| Project Overview | This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'A Smart Irrigation System Using the IoT and Machine Learning'. 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 | A Smart Irrigation System Using the IoT and Machine Learning |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Water Management Projects |
| Project Type | IoT Water Control |
| Required Tools / Software | Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle | Use soil/weather data to automate water-control decisions |
| Expected Output | A prototype for automated water management in fields |
| Possible Add-ons | Add pump scheduling and leakage alert |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "A Smart Irrigation System Using the IoT and Machine Learning" 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.