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1.3 million household fires, 3,400 civilian deaths, and 23 billion dollars indamage, a fire department is called to respond every 24 seconds. Manyfirefighters are injured during search and rescue operations due to hiddendangers. Additionally, fire-retardant water runoff pollution can threaten humanhealth. My goal is to develop a system to monitor calamity-induced environmentdamage to provide early-intelligence to incident-commanders. I have developed amulti-spectral sensing system to inspect air and water quality for safer andaccessible hazardous environment operations. Key components include a) dronemounted with four sensors (gas sensors, thermal camera, GPS sensor, visualcamera) and wireless communicator for inspection, b) AI-powered computer visionbase-station to identify targets, c) low-cost, portable, spectral water qualityanalyzer and d) robotic retriever. The prototype demonstrates the potential forsafer and more accessible search and rescue operations for fire-fighters andscientists. The gas sensor could identify thick smoke situations (thresholds >400). The visual and thermal cameras detected hidden hot objects and sentimages to AI-powered analyzer to identify and localize target with rescue GPScoordinates for robotic retrieval. Water quality was analyzed with spectralsignatures to indicate turbidity levels that correlate with potentialpollutants (threshold > 1.3). Prototype results were shown to the Sunnyvalefire department and received encouraging feedback. Future goals includemonitoring firefighter health and overexertion with smart clothes.

An early warning AI-powered portable system to reduce workload and inspect environmental damage after natural disasters