Enabling Green Crowdsourced Social Delivery Networks in Urban Communities
With the ever-increasing popularity of wearable devices, data on the time and location of popular walking, running, and bicycling routes is expansive and growing rapidly. These data are currently used primarily for route discovery and mobile context awareness, as it provides precise and updated info...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/4/1541 |
| _version_ | 1827652806968868864 |
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| author | Kevin Choi Luca Bedogni Marco Levorato |
| author_facet | Kevin Choi Luca Bedogni Marco Levorato |
| author_sort | Kevin Choi |
| collection | DOAJ |
| description | With the ever-increasing popularity of wearable devices, data on the time and location of popular walking, running, and bicycling routes is expansive and growing rapidly. These data are currently used primarily for route discovery and mobile context awareness, as it provides precise and updated information about urban dynamics. We leverage these data to build ad hoc transportation flows, and we present a novel model that creates delivery networks from these zero-emission transportation flows. We evaluate the model using data from two popular datasets, and our results indicate that such networks are indeed possible, and can help reduce traffic, emissions, and delivery times. Moreover, we demonstrate how our results can be consistently reproduced in different cities with different subsets of carriers. We then extend our work into predicting routes of vehicles, hence possible delivery flows, based on the traces history. We conclude this paper by laying the groundwork for a future real-world study. |
| first_indexed | 2024-03-09T21:06:20Z |
| format | Article |
| id | doaj.art-90e7d023f08d4008b5aabb4962405b10 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:06:20Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-90e7d023f08d4008b5aabb4962405b102023-11-23T22:01:21ZengMDPI AGSensors1424-82202022-02-01224154110.3390/s22041541Enabling Green Crowdsourced Social Delivery Networks in Urban CommunitiesKevin Choi0Luca Bedogni1Marco Levorato2Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USADepartment of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, 41125 Modena, ItalyDonald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USAWith the ever-increasing popularity of wearable devices, data on the time and location of popular walking, running, and bicycling routes is expansive and growing rapidly. These data are currently used primarily for route discovery and mobile context awareness, as it provides precise and updated information about urban dynamics. We leverage these data to build ad hoc transportation flows, and we present a novel model that creates delivery networks from these zero-emission transportation flows. We evaluate the model using data from two popular datasets, and our results indicate that such networks are indeed possible, and can help reduce traffic, emissions, and delivery times. Moreover, we demonstrate how our results can be consistently reproduced in different cities with different subsets of carriers. We then extend our work into predicting routes of vehicles, hence possible delivery flows, based on the traces history. We conclude this paper by laying the groundwork for a future real-world study.https://www.mdpi.com/1424-8220/22/4/1541mobile crowdsensingsmart cityperformance evaluation |
| spellingShingle | Kevin Choi Luca Bedogni Marco Levorato Enabling Green Crowdsourced Social Delivery Networks in Urban Communities Sensors mobile crowdsensing smart city performance evaluation |
| title | Enabling Green Crowdsourced Social Delivery Networks in Urban Communities |
| title_full | Enabling Green Crowdsourced Social Delivery Networks in Urban Communities |
| title_fullStr | Enabling Green Crowdsourced Social Delivery Networks in Urban Communities |
| title_full_unstemmed | Enabling Green Crowdsourced Social Delivery Networks in Urban Communities |
| title_short | Enabling Green Crowdsourced Social Delivery Networks in Urban Communities |
| title_sort | enabling green crowdsourced social delivery networks in urban communities |
| topic | mobile crowdsensing smart city performance evaluation |
| url | https://www.mdpi.com/1424-8220/22/4/1541 |
| work_keys_str_mv | AT kevinchoi enablinggreencrowdsourcedsocialdeliverynetworksinurbancommunities AT lucabedogni enablinggreencrowdsourcedsocialdeliverynetworksinurbancommunities AT marcolevorato enablinggreencrowdsourcedsocialdeliverynetworksinurbancommunities |