A dangerous situation monitoring and early warning system based on intelligent building
By using mobile AI robots equipped with environmental sensing devices in smart buildings, inspection routes can be planned, and risks can be monitored and predicted in real time. This solves the problems of false alarms and high costs in existing technologies and achieves comprehensive building safety management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUBEI POST TELECOMM PLANNING DESIGN
- Filing Date
- 2025-03-10
- Publication Date
- 2026-07-31
AI Technical Summary
Existing building fire monitoring systems suffer from false alarms and high equipment deployment costs, and cannot comprehensively monitor various hazardous scenarios within buildings, such as fires, toxic gas leaks, and earthquakes.
The system employs mobile AI robots equipped with environmental sensing devices to plan inspection routes, monitor the building's internal environment in real time, trigger alarms based on safety zone comparisons, predict risk areas, and provide interactive feedback to the management system.
It achieves full coverage monitoring of the building's internal environment, reduces management costs, improves the accuracy and timeliness of monitoring, and ensures building safety.
Smart Images
Figure CN120199017B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of building safety management technology, specifically to a crisis scenario monitoring and early warning system based on smart buildings. Background Technology
[0002] Smart building fire safety management leverages cutting-edge technologies such as the Internet of Things, big data, and artificial intelligence to achieve real-time monitoring of fire safety facilities, intelligent early warning of fire hazards, and efficient allocation of fire safety resources. Sensors detect anomalies such as smoke and temperature 24 / 7, quickly triggering alarms upon detection of problems. Data-driven precise location of hazards helps transform building fire safety from a reactive response to a proactive prevention approach.
[0003] Patent application number 202410821985.8 discloses a smart fire early warning system, including a sensor and camera module, a data acquisition module, a fire judgment module, a risk warning module, a linkage control module, and a communication module, all connected by communication. The sensor and camera module is used to monitor environmental parameters in real time, including temperature and smoke concentration, and to capture real-time images of a fire. The data acquisition module is used to receive data transmitted from the sensor and camera module. The system integrates and processes the acquired data; the fire judgment module uses collected environmental data and images, along with preset fire identification algorithms and models, to judge and identify the occurrence of a fire, and transmits the judgment information to the risk warning module; the risk warning module assesses the risk of a fire event, including providing risk level assessments and warning plans; the linkage control module triggers corresponding emergency measures and equipment based on the output of the risk warning module, including activating the automatic sprinkler system; and the communication module interacts with external systems or personnel, including issuing fire warning signals, contacting fire brigades, and reporting the fire situation to relevant departments.
[0004] The application aims to address the problem that "fire warnings are usually triggered only by smoke detectors. When the indoor smoke concentration is too high, the warning will be triggered regardless of whether it is fire smoke. Therefore, relying solely on smoke detectors may result in false alarms. At the same time, traditional fire warnings do not have a complete warning system. When fire warning information is issued, it is usually impossible to obtain specific information about the fire in a timely manner, nor is there a warning plan to be developed based on the fire information, which prevents relevant personnel from responding to the fire in a timely manner."
[0005] However, building fire protection includes not only fires, but also toxic gas leaks, earthquakes, etc. With current technology, the monitoring points for fire safety issues in buildings are mostly fixed, resulting in a large number of monitoring and sensing devices. This leads to excessively high management, maintenance, and deployment costs for these devices, and the maintenance area is limited to the deployment location of the monitoring and sensing devices.
[0006] To address this, a crisis scenario monitoring and early warning system based on smart buildings is proposed. Summary of the Invention
[0007] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a crisis scenario monitoring and early warning system based on smart buildings, which solves the technical problems mentioned in the background.
[0008] To achieve the above objectives, the present invention provides the following technical solution:
[0009] A crisis scenario monitoring and early warning system based on smart buildings, comprising:
[0010] The system comprises the following modules: a planning module for planning internal building inspection paths and importing these paths into the inspection robot; a data acquisition module for controlling the environmental sensing equipment on the inspection robot and collecting environmental information about the robot's current location within the building; an alarm module for receiving real-time environmental information collected by the data acquisition module and comparing it with preset safety zones to determine whether to trigger an alarm; a prediction module for predicting risky areas within the building; and an interaction module for receiving the predicted risky areas from the prediction module and providing feedback to the building management user.
