  1.3 million household fires, 3,400 civilian deaths, and 23 billion dollars in
damage, a fire department is called to respond every 24 seconds. Many
firefighters are injured during search and rescue operations due to hidden
dangers. Additionally, fire-retardant water runoff pollution can threaten human
health. My goal is to develop a system to monitor calamity-induced environment
damage to provide early-intelligence to incident-commanders. I have developed a
multi-spectral sensing system to inspect air and water quality for safer and
accessible hazardous environment operations. Key components include a) drone
mounted with four sensors (gas sensors, thermal camera, GPS sensor, visual
camera) and wireless communicator for inspection, b) AI-powered computer vision
base-station to identify targets, c) low-cost, portable, spectral water quality
analyzer and d) robotic retriever. The prototype demonstrates the potential for
safer and more accessible search and rescue operations for fire-fighters and
scientists. The gas sensor could identify thick smoke situations (thresholds >
400). The visual and thermal cameras detected hidden hot objects and sent
images to AI-powered analyzer to identify and localize target with rescue GPS
coordinates for robotic retrieval. Water quality was analyzed with spectral
signatures to indicate turbidity levels that correlate with potential
pollutants (threshold > 1.3). Prototype results were shown to the Sunnyvale
fire department and received encouraging feedback. Future goals include
monitoring firefighter health and overexertion with smart clothes.
