This research presents a novel approach to IoT-based solar energy measurement and monitoring. The proposed system incorporates various components such as solar panels, current and voltage sensors, temperature sensors, an ESP32 microcontroller, LED display, BLYNK cloud, and a battery for energy storage. The system enables the conversion of sunlight into electric energy and accurately measures and monitors the current, voltage, and temperature of the solar panels. The collected data is transmitted to the cloud and displayed on a mobile application for convenient access and analysis. A mathematical model is developed to establish the relationship between temperature, voltage, and current. The model accurately predicts the electrical output of the solar panel based on temperature variations. The experimental results demonstrate the reliability and accuracy of the model, with close alignment between the predicted and actual measurements. The power consumption readings obtained during different time intervals illustrate the varying demand patterns throughout the day. This information facilitates effective load balancing and energy management strategies, contributing to optimal energy utilization. The integration of the mobile application enhances the usability of the system, allowing users to monitor real-time and historical data, track energy generation and consumption trends, and receive notifications and alerts. This empowers users to make informed decisions regarding energy usage and optimize the performance of the solar energy system