| Project Overview | This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'AI-Enabled Water Quality Monitoring for Agricultural Applications'. The project connects agricultural engineering with artificial intelligence, machine learning, deep learning, IoT, computer vision, drone analytics, or RAG-style decision support. Students can use the linked 2023-onward paper/source as the academic base and convert it into an implementation-focused final-year project with sensors, datasets, dashboards, mobile/web interfaces, prediction models, or prototype automation. |
|---|---|
| Research Paper Title | AI-Enabled Water Quality Monitoring for Agricultural Applications |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Water Management Projects |
| Project Type | Water Quality AI |
| Required Tools / Software | Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle | Use sensor readings and ML to classify irrigation water quality |
| Expected Output | A water quality monitoring and alert system |
| Possible Add-ons | Add pH/TDS/EC sensor integration |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "AI-Enabled Water Quality Monitoring for Agricultural Applications" in "Agricultural Engineering" |
This B.Tech agricultural engineering project resource helps students connect a recent AI-based research direction with a practical implementation plan, tools, expected output, and possible extensions.