Building safety monitoring system based on wireless sensor network

Abstract

The invention provides a building safety monitoring system based on a wireless sensor network. The building safety monitoring system is used for monitoring and evaluating the structural safety and stability of a building in real time. According to the system, a plurality of sensor nodes, including an accelerometer, a strain gauge, a temperature sensor, a humidity sensor and the like, are connected into a self-organizing wireless network and are distributed at key positions of a building to collect physical parameter data in real time. The sensor node is provided with a solar panel and a battery, and long-time stable operation is ensured. Data is preliminarily processed by a microprocessor arranged in the node and then is transmitted to a central processing unit for deep analysis, and a data analysis algorithm and a model are used for identifying potential problems. When a threshold value is exceeded or an abnormity is found, the system triggers an alarm to inform related personnel. A user can check the monitoring data, the historical trend and the building model in real time through a visual user interface. The system has a security encryption mechanism and can be accessed by only authorized users, so that data privacy and integrity are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of building safety monitoring, and in particular to a building safety monitoring system based on a wireless sensor network. Background Art

[0002] With the acceleration of global urbanization, the construction of various large buildings, bridges, tunnels and other infrastructure is increasing. These complex structures may suffer damage during their service life due to a variety of reasons, such as earthquakes, wind loads, material aging, overuse and other external factors. In order to ensure the safety of these buildings and extend their service life, continuous and real-time structural safety monitoring becomes essential.

[0003] Traditional building safety monitoring methods usually rely on wired sensor systems that involve a lot of wiring and complex data acquisition and processing equipment. These sensors are usually installed in key parts of the building, such as supporting structures, walls and foundations, to monitor their force, displacement, vibration and other parameters. Although these sensors can provide high-precision data, their installation and maintenance costs are expensive, and they limit the monitoring coverage and real-time performance.

[0004] The emergence of Wireless Sensor Networks (WSN) has introduced a more forward-looking and cost-effective approach to building safety monitoring. WSN consists of wireless sensor nodes distributed inside or near buildings, which can automatically configure, self-organize and work together to collect and transmit various data types, such as temperature, humidity, vibration, stress and displacement. Compared with wired systems, WSN does not require wiring, and the installation process is simpler and faster; wireless sensors are cheaper than wired sensors, and due to the reduction in installation and maintenance costs, the overall system cost is also more economical; when it is necessary to increase monitoring points or expand the monitoring range, only new sensor nodes need to be added without complex rewiring and configuration.

[0005] However, despite the above advantages, WSN still faces some technical challenges in building safety monitoring applications. First, since sensor nodes are usually powered by batteries, how to effectively manage energy to extend the life of the network becomes a key issue. Secondly, ensuring the real-time and accuracy of data is also crucial, especially when evaluating the safety of buildings. In addition, the stability of the network, the security of the data, and the calibration of the sensors are also important issues that need to be addressed.

[0006] At the same time, the accuracy of data does not only involve the data collection of sensor nodes, but also includes the analysis and interpretation of data. Therefore, building safety monitoring systems require powerful data analysis algorithms that can extract useful information from the large amount of data generated by sensors, accurately assess the safety of the structure, and issue alarms or suggestions in a timely manner.

[0007] The existing public invention application number is 2012100425074, and the authorization announcement number is CN102607644B. ​​It provides a system that can continuously monitor the structural changes in the construction process in real time. Through several acquisition units connected to the host, the system can automatically collect and record the measurement data of the sensor unit and the vertical displacement measurement unit. However, this patent also has some shortcomings. For example, the system does not include a data analysis algorithm that enables monitoring personnel to more easily analyze and interpret monitoring data and extract useful information from it. If the monitoring system relies on power supply, then power outages or power failures may cause monitoring interruptions, reducing real-time performance.

[0008] The existing public invention application number is 201910894086X, and the authorization announcement number is CN110397298B. It adopts a comprehensive monitoring method that combines drones and WSN to provide more comprehensive and multi-angle building health monitoring data. However, the patent also has some shortcomings. For example, the invention relies on the reliability and stability of drones and WSN equipment. If these devices fail or are damaged, the monitoring system may be interrupted, affecting real-time monitoring, and the range and endurance of the drone may limit the scope of monitoring. For large buildings or wide areas, multiple drones or frequent charging / replacement of batteries may be required.

