Equinoct integrates AI and ML with community-sourced data to provide real-time monitoring and early warnings of climate change hazards.

Results to date: The flood monitoring and forecasting system has been piloted in the last two years with various community organizations. The solution engages women, children and students who collected household data through manual gauges, the system could monitor occurrence events in the river basin to alert local authorities. Strong local partnerships have been established for data generation and to develop tailored adaptation strategies. 

Workplan: Expanding the system and integrating advanced features supported by AI and ML algorithms would facilitate piloting the product in different areas, engaging additional local communities. The primary goal during the investment period is to develop these components, attract more users, and enhance the captured data to train the ML model.

Investment rationale: Equinoct works around multiple priorities for UNICEF, such as ensuring citizen engagement, implementing flood detection and early warning systems, and enabling incident reporting at the community level. The underlying frontier technology could also be used for alternate programmatic purposes.