[0011] Furthermore, the inspection robot is a mobile, conversational AI robot equipped with environmental sensing devices, which include: temperature sensor, humidity sensor, smoke sensor, infrared flame sensor, and vibration sensor integrated together.
[0012] The planning module has sub-modules at its lower level, including:
[0013] The upload unit is used to upload the coordinates of the building's internal location.
[0014] The building unit is used to receive the internal building location coordinates uploaded from the upload unit, and connect them sequentially based on the upload order of the internal building location coordinates to construct the internal building inspection path;
[0015] In this process, after the building unit completes the construction of the internal inspection path, it transmits it to the planning module. After receiving the internal inspection path, the planning module selects points on the internal inspection path as deployment points for the inspection robot.
[0016] Furthermore, the number of inspection robots configured on the internal inspection path of the building is customized by the system user. During the stage of selecting points on the internal inspection path of the building as deployment points for inspection robots, the corresponding number of points are selected based on the number of inspection robots.
[0017] After the building inspection path is imported into the inspection robot, a specified number of inspection robots are placed on the building inspection path. The current position coordinates and the deployment point coordinates of an inspection robot are simultaneously input into the inspection robot. The inspection robot moves based on the building inspection path and the current position coordinates to reach the deployment point coordinates of the inspection robot.
[0018] In the building interior inspection path planning stage, the starting point and ending point of the building interior inspection path are connected, and the movement direction of all inspection robots is consistent. Moreover, when the inspection robot moves to the deployment point coordinates based on the building interior inspection path and the current position coordinates, it does not follow the set movement direction, but chooses the direction close to the deployment point coordinates to perform the movement action.
[0019] Furthermore, the number of inspection robots configured on the internal inspection path of the building is customized by the system user. During the stage of selecting points on the internal inspection path of the building as deployment points for inspection robots, the corresponding number of points are selected based on the number of inspection robots.
[0020] After the building inspection path is imported into the inspection robot, a specified number of inspection robots are placed on the building inspection path. The current position coordinates and the deployment point coordinates of an inspection robot are simultaneously input into the inspection robot. The inspection robot moves based on the building inspection path and the current position coordinates to reach the deployment point coordinates of the inspection robot.
[0021] In the building interior inspection path planning stage, the starting point and ending point of the building interior inspection path are connected, and the movement direction of all inspection robots is consistent. Moreover, when the inspection robot moves to the deployment point coordinates based on the building interior inspection path and the current position coordinates, it does not follow the set movement direction, but chooses the direction close to the deployment point coordinates to perform the movement action.
[0022] Furthermore, the initial travel distance of the inspection robot is user-defined on the system side, and the update of the travel distance follows the following rules:
[0023] Safety zones are set for the information sensed by the temperature sensor, humidity sensor, smoke sensor, infrared flame sensor, and vibration sensor respectively.
[0024]
[0025] In the formula: ν is the reference value applied when updating the running distance; (C min C max (RH) represents the safe temperature range; min RH max ) represents the safe humidity range; (ρ) min , ρ max (L) represents the safe range for flue gas content; min L max (P) represents the safe range for infrared radiation wavelengths; min P max C represents the safe range for vibration signal amplitude. MAX RH MAX ρ MAX L MAX P MAX The maximum temperature, humidity, flue gas content, infrared radiation wavelength, and vibration signal amplitude sensed during continuous operation at a specified frequency within the parking period; d is the next operating distance; d0 is the current operating distance; α is a constant.
[0026] Wherein, min(|Cmax-C MAX |,|Cmin-C MAX |) indicates taking the minimum value within the parentheses. The constant α is user-defined on the system side and is used to control... The value is in the range (0, 2).
[0027] Furthermore, the environmental information collected by the acquisition module includes temperature, humidity, smoke concentration, infrared radiation wavelength, and vibration signal amplitude. The safe range (C) applied by the alarm module when performing the comparison operation is... min C max ), (RH min RH max ), (ρ min , ρ max ), (L min L max ), (P min P max );
[0028] The alarm module triggers an alarm when any environmental information meets the corresponding safety range: the inspection robot continuously broadcasts the internally preset alarm audio.
[0029] Furthermore, the inspection robot's face is always aligned with its direction of movement along its inspection path inside the building;
[0030] The alarm module contains sub-modules, including:
[0031] The identification unit is used to obtain the movement distance of the inspection robot that triggered the alarm in the two most recent runs, and to identify the best evacuation direction based on the two movement distances.
[0032] The optimal evacuation direction includes the direction in which the inspection robot's face is facing and the direction in which its back is facing. The two movement distances obtained by the recognition unit are denoted as d1 and d2, where d2 represents the most recent movement distance and d1 represents the previous movement distance adjacent to d2. If d1 > d2, the direction in which the inspection robot's back is facing is the optimal evacuation direction. If d1 < d2, the direction in which the inspection robot's face is facing is the optimal evacuation direction. When d1 = d2, the recognition unit is refreshed.
[0033] Furthermore, the optimal evacuation direction is broadcast in a loop by the inspection robot in the form of audio, synchronized with the alarm audio.
[0034] Furthermore, the prediction logic for areas with risks within the building in the prediction module is as follows:
[0035] Real-time monitoring of the latest three running distances of each inspection robot; when the latest three running distances are continuously decreasing, the coordinates of the two ends of the road segment where the three running distances are located in the internal inspection path of the building are determined, and the road segment with the coordinates of the two ends on the internal inspection path of the building is designated as the risk area.
[0036] The interactive module connects to the mobile computer device held by the building management user via a wireless network, marking the risk areas on the inspection path inside the building for the building management user to read;
[0037] The operation of marking risk areas on the building's internal inspection path involves replacing the corresponding road segment of the risk area on the building's internal inspection path with a specified line shape that is different from the building's internal inspection path.
[0038] Furthermore, the planning module has an upload unit and a construction unit connected to it via a wireless network at its lower level. The planning module also has a data acquisition module and an alarm module connected to it via a wireless network. The alarm module has an identification unit connected to it via a wireless network, and the alarm module also has a prediction module and an interaction module connected to it via a wireless network.
[0039] Compared with known public technologies, the technical solution provided by this invention has the following beneficial effects:
[0040] This invention provides a crisis monitoring and early warning system based on smart buildings. During operation, the system uses AI robots installed in the smart building as the main body to provide fire safety management for the smart building. By configuring inspection paths for the AI robots, deploying environmental sensing devices on the AI robots, and configuring operating logic, the AI robots can cyclically and comprehensively monitor and perceive the internal environment of the building as they move inside. Furthermore, based on the set environmental safety judgment and prediction logic, warnings are triggered and users can interact with the building management terminal, effectively and long-term ensuring the safety of the internal environment of the building. Attached Figure Description
[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.
[0042] Figure 1 This is a schematic diagram of a crisis scenario monitoring and early warning system based on smart buildings. Detailed Implementation
[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.
[0044] The present invention will be further described below with reference to embodiments.
[0045] Example:
[0046] This embodiment presents a crisis scenario monitoring and early warning system based on smart buildings, such as... Figure 1 As shown, it includes:
[0047] The planning module is used to plan the internal inspection path of the building and import the internal inspection path into the inspection robot.
[0048] The inspection robot is a mobile, conversational AI robot equipped with environmental sensing devices, which include temperature sensors, humidity sensors, smoke sensors, infrared flame sensors, and vibration sensors.
[0049] The planning module has sub-modules, including:
[0050] The upload unit is used to upload the coordinates of the building's internal location.
[0051] The building unit is used to receive the internal building location coordinates uploaded from the upload unit, and connect them sequentially based on the upload order of the internal building location coordinates to construct the internal building inspection path;
[0052] Among them, after the construction unit completes the construction of the internal inspection path of the building, it transmits it to the planning module in a synchronous manner. After receiving the internal inspection path of the building, the planning module selects points on the internal inspection path as the deployment points of the inspection robot in a synchronous manner.
[0053] The number of inspection robots configured on the internal inspection path of the building is customized by the system user. During the stage of selecting points on the internal inspection path of the building as the deployment points of the inspection robots, the corresponding number of points are selected based on the number of inspection robots.
[0054] After the building's internal inspection path is imported into the inspection robot, a specified number of inspection robots are simultaneously placed on the building's internal inspection path. The current position coordinates and the coordinates of a robot deployment point are simultaneously input into the inspection robot. The inspection robot moves based on the building's internal inspection path and the current position coordinates to reach the robot deployment point coordinates.
[0055] In the building interior inspection path planning stage, the starting point and the ending point of the building interior inspection path are connected, and the movement direction of all inspection robots is consistent. Moreover, the inspection robot does not follow the set movement direction when moving to the deployment point coordinates based on the building interior inspection path and the current position coordinates. Instead, it selects the direction close to the deployment point coordinates to perform the movement action.
