| Project Overview | This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'Smart agriculture system using IoT and machine learning for crop management'. 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. |
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| Research Paper Title | Smart agriculture system using IoT and machine learning for crop management |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Farm Automation |
| Project Type | IoT + ML Crop Management |
| Required Tools / Software | Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle | Collect sensor data and predict crop/field status for automation support |
| Expected Output | A smart crop management system with ML prediction |
| Possible Add-ons | Add auto-irrigation and fertilizer suggestion |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "Smart agriculture system using IoT and machine learning for crop management" 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.