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Delivery route optimization through occupancy prediction from electricity usage

机译:通过电力使用的占用预测递送路线优化

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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,20%的家庭包裹交付是重新交付,估计日本每年花费数十亿美元。另一方面,政府正在进行主动于2020年到2020年的东京所有家庭安装智能电表,并为日本的所有家庭到2024年。考虑到这项研究,我们为具有有效准确性的家庭建立了未来的占用预测因素从可以从智能仪表获得的电力使用数据,我们展示了如何使用此预测器的新路由算法可以减少回家包裹缺席87.5%。无缺乏交货的显着减少表明为该行业提供了大量时间。

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