Design of IoT-Based Control System Using Fuzzy Inference System

Sunardi Sunardi, Agung Mulyo Widodo, Karisma Trinanda Putra, Cahya Darmarjati, Prayitno Prayitno

Abstract


Industry 4.0 combines automation technology with cyber technology such as Internet of Things (IoT) technology. IoT services can provide a system with a huge amount of data in real-time monitoring from edge sensory nodes. However, in real-world industrial applications, IoT can not achieve a good result in decision-making tasks unless intelligent mechanisms are integrated into it. A control system based on the combination of IoT and artificial intelligence (AIIoT) is explored in this study. This research simulated the used of IoT devices for controlling tasks and can be monitored via the internet. In addition, an artificial intelligence, i.e., a fuzzy Inference System, is proposed. First, inputs are recorded from DHT11 temperature-humidity sensor and the MPX5100DP indoor air pressure sensor. Then, the inference model converts the inputs into fuzzy sets and then calculates the output during the inference phase using predefined rules. The proposed algorithm is implemented using an ESP8266 Arduino board which can connect to the server via WiFi. This prototype can record input data with errors measured by RMSE of 0.38 and 1.158 for humidity-temperature and air pressure sensors, respectively. Based on experiments, the system can respond optimally to the input changes that are manipulated through the FIS algorithm, as evidenced by using an average error of 0.0145 in five different scenarios

Keywords


fuzzy logic, IoT, microcontroller, servo motor, sensor

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DOI: http://dx.doi.org/10.30811/jpl.v20i2.2650

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