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Project Overview
To enhance river water quality assessment and management, an intelligent AI-Powered Water Quality Index (WQI) system was developed for WARPO. The system analyzes real-time and laboratory input data from four major rivers around Dhaka City and automatically generates a comprehensive Water Quality Index for evidence-based planning and water resource management.
Challenges
Traditional water quality evaluation depended on fragmented manual lab reporting and lacked consistent temporal and spatial analysis. Decision-makers required a unified tool that combines field sensing, laboratory results, and advanced analytics into a reliable, actionable water quality score.
Solution
We designed and implemented a scalable, hybrid data collection and AI processing pipeline that enables WARPO administrators to systematically input 18 critical water quality parameters—such as BOD, COD, DO, E. coli, and others—at defined time intervals.
Key features include:
IoT Integration: Direct interfacing with remote IoT sensors capturing in-field measurements.
Manual Data Input: Upload of laboratory test results for parameters not available via sensors.
AI-Driven WQI Calculator: Custom AI model that processes inputs and calculates the standardized Water Quality Index automatically.
Geospatial Dashboard: A centralized visualization platform for mapping trends, comparing rivers, and monitoring changes in water quality over time.
Dashboard & Monitoring
The integrated dashboard provides WARPO officials with:
Real-time and historical index values per river
Geospatial visualization of river health
Interactive graphs showing parameter trends
Exportable reports for policy and compliance review
This enhances transparency, supports early detection of pollution events, and strengthens sustainable water management practices.
Impact & Outcomes
Transformed raw field and lab data into a clear, unified Water Quality Index.
Eliminated manual index calculation and reporting delays.
Enabled nuanced river-by-river comparison for environmental planning.
Supported cross-agency communication with visual data insights.
Conclusion
The AI-Powered Water Quality Index System demonstrates advanced integration of IoT, manual lab data, and AI analytics—giving WARPO a robust tool to monitor and manage river health in Dhaka City with accuracy, consistency, and actionable insights.
