WattWise: Mobile-Based Energy Monitoring and Forecasting System for Home Appliances

Abstract

The research presents WattWise, a smartphone application that enables households to track and forecast electricity usage for improved management. The study aims to address the growing issue of high electricity costs in the Philippines by providing users with a convenient way to monitor appliance-level energy usage, estimate electricity expenses, and receive practical energy-saving recommendations. It integrates three core functions—live monitoring, appliance recognition, and predictive analysis—into one accessible mobile platform. The study utilized a developmental research approach guided by the Agile methodology to support the continuous design, development, testing, and improvement of the system. WattWise integrates an ESP32 microcontroller and PZEM-004T energy monitoring module to gather real-time electrical measurements such as voltage, current, power, and energy consumption. The system also incorporates a YOLOv8-based appliance identification feature, allowing users to scan household appliances using the mobile application camera. Captured data are processed through a Flask-based API and stored in Firebase Firestore for monitoring and analysis. Past consumption data are processed through ARIMA time-series analysis to generate forecasts of upcoming electricity demand and expenses. The system provides users with a dashboard that displays real-time energy usage, cumulative electricity consumption, estimated costs, and forecasted consumption trends. It also generates personalized recommendations and alerts that encourage more efficient electricity usage. Results indicate that combining AI, predictive modeling, and IoT-based monitoring enhances household energy management and raises user awareness of consumption patterns.