ANIMAL HEALTH MONITORING WITH MISSING AND THEFT PREVENTION DEVICE USING WIRELESS SENSOR NETWORK AND INTERNET OF THINGS
DOI:
https://doi.org/10.29284/ijasis.6.1.2020.38-44Keywords:
animal health monitoring, internet of things, IoT, WSN, animal missing, theft prevention.Abstract
A device to know the health status of all the animals in a farm along with its missing and theft prevention is proposed in this article. The necessary sensors to sense the health information of animals and the short range wireless communication technology and internet to communicate with the owner of the farm, are planned to use in the devices. This system will be very helpful to diagnose the health condition of all the animals simultaneously and to improve it. The system can prevent the animals from missing or theft. A mobile application which acts as a user interface provides the owner with useful information such as animal’s body temperature, heart rate, rumination and their presence inside the farm. The prototype of this idea is developed and is included for testing. Since the animal health status can be monitored from anywhere in world using a mobile application, the device will ease the work of farm owner and the laborers.
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References
A. Kumar & G.P. Hancke, “A Zigbee-Based Animal Health Monitoring System”, IEEE Sensors Journal, Vol. 15, No. 1, 2014, pp. 610-617.
H. Wang, A.O. Fapojuwo & R.J. Davies, “A Wireless Sensor Network for Feedlot Animal Health Monitoring”, IEEE Sensors Journal, Vol. 16, No. 16, 2016, pp. 6433-6446.
S.G. Matthews, A.L. Miller, J. Clapp, T. Plötz & I. Kyriazakis, “Early Detection of Health and Welfare Compromises Through Automated Detection of Behavioural Changes in Pigs”, The Veterinary Journal, Vol. 217, 2016, pp. 43-51.
R. Brugarolas, T. Latif, J. Dieffenderfer, K. Walker, S. Yuschak, B.L. Sherman, ... & A. Bozkurt, “Wearable Heart Rate Sensor Systems for Wireless Canine Health Monitoring”, IEEE Sensors Journal, Vol. 16, No. 10, 2015, pp. 3454-3464.
S. Sargolzaei, H. Elahi, A. Sokoloff & M. Ghovanloo, “A Dual-Mode Magnetic–Acoustic System for Monitoring Fluid Intake Behavior in Animals”, IEEE Transactions on Biomedical Engineering, Vol. 64, No. 9, 2016, pp. 2090-2097.
C.H. Antink, M. Pirhonen, H. Väätäjä, S. Somppi, H. Törnqvist, A.V. Cardó, ... & A. Vehkaoja “Sensor Fusion for Unobtrusive Respiratory Rate Estimation in Dogs”, IEEE Sensors Journal, Vol. 19, No. 16, 2019, pp. 7072-7081.
L. Camal, A. Kirtane, T. Blanco, R. Casas, F. Rossano & B. Aksanli, “A Wearable Device Network to Track Animal Behavior and Relationships in the Wild”, In IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019, pp. 0198-0202.
J. Cowton, I. Kyriazakis & J. Bacardit, “Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning”, IEEE Access, Vol. 7, 2019, pp. 108049-108060.
G. Salem, J. Krynitsky, M. Hayes, T. Pohida & X. Burgos-Artizzu, “Three-Dimensional Pose Estimation for Laboratory Mouse from Monocular Images”, IEEE Transactions on Image Processing, Vol. 28, No. 9, 2019, pp. 4273-4287.
T. Manning, M. Somarriba, R. Roehe, S. Turner, H. Wang, H. Zheng,... & P. Walsh, “Automated Object Tracking for Animal Behaviour Studies”, In IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019, pp. 1876-1883.
S. Benaissa, D. Plets, E. Tanghe, J. Trogh, L. Martens, L. Vandaele, ... & W. Joseph, “Internet of Animals: Characterisation of LoRa sub-GHz off-body Wireless Channel in Dairy Barns”, Electronics Letters, Vol. 53, No. 18, 2017, pp. 1281-1283.
S. Kumari & S.K. Yadav, “Development of IoT Based Smart Animal Health Monitoring System Using Raspberry Pi”, International Journal of Advanced Studies of Scientific Research, Vol. 3, No. 8, 2018, pp. 24-31.
H. Wu, F. Bai, Z. Zhong, X. Cheng & D. Fan, “Research on Cow Rumination Monitoring Based on New Activity Sensor”. In IEEE 9th International Conference on Information Science and Technology (ICIST), 2019, pp. 199-204.
https://www.allflex.global/rumination-monitoring-helps-livestock-health-management/
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