Speakers from the world's largest organizations will share their needs and experiences with many world first announcements. Learn of the requirements and case studies from end users and hear all about the latest innovations from companies across the value chain.
The capability of cost-effective and efficient building safety assessment after natural hazards and disasters or cyber-attacks has an immediate and quantifiable impact on minimizing the operational interruptions or loss-of-service within infrastructure. It maximizes human safety and quality of life following disruptive events. A robust, cost-effective, electromagnetic-interference (EMI)-immune, and reliable sensor system combined with advanced machine learning (ML) and artificial intelligence (AI) methodologies for damage identification and building and occupancy safety assessment are essential parts of an effective disaster recovery framework and system. IFOS is developing solutions for "smart buildings" based on its photonic sensing technology portfolio. Multiple, low-cost, distributed optical strain and temperature sensor arrays and acoustic emissions (AE) sensing arrays provide simultaneous static and dynamic measurements for structural performance and reliability assessment. Data is collected and processed by a high-bandwidth, small footprint, photonic data acquisition system based on the IFOS' patented photonic spectral processor (PSP) and state-of-art industrial embedded micro-processor technologies. The application of advanced ML and AI methodologies for damage identification and building occupancy safety assessment provide actionable condition and prognostics data to safety officials and civil engineers. Commercial applications include cost-effective monitoring of smart buildings and their safety assessment. Variants of the proposed platform could be used to monitor the health of other components of other infrastructure such as power generation and distribution networks and intelligent transportation systems.
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