Building intelligent fire alarm system
By leveraging IoT and edge computing technologies, combined with distributed fire detection equipment and cloud servers, efficient and real-time fire monitoring and response within buildings have been achieved, solving the problems of incomplete coverage and untimely alarms in traditional fire protection facilities, and improving the level of fire safety.
Patent Information
- Application Number
- CN202520535489.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-25
- Publication Date
- 2026-02-24
- Estimated Expiration
- 2035-03-25
AI Technical Summary
Traditional building fire protection facilities are difficult to cover a wide range of buildings, alarms are not timely, the location of fire cannot be quickly determined, equipment failures are not detected in time, which can easily lead to the spread of fire. Existing alarm systems cannot monitor the performance of equipment and there are cases of missed alarms.
By employing IoT and edge computing technologies, and combining distributed fire detection equipment, a central controller, and a cloud server, the system integrates smoke, heat, and gas sensors, a self-diagnostic module, a positioning module, and a wireless communication module. Through the edge computing module, it performs real-time fire assessment, triggers alarms, and activates fire sprinkler, ventilation, and emergency lighting systems, achieving efficient and real-time fire monitoring and response.
It enables efficient and real-time fire monitoring and response in buildings, improves the timeliness and accuracy of fire alarms, reduces equipment failure rates, ensures rapid fire response and handling, and reduces casualties and property losses.
Smart Images
Figure CN223941421U_ABST
Abstract
Description
Technical Field
[0001] This utility model belongs to the field of fire protection equipment technology and relates to a smart fire alarm system for buildings. Background Technology
[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.
[0003] With the acceleration of urbanization, the number of high-rise buildings, public buildings, and large commercial complexes has increased dramatically, leading to frequent building fires and posing a serious threat to people's lives and property. Studies show that fires exhibit certain patterns within a 24-hour day: more fires typically occur during the day and fewer at night; however, the rate of damage is lower during the day and higher at night; and the losses are lower during the day and higher at night. At night, people are often asleep and react slowly to initial fires. By the time flames ignite and smoke spreads, escape may be lost, resulting in greater casualties and property damage at night. Some fire accident investigation reports indicate that a significant cause of death in fire accidents is the exposure of people to toxic and harmful gases produced by the fire, leading to rapid poisoning, dizziness, and loss of escape ability and opportunity.
[0004] Traditional building fire protection facilities often suffer from problems such as difficulty in achieving comprehensive coverage in large-scale buildings, untimely alarms, and inability to quickly determine the location of a fire, which can easily lead to the spread of fire and cause greater harm. Moreover, existing alarm systems cannot monitor equipment performance, resulting in equipment failures not being detected in time and the occurrence of missed alarms, which can have serious consequences. Utility Model Content
[0005] To address the technical problems existing in the prior art, this utility model provides a smart fire alarm system for buildings, which utilizes technologies such as the Internet of Things, edge computing, and cloud services to achieve efficient, real-time, and intelligent fire monitoring and response, thereby further improving the fire safety level of buildings.
[0006] To achieve the above objectives, this utility model provides the following technical solution:
[0007] A smart fire alarm system for buildings includes distributed fire detection devices, a central controller, and a cloud server connected in sequence. The distributed fire detection devices include multiple detection devices, each integrating multiple modules, including a smoke detector, a heat detector, a gas sensor, a self-diagnostic module, a positioning module, a wireless communication module, and an edge computing module. The edge computing module is connected to the smoke detector, heat detector, gas sensor, self-diagnostic module, positioning module, and wireless communication module, respectively. The edge computing module communicates wirelessly with the central controller through the wireless communication module, and the central controller communicates wirelessly with the cloud server.
[0008] In a further technical solution, the smoke detector, temperature detector, and gas sensor are all connected to the edge computing module using shielded cables.
[0009] In a further technical solution, the detection device also integrates an alarm module, and the edge computing module controls the alarm module through pins.
[0010] In a further technical solution, the alarm module includes a buzzer and a first LED. One end of the buzzer is connected to a power supply, and the other end is connected to the collector of a first transistor. The base of the first transistor is connected to the ninth pin of the edge computing module and the first end of a first resistor. The second end of the first resistor is connected to the emitter of the first transistor and grounded. The positive terminal of the first LED is connected to the tenth pin of the edge computing module, and the negative terminal of the first LED is connected to the first end of a second resistor. The second end of the second resistor is grounded.
[0011] In a further technical solution, the detection device also integrates a battery module, which is connected to the self-diagnostic module via an I2C interface.
