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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 187 - Issue 120 |
| Published: June 2026 |
| Authors: Aiman Sultan Al Noamani, Hamad Anisul Hoque, Mohammad Nasar |
10.5120/ijca3652cec63b96
|
Aiman Sultan Al Noamani, Hamad Anisul Hoque, Mohammad Nasar . IoT-Enabled Smart Geofencing System for Sustainable Livestock Monitoring. International Journal of Computer Applications. 187, 120 (June 2026), 20-27. DOI=10.5120/ijca3652cec63b96
@article{ 10.5120/ijca3652cec63b96,
author = { Aiman Sultan Al Noamani,Hamad Anisul Hoque,Mohammad Nasar },
title = { IoT-Enabled Smart Geofencing System for Sustainable Livestock Monitoring },
journal = { International Journal of Computer Applications },
year = { 2026 },
volume = { 187 },
number = { 120 },
pages = { 20-27 },
doi = { 10.5120/ijca3652cec63b96 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2026
%A Aiman Sultan Al Noamani
%A Hamad Anisul Hoque
%A Mohammad Nasar
%T IoT-Enabled Smart Geofencing System for Sustainable Livestock Monitoring%T
%J International Journal of Computer Applications
%V 187
%N 120
%P 20-27
%R 10.5120/ijca3652cec63b96
%I Foundation of Computer Science (FCS), NY, USA
With the ever-evolving Internet of Things (IoT) technologies, modern agriculture has seen a dramatic change in practices, and solutions for intelligent and automated livestock management are becoming a reality. Poorly designed traditional physical fencing in livestock production systems can be expensive, inflexible, and require constant upkeep and maintenance, and can cause environmental issues, including overgrazing and poor land use. To overcome these drawbacks, in this study, a smart geofencing system based on wireless communication, GPS location tracking, and cloud-assisted monitoring technologies is proposed and applied to the field of sustainable livestock monitoring. The proposed system involves connecting a NEO-6M GPS module, an ESP8266 microcontroller, a water sensor, a relay module, an LCD screen, and a cloud-based platform called Blynk. As soon as an animal enters the predefined geofence area, the system notifies the farmer using wireless communication and sends an alert. Moreover, the built-in environmental sensing mechanism ensures livestock safety by monitoring the surrounding environment. The proposed framework will help minimize reliance on physical fencing and increase the efficiency of operations, safety of livestock, environmental sustainability, and remote access of farmers. The experimental results indicate that the location monitoring is accurate, the deployment is economical, and the alerts are issued in real time, which is suitable for smart agriculture applications. In addition, this study covers the limitations of the system, connectivity requirements, and future enhancements, including the use of artificial intelligence, LoRaWAN communication, and predictive solutions for livestock analytics, for future precision farming systems.