Climate Adaptive IoT Drip Irrigation System
| dc.contributor.author | Sankalpa Kashyap 1NH22CE048 Mrinank Kumar Saini 1NH22CE030 Jaydeep Mukharjee 1NH22EC066 Kiran Ghosh 1NH22EC076 | |
| dc.date.accessioned | 2026-02-06T05:51:05Z | |
| dc.date.available | 2026-02-06T05:51:05Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | Agriculture today faces growing challenges due to erratic weather conditions, water scarcity, and inefficient irrigation methods. Most conventional systems follow fixed irrigation schedules or manual operation, which often results in over-irrigation, increased labour, and suboptimal crop performance. To overcome these limitations, our project—Climate-Adaptive IoT Drip Irrigation System—aims to design a real-time, intelligent irrigation solution that adapts based on soil conditions and weather forecasts. The system integrates soil moisture sensors to continuously monitor field conditions. A microcontroller-based control unit processes this data and makes irrigation decisions dynamically. Instead of using ESP32, an alternative microcontroller suited for stable connectivity and modular expansion has been implemented to support multiple sensor inputs and control components. To avoid unnecessary irrigation, the system fetches real-time weather forecasts from the OpenWeatherMap API, delaying irrigation when rain is expected. For data communication, we use the MQTT (Message Queuing Telemetry Transport) protocol—a lightweight and efficient IoT protocol that allows real-time transmission of sensor data and control commands. The microcontroller publishes the data to a cloud server, where it is stored and displayed through a custom web dashboard. The dashboard provides users with access to live soil conditions, system status, and irrigation history, along with manual override features for better user control. This is an interdisciplinary project, with contributions from both Electronics and Communication Engineering (ECE) and Computer Engineering (CE) domains. The ECE team handled sensor calibration, hardware interfacing, and relay-based control of solenoid valves for drip irrigation. Meanwhile, the CE team focused on backend development, API integration, cloud database setup, and dashboard design, ensuring smooth real-time monitoring and user interaction. | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/20931 | |
| dc.language.iso | en | |
| dc.publisher | New Horizon College of Engineering | |
| dc.title | Climate Adaptive IoT Drip Irrigation System | |
| dc.type | Learning Object |