Tracking Human Motions in Photographing: A Context-Aware Energy-Saving Scheme for Smart Phones

摘要

Due to the portability of smart phones, more and more people tend to take photos with smart phones. However, energy-saving continues to be a thorny problem, since photographing is a rather power hungry function. To extend the battery life of phones while taking photos, we propose a context-aware energy-saving scheme called "SenSave." SenSave senses the user's activities during photographing and adopts suitable energy-saving strategies accordingly. SenSave works based on the observation that a lot of energy during photographing is wasted in preparations before shooting. By leveraging the low power-consuming embedded sensors, such as accelerometer and gyroscope, we can recognize the user's activities and reduce unnecessary energy consumption. Besides, by maintaining an activity state machine, SenSave can determine the user's activity progressively and improve the recognition accuracy. Experiment results show that SenSave can recognize the user's activities with an average accuracy of 95.5% and reduce the energy consumption during photographing by 30.0%, when compared to the approach by frequently turning ON/OFF the camera or screen. Additionally, we enhance "SenSave" by introducing an extended Markov chain to predict the next activity state and adopt the energy-saving strategy in advance. Then, we can reduce the energy consumption during photographing by 36.1%.