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What can users do if they need their device to last for a specific duration in order to perform a specific task?To this extent, we developed Battery Extender, a user-guided power management tool that enables the reconfiguration of the device’s resources based on the workload requirement, similar to the principle of creating virtual machines in the cloud.The distributed methods iteratively converge to solutions which are comparable to centralized methods.DPI-LBP also reduces energy consumption by a factor of 7 to 40, where a centralized unit or infrastructure is not required.We evaluate their performance using an experiment in which 10 individuals play 6 team sports and show that these activities are emergent in nature through natural processes.Centralized recognition performs very well, upwards of an F-score of 0.95 for large window sizes.



We introduce 2 novel algorithms for distributed probabilistic inference (DPI) of group activities using loopy belief propagation (LBP).The 18 edition of ISWC is scheduled to include dedicated workshops, a juried design competition, a lively gadget show, and high-quality paper presentation sessions revealing the latest in wearable computing progress. Humans are social beings and spend most of their time in groups.Group behavior is emergent, generated by members’ personal characteristics and their interactions.Much of the literature focuses on accurately profiling the power consumption of device components or enabling application developers to develop energy-efficient applications through fine-grained power profiling.

However,there is a lack of tools to enable users to extend battery life on demand.

It predicts the battery life savings based on the new configuration, in addition to predicting the impact of running applications on the battery life.



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