[0009] In summary, developing a building safety monitoring system based on wireless sensor networks, which can fully utilize the advantages of WSN while overcoming its technical challenges and combining it with data analysis algorithms, has important practical significance for improving the safety of buildings and extending their service life. Summary of the invention

[0010] In order to solve the deficiencies pointed out in the above background technology, the present invention provides a building safety monitoring system based on a wireless sensor network (WSN), aiming to achieve real-time, efficient and accurate safety monitoring of building structures.

[0011] The following are the main components and functions of the present invention: Sensor nodes: The system uses a variety of sensors, such as accelerometers, strain gauges, temperature sensors and humidity sensors, to monitor various physical parameters of the building. Each sensor node is equipped with a small solar panel and battery to ensure continuous operation without an external power supply. The sensor node has a built-in microprocessor to perform preliminary processing and analysis on the raw data, thereby reducing the amount of data that needs to be transmitted; Communication module: A self-organizing wireless network is formed between the sensor nodes to ensure that data is reliably transmitted in a complex building environment. Through the Internet or mobile network, users can remotely access the system to view monitoring data and analysis results in real time; Central processing unit: Receive data from each sensor node wirelessly, use algorithms and models to conduct in-depth analysis of the collected data to evaluate the safety status of the building, and when potential structural problems or parameters exceeding predetermined thresholds are detected, the system will automatically trigger an alarm to notify relevant personnel; User interface: Provides an intuitive graphical interface to display the three-dimensional model of the building and the data of each monitoring point. Users can query and replay historical monitoring data to analyze the long-term change trends of buildings, allowing users to customize the thresholds of monitoring parameters to meet different monitoring needs; Security and encryption: To ensure data security, all transmitted data is encrypted, and only authorized users can access the system to ensure data privacy and integrity.

[0012] Specifically, the system uses a variety of sensors, such as accelerometers, strain gauges, temperature sensors, and humidity sensors to monitor various physical parameters of the building.

[0013] Among them, the accelerometer uses the inertia of a particle when it is subjected to acceleration to measure the acceleration of an object. It is mainly used to monitor the vibration response of a building under external forces such as wind loads or earthquakes. By analyzing these data, the dynamic characteristics and structural health of the building can be evaluated.

[0014] When a material is subjected to external forces, it will deform. Strain gauges can measure this deformation and obtain strain values. They are mainly used to monitor static and dynamic strains in buildings, such as the formation and expansion of cracks, bending of beams and columns, etc. These data are crucial for assessing the safety of structures and predicting potential structural problems.

[0015] Temperature sensors use the thermal properties of materials, such as the temperature coefficient of resistance, to measure temperature. Monitoring temperature changes inside and outside buildings is critical to assessing factors such as material aging, thermal expansion and contraction.

[0016] Humidity sensors use the sensitivity of materials to changes in humidity, such as the humidity coefficient of capacitance, to measure relative humidity. Monitoring humidity changes inside and outside buildings can help assess corrosion, mildew, and other humidity-related problems in structural materials.

[0017] Each sensor node is equipped with a small solar panel and battery for energy management. The small solar panel uses the photovoltaic effect to convert sunlight into electrical energy. It has self-charging capabilities and is suitable for outdoor environments, which can effectively extend the working time of the sensor node. The battery uses high-energy-density lithium-ion batteries or lithium-polymer batteries with long life, low self-discharge rate and high charging efficiency, ensuring that the sensor node can continue to work even without solar power supply.

[0018] The sensor node has a built-in microprocessor to perform preliminary processing and analysis on the raw data, thereby reducing the amount of data that needs to be transmitted. The present invention adopts a low-power, high-performance embedded microprocessor that can periodically collect data from each sensor, perform noise filtering, outlier detection and basic statistical analysis on the data, and store a certain amount of data in the built-in flash memory for subsequent inquiries or data backup in the event of communication interruption.

[0019] Specifically, in the communication module, after deployment, the sensor node will automatically search for other nearby nodes and establish connections with them to form a multi-hop wireless network. According to the real-time status of the network, it will automatically select the best data transmission path. When a node fails or communication is interrupted, the network will automatically reorganize to ensure the continuity and integrity of the data. All transmitted data is encrypted to prevent theft or tampering. Through the Internet or mobile network, authorized users can remotely access the system, view monitoring data and analysis results in real time, and receive commands from remote users and forward them to the sensor network, such as modifying parameters, requesting specific data, etc.

[0020] Specifically, the central processing unit will use high-frequency wireless communication technology, such as Wi-Fi, LoRa or Zigbee, to receive data sent by sensor nodes, ensuring that a large amount of sensor node data can be transmitted in real time and the stability of data transmission in complex building environments. At the same time, all transmitted data will be encrypted to prevent data from being stolen or tampered with. High-speed RAM or SSD will be used as cache to temporarily store received data to ensure data continuity and integrity, and provide support for subsequent data analysis.

[0021] Using data analysis algorithms and models, such as machine learning, time series analysis, and frequency domain analysis, the collected data is analyzed in depth to monitor the long-term change trend of the building, such as structural settlement, crack expansion, etc.; real-time detection of abnormal values ​​in the data, such as sudden vibration, rapid changes in temperature or humidity, etc.; combined with the building's design parameters and real-time monitoring data, its structural health status is evaluated. And a relational or time-series database, such as MySQL, PostgreSQL, or InfluxDB, is used to store the collected data and analysis results for a long time, supporting efficient data query and playback.

[0022] Among them, machine learning is a data-driven method that automatically learns the patterns and regularities of data by training models, and then uses these models to classify, regress or detect anomalies on new data. In building safety monitoring, machine learning algorithms can be used in the following aspects: Anomaly detection: Use unsupervised learning algorithms, such as clustering-based methods or autoencoders, to detect outliers in sensor data, such as sudden vibrations or temperature anomalies; Trend analysis: Use time series prediction models, such as ARIMA (autoregressive integrated moving average model) or Prophet, to predict future trends in building parameters, such as structural settlement or temperature changes; Classification: Use supervised learning algorithms, such as decision trees or random forests, to classify the health status of buildings, such as normal, needing maintenance, or needing further monitoring.

[0023] Time series analysis is a statistical method specifically used to process data points arranged in time order. It includes analyzing the periodicity, trend, seasonality, and noise components of the data. In building safety monitoring, time series analysis can be used in the following aspects: Trend analysis: Use techniques such as moving average or exponential smoothing to capture the long-term trend of building parameters in order to detect structural settlement or other potential problems; Periodicity analysis: Use Fourier transform or autocorrelation function to analyze whether the data has obvious periodicity, such as seasonal vibration; Anomaly detection: Use statistical methods to identify abnormal points or abnormal patterns, thereby alerting possible problems.

[0024] Frequency domain analysis is a method of decomposing a signal into its different frequency components. It usually involves techniques such as Fourier transform or wavelet analysis. In building safety monitoring, frequency domain analysis can be used for the following: Vibration analysis: Through Fourier transform, the vibration signal is decomposed into components of different frequencies to identify possible structural vibration modes, such as vibrations caused by earthquakes; Resonance detection: Through frequency domain analysis, it is determined whether the building is in a resonant state, thereby identifying possible dangerous situations of the structure; Spectral analysis: Analyze the spectrum of sensor data to determine abnormal or abnormal peaks in the frequency domain, indicating potential problems.

[0025] The system allows users to customize the thresholds of various monitoring parameters according to the characteristics of the building and the use environment. When potential structural problems are detected or parameters that exceed the predetermined thresholds are detected, the system will automatically trigger an alarm, supporting multiple alarm methods such as sound, light, SMS, and email. Depending on the severity of the problem, different levels of personnel will be notified, such as general problems notifying maintenance personnel and major problems notifying management. At the same time, all notification events are recorded to ensure that the problem is handled in a timely manner.

