STUDY OF ROOM THERMAL CHARACTERISTIC FOR AC CONTROL PARAMETER USING INTERNET OF THINGS (IOT).
Energy efficiency is an effort to reduce energy use in doing work. One technology that can be used for energy efficiency is the Internet of Things (IoT). In this study, the energy savings of the AC system were reviewed. In order to achieve energy savings in the AC system, it takes an AC control that...
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| Format: | Final Project |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/41399 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Energy efficiency is an effort to reduce energy use in doing work. One technology that can be used for energy efficiency is the Internet of Things (IoT). In this study, the energy savings of the AC system were reviewed. In order to achieve energy savings in the AC system, it takes an AC control that can perform energy efficiency while still considering thermal comfort. In this research, a study of the thermal characteristics of the room using IoT technology was carried out. From the results of this study, thermal parameters can be obtained from the room. This parameters is then processed into input variabel to obtain the AC system control function using machine learning. Experiments and studies that have been carried out in this research are experiments in temperature and humidity data collection, study of temperature data retrieval time that can produce stable fitting values of room thermal resistance and capacitance (RC), study of room occupancy effect on RC values, study of ambient temperature effect on room temperature, study of duty cycle (DC) effect on room temperature, study of architectural variations of the artificial neural network (ANN) model of machine learning, and study of the relationship between room humidity and room temperature. From the experiments that have been carried out, some conclusions are obtained. It was found that the system was able to receive and store temperature and humidity data sent every 5 seconds by the sensors. Temperatur data retrieval in a range of 4-7.5 minute range can produce a stable RC value. The room occupancy can be represented by the RC value. External temperature is a parameter that needs to be included in the AC control parameters. There is a minimum temperature that can be done by an AC where if the temperature set is smaller than this temperature, energy efficiency cannot be done. With machine learning, AC control functions can be obtained with a maximum error of 2% on the predicted results. Room humidity has a positive correlation with the value of room temperature.
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