[0056] When configuring the number of inspection robots for internal building inspection paths, the following rule applies: the longer the internal building inspection path and the larger the building volume, the more inspection robots should be configured, and vice versa.
[0057] The inspection robot is deployed along the inspection path inside the building. After reaching its corresponding deployment point coordinates, the robot's single running distance and dwell time are set simultaneously. The dwell time is used for the operation of the environmental sensing equipment.
[0058] The set dwell time is a fixed value, and the set running distance is updated based on the environmental information sensed by the environmental sensing device during the main time period.
[0059] The initial travel distance of the inspection robot is defined by the system user, and the update of the travel distance follows the following rules:
[0060] Safety zones are set for the information sensed by the temperature sensor, humidity sensor, smoke sensor, infrared flame sensor, and vibration sensor respectively.
[0061]
[0062] In the formula: ν is the reference value applied when updating the running distance; (C min C max (RH) represents the safe temperature range; min RH max ) represents the safe humidity range; (ρ) min , ρ max (L) represents the safe range for flue gas content; min L max (P) represents the safe range for infrared radiation wavelengths; min P max C represents the safe range for vibration signal amplitude. MAX RH MAX ρ MAX L MAX P MAX The maximum temperature, humidity, flue gas content, infrared radiation wavelength, and vibration signal amplitude sensed during continuous operation at a specified frequency within the parking period; d is the next operating distance; d0 is the current operating distance; α is a constant.
[0063] Wherein, min(|Cmax-C MAX |,|Cmin-C MAX |) indicates taking the minimum value within the parentheses. The constant α is user-defined on the system side and is used to control... The value is within the range (0, 2);
[0064] The above logical formula is used to calculate the following one-time travel distance for the inspection robot in real time, ensuring that the inspection robot's process of sensing environmental information has a higher degree of full coverage of the building and a better level of intelligent adaptive operation.
[0065] The data acquisition module is used to control the operation of the environmental sensing equipment mounted on the inspection robot and to collect environmental information of the building where the inspection robot is currently located based on the environmental sensing equipment.
[0066] The environmental information collected by the acquisition module includes temperature, humidity, smoke concentration, infrared radiation wavelength, and vibration signal amplitude. The alarm module uses a safe range (C) when performing comparison operations. min C max (RH) min RH max )(ρ min , ρ max(L) min L max )
[0067] ,,,,(P min P max );
[0068] Among them, the alarm module triggers an alarm when any environmental information meets the corresponding safety range: the inspection robot continuously broadcasts the internally preset alarm audio;
[0069] The alarm module is used to receive environmental information of the building interior scene collected by the acquisition module in real time, and decide whether to trigger an alarm based on the comparison of the environmental information with the preset safety range.
[0070] The inspection robot's face is always aligned with its direction of movement along its inspection path inside the building;
[0071] The alarm module contains sub-modules, including:
[0072] The identification unit is used to obtain the movement distance of the inspection robot that triggered the alarm in the two most recent runs, and to identify the best evacuation direction based on the two movement distances.
[0073] The optimal evacuation direction includes the direction in which the inspection robot's face is facing and the direction in which its back is facing. The two movement distances obtained by the recognition unit are denoted as d1 and d2, where d2 represents the most recent movement distance and d1 represents the previous movement distance adjacent to d2. If d1 > d2, the direction in which the inspection robot's back is facing is the optimal evacuation direction. If d1 < d2, the direction in which the inspection robot's face is facing is the optimal evacuation direction. When d1 = d2, the recognition unit is refreshed.
[0074] The optimal evacuation direction is announced in audio form, synchronized with the alarm audio, and is broadcast repeatedly by the inspection robot.
[0075] The prediction module is used to predict areas within a building that pose a risk.
[0076] The interaction module is used to receive the risk areas predicted by the prediction module and to provide feedback on the risk areas to the building management user.
[0077] The prediction logic for areas with risks within the building in the prediction module is as follows:
[0078] Real-time monitoring of the latest three running distances of each inspection robot; when the latest three running distances are continuously decreasing, the coordinates of the two ends of the road segment where the three running distances are located in the internal inspection path of the building are determined, and the road segment with the coordinates of the two ends on the internal inspection path of the building is designated as the risk area.
