The solution consists of three main components: 1) an IoT sensor network deployed on structures under monitoring, 2) advanced signal and data analysis of incoming sensor data, 3) a software IoT data platform for data displays, maps, analytics, and web/mobile interfaces for user interaction.
Our IoT sensor network nodes involve embedded sensors and processing hardware, including high-accuracy and cost-effective MEMS sensors designed specifically for such sort of monitoring use cases, as well as other sensor hardware for measuring indicators of seismic, weather, and wildfire risks. The sensor node is used for real-time and continuous data collection and data fusion.
Advanced data analysis is our fundamental contribution. We employ techniques such as advanced spectral analysis, digital signal processing, machine-learning and deep-learning AI (artificial intelligence) models for structural health monitoring, change and anomaly detection, predictive maintenance, signal pattern recognition, and damage identification. We provide automatic, real-time, and continuous assessment of structures for their disaster risks and damage, identifying any change over time or any deviation from their nominal behaviour.