Electrical Energy Consumption Monitoring System in the Residential Sector using IoT

In Latin America and the Caribbean, the consumption of energy, that comes mainly from fossil resources, have carried an increase in the air pollution. Electricity generation and its consumption in residential sector contributes to this problem with a significant percentage. On the other hand, recent research has demonstrated that the use of smart energy meters in developed countries reduces the electricity consumption due the continuous feedback gave to the consumer. This research presents the developing and implementation of an electrical energy consumption monitoring system based on smart sensors with IoT technology. The system calculates the instant power and the electrical efficiency as well as the energy consumed and its cost. The information of these variables is processed and transferred trough a WIFI ESP8266 module to a ThingSpeak server that works like a cloud database. Also, an Android mobile application that interacts directly with the database was developed to users visualize the variables behavior. For validate the smart sensor accuracy its measures were compared with the measures of an oscilloscope and a multimeter. Relative errors between -2.34 and 1.92 % were observed.

Automated summary

In Latin America and the Caribbean, the use of fossil resources for energy consumption has led to increased air pollution. The residential sector, particularly in electricity generation and consumption, contributes significantly to this problem. However, recent research has shown that smart energy meters can reduce electricity consumption in developed countries by providing continuous feedback to consumers. This study presents the development and implementation of an electrical energy consumption monitoring system using IoT technology. The system calculates instant power, electrical efficiency, energy consumption, and cost. The data is processed and transmitted to a cloud database using a WIFI ESP8266 module. An Android mobile application is also developed for users to visualize the variables. The accuracy of the smart sensors is validated by comparing their measurements with those of an oscilloscope and a multimeter, with relative errors ranging from -2.34% to 1.92%.