Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63196
Volume:
10 |
5 |
May 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Electronics and communications engineering
Sri Siddhartha Institute of Technology

Electronics and communications engineering
Sri Siddhartha Institute of Technology

Electronics and communications engineering
Sri Siddhartha Institute of Technology

Electronics and communications engineering
Sri Siddhartha Institute of Technology

Electronics and communications engineering
Sri Siddhartha Institute of Technology
This project presents a GPS-based health alert system for livestock herd monitoring using Internet of Things (IoT), embedded systems, and wireless communication technologies. Managing large livestock herds in remote and wide geographical areas using traditional methods is difficult, labor-intensive, and often ineffective. Farmers frequently face problems such as delayed disease detection, animal theft, wandering livestock, and lack of real-time monitoring, which lead to economic losses and reduced farm productivity. To overcome these challenges, the proposed system introduces a wearable smart neckband integrated with sensors such as GPS module, temperature sensor, and accelerometer. The system is built around the ESP32 microcontroller, which processes real-time data and enables wireless communication through Wi-Fi/GSM technology. The temperature sensor continuously monitors the body temperature of livestock, while the accelerometer tracks animal movement and activity patterns. The GPS module provides live location tracking and geofencing functionality. The collected sensor data is continuously compared with predefined threshold values to identify abnormal conditions such as fever, prolonged inactivity, or movement outside the predefined geographical boundary. Whenever an abnormal condition is detected, the system immediately generates an alert and sends the real-time location and health information to the farmer through a Telegram bot or mobile monitoring interface. The system operates using a rechargeable Li-ion battery, making it portable and suitable for remote environments. The proposed model provides an efficient, low-cost, and reliable solution for smart livestock monitoring and helps improve livestock safety, productivity, and farm management.
KEYWORDS
• Dairy farm livestock monitoring. • Sheep and goat farm management. • Smart agriculture and precision farming systems. • Veterinary health monitoring applications. • Large cattle ranches and grazing fields. • Livestock theft prevention systems. • Remote animal tracking and monitoring. • Research applications in animal behavior analysis. • Automated farm management systems. such as fever, prolonged inactivity, or geofence violations are detected, the system immediately generates alert notifications and transmits them to the farmer through a Telegram-based mobile interface. This allows farmers to take quick action and prevent livestock losses. The implementation results prove that the integration of IoT and wearable sensor technologies can provide an efficient, reliable, and low-cost solution for modern livestock management. The proposed system significantly improves livestock safety, reduces manual effort, enhances farm productivity, and supports precision farming practices. Furthermore, the developed system is portable, scalable, and suitable for deployment in remote agricultural environments. Future enhancements may include machine learning-based disease prediction, cloud-based analytics, solar-powered battery systems, and large-scale smart agriculture integration to further improve system performance and reliability.
[1] Bhatla, Y. B. Kikani, D. G. Joshi, R. Jain, and K. Patel , “Real Time Cattle Health Monitoring Using IoT, ThingSpeak and Mobile App,” Journal of Engineering & Applied Sciences, 2023. [2] S. Montalván, P. Arcos, P. Sarzosa, R. A. Rocha, and Y. Kim , “Technologies and Solutions for Cattle Tracking: A Review,” Sensors, vol.24, no.19, 2024. [3] S. Nyamuryekung’e, “Precision livestock management in the Internet of Things era,” Computers and Electronics in Agriculture, 2024. [4] M. Modak, M. M. Pritom, S. C. Banik, Md. S. Rabbi, “Internet of Things-Based Health Surveillance Systems for Livestock: A Review of Recent Advances and Challenges,” IET Wireless Systems, (or similar) Jul 2025. [5] Lukas Schulthess, Fabrice Longchamp, Christian Vogt, Michele Magno, “A LoRa-Based and Maintenance-Free Cattle Monitoring System for Alpine Pastures and Remote Locations,” arXiv preprint, Jun 2024. [6] Hitesh Mohapatra, “A LoRa IoT Framework with Machine Learning for Remote Livestock Monitoring in Smart Agriculture,” arXiv preprint, Sep 2025. [7] D. Dhakshinamoorthy, A. Jha, S. Majumdar, D. Ghosh, R. Chakraborty, and H. Ray, “Classification of Cattle Behaviour and Detection of Heat (Estrus) using Sensor Data,” arXiv preprint, Jun 2025. [8] M. Lamanna, M. Bovo, and D. Cavallini,“Wearable Collar Technologies for Dairy Cows,” 2025. [9] S. R. Vanga, N. R. Thontla, and H. C. Bolla, “Smart Cattle Health Monitoring: A Heat Stress Management System,” 6th International Conference for Emerging Technology (INCET), Belgaum, India, 2025. [10] D. Kaur & A. K. Virk, “Smart Neck Collar: IoT-based Disease Detection and Health Monitoring for Dairy Cows,” Internet of Things, vol. 5, article 12, 2025.
Publication Date
5/14/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...