[0026] Specifically, the user interface provides an intuitive graphical interface, such as using modern graphics rendering technology to display the three-dimensional model of the building. Users can freely rotate, zoom and pan the model to view various parts of the building. The location of each monitoring point will display the corresponding real-time data, such as temperature, humidity, vibration, etc., and use different colors and icons according to the size and importance of the data, so that users can quickly identify potential problem areas. It also provides a variety of chart types, such as curve charts, bar charts, pie charts and heat maps, which are automatically updated according to the real-time data received. Users can select multiple monitoring points or time periods to compare and analyze the data.

[0027] This system provides a simple query interface where users can enter query conditions, such as time range, monitoring point and parameter type. Based on the user's query conditions, the corresponding historical data will be retrieved from the database and displayed on the interface. The query results can be exported to common file formats, such as CSV, Excel and PDF, for further analysis and sharing.

[0028] Specifically, to ensure the security of data, all transmitted data is encrypted, which can be divided into transport layer encryption and end-to-end encryption. Encrypt data using encryption algorithms to ensure the security of data during transmission, such as TLS / SSL, which is a widely used security protocol for protecting the security of data transmission on the Internet. It can not only encrypt data, but also verify the identity of the server and the client; use algorithms such as Diffie-Hellman or ECDHE to ensure the secure exchange of keys, so that even if the communication is monitored, the attacker cannot decrypt the data. Data is encrypted at the source and decrypted at the destination to ensure the security of data during the entire transmission and storage process. Symmetric encryption such as AES and Blowfish are used to encrypt and decrypt with the same key, which is suitable for the encryption of large amounts of data. Asymmetric encryption such as RSA and ECC are used to use a pair of public and private keys, the public key is used for encryption, and the private key is used for decryption, which is suitable for the encryption of keys and sensitive information.

[0029] At the same time, access control is performed to ensure that only legitimate users can access the system. The most basic authentication method requires users to enter a pre-set username and password, and also provide other authentication information, such as SMS verification code, fingerprint or facial recognition. Different access rights are assigned to users according to their roles, such as administrators, maintenance personnel and ordinary users. Each role has its own specific permissions and restrictions. System administrators can configure the resources and operations that each role can access, such as viewing data, modifying parameters and managing users. Sensitive data is desensitized and anonymized to ensure that user privacy is not leaked, such as replacing specific location information with a general area, replacing specific values ​​with a range, or using a unique ID to replace the user's real name and contact information. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is the overall framework diagram of this system;

[0031] Figure 2 This is the sensor node structure diagram of this system;

[0032] Figure 3 This is the wireless network topology diagram of this system;

[0033] Figure 4 This is the block diagram of the central processing unit of this system;

[0034] Figure 5 This is the relationship diagram of the user interface components of this system;

[0035] Figure 6 This is the security and encryption flow chart of this system;

[0036] Figure 7 This is the alarm and notification flow chart of this system. DETAILED DESCRIPTION

[0037] Reference Figure 1 To Attachment Figure 7, the present invention provides a specific embodiment, the method of this embodiment is to deploy sensor nodes at key locations of a building, such as beams, columns, walls and foundations. Since the beam is a key structure that bears the load and transfers it to the column, sensors should be deployed at the upper and lower parts of the beam to monitor its bending, torsion and shear; the column is the main supporting structure of the building. Sensors should be deployed at the top, middle and bottom of the column to monitor its compression, displacement and rotation; wall sensors are mainly used to monitor cracks, deformation and humidity in the wall. Key locations of the wall should be selected, such as around windows and doors, corners and joints of the wall; the foundation is the foundation of the building, and sensors should be deployed in all corners and centers of the foundation to monitor its settlement, displacement and vibration. Subsequently, a special fixing clip or glue is used to ensure that the sensor is firmly fixed to the structure and is in full contact with the surface of the structure to obtain accurate data. Of course, other key locations can also be used, and this embodiment is not limited.

[0038] refer to Figure 3 In this paper, we show four sensor nodes (Sensor Node 1, Sensor Node 2, Sensor Node 3 and Sensor Node 4) and a central processing unit. When the sensor nodes are first started, they automatically search for other nearby nodes and establish connections with them to form a preliminary network topology. Routing information is exchanged between nodes to ensure that data can be transmitted from the source node to the target node. The central processing unit acts as the gateway of the network, and all data will be transmitted through it. The sensor nodes will automatically search and connect to the central processing unit, or indirectly connect through other nodes. The sensor nodes will collect data regularly according to preset time intervals, such as every minute or every hour. In specific events or conditions, such as earthquakes or strong winds, the nodes will increase the collection frequency to obtain more detailed data. The collected data will first be processed preliminarily inside the node, such as filtering, compression and encryption. Then, the data will be transmitted to the central processing unit through the wireless network, which can be direct transmission or multi-hop transmission.

