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Tracking energy consumption for individual operating machines (e.g., home appliance) is a prerequisite for making energy conservation and management efficient. In order to meet the requirement for monitoring home energy consumption, several industries and researchers came up with different solutions. Unfortunately, all these solutions require invasive and expensive installation of sensor devices. Furthermore, many of these solutions can't measure the energy consumption of individual machines. In this paper, we propose and evaluate the feasibility of using smart phones in machines's energy monitoring system. We call our system EnergySniffer in which it exploits various sensors, such as magnetic sensor, light, microphone, temperature, camera, WiFi, in smart phones to build a multi sensing framework. This framework is used to build a unique fingerprint profile for each individual machine. As a proof of concept, we develop a simple sensing framework prototype that utilizes only the microphone sensor on the phone. We call this framework a sound sensing framework. Experimental evaluation on sound sensing framework demonstrate the feasibility of continuously identifying and monitoring individual machine in real-time.