Implementation of Kalman Filter With Pi-Controller for Temperature Sensor in Fish Pond Monitoring System - Wardah Alfalah; Varlenda Sarma Quraini; Nabilah Qurrotuayun (Journal of Robotics, Automation, and Electronics Engineering, 2024)
The research aims to determine monitoring the temperature in fish ponds is crucial for successful cultivation, especially in tropical climates that often experience hot weather. This study proposes an approach using the Kalman Filter method and PI (Proportional-Integral-Derivative). Aside from that, to controller to improve the accuracy of monitoring the temperature in fish ponds. Integration with the Firebase Realtime Database allows for real-time data monitoring. Testing was conducted by comparing the DS18B20 temperature sensor without a filter with three variations of the Kalman Filter and PI controller. The results show that using Kalman Filter 3 with the PI controller resulted in a significant reduction in error and noise compared to using Kalman Filter alone. In conclusion, the integration of the Kalman Filter and PI controller with the Firebase Realtime Database can improve the accuracy of monitoring the temperature in fish ponds and has positive implications for increasing efficiency and fish welfare.