[0079] The interactive module connects to the mobile computer device held by the building management user via a wireless network, marking risk areas on the inspection path inside the building for the building management user to read;
[0080] The operation of marking risk areas on the building's internal inspection path involves replacing the corresponding road segment of the risk area on the building's internal inspection path with a specified line shape that is different from the building's internal inspection path.
[0081] The planning module has an upload unit and a construction unit connected to it via a wireless network. The planning module also has a data acquisition module and an alarm module connected to it via a wireless network. The alarm module has an identification unit connected to it via a wireless network. The alarm module also has a prediction module and an interaction module connected to it via a wireless network.
[0082] In this embodiment, the planning module plans the internal inspection path of the building and imports it into the inspection robot. The uploading unit synchronously uploads the internal location coordinates of the building. The construction unit receives the internal location coordinates uploaded by the uploading unit in real time and connects them sequentially based on the upload order to construct the internal inspection path. The acquisition module controls the operation of the environmental perception device on the inspection robot and collects environmental information of the current internal scene of the inspection robot based on the environmental perception device. The alarm module further receives the environmental information of the internal scene of the building collected by the acquisition module in real time, compares the environmental information with the preset safety zone, and decides whether to trigger an alarm. The identification unit synchronously obtains the two most recent running distances of the inspection robot that triggered the alarm and identifies the best evacuation direction based on the two running distances. Then, the prediction module predicts the risk areas inside the building. Finally, the interaction module receives the risk areas predicted by the prediction module and feeds the risk areas back to the building management user.
[0083] By operating the system in the above embodiments, the building fire safety management is combined with the AI robots deployed inside the smart building, which effectively reduces the overall cost of building fire safety management and brings more comprehensive maintenance results to building fire safety management.
[0084] In summary, the system in the above embodiments, with AI robots installed in smart buildings as the main body, provides fire safety management for smart buildings. By configuring inspection paths for AI robots, deploying environmental perception devices on AI robots, and configuring operating logic, the AI robots can cyclically and comprehensively monitor and perceive the internal environment of the building as they move inside. Furthermore, based on the set environmental safety judgment and prediction logic, warnings are triggered and users on the building management end interact with the system, effectively and long-term ensuring the safety of the building's internal environment.
[0085] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A crisis scenario monitoring and early warning system based on smart buildings, characterized in that, include: The planning module is used to plan the internal inspection path of the building and import the internal inspection path into the inspection robot. The data acquisition module is used to control the operation of the environmental sensing equipment mounted on the inspection robot and to collect environmental information of the building where the inspection robot is currently located based on the environmental sensing equipment. The alarm module is used to receive environmental information of the building interior scene collected by the acquisition module in real time, and decide whether to trigger an alarm based on the comparison of the environmental information with the preset safety range. The prediction module is used to predict areas within a building that pose a risk. The interaction module is used to receive the risk areas predicted by the prediction module and to provide feedback on the risk areas to the building management user. The inspection robot is a mobile, conversational AI robot equipped with environmental sensing devices, which include: temperature sensor, humidity sensor, smoke sensor, infrared flame sensor, and vibration sensor. The planning module has sub-modules at its lower level, including: The upload unit is used to upload the coordinates of the building's internal location. The building unit is used to receive the internal building location coordinates uploaded from the upload unit, and connect them sequentially based on the upload order of the internal building location coordinates to construct the internal building inspection path; Among them, after the construction unit completes the construction of the internal inspection path of the building, it transmits it to the planning module in a synchronous manner. After receiving the internal inspection path of the building, the planning module selects points on the internal inspection path as the deployment points of the inspection robot in a synchronous manner. The number of inspection robots configured on the internal inspection path of the building is customized by the system user. During the stage of selecting points on the internal inspection path of the building as the deployment points of the inspection robots, the corresponding number of points are selected based on the number of inspection robots. After the building inspection path is imported into the inspection robot, a specified number of inspection robots are placed on the building inspection path. The current position coordinates and the deployment point coordinates of an inspection robot are simultaneously input into the inspection robot. The inspection robot moves based on the building inspection path and the current position coordinates to reach the deployment point coordinates of the inspection robot. In the building interior inspection path planning stage, the starting point and ending point of the building interior inspection path are connected, and the movement direction of all inspection robots is consistent. Moreover, when the inspection robot moves to the deployment point coordinates based on the building interior inspection path and the current position coordinates, it does not follow the set movement direction, but chooses the direction close to the deployment point coordinates to perform the movement action.
