Implementation of fuzzy inference system algorithm in brooding system simulator with the concept of IoT and wireless nodes

Abstract

This paper aims to implement the Fuzzy Inference System algorithm as a controller in an IoT-based observation system in a brooding system simulator. The system consists of sensor and actuator nodes that are connected to the internet using a microcontroller. The two nodes are connected wirelessly. Sensor nodes as devices that collect input data variables that are temperature and humidity. The value of the sensor readings is sent to Antares cloud storage by a microcontroller which functions as data storage so that it can be accessed by the user as well as an input controller. The Mamdani Fuzzy Inference System algorithm is implemented on the actuator node. The actuator node takes fuzzy input values from Antares and then outputs in the form of a PWM crisp value that aims to regulate blower speed and heating level. The experiments performed were comparing the calculation of the algorithm using MATLAB and the brooding system simulator. The results showed identical outputs with practical results with an average error of 0.11% for the PWM value of the blower and 0.22% for the PWM value of the heater. The scheme is expected to be an alternative solution for implementing the control algorithm on an IoT-based system.