The growing need for intelligent energy monitoring systems in both residential and industrial settings has driven the advancement of smart metering technologies. This study presented the development and evaluation of a cost-effective, IoT-enabled energy metering system utilizing the ACS712 current sensor and ZMPT101B voltage sensor, interfaced with an ESP32 microcontroller. The system designed had real-time acquisition of voltage and current values, from which it derived instantaneous power and energy consumption data. Leveraging the computational and communication capabilities of the ESP32, sensor data were processed and transmitted over Wi-Fi to a blynk cloud-based platform for continuous monitoring and control of energy consumption. The design offered a scalable, low-power solution for remote energy management and it paved the way for further integration with home automation and smart grid systems. The system achieved an average accuracy of over 97% when compared to standard multimeter readings, which indicates its suitability for real-world applications. Voltage measurements exhibited a maximum deviation of ±1.5V, while current readings were stable within ±0.02A. While these deviations are relatively minor, they highlighted the limitations of the analog sensor system, particularly under rapidly fluctuating load conditions. The ESP32's 12-bit ADC provided sufficient resolution for capturing voltage and current signals; however, noise from unshielded wiring and sensor non-linearity contributed to minor measurement errors. Further calibration and filtering techniques could mitigate these issues, improving accuracy, especially in high-frequency applications or environments with considerable electrical noise. This research has offered a design framework for low-cost blueprint for an IoT-based energy meter and also provided outlined strategic sensor integration approach with the effective use of ACS712 and ZMPT101B with ESP32. On the other hand, it has demonstrated reliable wireless data communication with real-time visualization. For researchers hoping to further on this topic, it is recommended that mechanism for phase detection (e.g., zero-crossing detector) to measure real power (Watts) and power factor for more accurate energy readings should be incorporated.
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