India faces a growing range of environmental and climate-related risks including urban flooding, river floods, cyclones, forest fires, air pollution, droughts, landslides, and extreme weather events. Floods remain among the most frequent disasters across states such as Assam, Bihar, Kerala, and Maharashtra, while forest fires increasingly affect Uttarakhand, Himachal Pradesh, and central Indian forests. Air pollution continues to effect major urban centers, and climate change is increasing the f
Design an Environmental Intelligence Network, a distributed system of interconnected AI-powered sensor nodes deployable across cities, rivers, forests, industrial zones, and vulnerable communities.
India faces a growing range of environmental and climate-related risks including urban flooding, river floods, cyclones, forest fires, air pollution, droughts, landslides, and extreme weather events Floods remain among the most frequent disasters across states such as Assam, Bihar, Kerala, and Maharashtra, while forest fires increasingly affect Uttarakhand, Himachal Pradesh, and central... Air pollution continues to effect major urban centers, and climate change is increasing the f
Design an Environmental Intelligence Network, a distributed system of interconnected AI-powered sensor nodes deployable across cities, rivers, forests, industrial zones, and vulnerable communities. Each node should use local (on device) AI inference to continuously monitor environmental conditions and identify emerging risks such as: • Rising water levels and flash flooding • Forest fires and smoke events • Hazardous air pollution • Extreme heat conditions • Landslide precursors • Industrial emissions or chemical leaks • Water quality degradation The sensor network should process data locally to reduce latency, minimize bandwidth requirements, and continue operating even during network outages. Only critical alerts, summarized insights, and risk assessments should be transmitted to regiona