STRUCTURAL HEALTH MONITORING USING IOT FOR BUILDING COLLAPSE DETECTION

In the construction industry, maintaining structural integrity is pivotal for safety, efficiency, and economic viability. Traditional inspection methods, often sporadic and reliant on visual assessments, can overlook critical issues, especially in challenging environments where access is restricted or hazardous. The integration of IoT (Internet of Things) technology has revolutionized structural health monitoring by enabling continuous, remote data collection and analysis through sophisticated sensor networks. These networks, comprising wireless sensors strategically placed across buildings or infrastructure, monitor a range of parameters including temperature, humidity, light levels, vibration, and structural strain. This real-time data is transmitted wirelessly to central hubs or gateways, typically utilizing cost-effective solutions like Raspberry Pi devices programmed with Python for efficient data management. The collected data is then processed and stored in cloud servers, leveraging the scalability and accessibility of cloud computing to facilitate advanced signal processing and analysis. MATLAB is utilized for its robust capabilities in numerical computing and visualization, presenting the data in graphical formats that highlight trends, anomalies, and potential deterioration patterns. Crucially, this system incorporates an alert mechanism, notifying stakeholders via email of critical sensor readings or emerging issues, enabling swift responses to prevent accidents or structural failures. The adoption of IoT-enabled structural health monitoring offers multifaceted benefits to the construction industry and broader economic landscape. By continuously monitoring infrastructure health, this approach allows for early detection of defects or wear, facilitating proactive maintenance interventions that can significantly extend the service life of buildings and infrastructure. This proactive maintenance not only enhances safety and reliability but also reduces long-t