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As infrastructure ages, maintaining its integrity becomes more challenging. Aging infrastructure is prone to wear and tear, which can lead to failures and safety hazards. Structural health monitoring systems are essential for assessing the condition of bridges, buildings, dams, and other critical infrastructure to prevent catastrophic failures and ensure public safety. Advancements in environmental monitoring technologies have enhanced the ability to collect and analyze data from various sources. For instance, in November 2023, Arahas and Quakelogic jointly introduced a new Structural Health Monitoring and Early Warning System. This advanced technology is designed to improve safety in earthquake-prone areas of the Indian Subcontinent, representing an important step forward in helping the region prepare for and reduce risks from seismic events.
The integration of AI with Internet of Things (IoT) sensors and remote sensing technologies is on the rise. IoT sensors collect data from various seismic monitoring points, while remote sensing technologies provide additional information on environmental conditions. AI systems integrate and analyze data from these sources to provide a comprehensive view of seismic activity and its impact. AI is increasingly being used to develop predictive and early warning systems for seismic events. Predictive models use AI to analyze historical and real-time data, forecasting potential earthquakes and volcanic activity. Early warning systems leverage AI to provide advance notifications of seismic events, allowing for timely evacuation and preparedness measures.
For instance, In June 2023, Nanometrics unveiled a major enhancement in passive seismic monitoring with the launch of its next-generation AI-powered automated event detection engine. This advancement in seismic data analysis offers improved accuracy, accelerated processing, and more detailed seismic event catalogues.