[0012] In a further technical solution, the self-diagnostic module includes a battery monitoring chip. The positive input pin of the battery monitoring chip is connected to the positive terminal of the battery module, and the negative input pin is connected to the negative terminal of the battery module. The fifth pin of the battery monitoring chip is connected to the thirty-fifth pin of the edge computing module, and the sixth pin is connected to the thirty-sixth pin of the edge computing module.
[0013] In a further technical solution, the positioning module includes a positioning chip, the second pin of the positioning chip is connected to the twentieth pin of the edge computing module, the second pin of the positioning chip is connected to ground after being connected in series with a second capacitor and a third capacitor, the thirty-fifth pin of the positioning chip is connected to the twenty-eighth pin of the edge computing module, and the thirty-fourth pin of the positioning chip is connected to the twenty-seventh pin of the edge computing module.
[0014] In a further technical solution, the edge computing module is implemented using a microcontroller.
[0015] A further technical solution for the intelligent fire alarm system also includes an execution module, which includes relays for the fire sprinkler system, ventilation system, and emergency lighting system. The edge computing module is connected to the fire sprinkler system relays, ventilation system relays, and emergency lighting system relays via GPIO interfaces.
[0016] In a further technical solution, the distributed fire detection device adopts a metal casing with electromagnetic shielding properties.
[0017] The beneficial effects of this utility model are:
[0018] This invention proposes a smart fire alarm system for buildings, equipped with distributed fire detection devices that can widely cover various areas within the building. Shielded cables effectively resist electromagnetic interference, improving the accuracy of data acquisition and transmission. The distributed fire detection devices integrate multiple sensors (smoke, heat, and gas sensors) to monitor each area in real time. Combined with an edge computing module, fire detection is based on sensor data, enabling a rapid response in the early stages of a fire, quickly triggering the alarm system and preventing the fire from spreading.
[0019] This utility model's distributed fire detection device is equipped with an edge computing module, enabling it to perform fire detection locally, react quickly to fires, and issue early warnings. The fire alarm system also includes an execution module, which, upon detection of a fire by the edge computing module, activates the fire sprinkler system to combat the fire, starts the ventilation system to dilute smoke, and provides lighting for evacuation routes.
[0020] This utility model's distributed fire detection device integrates a self-diagnostic module that periodically checks the battery's operational status to ensure the device is in good working order, reducing the failure rate and preventing missed alarms. The integrated positioning module provides the precise location of fires and malfunctions, offering personnel a basis for rapid response and improving efficiency in emergency situations.
[0021] This utility model's distributed fire detection device communicates with a central controller via a wireless communication module. The central controller then communicates with a cloud server via a 5G network. By using Internet of Things (IoT) technology, the distributed fire detection device, central controller, and cloud server are interconnected in real time, which can greatly improve the timeliness of fire alarms and enable staff to handle fires promptly through remote alarm notifications. Attached Figure Description
[0022] The accompanying drawings are provided to further understand the present invention and form part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation thereof.
[0023] Figure 1This is a diagram illustrating the architecture of a smart fire alarm system for buildings, as described in this utility model embodiment.
[0024] Figure 2 This is a structural diagram of a distributed fire detection device module according to an embodiment of the present invention;
[0025] Figure 3 This is a schematic diagram of the edge computing module in an embodiment of the present invention;
[0026] Figure 4 This is a circuit diagram of the alarm module in an embodiment of the present invention;
[0027] Figure 5 This is a circuit diagram of the self-diagnostic module in an embodiment of this utility model;
[0028] Figure 6 This is a circuit diagram of the positioning module in an embodiment of the present invention;
[0029] Figure 7 This is a circuit diagram of the fire sprinkler system control circuit in the execution module of this utility model embodiment;
[0030] Figure 8 This is a circuit diagram of the exhaust system control circuit in the execution module of this utility model embodiment;
[0031] Figure 9 This is a circuit diagram of the emergency lighting system control circuit in the execution module of this utility model embodiment. Detailed Implementation
[0032] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0033] like Figure 1 , Figure 2 As shown in the figure, this utility model embodiment provides a smart fire alarm system for buildings, including distributed fire detection devices, a central controller, and a cloud server connected in sequence. The distributed fire detection devices include multiple detection devices, each integrating multiple modules, including a smoke detector, a heat detector, a gas sensor, a self-diagnostic module, a positioning module, a wireless communication module, and an edge computing module. The edge computing module is connected to the smoke detector, heat detector, gas sensor, self-diagnostic module, positioning module, and wireless communication module, respectively. The edge computing module communicates wirelessly with the central controller through the wireless communication module, and the central controller communicates wirelessly with the cloud server.
