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

本论文提出了一种称为 Energy Loss Prediction（ELP）的框架，用于估计共享众包能源服务中的能量损失。 提出了一种名为 Easeformer 的新型基于注意力机制的算法，用于在共享能源环境中预测物联网设备的电池电量，从而估计能量损失。 通过实验验证，该框架优于现有方法。