Smart Watershed Management Pilot
A 50-node IoT sensor network and Azure ML dashboarding to optimise irrigation and guide community-run check dams across a watershed.
The Challenge
Hardware reliability in the field, data gaps, and adoption of new irrigation practices by farming households.
What We Are Trying To Do
Deploy an IoT sensor network across a watershed and use Azure ML to optimise irrigation scheduling and reduce water usage, alongside community-run check dams and recharge structures.
Who It Serves
5,000 downstream farming households across 10 villages in a critical watershed zone.
Key Activities
- Install 50 IoT rain gauges, soil moisture sensors, and groundwater monitoring nodes
- Build an Azure IoT Hub and ML pipeline for real-time water prediction and alerts
- Create Power BI dashboards for Panchayat water committees and district officials
- Train 20 local water managers in smart irrigation scheduling techniques
- Construct 3 check dams and 10 recharge trenches guided by sensor data
Targets
Water saved
25% reduction in irrigation use (target)
Groundwater rise
+2m in dry season (target)
Crop yield
20% improvement (target)
Water managers trained
20 (target)
Infrastructure built
3 check dams + 10 recharge structures (target)
Training
20 local water managers proposed to be trained in smart irrigation scheduling.
Connects with the Water, Climate & Disaster Resilience and Digital, Technology & AI schools in Learn & Train.
Partnership Opportunities
Microsoft Ask: Azure IoT credits ($40K), AI for Earth Water grant, 10 volunteer IoT/AI engineers, Power BI nonprofit licenses, sensor hardware co-donation.
Discuss This ProgrammeNo verified results have been recorded for this programme yet. Targets above represent proposed goals, not achieved outcomes.