Empowering Agriculture with Real-Time IoT Monitoring
The paper deals with the development of Internet of Things (IoT) which is transforming our day-to-day life. The smart irrigation system developed utilizing the Arduino IDE platform, guarantees smooth Internet of Things connectivity, permitting remote monitoring and management of irrigation procedures in real time. The system continuously monitors soil and environmental parameters by integrating an Arduino UNO microcontroller with a DHT11 humidity sensor and a soil moisture sensor. The water pump is turned on by a relay module to automate irrigation when the soil moisture content falls below a set level. Furthermore, a real-time sensor data monitoring LED display is included on-site, allowing customers to examine current conditions right there at the place. Users now have the flexibility to remotely monitor and modify irrigation settings worldwide because to the Internet of Things capacity. In order to address both over- and under-irrigation, the system maximizes water utilization, automates water distribution, and effectively manages water reserves based on real-time data. This technique works well with drip, sprinkler, and surface irrigation systems. It is especially helpful in places where 2G connectivity is scarce, such poor countries. This adaptable and scalable technology increases agricultural output and functions as a vital instrument for contemporary precision agriculture across a variety of geographic regions by preserving water, cutting waste, and improving network stability. By addressing critical challenges in modern irrigation, this technology promotes water conservation, making it a valuable tool for sustainable agriculture.
Authors
- Pranav Adithya
- Shankar Nalinakshan (ORCID: https://orcid.org/0000-0003-4114-8055)
- Saurabh Tiwari (ORCID: https://orcid.org/0000-0001-7963-453X)
- K R Jayasree
- Abhaykrishnan Namboothiri P J
- Malavika Sreejith
- R Krishnaj
Institutions
- Amrita Vishwa Vidyapeetham (IN)
Publication Details
- Published
- 2025-02-07
- DOI
- https://doi.org/10.1109/etis64005.2025.10961073
- Citations
- 2
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 3.50