| Project Overview | This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'Smart farming using IoT for efficient crop growth'. 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 farming using IoT for efficient crop growth |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2023 |
| Project Area | Farm Automation |
| Project Type | IoT Farm Automation |
| Required Tools / Software | Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle | Use IoT sensor data to automate crop-growth monitoring and irrigation decisions |
| Expected Output | A smart farming dashboard with sensor readings and decision output |
| Possible Add-ons | Add mobile app and cloud database |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "Smart farming using IoT for efficient crop growth" 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.