Proactive Urban Flood Management Through Spatio-Temporal Graph Reasoning
Engineered at Makerere University. Drain is a multi-modal, predictive AI infrastructure that abandons reactive municipal maintenance in favor of real-time visual detection and graph-based flood propagation forecasting.
What is Drain?
Drain is an intelligent urban infrastructure platform built for municipal authorities and environmental engineers. It integrates edge computing and cloud-based deep learning into a centralized Web-GIS dashboard. By fusing lightweight object detection (YOLOv8-Nano) operating at the edge via drones and cameras, semantic understanding (CLIP), and Spatio-Temporal Graph Neural Networks (ST-GNN), the system does not just detect a blocked drain—it predicts how that localized blockage will cascade and flood the interconnected city grid.
Municipal Authorities
Automated alerts and dashboard visualizations for maintenance optimization
Emergency Response Agencies
Data-driven foresight into flood propagation and risk mitigation
Smart City Contractors
Scalable API for integrating environmental telemetry into civic platforms
Lightweight Edge Vision
YOLOv8-Nano for real-time detection on drones and cameras
Semantic Generalization
CLIP alignment for deep contextual understanding
Generative Augmentation
GANs and Diffusion for synthetic training data
Spatio-Temporal Graph
ST-GNN for flood propagation forecasting
The Problem We Solve
Recurring Urban Flooding
Drainage channels choked with solid waste, silt, and vegetation cause catastrophic surface flooding in rapidly expanding cities.
Reactive Maintenance
Current maintenance relies on costly, inefficient manual inspections that only identify blockages after flooding has occurred.
Black-Box Sensors
IoT sensors measure water levels without identifying the cause of obstruction, providing no actionable intelligence.
Our Strategic Market Opportunity
In Kampala and across Sub-Saharan Africa, improper urbanization and poor solid waste management have turned seasonal rains into severe economic and humanitarian threats. Addressing this cannot rely on importing expensive, pre-packaged sensor networks designed for Western topographies.
By engineering Drain locally, we operationalize a "Buy Uganda, Build Uganda" philosophy. We provide a frugal, highly scalable infrastructure that empowers local authorities to manage climate adaptation and urban resilience using homegrown computational intelligence, ensuring data sovereignty and context-aware public administration.
Impact at a Glance
Founders & Strategic Leads
Nabbumba Margaret
Project Visionary, Team Lead & ML Expert
Specializing in YOLO architectures, generative data augmentation, and system pipeline design. Leads the engineering of the Drain detection models.
Ssozi Gloria Edith
Deployment Lead & AI Engineer
Specializing in Spatio-Temporal Graph Neural Networks, MLOps, edge deployment, and Web-GIS dashboard integration.
Dr. Ggaliwango Marvin
Strategic Advisor & AI Mentor
Providing oversight on model optimization, research-to-product commercialization, and responsible AI governance.
Ready to Transform Urban Flood Management?
Join us in building proactive, data-driven resilience for African cities.
Request Dashboard Access
Get real-time, color-coded alerts and dynamic flood risk maps for your municipality.
Get StartedJoin the Municipal Pilot
Participate in our 12-week pilot program and transition from reactive to proactive maintenance.
Learn MorePartner as a Drone/IoT Provider
Supply edge infrastructure for our lightweight YOLOv8-Nano detection models.
Partner Now