Journal article

Monitoring and Control of Liquid Waste using fuzzy logic based Internet of Things (IoT)

I MADE MATARAM I Ketut Wijaya

Volume : 8 Nomor : 11 Published : 2023, November

International Journal of Latest Engineering Research and Applications (IJLERA)

Abstrak

Abstract: The increasing concerns about environmental degradation and the proper management of liquid waste have led to the exploration of innovative technological solutions. This project presents a comprehensive approach to monitoring and controlling liquid waste utilizing Internet of Things (IoT) technology and fuzzy logic. The system aims to achieve real-time data collection, intelligent decision-making, and remote control through the aerator system by integration of sensors, microcontrollers, and the Thing Speak IoT platform. The project focuses on developing a smart liquid waste management system capable of measuring key parameters such as COD(chemical Oxygen Demand). The collected data are then processed through a fuzzy logic algorithm to make informed control decisions. The system employs a Node MCU ESP8266 microcontroller to interface with the sensors and actuators. The collected data are transmitted to the Thing Speak platform, where they are visualized and analyzed. The key advantage of integrating fuzzy logic lies in its ability to handle imprecise and uncertain data, which are often encountered in environmental monitoring scenarios. By leveraging fuzzy logic, the system can provide adaptive control decisions that respond to the dynamic nature of liquid waste conditions. Furthermore, the integration with Thing Speak enhances the system's capabilities by enabling real-time monitoring, data visualization, and remote control through mobile applications. The implementation of this project underscores the significance of IoT and fuzzy logic in addressing critical environmental challenges. The outcomes demonstrate the potential for optimizing liquid waste management practices, reducing the environmental impact, and promoting efficient resource utilization. This project contributes to the growing field of IoT-enabled environmental monitoring and offers insights into the effective utilization of fuzzy logic for decision-making in real-world applications