[0034] In this embodiment, the detection device integrates multiple sensors, including smoke detectors (smoke sensors), heat detectors (temperature sensors), and gas sensors, to cover more fire types. Each detection device acts as a detection node, deployed in various areas of the building (such as floor corridors). Each node can independently collect data and assess the fire situation. If a detection node detects a fire risk, it will trigger an alarm and report the event to the central controller. Each detection node communicates wirelessly with the central controller via a wireless communication module, enabling the transmission of alarm and location information.
[0035] Smoke detectors, temperature detectors, and gas sensors are all connected to the edge computing module using shielded cables to transmit data. In buildings, electromagnetic interference can negatively impact the stability and accuracy of detection equipment; using shielded cables effectively reduces the impact of external electromagnetic interference and noise on data transmission. The sensors transmit the collected data to the edge computing module, which receives, processes, and makes judgments based on the data.
[0036] Fires tend to occur in a certain pattern within a 24-hour period. Based on this pattern, smoke detectors, heat detectors, and gas sensors use different sampling frequencies at different times of the day. During peak hours with high pedestrian traffic, the sampling frequency is reduced, while at night when pedestrian traffic is lower, the sampling frequency is increased.
[0037] The edge computing module receives data collected by various sensors and judges the sensor data according to preset thresholds to identify the possibility of fire. For example, if one or more of the smoke concentration, ambient temperature, or CO gas concentration exceeds a preset safety threshold, a fire risk is determined. If the edge computing module determines a fire risk based on the sensor data, it triggers the alarm module and sends the disaster alarm information to the central controller via the wireless communication module. Once the remote alarm is triggered, staff can remotely control, handle, or conduct on-site inspections after receiving the alarm.
[0038] Furthermore, the edge computing module can send alarm information to the central controller via a wireless communication module (such as a Wi-Fi module, LoRa module, etc.) to realize remote alarm function and promptly notify remote staff.
[0039] The detection device also integrates an alarm module. The edge computing module controls the alarm module (such as a buzzer, LED light, etc.) through pins. The alarm module receives the control signal from the edge computing module, thereby triggering an audible and visual alarm.
[0040] Furthermore, such as Figure 3 , Figure 4As shown, the alarm module includes a buzzer BZ1 and a first LED LED1. One end of the buzzer BZ1 is connected to a power supply, and the other end is connected to the collector of a first transistor Q1. The emitter of the first transistor Q1 is grounded, and the base of the first transistor Q1 is connected to the ninth pin of the edge computing module U1 and the first end of the first resistor R1. The second end of the first resistor R1 is connected to the emitter of the first transistor and grounded. The positive terminal of the first LED LED1 is connected to the tenth pin of the edge computing module U1, and the negative terminal of the first LED LED1 is connected to the first end of the second resistor R2. The second end of the second resistor R2 is grounded. When the edge computing module detects a fire risk, it outputs a control signal to the alarm module to make the buzzer BZ1 sound or the first LED LED flash.
[0041] After a fire alarm is triggered, the edge computing module will also send the data collected by the smoke detector, heat detector, and gas sensor within a set time period before and after the alarm to the central controller via the wireless communication module. The central controller will then connect to the Internet and transmit the various parameters collected by the sensors, such as smoke concentration, ambient temperature, and CO gas concentration, to the cloud server via the 5G network.
[0042] In some embodiments, the smoke sensor, temperature sensor, and gas sensor are all implemented using existing components. Various types of components can achieve the corresponding functions of this embodiment, and there is no specific limitation on the model of each component. For example, the smoke sensor can be MQ-2, MQ-7, etc., the temperature sensor can be DS18B20, DHT11, DHT22, etc., and the gas sensor can be CCS811.
[0043] In this embodiment, the detection device integrates a self-diagnostic module and a battery module, enabling it to monitor battery power, ensure system reliability, and promptly detect battery faults or performance degradation, avoiding false alarms or missed alarms. The self-diagnostic module is implemented using a battery monitoring chip, connected to both the battery module and the edge computing module via an I2C interface. The edge computing module communicates with the central controller via a wireless communication module. The battery monitoring chip collects battery status data in real time and sends it to the edge computing module. The edge computing module determines whether the battery voltage is below a safety threshold; if so, it sends a battery alarm message to the wireless communication module (such as a Wi-Fi module or LoRa module). Subsequently, the wireless communication module sends the battery alarm message to the central controller (monitoring center) via a Wi-Fi network. Upon receiving the battery alarm message, the central controller sends SMS messages to staff via a 5G network, enabling alarms when battery performance deteriorates and timely notification of staff for repairs.
