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Real-Time Livestock Tracking System with Integration of Sensors and Beacon Navigation

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Abstract

This paper presents the design and development of a livestock tracking system, with the objective of transmitting the location and activity status of the animals, in real-time, to an end-user. The system comprises of tag, beacon and base station nodes, communicating wirelessly with each other. Tag nodes receive location information from neighbouring beacon nodes and through the process of trilateration, the location of a specific animal is determined. Motion sensors within the tags, are used to determine activity status of the animal. The base station node receives the identity, location and activity information, from the tag nodes and transfers the data to a web server, where a database stores the tag information in real-time. An Android application, serves as an interface between the end user and the web server, enabling the remote monitoring and tracking of the livestock. The performance of the system is evaluated in terms of its range, accuracy and the ability to detect and store information. The nodes in the system are able to communicate within the expected ranges. The tag data can be inserted into the database and be retrieved for end user needs. The results demonstrate that the system can successfully read, process, transmit and display the location and activity information.

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References

  1. Awad, A. I. (2016). From classical methods to animal biometrics: A review on cattle identification and tracking. Computers and Electronics in Agriculture, 123, 423–435.

    Article  Google Scholar 

  2. Ruiz-Garcia, L., & Lunadei, L. (2011). The role of RFID in agriculture: Applications, limitations and challenges. Computers and Electronics in Agriculture, 79(1), 42–50.

    Article  Google Scholar 

  3. Kays, R., Crofoot, M. C., Jetz, W., & Wikelski, M. (2015). Terrestrial animal tracking as an eye on life and planet. Science, 348(6240), aaa2478.

    Article  Google Scholar 

  4. Andonovic, I., Michie, C., Gilroy, M., Goh, H., Kwong, K.H., Sasloglou, K., & Wu, T. (2009). Wireless sensor networks for cattle health monitoring. In ICT Innovations.

  5. Bai, H., Zhou, G., Hu, Y., Sun, A., Xu, X., Liu, X., et al. (2017). Traceability technologies for farm animals and their products in China. Food Control, 79, 35–43.

    Article  Google Scholar 

  6. Raizman, E., Rasmussen, H., King, L., Ihwagi, F., & Douglas-Hamilton, I. (2013). Feasibility study on the spatial and temporal movement of Samburu’s cattle and wildlife in Kenya using GPS radio-tracking, remote sensing and GIS. Preventive Veterinary Medicine, 111(1), 76–80.

    Article  Google Scholar 

  7. Voulodimos, A. S., Patrikakis, C., Sideridis, A. B., Ntafis, V. A., & Xylouri, E. M. (2010). A complete farm management system based on animal identification using RFID technology. Computers and Electronics in Agriculture, 70(2), 380–388.

    Article  Google Scholar 

  8. Sheikh, S. (2015). A survey on machine learning techniques used in tracking livestock in rural areas using wireless sensor networks. International Journal of Electronics Communication and Computer Technology, 5(1), 812–820.

    MathSciNet  Google Scholar 

  9. Choi, S. G., Chimeddorj, G., Altankhuyag, B., & Dunkhorol, S. (2016). Design and implementation of a GPS-enabled mobile wireless sensor network for livestock herd tracking in mongolian nomadic herding. In 11th International forum on strategic technology (IFOST), 1–3 June, Novosibirsk, Russia, pp. 423–427.

  10. Gaur, M., Chand, K., Louhaichiz, M., Johnson, D., Mishra, A., & Roy, M. (2013). Role of GPS in monitoring livestock migration. Journal of Indian Cartographer, 33, 496–501.

    Google Scholar 

  11. Lubaba, C. H., Hidano, A., Welburn, S. C., Revie, C. W., & Eisler, M. C. (2015). Movement behaviour of traditionally managed cattle in the Eastern Province of Zambia captured using two-dimensional motion sensors. PLoS ONE, 10(9), 1–14.

    Article  Google Scholar 

  12. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazines, 40(8), 102–114.

    Article  Google Scholar 

  13. Handcock, R. N., Swain, D. L., Bishop-Hurley, G. J., Patison, K. P., Wark, T., Valencia, P., et al. (2009). Monitoring animal behaviour and environmental interactions using wireless sensor networks, GPS collars and satellite remote sensing. Sensors, 9(5), 3586–3603.

    Article  Google Scholar 

  14. Nadimi, E., Søgaard, H., Bak, T., & Oudshoorn, F. (2008). Zigbee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass. Computers and Electronics in Agriculture, 61(2), 79–87.

    Article  Google Scholar 

  15. Guo, Y., Corke, P., Poulton, G., Wark, T., Bishop-Hurley, G., & Swain, D. (2006). Animal behaviour understanding using wireless sensor networks. In Proceedings, 31st IEEE conference on local computer networks, 14–16 November, Florida, USA, pp. 607–614.

  16. Radoi, I. E., Mann, J., & Arvind, D. K. (2015). Tracking and monitoring horses in the wild using wireless sensor networks. In 11th International conference on wireless and mobile computing, networking and communications (WiMob), 19–21 October, Abu Dhabi, UAE, pp. 732–739.

  17. Wang, H., Davies, B., & Fapojuwo, A. O. (2015). Inter-wireless body area network scheduling algorithm for livestock health monitoring. In IEEE Wireless communications and networking conference (WCNC), 9–12 March, New Orleans, USA, pp. 2132–2137.

  18. Hwang, J., & Yoe, H. (2014). Design and implementation of the livestock activity monitoring system using RSSI of Zigbee and ratiometric. International Information Institute Tokoyo Information, 17(3), 1047–1052.

