Smart Water Management Solution for Sustainability
AquaSense is a MVP for a smart water management mobile application designed to address global water scarcity, leakage, and pollution challenges. It leverages Artificial Intelligence (AI) and the Internet of Things (IoT) to assist homeowners and organizations in:
- Real-time leak detection in looped and branched water distribution networks
- Water quality prediction and analysis
- Smart consumption monitoring and forecasting
- Community-driven water resource mapping
- Access the latest news and helps them to save and manage water.
- Implemented RESTful APIs with Express.js for mobile app communication
- Created basic authentication with JWT
- Optimized MongoDB schemas for high-performance querying of time-series data
| Feature | Technology | My Role |
|---|---|---|
| Water Leak Detection | DNN with TensorFlow | Model training & API deployment |
| Water Potability Prediction | Random Forest (Scikit-learn) | Feature engineering & deployment |
| Water Quality Analysis | Deep Neural Networks | Model development & optimization |
| Tank Level Monitoring | LSTM Time Series | Sequence modeling & real-time API |
| Consumption Prediction | LSTM Forecasting | Data pipeline & model serving |
| Water Sources Map | MongoDB Geospatial queries | Database design & API development |
| Model | Accuracy/Loss | Technology | Implementation Details |
|---|---|---|---|
| Leak Detection (Pressure) | 98% (branched), 94% (looped) | DNN + TensorFlow | Real-time sensor data processing |
| Leak Detection (Sound) | 99% (branched), 91% (looped) | DNN + Audio Processing | Hydrophone data analysis |
| Water Potability | 89% | Random Forest | Chemical parameter analysis |
| Water Quality | 94.5% | DNN | Multi-element concentration prediction |
| Tank Level | Loss: 0.0649 | LSTM | Time series forecasting |
| Consumption | Loss: 1.6708 | LSTM | User behavior pattern analysis |
- Node.js: API server with Express.js
- MongoDB: NoSQL database with geospatial indexing
- TensorFlow/TensorFlow.js/Keras: Deep learning model development
- Scikit-learn: Traditional ML algorithms
- Pandas/NumPy: Data preprocessing and analysis
- Google Maps API: Geospatial mapping and routing
- Google Search API: Water news aggregation
Comprehensive Solution: End-to-end water management with 6 integrated AI features
High Accuracy Models: Industry-leading accuracy rates for critical predictions
Real-time Processing: Instant leak detection and quality analysis
First in Region: Unique water mapping feature for Middle East
Cost Reduction: 20-30% reduction in water bills through leak prevention
Sustainability: Supports Vision 2030 goals for water conservation
Proactive Management: Early warning systems prevent infrastructure damage
Community Building: User-contributed water map fosters collaboration
- Backend Source Code: AquaSense Backend
- Frontend Source Code: AquaSense Frontend
- AI Models & Datasets: Water AI Models
