Animal Monitoring Scheme in Smart Farm using Cloud-Based System
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Abstract
Currently, many operations are carried out manually on farms for raising livestock. In particular, it does not use equipment to understand the condition of animals, but relies only on the farmer’s perspective. If information can be obtained by monitoring farm animals, manager can determine the behavior of the animals and use this information to predict the health of the animals. In this paper, we propose a livestock monitoring system based on WSN. The proposed system can monitor farm animals using IoT equipment and cloud platforms. A collar was mounted on the neck of an animal using IoT equipment, and the activity of the livestock was monitored. Farming man- ager can supervises live information by transmitting livestock observation information to cloud platforms. Through actual implementation, we verified that the proposed system can monitor animals on farms in real time.
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References
S. Jo, D. Park, H. Park, S. Kim: Smart Livestock Farms Using Digital Twin: Feasibility Study, In Proc. of 2018 International Conference on Information and Communication Technology Convergence (ICTC) pp. 1461–1463, Oct. 2018.
E. Tullo, I. Fontana, M. Guarino, Precision Livestock Farming: An Overview of Image and Sound Labelling, In Proc. of 6th European Conference on Precision Livestock Farming, pp. 30—38, Sept. 2013.
National Law Information Cen- ter, Livestion Law, 17099, http://www.law.go.kr/%EB%B2%95%EB%A0 %B9/%EC%B6%95%EC%82%B0%EB%B2%95, Mar. 2020.
A. Zgank, Bee Swarm Activity Acoustic Classification for an IoT-Based Farm Service, Sensors (Basel), vol. 20, no. 1, pp. 1–14, Dec. 2019.
J. Vaughan, P. M. Green, M. Salter, B. Grieve and K. B. Ozanyan, Floor sensors of animal weight and gait for precision livestock farming, In Proc. of 2017 IEEE SENSORS, pp. 1–3, Oct. 29-Nov. 1, 2017.
S. P. le Roux, R. Wolhuter and T. Niesler, Energy-Aware Feature and Model Selection for Onboard Behavior Classification in Low-Power Animal Borne Sensor Applications, IEEE Sensors Journal, vol. 19, no. 7, pp. 2722-2734, Apr. 2019.
L. No ́brega, A. Tavares, A. Cardoso, P. Goncalves, Animal monitoring based on IoT technologies, In Proc. of 2018 IoT Vertical and Topical Summit on Agriculture - Tuscany (IOT Tuscany), pp. 1–5, May 2018.
K. H. Kwong, T. Wu, H. G. Goh, K. Sasloglou, B. Stephen, et. al., Practical Considerations for Wireless Sensor Networks in Cattle Monitoring Applications, Computers and Electronics in Agriculture, vol. 81, pp. 33–44, 2013.
Faruq, I. Syarif, A. S. Ahsan, M. U. H. A. Rasyid, Y. P. Pratama, Health Monitoring and Early Diseases Detection on Dairy Cow Based on Internet of Things and Intelligent System, In Proc. of 2019 International Electronics Symposium (IES), pp. 183–188, Sept. 2019.
D. F. Lott, B. L.Hart, Applied ethology in a nomadic cattle culture, Applied Animal Ethology, vol. 5, no. 4, pp. 309–319, Oct. 1979.
B. Sharma, D. Koundal, Cattle health monitoring system using wireless sensor network: a survey from innovation perspective, IET Wireless Sensor Systems, vol. 81, no. 4, pp. 143–151, Mar. 2018.
P. Khatate, A. Savkar, C. Y. Patil, Wearable Smart Health Monitoring System for Animals, In Proc. of 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), pp. 162–164, May 11-12, 2018.
E. S.Nadimi, R. N .Jørgensen, V. Blanes-Vidala, S. Christensen, Monitoring and Classifying Animal Behavior Using ZigBee-Based Mobile Ad Hoc Wireless Sensor Networks and Artificial Neural Networks, Computers and Electronics in Agriculture, vol. 82, pp. 44–54, Mar. 2012.
L. T. Beng, P. B. Kiat, L. N. Meng, P. N. Cheng, Field testing of IoT devices for livestock monitoring using Wireless Sensor Network near field communication and Wireless Power Transfer, In Proc. of 2016 IEEE Conference on Technologies for Sustainability (SusTech), pp. 169–173, Oct. 2016.
V. Puranik, Sharmila, A. Ranjan, A. Kumari, Automation in Agriculture and IoT, In Proc. of 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), pp. 1–6, Apr. 2019.
L. Chettri, R. Bera, A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems, IEEE Internet of Things Journal, vol. 7, no. 1, pp. 16-32, 2020.
Y. Park, J. Choi, J. Choi, A system architecture to control robot through the acquisition of sensory data in IoT environments, In Proc. of 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 749–752, Aug. 2016.
D. Shadrin, A. Menshchikov, D. Ermilov, A. Somov, Designing Future Precision Agriculture: Detection of Seeds Germination Using Artificial Intelligence on a Low-Power Embedded System, IEEE Sensors Journal, vol. 19, no. 23, pp. 11573– 11582, 2019.
J. K. Park and H. Park, Implementation of a Smart Farming Monitoring System Using Raspberry Pi, Journal of Next-generation Convergence Technology Association, vol. 4, no. 4, pp. 354-360, 2020.
M. Hate, S. Jadhav and H. Patil, Vegetable Traceability with Smart Irrigation, In Proc. of 2018 International Conference on Smart City and Emerging Technology (ICSCET), pp. 1-4, Nov. 2018.
Y. J. Jeong, K. E. An, S. W. Lee, D. Seo, Improved durability of soil humidity sensor for agri- cultural IoT environments, In Proc. of 2018 IEEE International Conference on Consumer Electronics (ICCE), pp. 1–2, Jan. 2018.
M. M. Islam, S. Sourov Tonmoy, S. Quayum, A. R. Sarker, S. Umme Hani, M. A. Mannan, Smart Poultry Farm Incorporating GSM and IoT, In Proc. of 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), pp. 277–280, Jan. 2019.
H. Wang, A. O. Fapojuwo, R. J. Davies, A Wireless Sensor Network for Feedlot Animal Health Monitoring, IEEE Sensors Journal, vol. 16, no. 16, pp. 6433-6446, Aug. 2016.
P. Juang, H. Oki, Y. Wang, M. Martonosi, Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet, In Proc. of 10th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), pp. 96–107, Oct. 2002.
Texas Instruments. MSP430F22x2, MSP430F22x4 Mixed Signal Microcontroller, http://www.ti.com/lit/ds/symlink/msp430f2272.pdf, Aug. 2012.
Texas Instruments. eZ430-RF2500 Development Tool User’s Guide, http://www.ti.com/lit/ug/slau227f/slau227f.pdf, Jun. 2015.