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Delivery Route Optimization Through Occupancy Prediction from Electricity Usage

机译:通过用电量的占空预测优化输送路线

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20% of home parcel delivery is redelivery due to absence, which is estimated to cost $ billions a year in Japan. On the other hand, government is proceeding initiative to install smart meters for all households in Tokyo by 2020, and for all households in Japan by 2024. Considering those two factors, in this research, we built up future occupancy predictor for households with valid accuracy from electricity usage data which can be obtained from a smart meter, and we showed how a new routing algorithm equipped with this predictor can reduce home parcel absent delivery by 87.5%. Significant reduction of absent delivery indicates a great amount of time saved for the industry.
机译:由于缺席,有20%的家庭包裹要交还,据估计在日本每年要花费数十亿美元。另一方面,政府正在采取措施,到2020年在东京所有家庭和2024年在日本所有家庭安装智能电表。在这两个因素的考虑下,我们在研究中建立了有效准确性的未来家庭用电预测器从可以从智能电表获得的用电量数据中,我们展示了配备此预测器的新路由算法如何将缺少包裹的家庭包裹减少87.5%。大大减少了缺席交付时间,这表明该行业节省了大量时间。

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