Condition Monitoring of Frozen Storage for Energy Optimization

High electrical consumption in operating the factory has been a critical source of expense, especially for a frozen food warehouse. Hence, this project is proposing a solution by utilising Industrial IoT and Machine Learning to reduce the use of electricity. A simple prototype has been built by using ESPS266, DHT22 and Raspberry Pi, with the aid of NodeRed and TensorFlow for data collection and machine learning for prediction. The predicted temperature has obtained an accuracy of up to 98.24% for operating frozen food storage. Besides that, the efficiency of energy optimization forthe refrigeration compressor is up to 9 hours with the cost saved up to RM869.62 per year for 1HP.