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We propose a novel Energy Loss Prediction(ELP) framework that estimates theenergy loss in sharing crowdsourced energy services. Crowdsourcing wirelessenergy services is a novel and convenient solution to enable the ubiquitouscharging of nearby IoT devices. Therefore, capturing the wireless energysharing loss is essential for the successful deployment of efficient energyservice composition techniques. We propose Easeformer, a novel attention-basedalgorithm to predict the battery levels of IoT devices in a crowdsourced energysharing environment. The predicted battery levels are used to estimate theenergy loss. A set of experiments were conducted to demonstrate the feasibilityand effectiveness of the proposed framework. We conducted extensive experimentson real wireless energy datasets to demonstrate that our frameworksignificantly outperforms existing methods.

Energy Loss Prediction in IoT Energy Services