[0044] Furthermore, such as Figure 3 , Figure 5As shown, the self-diagnostic module includes a battery monitoring chip U2. The first pin, IN+ (positive input pin), of the battery monitoring chip U2 is connected to the positive terminal of the battery module via a series connection to fuse F1. The second pin, IN- (negative input pin), is connected to the negative terminal of the battery module. The second end of fuse F1 is connected to the first end of a third resistor R3, and the second end of the third resistor R3 is connected to the second pin, IN-. The fourth pin of the battery monitoring chip U2 is connected to ground via a series connection to a first capacitor C1. The fifth pin of the battery monitoring chip U2 is connected to the thirty-fifth pin of the edge computing module U1, and the sixth pin of U2 is connected to the thirty-sixth pin of the edge computing module U1. The fifth pin of the battery monitoring chip U2 is connected to the output terminal VCC of the battery module via a series connection to a fifth resistor R5, and the sixth pin is connected to the output terminal VCC of the battery module via a series connection to a fourth resistor R4. The battery monitoring chip U2 detects the battery module and sends the monitoring data to the edge computing module U1, which then determines whether the battery voltage is below a safety threshold.
[0045] In some implementations, the Wi-Fi module can be selected from ESP8266 or ESP32, and the LoRa module can be selected from SX1278. The battery monitoring chip can be selected from MAX17043 or INA219 to ensure that the self-diagnostic results can be transmitted to the edge computing module in a timely manner.
[0046] In this embodiment, the detection device integrates a positioning module. By locating the detection device in real time, it is possible not only to accurately determine the location of the fire, but also to help quickly locate faulty equipment, thereby improving the system's response speed and maintenance efficiency.
[0047] The positioning module connects to the edge computing module via a serial communication interface (such as UART, I2C, or SPI), and the edge computing module communicates with the central controller via a wireless communication module. The positioning module acquires the location information of the detection device in real time and transmits it to the central controller through the edge computing module. After receiving the alarm information and location information, the central controller feeds back the specific location of the fire to the staff to facilitate timely action.
[0048] Furthermore, such as Figure 3 , Figure 6 As shown, the positioning module includes a positioning chip U3. The second pin of the positioning chip U3 is connected to the twentieth pin of the edge computing module to provide a 3.3V voltage. The second pin of U3 is connected in series with the second capacitor C2 and the third capacitor C3 and then grounded. The thirty-fifth pin TXD0 of the positioning chip U3 is connected to the twenty-eighth pin of the edge computing module U1 to send the positioning information to the edge computing module through the twenty-eighth pin. The thirty-fourth pin RXD0 of U3 is connected to the twenty-seventh pin of the edge computing module.
[0049] In some implementations, the positioning module can be implemented using UWB, Wi-Fi, Bluetooth, etc. In this embodiment, a Wi-Fi module is selected, which can utilize an existing Wi-Fi router without the need to deploy other devices. The detection device's built-in Wi-Fi module locates the device by signal strength. The Wi-Fi module can be an ESP32.
[0050] In this embodiment, the battery module is the power source for the detection device. Considering the advantages of size, capacity and charging efficiency, a lithium battery is selected.
[0051] The edge computing module is implemented by a microprocessor (MCU). When selecting a microcontroller with suitable data processing capabilities and low power consumption, the STM32 series MCU can be used.
[0052] In some implementations, the detection device uses an aluminum alloy casing or other metal casing with good electromagnetic shielding properties, which can effectively shield external electromagnetic radiation and improve the system's anti-interference capability against strong electromagnetic radiation. The shape of the casing of the detection device can be selected according to the actual installation location, such as circular or rectangular, as long as it can be easily installed and fixed.
[0053] In this embodiment, the building's intelligent fire alarm system also includes an execution module, which includes relays for the fire sprinkler system, ventilation system, and emergency lighting system. The edge computing module is connected to the fire sprinkler system relay, ventilation system relay, and emergency lighting system relay via GPIO interfaces. When the edge computing module determines a fire risk based on sensor data, it also triggers the execution module to output control signals to the execution module, thereby starting or stopping the fire sprinkler system, ventilation system, and emergency lighting system. This enables the fire sprinkler system to be activated to deal with the fire, the ventilation system to be activated to dilute the smoke, and the lighting to be provided for evacuation routes when a fire occurs.
