Name
Abstract | ||
|---|---|---|
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 |
Year | Venue | Field |
|---|---|---|
2018 | COMPSAC | Metre,Computer science,Electricity,Real-time computing,Feature extraction,Occupancy,Smart meter,Usage data,Government,Routing algorithm |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shimpei Ohsugi | 1 | 0 | 0.34 |
| Noboru Koshizuka | 2 | 225 | 46.68 |