This paper presents a novel energy tapping identification system utilizing a wireless data acquisition framework aimed at enhancing the detection of unauthorized energy usage in electrical networks. Energy theft poses significant challenges to utility companies, leading to substantial financial losses and compromising the integrity of power distribution systems. The proposed system leverages advanced sensors and wireless communication technologies to monitor electrical parameters in real-time, enabling the identification of irregular consumption patterns indicative of energy tapping. By employing data analytics and machine learning algorithms, the system can differentiate between legitimate usage and potential theft, providing accurate alerts for further investigation. Experimental results demonstrate the effectiveness of the system in various operational conditions, showcasing its potential to significantly improve the monitoring and management of energy resources. This research contributes to the development of intelligent energy management solutions, ultimately helping utility providers reduce losses, enhance operational efficiency, and promote sustainable energy practices. The findings underscore the importance of integrating wireless data acquisition systems in modern power distribution networks to combat energy theft effectively.