[0054] Furthermore, such as Figure 3 , Figure 7As shown, the contacts of the fire sprinkler system relay K1 in the execution module are connected in series with the fire sprinkler system. The first end of the coil of relay K1 is connected to the positive terminal of the first diode D1, the second end of the sixth resistor R6, and the collector of the second transistor Q2. The negative terminal of the first diode D1 is connected to the output terminal of the battery module, the positive terminal of the second LED LED2, and the second end of the coil of K1. The negative terminal of the second LED LED2 is connected to the first end of the sixth resistor R6. The output terminal of the battery module is connected to the positive terminal of the second LED LED2, the negative terminal of the first diode D1, and the second end of the coil of K1. The emitter of the second transistor Q2 is grounded. The base of Q2 is connected in series with the seventh resistor R7 and then connected to the twelfth pin of the edge computing module. One end of the seventh resistor R7 is connected to the base of Q2 and the first end of the eighth resistor R8. The second end of the eighth resistor R8 is grounded. The edge computing module sends a high level to the execution module through its twelfth pin, which turns on the second transistor Q2, energizes the coil of the fire sprinkler system relay K1, and thus starts the fire sprinkler system to deal with the fire. The edge computing module sends a low level to the execution module through its twelfth pin to stop the fire sprinkler system.
[0055] like Figure 8 As shown, in the execution module, the contacts of the exhaust system relay K2 are connected in series with the exhaust system. The first end of the coil of relay K2 is connected to the positive terminal of the second diode D2, the second end of the ninth resistor R9, and the collector of the third transistor Q3. The negative terminal of the second diode D2 is connected to the output terminal of the battery module, the positive terminal of the third LED LED3, and the second end of the coil of K2. The negative terminal of the third LED LED3 is connected to the first end of the ninth resistor R9. The output terminal of the battery module is connected to the positive terminal of the third LED LED3, the negative terminal of the second diode D2, and the second end of the coil of K2. The emitter of the third transistor Q3 is grounded. The base of Q3 is connected in series with the tenth resistor R10 and then connected to the thirteenth pin of the edge computing module. One end of the tenth resistor R10 is connected to the base of Q3 and the first end of the eleventh resistor R11. The second end of the eleventh resistor R11 is grounded. The edge computing module sends a high level to the execution module through pin 13, turning on the third transistor Q3, energizing the coil of the exhaust system relay K2, and thus starting the exhaust system to dilute the smoke. The edge computing module sends a low level to the execution module through pin 13 to stop the exhaust system.
[0056] like Figure 9As shown, the contacts of the emergency lighting system relay K3 in the execution module are connected in series with the emergency lighting system. The first end of the coil of relay K3 is connected to the positive terminal of the third diode D3, the second end of the twenty-third resistor R23, and the collector of the fourth transistor Q4. The negative terminal of the third diode D3 is connected to the output terminal of the battery module, the positive terminal of the fourth LED LED4, and the second end of the coil of K3. The negative terminal of the fourth LED LED4 is connected to the first end of the twenty-third resistor R23. The output terminal of the battery module is connected to the positive terminal of the fourth LED LED4, the negative terminal of the third diode D3, and the second end of the coil of K3. The emitter of the fourth transistor Q4 is grounded. The base of Q4 is connected in series with the thirteenth resistor R13 and then connected to the fourteenth pin of the edge computing module. One end of the thirteenth resistor R13 is connected to the base of Q4 and the first end of the fourteenth resistor R14. The second end of the fourteenth resistor R14 is grounded. The edge computing module sends a high level to the execution module through its fourteenth pin, which turns on the fourth transistor Q4, energizes the coil of the emergency lighting system relay K3, and thus starts the emergency lighting system to dilute the smoke. The edge computing module sends a low level to the execution module through its fourteenth pin to stop the emergency lighting system.
[0057] It should be noted that the edge computing module in the distributed fire detection equipment is connected to the execution module in the area where the detection equipment is located. The execution module is also a distributed structure, distributed in various areas of the building.
[0058] In this embodiment, the central controller receives data from distributed fire detection devices (i.e., all detection devices), receives alarm information and location information of fire situations, and communicates with the cloud server via a 5G network to achieve data transmission. The cloud server is the data aggregation center of the building's intelligent fire alarm system. The cloud server receives and stores various data, alarm information, and location information collected by sensors, providing data for subsequent fire analysis by staff.
