Monitoring the movement of housed animals by means of wireless technology

Olmr M., Pačes M., Lešetický J., Přikryl M. (2022): Monitoring the movement of housed animals by means of wireless technology. Res. Agr. Eng., 68: 142–149.

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Currently, several, more or less, suitable means for detecting, identifying and monitoring the position of housed animals exist. However, these means suffer from various limitations, which could be eliminated with regard to the current technical and technological possibilities. One possible solution could be the use of some wireless technologies from the Internet of Things (Wi-Fi, Bluetooth, Zigbee, etc.). The uninterrupted supervision of individual housed animals would bring important information about the daily routine of individuals and then, based on the deviations from this daily routine, the opportunity to derive their physical and mental state from these deviations would be potentially possible. This article presents a proof of concept of a low-cost monitoring system of the movement of housed animals. The proposed system is able to detect the client's (prototype's) position in the space by means of Wi-Fi (IEEE 802.11 standard) and received signal strength indication (RSSI) technologies. A fingerprint method and a triangulation method of analysing the space are used to calculate the position in space with a resulting accuracy within metres of the real position.

Ascher A., Eberhardt M., Lehner M., Biebt E. (2016): A GPS based fawn saving system using relative distance and angle determination. Advances in Radio Science, 14: 71–76.
Bahl P., Padmanabhan V. (2000): RADAR: An in-building RF-based user location and tracking system. In: INFOCOM 2000 – Proceeding of the 19th Annual Joint Conference of the IEEE Computer and Communications Societies, Mar 26–30, 2000, Tel Aviv, Izrael: 775–784.
Chen Z., Zhu G., Wang S., Xu Y., Xiong J., Zhao J., Luo J., Wang X. (2021): Multipath assisted Wi-Fi localization with a single access point. IEEE Transactions on Mobile Computing, 20: 588–602.
Eberhardt M., Ascher A., Lehner M., Biebl E. (2015): Array manifold manipulation for short distance DOA estimation with a handheld device. In: Rachev B., Smrikarov A. (eds): Smart SysTech. European Conference on Smart Objects, Systems and Technologies. July 16–17, 2015, Aachen, Germany: 1–7.
Halbich Č., Vostrovský V. (2011): GIS as spatial decision support system. Agris On-line Papers in Economics and Informatics, 3: 67–73.
Jarolímek J., Masner J., Ulman M., Dvorák S. (2012): Cloven-hoofed animals spatial activity evaluation methods in Doupov Mountains in the Czech Republic. AGRIS On-line Papers in Economics and Informatics, 4: 41–48.
Jiangfan F., Yanhong L. (2012): Wifi-based indoor navigation with mobile GIS and speech recognition. IJCSI International Journal of Computer Science, 9: 256–263.
Kim T., Lee D. (2020): Intelligent animal detection system using sparse multi discriminative-neural network (SMD-NN) to mitigate animal-vehicle collision. The Journal of Korean Institute of Communications and Information Sciences, 41: 1463–1471.
Meena S., Loganathan A. (2020): Intelligent animal detection system using sparse multi discriminative-neural network (SMD-NN) to mitigate animal-vehicle collision. Environmental Science and Pollution Research (ESPR), 27: 39619–39634.
Navarro E., Peuker B., Quan M. (2010): Wi-Fi Localization Using RSSI Fingerprinting. BS in Computer Engineering Project; Computer Engineering Department, California Polytechnic State University. Available at: (accessed 20 Jan 2020).
Tremetsberger L., Winckler C., Kantelhardt J. (2019): Animal health and welfare state and technical efficiency of dairy farms: Possible synergies. Animal Welfare, 28: 345–352.
Vasisht D., Kumar S., Katabi D. (2016): Decimeter-level localization with a single WiFi access point. In: 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI). Mar 16–18, 2016, Santa Clara, United States: 165–178.
Xiong J., Jamieson K. (2012): Towards fine-grained radio-based indoor location. In: Proceedings of the 12th Workshop on Mobile Computing Systems & Applications, Feb 28–29, 2012, New York, United States: 1–6.
Xiong J., Sundaresan K., Jamieson K. (2015): ToneTrack: Leveraging frequency-agile radios for time-based indoor wireless localization. In: 21st Annual International Conference on Mobile Computing and Networking (MobiCom). Sept 7–11, 2015, Paris, France: 537–549.
Yu F., Jiang M., Jing L., Xiao Q. (2014): 5G WiFi signal-based indoor localization system using cluster-nearest neighbor algorithm. International Journal of Distributed Sensor Networks, 10: 1–12.
Zviedris R., Elsts A., Strazdins G., Mednis A., Selavo L. (2010): LynxNet: Wild animal monitoring using sensor networks. Real-World Wireless Sensor Networks, 6511: 170–173.
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