Smart Irrigation Management Using Deep Learning and IoT Sensors — Project Overview
| Project Overview |
This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'Smart Irrigation Management Using Deep Learning and IoT Sensors'. 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 |
Smart Irrigation Management Using Deep Learning and IoT Sensors |
| Research Paper / PDF Link |
Open Paper / PDF |
| Year |
2024 |
| Project Area |
Smart Irrigation Systems |
| Project Type |
Deep Learning Irrigation |
| Required Tools / Software |
Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle |
Use deep learning on time-series sensor data to automate irrigation scheduling |
| Expected Output |
A smart irrigation dashboard with predicted pump ON/OFF status |
| Possible Add-ons |
Add rainfall API and battery monitoring |
| Get Help |
Get Help on WhatsApp
Message: Hi FE, I need help with "Smart Irrigation Management Using Deep Learning and IoT Sensors" in "Agricultural Engineering"
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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.
