Monitoring and controlling the electricity usage of 2 Room rented house based on IoT
DOI:
https://doi.org/10.24036/jiaee.v2.i2.pp48-53Keywords:
IoT , ESP32 , PZEM - 004T , Blynk , Google Sheet MonitoringAbstract
Uncontrolled use of electrical energy in boarding houses and rentals often causes waste of power and high electrical loads. This research aims to design an Internet of Things (IoT)-based electric power monitoring and control system in two rooms using ESP32 microcontroller, PZEM-004T sensor, and OLED display. The system is integrated with the Blynk platform for remote monitoring, six relays to control electrical loads, and Google Sheet as a medium for storing monitoring data. Tests were conducted using several types of loads, including a 15-watt lamp, soldering iron, fan, cell phone charger, and 600-watt water heater. The test results showed a difference in readings between the sensor and multimeter with an average percentage error of 0.3% for voltage, 4% for current, and 0.53% for power. The current error is relatively high because the current value is so small that the difference slightly affects the percentage. In addition, testing on the relay shows that the system is able to automatically cut off the current when the cost limit is reached, as well as the buzzer works well when the cost limit is approaching. Based on these results, this system can be an effective solution in saving energy and controlling electricity usage based on IoT
Downloads
References
[1] H. Haller, V. -B. Nguyen, G. Debizet, Y. Laurillau, J. Coutaz and G. Calvary, "Energy consumption in smarthome: Persuasive interaction respecting user's values," 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Bucharest, Romania, 2017, pp. 804-809, doi: 10.1109/IDAACS.2017.8095199.
[2] D. MohanaPriya, R. Reshma, D. Priyadharshini and S. Vinod, "IoT Based Automation of Electricity Consumption in Smarthomes," 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), Pondicherry, India, 2019, pp. 1-6, doi: 10.1109/ICSCAN.2019.8878868.
[3] A. F. Ikhfa and M. Yuhendri, “Monitoring Pemakaian Energi Listrik Berbasis Internet of Things,” JTEIN J. Tek. Elektro Indones., vol. 3, no. 1, pp. 257–266, 2022.
[4] M. I. Ardelean, R. A. Munteanu, T. E. Crişan, L. Rapolti and V. I. Farcas, "Low-cost smarthome automation system for elderly," 2023 10th International Conference on Modern Power Systems (MPS), Cluj-Napoca, Romania, 2023, pp. 01-04, doi: 10.1109/MPS58874.2023.10187565
[5] L. A. Latif, R. Maulana, and R. Hidayat, “Monitoring and Controlling Electric Energy Usage Based on the Internet of Things,” Journal of Industrial Automation and Electrical Engineering., vol. 01, no. 01, pp. 75–81, 2024.
[6] M. I. Ardelean, R. A. Munteanu, T. E. Crişan, L. Rapolti and V. I. Farcas, "Low-cost smarthome automation system for elderly," 2023 10th International Conference on Modern Power Systems (MPS), Cluj-Napoca, Romania, 2023, pp. 01-04, doi: 10.1109/MPS58874.2023.10187565.
[7] R. Aisuwarya, D. Yolanda and A. T. Talmera, "An Electricity Usage Monitoring System Using Internet of Things (IoT) for Small Business Stalls," 2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC), Kediri, Indonesia, 2023, pp. 287-291, doi: 10.1109/ICONNIC59854.2023.10467584.
[8] F. Amsyari, D. S. Maylawati, A. Wahana, W. Uriawan, N. Lukman and H. Fikra, "Enhancing Electricity Usage Monitoring and Prediction with IoT-based Multiple Linear Regression Algorithm," 2024 10th International Conference on Wireless and Telematics (ICWT), Batam, Indonesia, 2024, pp. 1-6, doi: 10.1109/ICWT62080.2024.10674733.
[9] Q. Mi, T. Yu, H. Luo, H. Li, Z. Xiao and L. Chen, "A Combined LSTM-CNN Model for Abnormal Electricity Usage Detection," 2024 IEEE 4th International Conference on Software Engineering and Artificial Intelligence (SEAI), Xiamen, China, 2024, pp. 242-246, doi: 10.1109/SEAI62072.2024.10674051.
[10] A. Choudhari, J. Gawai, A. Lekurwale, S. Ranglani and P. Dhongde, "A Mobile App for Smart Electricity Usage Monitoring," 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), Coimbatore, India, 2022, pp. 1667-1673, doi: 10.1109/ICAIS53314.2022.9742787.
[11] R. A. Nugroho, S. Mu’Min, A. Saputro, A. Andhyka, A. S. Editya and A. Mufliq, "Forecasting of Electricity Usage of Indonesian Consumer Using Transformer Time Series," 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA), Surabaya, Indonesia, 2023, pp. 707-710, doi: 10.1109/ICAMIMIA60881.2023.10427799.
[12] U. T. Kartini, D. P. Ardyansyah and E. Yundra, “Hybrid Model For The Next Hourly Electricity Load Demand Forecasting Based on Clustering and Weather Data,” 2020 Third International Conference on Vocational Education and Electrical Engineering (ICVEE), Surabaya, Indonesia, 2020, pp. 1 - 4, doi: 10.1109/ICVEE50212.2020.9243243.
[13] A. Wong et al., “Machine Learning Models Application in Daily Forecasting of Hourly Electricity Usage,” 2022 IEEE International Systems Conference (SysCon), Montreal, QC, Canada, 2022, pp. 1 - 5, doi: 10.1109/SysCon53536.2022.9773835.
[14] T. Myagmarjav, T. Bandi, B. -E. Bayar and S. Ohtsuka, "Changes in Electric Power Demands of Mongolian and Japanese Local Areas in 2020 and Discussion on Seasonal Electricity Usage Based on the Temperature Dependence," 2022 9th International Conference on Condition Monitoring and Diagnosis (CMD), Kitakyushu, Japan, 2022, pp. 355-359.
[15] C. A. Sibiya, K. A. Ogudo and E. J. Aladesanmi, "Machine Learning-Based Anomaly Detection in Residential Electricity Usage Patterns Using Meter Data - Case Study (Msunduzi Municipality)," 2024 IEEE PES/IAS PowerAfrica, Johannesburg, South Africa, 2024, pp. 1-5, doi: 10.1109/PowerAfrica61624.2024.10759457.