[0039] The central processing unit will conduct in-depth analysis of the received data, such as trend analysis, anomaly detection and health assessment. The analysis results will be stored in the database and used for subsequent queries and alarms. Users can view monitoring data and analysis results in real time through the web interface or mobile application. The interface provides a variety of charts and models, allowing users to intuitively understand the status of the building.

[0040] When the analysis results show that a parameter exceeds a predetermined threshold, or a potential structural problem is detected, the system will automatically trigger an alarm, which can be sound, light, SMS or email, depending on the user's settings and the severity of the problem. The system will automatically notify relevant personnel, such as maintenance personnel, management or security departments according to the preset notification strategy. The notification can be made by SMS, email or phone to ensure that the problem is handled in a timely manner.

[0041] Through the above-mentioned implementation mode, the present invention ensures real-time, efficient and accurate safety monitoring of buildings, and provides strong technical support for ensuring public safety and extending the service life of buildings. The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A building safety monitoring system based on a wireless sensor network, characterized in that: Includes the following components: Sensor nodes, each sensor node includes: a. At least one physical parameter sensor, such as an accelerometer, a strain gauge, a temperature sensor or a humidity sensor; b. An energy management module to ensure that the node can continue to work without external power supply, where solar panels and batteries are used for energy supply; c. A microprocessor for preliminary processing and analysis of the raw data, thereby reducing the amount of data that needs to be transmitted; d. a wireless communication module to establish connections with other sensor nodes and the central processing unit, wherein the communication module supports self-organizing network formation; Central processing unit for: a. Receive data from each sensor node wirelessly; b. Using advanced algorithms and models, conduct in-depth analysis of the collected data to assess the safety status of the building; c. Automatically trigger an alarm to notify relevant personnel when potential structural problems are detected or parameters exceed predetermined thresholds; A communication module, wherein: a. A self-organizing wireless network is formed between sensor nodes to ensure reliable data transmission in complex building environments and support adaptive routing algorithms; b. Through the Internet or mobile network, users can remotely access the system and view monitoring data and analysis results in real time; User interface with the following features: a. Provide an intuitive graphical interface to display the three-dimensional model of the building and the data of each monitoring point; b. Allow users to query and replay historical monitoring data to analyze the long-term change trend of buildings; c. Allow users to customize the thresholds of monitoring parameters to meet different monitoring needs; Security and encryption mechanisms, including: a. Encryption measures are used during data transmission to ensure the confidentiality of the data; b. Access control, only authenticated users can access the system; c. The storage and transmission of alarm information and monitoring data are protected by strict security measures, including identity authentication, data encryption and data integrity verification.

2. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: The energy management module of the sensor node includes solar panels and batteries to ensure continuous operation without external power supply.

3. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: The data analysis engine includes but is not limited to machine learning, time series analysis and frequency domain analysis, which is used to identify abnormal conditions of buildings. The algorithm can continuously optimize the model based on historical data.

4. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: Alarm systems are automatically triggered to notify appropriate personnel when potential structural issues are detected or parameters exceed pre-determined thresholds.

5. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: The user interface can display changes in monitoring data in real time and provide visualization of data analysis results, including trend graphs, heat maps, and identification of abnormal points.

6. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: The communication module supports multiple communication protocols, including Wi-Fi, Bluetooth, LoRa, etc., to adapt to different communication environments and distance requirements.

7. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: The user interface can be integrated with building management systems to enable intelligent control and predictive maintenance, improving the energy efficiency and safety of buildings.

8. A building safety monitoring system based on a wireless sensor network according to claim 1, characterized in that: Security and encryption mechanisms include regularly updated security protocols and key management to protect the system from potential cyber attacks and data breaches.

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