Water-Efficient Irrigation Scheduling Using Machine Learning and Weather Forecasting — Project Overview
| Project Overview |
This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'Water-Efficient Irrigation Scheduling Using Machine Learning and Weather Forecasting'. 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 |
Water-Efficient Irrigation Scheduling Using Machine Learning and Weather Forecasting |
| Research Paper / PDF Link |
Open Paper / PDF |
| Year |
2024 |
| Project Area |
Smart Irrigation Systems |
| Project Type |
Water Optimization |
| Required Tools / Software |
Arduino/ESP32, soil moisture sensor, DHT sensor, relay module, Python/Flask, Firebase/MySQL, ML model |
| Main Features / Working Principle |
Combine soil and weather data to recommend water-efficient irrigation schedules |
| Expected Output |
A water-saving irrigation scheduler |
| Possible Add-ons |
Add expected water saving percentage |
| Get Help |
Get Help on WhatsApp
Message: Hi FE, I need help with "Water-Efficient Irrigation Scheduling Using Machine Learning and Weather Forecasting" 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.