[0059] It should be noted that this embodiment does not limit the types of components used in each module, and selection can be made according to actual conditions. The fire sprinkler system, ventilation system, and emergency lighting system connected to the execution module are all existing systems, and their composition and working principle will not be described in detail here.
[0060] Detailed explanation of working principle:
[0061] The system collects data on smoke concentration, temperature, and CO gas concentration within the building using distributed fire detection devices and sends this data to an edge computing module. The edge computing module processes the sensor data, determines the presence of fire risk in real time, and issues alarms via alarm modules (such as buzzers and LED lights). Simultaneously, it outputs a high-level signal to the execution module to activate the fire sprinkler system, ventilation system, and emergency lighting system to respond to a fire. The system also transmits alarm and location information to the central controller via a wireless communication module. Upon receiving the alarm and location information, the central controller sends the information to staff, enabling a rapid response in the early stages of a fire and preventing its spread. Furthermore, the central controller communicates with a cloud server via a 5G network, sending and storing fire alarm and location information for later review by staff.
[0062] Although the specific embodiments of the present utility model have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present utility model. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solution of the present utility model are still within the scope of protection of the present utility model.
Claims
1. A smart fire alarm system for buildings, characterized in that: The system includes a distributed fire detection device, a central controller, and a cloud server connected in sequence. The distributed fire detection device includes multiple detection devices, each integrating multiple modules, including a smoke detector, a heat detector, a gas sensor, a self-diagnostic module, a positioning module, a wireless communication module, and an edge computing module. The edge computing module is connected to the smoke detector, heat detector, gas sensor, self-diagnostic module, positioning module, and wireless communication module, respectively. The edge computing module communicates wirelessly with the central controller through the wireless communication module, and the central controller communicates wirelessly with the cloud server.
2. The intelligent fire alarm system for buildings as described in claim 1, characterized in that: The smoke detector, temperature detector, and gas sensor are all connected to the edge computing module using shielded cables.
3. The intelligent fire alarm system for buildings as described in claim 1, characterized in that: The detection device also integrates an alarm module, which is controlled by the edge computing module via pins.
4. The intelligent fire alarm system for buildings as described in claim 3, characterized in that: The alarm module includes a buzzer and a first LED. One end of the buzzer is connected to a power supply, and the other end is connected to the collector of a first transistor. The base of the first transistor is connected to the ninth pin of the edge computing module and the first end of a first resistor. The second end of the first resistor is connected to the emitter of the first transistor and grounded. The positive terminal of the first LED is connected to the tenth pin of the edge computing module, and the negative terminal of the first LED is connected to the first end of a second resistor. The second end of the second resistor is grounded.
5. The intelligent fire alarm system for buildings as described in claim 1, characterized in that: The detection device also integrates a battery module, which is connected to the self-diagnostic module via an I2C interface.
6. The intelligent fire alarm system for buildings as described in claim 5, characterized in that: The self-diagnostic module includes a battery monitoring chip. The positive input pin of the battery monitoring chip is connected to the positive terminal of the battery module, and the negative input pin is connected to the negative terminal of the battery module. The fifth pin of the battery monitoring chip is connected to the thirty-fifth pin of the edge computing module, and the sixth pin is connected to the thirty-sixth pin of the edge computing module.
7. The intelligent fire alarm system for buildings as described in claim 1, characterized in that: The positioning module includes a positioning chip. The second pin of the positioning chip is connected to the twentieth pin of the edge computing module. The second pin of the positioning chip is connected to a second capacitor and a third capacitor in series and then grounded. The thirty-fifth pin of the positioning chip is connected to the twenty-eighth pin of the edge computing module, and the thirty-fourth pin of the positioning chip is connected to the twenty-seventh pin of the edge computing module.
8. The intelligent fire alarm system for buildings as described in claim 1, characterized in that: The edge computing module is implemented using a microcontroller.
9. A smart fire alarm system for buildings as described in claim 1, characterized in that: The intelligent fire alarm system also includes an execution module, which includes relays for the fire sprinkler system, ventilation system, and emergency lighting system. The edge computing module is connected to the fire sprinkler system relay, ventilation system relay, and emergency lighting system relay via GPIO interfaces.
10. A smart fire alarm system for buildings as described in claim 1, characterized in that: The distributed fire detection device uses a metal casing with electromagnetic shielding properties.