IOT Based Animal Health Monitoring System

Authors

  • Dr. Pradeep N. Fale Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author
  • Prof. Rachana Kurehekar Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author
  • Shraddha Marsattiwar Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author
  • Gayatri Nikame Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author
  • Kasturi Deogirkar Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author
  • Abhay Badwaik Priyadarshini College of Engineering, Nagpur, Maharashtra, India Author

DOI:

https://doi.org/10.32628/IJSRSET

Keywords:

GPS, Internet of Things, WiFi, Farm Animal Tracking System

Abstract

Animals are an essential part of the ecosystem, but their lives are now in danger. It is common for animals to roam freely in the farm, but if any accidents occur, such as physical injuries or illnesses, the farmer may not be able to determine the exact location of the animal. The Farm Animal Tracking System (FATS) project is a pioneering initiative designed to revolutionize livestock management within agricultural contexts by leveraging state-of-the-art tracking technologies. Animal Tracking System has implemented the use of GPS technology and the Internet of Things (IoT) to monitor and track farm animals, and sensors to collect real-time data on the location, behaviour, and vital signs of individual animals. This information is then processed through a centralized platform, providing farmers with valuable insights into herd dynamics, grazing patterns, and overall animal well-being. This paper outlines the application and use of these technologies. The primary goal of this project is to create a cost-effective solution to monitor a herd as a whole. The solution is an Internet of Things (IoT) based system, where some animals in the herd are equipped with GPS collars that are connected to the WiFi network.

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References

Kataria, B., Jethva, H.B., Shinde, P.V., Banait, S.S., Shaikh, F., Ajani, S. (2023). SLDEB: Design of a secure and lightweight dynamic encryption bio-inspired model for IoT networks. International Journal of Safety and Security Engineering, Vol. 13, No. 2, pp. 325-331. https://doi.org/10.18280/ijsse.130214

Shivadekar, S., Kataria, B., Limkar, S. et al. Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08709-5

Shivadekar, S., Kataria, B., Hundekari, S. ., Kirti Wanjale, Balpande, V. P., & Suryawanshi, R. . (2023). Deep Learning Based Image Classification of Lungs Radiography for Detecting COVID-19 using a Deep CNN and ResNet 50. International Journal of Intelligent Systems and Applications in Engineering, 11(1s), 241–250. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2499.

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Sanskrit Manuscripts Using Convolution Neural Networks, Webology, ISSN: 1735-188X, Volume 18 Issue 5, October-2021, pp. 403-424. Available at https://www.webology.org/abstract.php?id=1681

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Indian Language Manuscripts using Convolutional Neural Networks. Design Engineering, 2021(3), 894-911. doi : https://doi.org/10.17762/de.v2021i3.7789

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2020). Sanskrit Character Recognition using Convolutional Neural Networks : A Survey. International Journal of Advanced Science and Technology, 29(7), 1059 – 1071, May 2020. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/15068

Bhavesh Kataria, Dr. Harikrishna B. Jethva, "CNN-Bidirectional LSTM Based Optical Character Recognition of Sanskrit Manuscripts : A Comprehensive Systematic Literature Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology , ISSN : 2456-3307, Volume 5, Issue 2, pp.1362-1383, March-April-2019. Available at doi : https://doi.org/10.32628/cseit2064126

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Published

20-05-2024

Issue

Section

Research Articles

How to Cite

[1]
Dr. Pradeep N. Fale, Prof. Rachana Kurehekar, Shraddha Marsattiwar, Gayatri Nikame, Kasturi Deogirkar, and Abhay Badwaik, “IOT Based Animal Health Monitoring System”, Int J Sci Res Sci Eng Technol, vol. 11, no. 3, pp. 149–157, May 2024, doi: 10.32628/IJSRSET.

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