Monitoring behavior of poultry based on RFID radio frequency network

Zhang Feiyang, Hu Yueming, Chen Liancheng, Guo Lihong, Duan Wenjie, Wang Lu

Abstract


Abstract: Poultry behavior monitoring is an important basis for the poultry disease warning. Manual monitoring is mostly used nowadays. In this work, the automatic monitoring system for assisting manual monitoring was examined. Sophisticated data mining techniques were used to leverage the data collected by RFID devices. Specifically, (1) weighing sensors and wireless networks of Multiple RFID-tag-collector groups were used to monitor the poultry behavior; (2) RFID tags were putted on individual poultry so that the moving time of the poultry between two RFID-tag-collectors could be recorded. Thus, the characteristic functions of poultry behaviors such as speed, ability to snatch food and resting time could be extracted based on the distance between two RFID-tag-collectors and the relevant time parameters; (3) the sick, normal, active and other poultry groups were categorized by using the K-means method which utilizing the behavior characteristics and poultry weight data in data mining. The results demonstrated that accurate classifications could be obtained according to the poultry characteristics, and the clustering results matched with the results obtained by manual method to identify the poultry groups. Consequently, the technique in this paper has great potential for large-scale poultry disease warning and poultry classification.
Keywords: poultry behavior, monitoring, cloud computing, internet of things (IoT), radio-frequency identification, data mining
DOI: 10.3965/j.ijabe.20160906.1568

Citation: Zhang F Y, Hu Y M, Chen L C, Guo L H, Duan W J, Wang L. Monitoring behavior of poultry based on RFID radio frequency network. Int J Agric & Biol Eng, 2016; 9(6): 139－147.

Keywords


poultry behavior, monitoring, cloud computing, internet of things (IoT), radio-frequency identification, data mining

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References


Luca C, Riccardo C, Luca M, Vincenzo M, Luigi P, Stefano P, et al. An RFID tracking system supporting the behavior analysis of colonial laboratory animals. International Journal of RF Technologies, 2013; 5(1-2): 63–80.

Guarino M, Jans P. Field test of algorithm for automatic cough detection in pig houses. Computer and Electronics in Agriculture, 2008; 62(1): 22–28.

Kwong T, Wu T, Goh H G, Stephen B, Gilroy M, Michie C, et al. Wireless sensor networks in agriculture: Cattle monitoring for farming industries. Piers Online, 2009; 5(1): 31–35.

Venkatraman S, Long J D, Pister K S, Carmena J M. Wireless inertial sensors for monitoring animal behavior. Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. IEEE, 2007; pp.378–381.

Catarinucci L, Colella R, Mainetti L, Patrono L, Pieretti S, Sergi I, et al. Smart RFID antenna system for indoor tracking and behavior analysis of small animals in colony cages. Sensors Journal, IEEE, 2014; 14(4): 1198–1206

Ricardo B M, Javier G H, Luis R G, Tatiana J A, José I R V, Pilar B. Assessing the dynamic behavior of WSN motes and RFID semi-passive tags for temperature monitoring. Computers and Electronics in Agriculture, 2014; 103(2): 11–17.

Rodney B M, Debra E G, Alan C, Ronald J T. Use of a programmable protocol timer and data logger in the monitoring of animal behavior. Pharmacology Biochemistry and Behavior, 1981; 15(1): 135–140.

Leroy T, Vranken E, Struelens E, Sonck B, Berckmans D. Modeling and recognizing behavior patterns of laying hens in furnished cages. Livestock Environment VII, 2005; pp.685–693.

Ye W, Xin H. Themo graphical quantification of physiological and behavioral responses of group housed young pigs. Transaction of the ASAE, 2000; 43(6): 1843–1851.

Shao B, Xin H W. A real-time computer vision assessment and control of the thermal comfort for group-housed pigs. Computer and Electronics in Agriculture, 2008; 62(2): 15–21.

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

Watanabe T, Sakurai A, Kitazaki K. Dairy cattle monitoring using wireless acceleration-sensor networks. Proceedings of IEEE Sensors, 2008; pp.526–529.

Kwong K H, Goh H G, Michie C, Andonovic I, Stephen B, Mottram T, et al. Wireless sensor networks for beef and dairy herd management. Michigan: ASABE Annual International Meeting, St. Joseph, 2008; pp.5623–5636.

Warren S, Martinez A, Sobening T, Andresen D. Electrocardiographic pill for cattle heart rate determination. 30th Annual International IEEE EMBS Conference Vancouver, British Columbia, Canada, 2008; pp.4852–4855.

Nadimi E S, Sogaard H T, Bak T. ZigBee-based wireless sensor networks for classifying the behaviour of a herd of animals using classification trees. Biosystems Engineering, 2008; 100(2): 167－176.

Yi L, Liu C X. Design of system for monitoring dairy cattle’s behavioral features based on wireless sensor networks. Transactions of the CSAE, 2010; 26(3): 203–208. (in Chinese with English abstract)

Ricardo B M, Javier G H, Luis R G, Tatiana J A, José I R V,

Pilar B. Assessing the dynamic behavior of WSN motes and RFID semi-passive tags for temperature monitoring. Computers and Electronics in Agriculture, 2014; 103(2): 11–16.

Yu P X, Wu Y M, Hu Y M, Chen L C, Wang L. Optimal policy for read rate in RFID food safety traceability system. Transactions of the CSAE, 2008; 24(7): 132–136. (in Chinese with English abstract)

Christopher L H, Joseph P G, Joy A M. A system utilizing radio frequency identification (RFID) technology to monitor individual rodent behavior in complex social settings. Journal of Neuroscience Methods, 2012; 209(1): 74–152.

Parsons J, Kimberling C, Parsons G, Le Valley S. Colorado sheep ID project: Using RFID for tracking sheep. Journal of Animal Science, 2005; 83(7): 119－120.

Ronald B, Siarhei S. Experiments for evaluating sensors' precision in wireless sensor networks. International Journal of Ad Hoc, Sensor & Ubiquitous Computing, 2012; 3(3): 105–121.

Rani K S S, Devarajan N. Multiobjective sensor node deployment in wireless sensor networks. International Journal of Engineering Science and Technology, 2012; 4(4): 1262–1266.

Praveen K, Satish C. An intelligent system based on sensor integration & sensor fusion. International Journal of Advanced Research In Computer Science and Software Engineering, 2012; 2(3): 2277–2283.

Zhang Q, Yang X L, Zhou Y M, Wang L R, Guo X S. A wireless solution for greenhouse monitoring and control system based on ZigBee technology. Journal of Zhejiang University Science A, 2007; 8(10): 1584–1587.

Laszlo G, Sergiu F, Igor T. Long-term synchronized electrophysiological and behavioral wireless monitoring of freely moving animals. Journal of Neuroscience Methods, 2013; 212(2): 237–241.

Vellidis G, Tucker M, Perry C, Kvien C, Bednarz C. A real-time wireless smart sensor array for scheduling irrigation. Computers and Electronics in Agriculture, 2008; 61(1): 44–50.

Li Z, Hong T, Ning W, Wen T. Data transmission performance for 2.4GHz in-field wireless sensor network. International Conference on Computer Engineering and Technology. IEEE, 2010; pp.V1-465 - V1-469.

Lin G, John A S. Radio-triggered wake-up for wireless sensor networks. Real-Time Systems, 2005; 29(2-3): 157–182.

Ruiz-Mirazo J, Bishop-Hurley G J, Swain D L. Automated animal control: can discontinuous monitoring and aversive stimulation modify cattle grazing behavior. Journal of Range Management, 2011; 64(3): 240–248.

Ma Z, Ma J, Li Y. Intelligent greenhouse monitoring and control system design based on wireless fidelity. Journal of Agricultural Mechanization Research, 2011, 33(2): 154–157. (in Chinese with English abstract)

Kim Y, Evans R G. Software design for wireless sensor-based site-specific irrigation. Computers and Electronics in Agriculture, 2009; 66(2): 159–165.

Chang D X, Zhang X D, Zheng C W. A genetic algorithm with gene rearrangement for K-means clustering. Pattern Recognition, 2009; 42(7): 1210–1222

Momin B F; Yelmar P M. Modifications in K-Means clustering algorithm. International Journal of Soft Computing & Engineering, 2012; 2(3): 34–354.

Chawan P P M, Bhond S R, Shirish P. Improvement of k-means clustering algorithm. International Journal of Engineering Research and Applications, 2012; 2(2): 1378–1382.

Xie J, Jiang S, Xie W, Gao X. An efficient global K-means clustering algorithm. Journal of Computers, 2011; 6(2): 271–280.




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