Thermal optimization on incubator using fuzzy inference system based IoT

Renny Rakhmawati; Irianto; Farid Dwi Murdianto; Atabik Luthfi; Aviv Yuniar Rahman

doi:10.1109/ICAIIT.2019.8834530

Thermal optimization on incubator using fuzzy inference system based IoT

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Renny Rakhmawati, Irianto, Farid Dwi Murdianto, Atabik Luthfi, Aviv Yuniar Rahman

2019 Proceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019 Conference paper Cited by 20

Abstract

Incubators are very important in the poultry industry for hatching eggs. The control system used in poultry hatching in the industry usually uses control ON/OFF and is monitored with a local network (LAN). The control system using ON/OFF produces an unstable heating. In addition, systems that are accessed on the LAN only can be monitored in incubator locations. Therefore, this study introduces the optimization of the egg incubator system using fuzzy inference and based on Internet of Things (IoT). So the egg hatching system is more stable when it warms up the temperature at the incubator and can be controlled via the internet network. The results obtained by running IoT-based incubator system on the 38 °C set point, system are running optimally. When it reaches 115 seconds, the temperature reaches a steady 38 °C. While the highest overshoot temperature 38.6 °C occurred at 60 seconds. © 2019 IEEE.

Affiliations

Department of Electrical Engineering, Electronics Engineering Polytechnic, Institute of Surabaya, Surabaya, Indonesia; Department of Informatics Engineering, Universitas Widyagama, Malang, Indonesia

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