2. The emergency situation monitoring and early warning system based on smart buildings according to claim 1, characterized in that, When configuring the number of inspection robots for the internal inspection path of a building, the following rule applies: the longer the internal inspection path and the larger the building volume, the more inspection robots are configured, and vice versa. The inspection robot is deployed on the inspection path inside the building. After reaching the coordinates of its corresponding deployment point, the single running distance and dwell time of the inspection robot are set simultaneously. The dwell time is used for the operation of the environmental sensing equipment. The set dwell time is a fixed value, and the set running distance is updated based on the environmental information sensed by the environmental sensing device within the main time period.
3. A crisis scenario monitoring and early warning system based on smart buildings according to claim 2, characterized in that, The initial travel distance of the inspection robot is defined by the system user, and the update of the travel distance follows the following rules: Safety zones are set for the information sensed by the temperature sensor, humidity sensor, smoke sensor, infrared flame sensor, and vibration sensor respectively. ； In the formula: The reference value for the application when the running distance is updated; This is within the safe temperature range; This is within the safe humidity range. The safe range for flue gas content; This is within the safe range for infrared radiation wavelengths. This is the safe range for vibration signal amplitude. The maximum temperature, humidity, flue gas content, infrared radiation wavelength, and vibration signal amplitude sensed during continuous operation at a specified frequency within the parking period; The distance to travel in the next run; This represents the current distance traveled. It is a constant; in, This indicates taking the minimum value within the parentheses, a constant. User-defined constants on the system side Used for control The value is in the range (0, 2).
4. A crisis scenario monitoring and early warning system based on smart buildings according to claim 1, characterized in that, The environmental information collected by the acquisition module includes temperature, humidity, smoke concentration, infrared radiation wavelength, and vibration signal amplitude. The alarm module uses a safe range during the comparison operation. , , , , ; The alarm module triggers an alarm when any environmental information meets the corresponding safety range: the inspection robot continuously broadcasts the internally preset alarm audio.
5. A crisis scenario monitoring and early warning system based on smart buildings according to claim 1, characterized in that, The inspection robot's face is always aligned with its direction of movement along its inspection path inside the building. The alarm module contains sub-modules, including: The identification unit is used to obtain the movement distance of the inspection robot that triggered the alarm in the two most recent runs, and to identify the best evacuation direction based on the two movement distances. The optimal evacuation direction includes the direction in which the inspection robot's face is facing and the direction in which its back is facing. The two movement distances obtained by the recognition unit are denoted as d1 and d2, where d2 represents the most recent movement distance and d1 represents the previous movement distance adjacent to d2. If d1 > d2, the direction in which the inspection robot's back is facing is the optimal evacuation direction. If d1 < d2, the direction in which the inspection robot's face is facing is the optimal evacuation direction. When d1 = d2, the recognition unit is refreshed.
6. A crisis scenario monitoring and early warning system based on smart buildings according to claim 5, characterized in that, The optimal evacuation direction is announced in audio form, synchronized with the alarm audio, and is broadcast repeatedly by the inspection robot.
7. A crisis scenario monitoring and early warning system based on smart buildings according to claim 1, characterized in that, The prediction logic for areas with risks inside the building in the prediction module is as follows: Real-time monitoring of the latest three running distances of each inspection robot; when the latest three running distances are continuously decreasing, the coordinates of the two ends of the road segment where the three running distances are located in the internal inspection path of the building are determined, and the road segment with the coordinates of the two ends on the internal inspection path of the building is designated as the risk area. The interactive module connects to the mobile computer device held by the building management user via a wireless network, marking the risk areas on the inspection path inside the building for the building management user to read; The operation of marking risk areas on the building's internal inspection path involves replacing the corresponding road segment of the risk area on the building's internal inspection path with a specified line shape that is different from the building's internal inspection path.
8. A crisis scenario monitoring and early warning system based on smart buildings according to claim 1, characterized in that, The planning module has an upload unit and a construction unit connected to it via a wireless network. The planning module also has a data acquisition module and an alarm module connected to it via a wireless network. The alarm module has an identification unit connected to it via a wireless network. The alarm module also has a prediction module and an interaction module connected to it via a wireless network.