    Google Scholar 

  19. Mudziwepasi, S. K., & Scott, M. S. (2014). Assessment of a wireless sensor network based monitoring tool for zero effort technologies: A cattle-health and movement monitoring test case. In 6th International conference on adaptive science and technology, IEEE ICAST 2014, 29–31 October, Ota, Nigeria.

  20. Kumar, A., & Hancke, G. P. (2015). A Zigbee-based animal health monitoring system. IEEE Sensors Journal, 15(1), 610–617.

    Article  Google Scholar 

  21. Mao, G., Fidan, B., & Anderson, B. D. O. (2007). Wireless sensor network localization techniques. Computer Networks, 51(10), 25292553.

    MATH  Google Scholar 

  22. Ni, L., Zhang, D., & Souryal, M. R. (2011). RFID-based localization and tracking technologies. IEEE Wireless Communications, 18(2), 45–51.

    Article  Google Scholar 

  23. Pal, A. (2010). Localization algorithms in wireless sensor networks: Current approaches and future challenges. Network Protocols and Algorithms, 2(1), 45–73.

    Article  Google Scholar 

  24. Manley, E. D., Nahas, H. A., & Deogun, J. S. (2006). Localization and tracking in sensor systems. In IEEE International conference on sensor networks, ubiquitous, and trustworthy computing (SUTC’06), 5–7 June, Taichung, Taiwan, vol. 2, pp. 237–242.

  25. Lanzisera, S., Lin, D. T., & Pister, K. S. J. (2006). RF time of flight ranging for wireless sensor network localization. In International workshop on intelligent solutions in embedded systems, 30 June, Vienna, Austria, pp. 1–12.

  26. Lanzisera, S., Zats, D., & Pister, K. S. J. (2011). Radio frequency time-of-flight distance measurement for low-cost wireless sensor localization. IEEE Sensors Journal, 11(3), 837–845.

    Article  Google Scholar 

  27. dsPIC30F3014/4013 High-Performance Digital Signal Controllers, Microchip Technology, (2004).

  28. ADXL335: Small, Low Power, 3-Axis 3 g Accelerometer, Analog Devices (2009). [Rev.0]. https://www.sparkfun.com/datasheets/Components/SMD/adxl335.pdf. Accessed 19 Oct 2018.

  29. nRF24L01+ Single Chip 2.4GHz Transceiver, Nordic Semiconductor (2007) [Version 2.0]. https://www.nordicsemi.com/.../nordic/.../nRF24L01_Product_Specification_v2_0.pdf. Accessed 19 Oct 2018.

  30. LD1117: Low drop fixed voltage adjustable positive voltage regulator, ST, December 2005. [Rev.19]. https://www.nordicsemi.com/.../nordic/.../nRF24L01_Product_Specification_v2_0.pdf. Accessed 19 Oct 2018.

  31. SPLC780D: 16COM/40SEG Controller/Driver, Sunplus, August 2003, [Version 0.1]. https://www.newhavendisplay.com/app_notes/SPLC780D.pdf. Accessed 19 Oct 2018.

  32. Model No.: YSL-R531R3D-D2, China Young Sun LED Technology, 2009. http://cdn.sparkfun.com/datasheets/Components/General/YSL-R1042WC-D15.pdf. Accessed 19 Oct 2018.

  33. FT232R USB UART IC Datasheet, Future Technology Devices International Ltd., 2015, [Version 2.13]. https://www.ftdichip.com/Documents/DataSheets/ICs/DS_FT232R.pdf. Accessed 19 Oct 2018.

  34. Ramirez, M. (2011). Time-of-flight in wireless networks as information source for positioning. Ph.D. Dissertation: Technical University of Munich.

  35. Jose, A. C., & Malekian, R. (2017). Improving smart home security: Integrating logical sensing into smart home. IEEE Sensors Journal, 17(3), 4269–4286.

    Article  Google Scholar 

  36. Jose, A. C., Malekian, R., & Ye, N. (2016). Improving home automation security; integrating device fingerprinting into smart home. IEEE Access, 4, 5776–5787.

    Article  Google Scholar 

  37. Malekian, R., Bogatinoska, D. C., Karadimce, A., Ye, N., Trengoska, J., & Nyako, W. A. (2015). A novel smart ECO model for energy consumption optimization. Elektronika ir Elektrotechnika, 21(6), 75–80.

    Article  Google Scholar 

  38. Malekian, R., Moloisane, N. R., Nair, L., Maharaj, B. T., & Chude-Okonkwo, U. A. (2017). Design and implementation of a wireless OBD II fleet management system. IEEE Sensors Journal, 17(4), 1154–1164.

    Article  Google Scholar 

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Acknowledgements

The research is supported by and National Research Foundation, South Africa (Grant numbers: IFR160118156967 and RDYR160404161474).

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Authors and Affiliations

  1. Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, 0002, South Africa

    Nthetsoa Alinah Molapo, Reza Malekian & Lakshmi Nair

  2. Department of Computer Science and Media Technology, Malmö University, Malmö, Sweden

    Reza Malekian

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  1. Nthetsoa Alinah Molapo
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  2. Reza Malekian
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  3. Lakshmi Nair
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Correspondence to Reza Malekian.

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Molapo, N.A., Malekian, R. & Nair, L. Real-Time Livestock Tracking System with Integration of Sensors and Beacon Navigation. Wireless Pers Commun 104, 853–879 (2019). https://doi.org/10.1007/s11277-018-6055-0

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