaranteeing the timeliness and accuracy of the fire emergency response.

[0027] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A fire fighting equipment availability monitoring and intelligent automated storage and retrieval system, including an intelligent automated storage and retrieval module, characterized in that: The intelligent automated storage module is used to store fire-fighting equipment and manage the access of fire-fighting equipment based on an automated storage and retrieval system and a robot scheduling system. The intelligent automated storage module includes a pre-allocation mechanism for fire-fighting equipment based on dynamic storage optimization. The pre-allocation mechanism for fire-fighting equipment based on dynamic storage optimization combines fire risk analysis, historical fire-fighting equipment usage data, and fire-fighting equipment life prediction data to dynamically adjust the storage locations of fire-fighting equipment, so that high-demand fire-fighting equipment is stored in easily accessible locations. The pre-allocation mechanism for fire-fighting equipment based on dynamic storage optimization optimizes the layout of fire-fighting equipment based on the regional fire risk level. When the fire risk in a certain area increases, the management system automatically moves key fire-fighting equipment to the storage unit near that area, reducing the fire-fighting equipment extraction time and improving the emergency response efficiency.

2. The availability monitoring and intelligent automated storage and retrieval system for fire fighting equipment according to claim 1, wherein: The intelligent automated storage module includes high-density storage racks, automatic access manipulators, a rail conveyor system, and an NFC identification device. The identity of fire-fighting equipment is identified through QR codes, and storage and retrieval operations are performed by the automatic access manipulators.

3. The availability monitoring and intelligent automated storage and retrieval system for fire fighting equipment according to claim 1, characterized in that: The fire-fighting equipment availability monitoring module includes embedded intelligent sensors. The embedded intelligent sensors include a pressure sensor, a temperature and humidity sensor, a gas leakage sensor, a battery power monitoring module, and an intelligent tag. The pressure sensor is used to detect the pressure of fire extinguishers or gas cylinders. The temperature and humidity sensor is used to monitor the storage environment of fire-fighting equipment. The gas leakage sensor is used to detect the leakage of gas fire extinguishers. The battery power monitoring module is used to monitor the remaining power of battery-powered equipment. The intelligent tag communicates with the gateway to achieve remote monitoring data transmission. The fire-fighting equipment availability monitoring module further includes an intelligent self-check unit. The intelligent self-check unit periodically self-checks fire extinguishers, respirators, and battery-powered equipment through the embedded intelligent sensors, and analyzes the fault trend of the equipment based on the AI diagnosis algorithm to predict the time of fault occurrence. When the fire-fighting equipment has not been used for a long time, the intelligent self-check unit regularly performs self-check operations in the minimum power consumption mode, and automatically generates a maintenance work order and sends it to the intelligent scheduling and operation and maintenance management module when the equipment failure is approaching.

4. A fire fighting equipment availability monitoring and intelligent automated storage and retrieval system according to claim 1, characterized in that: The intelligent scheduling and operation and maintenance management module further includes an AI analysis unit, which analyzes the health status, service life, and maintenance cycle of fire-fighting equipment through a deep learning model, and predicts the equipment failure risk based on historical data to specify a maintenance plan in advance.

5. The fire-fighting equipment availability monitoring and intelligent automated storage and retrieval system according to claim 1, wherein: The automatic inventory unit uses AI vision recognition technology combined with RFID batch scanning technology to perform automatic inventory periodically and automatically alarms when fire-fighting equipment is missing, the equipment is aging or damaged.

6. The availability monitoring and intelligent vertical warehouse storage management system for fire protection equipment according to claim 1, characterized in that: The management system further includes an emergency linkage module. The emergency linkage module communicates with the fire alarm system in real time. When the fire alarm is triggered, the management system automatically calculates the types and quantities of fire-fighting equipment required, controls the intelligent automated storage module to retrieve fire-fighting equipment, and quickly distributes it to the designated emergency area through an AGV or a rail conveyor system.

7. The availability monitoring and intelligent automated storage and retrieval system for fire fighting equipment according to claim 1, characterized in that: The management system further includes a cloud and edge computing architecture, which includes edge computing devices and cloud servers. The edge computing devices are responsible for local real-time processing of fire equipment monitoring data to reduce data latency. The cloud servers are used to store historical data and perform big data analysis to optimize the fire equipment management strategy. The management system further has a remote operation and maintenance function. Operation and maintenance personnel can remotely query the status of fire equipment, receive fault alarms, and perform remote management operations through a mobile APP or a Web platform. The management system further also has an abnormal status warning mechanism. When a fire equipment fails, exceeds the storage temperature and humidity threshold, the battery power is lower than the set value, or the equipment has not been used for a long time, the management system automatically sends a warning notice and recommends a maintenance treatment plan.

8. The availability monitoring and intelligent automated storage and retrieval system for fire fighting equipment according to claim 1, characterized in that: The intelligent automated storage and retrieval module further includes a fire equipment availability monitoring module. The fire equipment availability monitoring module includes multiple sensor units and data collection devices, which are used to monitor the health status of fire equipment in real time, including pressure, temperature and humidity, battery power, and gas leakage, and send the monitoring data to the data processing center. The intelligent scheduling and operation and maintenance management module includes an AI analysis unit and an automatic inventory unit, which perform predictive maintenance based on the usage frequency, health status, and environmental impact of fire equipment, and automatically inventory the status of the fire equipment in stock; The fire equipment availability monitoring module monitors the status of fire equipment through embedded intelligent sensors, and uploads the collected data to the intelligent scheduling and operation and maintenance management module for real-time analysis. The intelligent scheduling and operation and maintenance management module evaluates the health status of fire equipment in combination with the data collected by the fire equipment availability monitoring module and AI algorithms, generates maintenance suggestions or automatically triggers maintenance tasks, and at the same time synchronizes the fire equipment status data to the cloud and edge computing architecture for long-term storage and trend analysis.

9. The availability monitoring and intelligent automated storage and retrieval system for fire fighting equipment according to claim 1, wherein: The intelligent automated storage and retrieval module further includes an energy recovery unit. The energy recovery unit converts the kinetic energy generated during the mechanical movement into electrical energy through the motion energy recovery device of the automatic storage and retrieval robotic arm, AGV, or rail conveyor system, and stores it in the energy management system. The energy recovery unit adopts a combined mode of electromagnetic induction and mechanical energy recovery. During the storage process of fire equipment, the overall energy consumption of the management system is reduced through braking energy recovery technology, and the energy utilization efficiency of the intelligent automated storage and retrieval is improved.

10. A fire fighting equipment availability monitoring and intelligent automated storage and retrieval system according to claim 1, characterized in that: The intelligent automated storage and retrieval module further includes an environment control unit. The environment control unit monitors the temperature and humidity of the storage environment in real time, and controls air conditioners, dehumidifiers, or ventilation equipment to ensure that the environmental condition parameters of the fire equipment storage environment are maintained within the set range, so as to extend the service life of the fire equipment. The environment control unit performs intelligent environment adjustment in combination with the type of fire equipment. For dry powder fire extinguishers, gas fire extinguishers, and lithium battery-powered equipment, the storage temperature and humidity range are dynamically adjusted to prevent the aging or failure of fire equipment and reduce the risk of storage accidents.

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