| Project Overview | This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'AI and IoT Enabled Smart Greenhouse Monitoring and Control System'. 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 | AI and IoT Enabled Smart Greenhouse Monitoring and Control System |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Farm Automation |
| Project Type | Smart Greenhouse |
| Required Tools / Software | Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle | Monitor temperature, humidity, soil moisture and automate control actions |
| Expected Output | A smart greenhouse automation prototype |
| Possible Add-ons | Add ML-based climate prediction and actuator control |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "AI and IoT Enabled Smart Greenhouse Monitoring and Control System" 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.