International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 2
March-April 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Agriedge: Lora-based Edge Iot Smart Irrigation System for Precision Agriculture

Author(s) Mr. Amit Kumar Behera, Mr. Dhruv Kumar .
Country India
Abstract Precision agriculture needs irrigation management systems that are reliable and can be de-ployed in remote settings without much infrastructure. Presented in this paper is a multi-sensor Internet-of-Things (IoT)-based smart irrigation monitoring system, leveraging Arduino-based real-time control combined with Raspberry Pi edge computing and long-range LoRa communication. The proposed architecture monitors field conditions continuously by collecting environmental data from various sensors, including soil moisture, temperature, humidity, water level, and turbidity, and makes irrigation decisions based on a threshold-based control mechanism augmented by hysteresis protection. A 72-hour experimental deployment was carried out for system performance evalua-tion, during which, behavioral studies and environmental trends were analyzed based on the data recorded by the environmental sensors. The irrigation cycles are triggered automatically when the soil moisture exceeds the given threshold while other environmental parameters remain stable un-der monitoring. A classification using a Random Forest machine learning algorithm was developed for predicting irrigation requirements, with an overall classification accuracy of approximately 87% and an AUC value of just under 0.90. Communication performance tests exhibited a strong LoRa connectivity and high-performance transmission with Received Signal Strength Indicator (RSSI) values ranging from 33 dBm to 10 dBm and a packet delivery ratio of 98.5%. This architecture is predicated on deterministic microcontroller irrigation control integrated with edge-based analytics, limiting reliance on uninterrupted cloud connectivity yet allowing for monitoring agricultural ac-tivities in real-time. The experiment shows that the system is a scalable and cost-efficient solution to precision irrigation and resource-efficient water management in smart agricultural environments.
Keywords Precision Agriculture, Smart Irrigation, Internet of Things (IoT), Edge Computing, LoRa Communication, Raspberry Pi, Arduino-Based Monitoring, Machine Learning
Field Computer > Electronics
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-03-13
DOI https://doi.org/10.36948/ijfmr.2026.v08i02.71217
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 1Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals