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Develop a low-cost remote monitoring and control system for poultry barn

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2017 ASABE Annual International Meeting  1701286.(doi:10.13031/aim.201701286)
Authors:   Jianfeng Zhou, Alexander Beattie, Jing Zhou , Leon Schumacher
Keywords:   Internet of things (IOT), Raspberry PI, wireless sensing network, animal welfare.

Abstract. Animal welfare is significantly affected by the environmental conditions in which animals are living. The direct environmental parameters including temperature, relative humidity and carbon dioxide, are usually controlled through heating and ventilation systems. It is a labor intensive work to check animal conditions and monitor environmental conditions. Manual control of ventilation system is not optimized in regulation of air quality in barns. To improve animal‘s living condition and to reduce labor intensity, it is critical to develop a remote real-time monitor and automatic control system for poultry barn management. The goal of this study was to develop a low-cost remote monitoring and control system for poultry barns based on internet of things (IOT) technology and low-cost wireless sensor network (WSN). The system is consisted of two subsystems, including (1) local wireless sensing network (WSN), which is used to collect environmental data and control ventilation devices in each individual barn. It is consisted of sensors (temperature, RH and CO2), Arduino microcontrollers, ZigBee modules, a Raspberry Pi, and motor drivers. (2) Cloud-based monitor and control system, which is used to visualize environmental data, save data to cloud database and transmit commands from users to endpoints. The cloud monitor and control system consisted of ARTIK Cloud IOT platform, MySQL database and a website interface. The system was tested in lab, the results show that the system was capable to collect environmental data remotely and visualize them in website, and is extensible with more local sensing nodes.

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