Sahyadri-Siri: An AI-Powered Environmental Intelligence Platform for Water Quality Monitoring in the Western Ghats

Sahyadri-Siri is a community-driven environmental intelligence platform integrating Android development, generative AI, computer vision, geospatial analysis, and cloud infrastructure. It aims to address water quality monitoring issues in the Western Ghats, enabling real-time monitoring and intelligent analysis, and empowering communities to participate in environmental governance.

The Western Ghats are a biodiversity hotspot in India (with over 7400 vascular plant species, nearly 1/3 of which are endemic, and habitats for endangered species). They are also the source of major rivers like the Godavari, providing water to downstream areas. However, they face threats such as industrial/domestic sewage discharge, agricultural non-point source pollution, mining damage, and climate change. Traditional monitoring relies on manual sampling and laboratory analysis, which has long cycles and limited coverage, making it difficult to respond in real time. Community participation is key, but the lack of professional equipment and training limits their ability to participate.

It adopts a layered architecture (data collection layer: mobile app + low-cost sensors; edge processing layer: preliminary processing on the device; cloud analysis layer: in-depth AI analysis; application display layer: intuitive interface). The mobile app supports manual input, photo visual analysis, Bluetooth sensor data collection (pH, turbidity, etc.), and integrates GPS. The backend uses cloud microservices and multi-database storage. Computer vision uses CNN to identify visual features of water quality (color, floating objects), with mobile optimization (quantization, pruning) to achieve real-time inference. Generative AI generates natural language reports, personalized recommendations, and educational content. Geospatial analysis uses GIS visualization (heat maps, time-series animations), watershed analysis, and spatial interpolation to fill monitoring gaps.

The core is community participation, with incentive mechanisms (points, badges, leaderboards) designed to encourage contributions. Data quality control is achieved through multiple verifications (multi-report checks, expert reviews, sensor cross-validation, anomaly detection). Privacy protection supports anonymity and location obfuscation. Cooperation with environmental organizations, governments, and research institutions allows data to be used for law enforcement, research, and advocacy.

Real-time monitoring shortens pollution response time; historical data supports trend analysis and policy evaluation; spatial data guides resource allocation. Community empowerment transforms citizens from information recipients to guardians, enhancing environmental awareness; crowdsourced data provides high-density input for scientific research, accelerating scientific discoveries.

Sahyadri-Siri combines technological innovation (AI, mobile computing) with social innovation (citizen science) to provide a new tool for the protection of the Western Ghats. Technology is an enabling means aimed at supporting decision-making and promoting sustainable development, and we look forward to a more intelligent and participatory future of environmental governance.

Expand to air quality, noise, and biodiversity monitoring; promote cross-watershed collaboration and establish a standardized data network; integrate climate adaptation strategies to support risk assessment and adaptation investment; continuously optimize model fairness and system reliability.