| dc.contributor.author | Fiandrino, Claudio | |
| dc.contributor.author | Capponi, Andrea | |
| dc.contributor.author | Kliazovich, Dzmitry | |
| dc.contributor.author | Bouvry, Pascal | |
| dc.date.accessioned | 2021-07-13T09:41:26Z | |
| dc.date.available | 2021-07-13T09:41:26Z | |
| dc.date.issued | 2020-02 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12761/793 | |
| dc.description.abstract | Smart cities take advantage of information and communication technology developments to provide added value to existing public services and improve citizens' quality of life. Mobile crowdsensing (MCS) has become, in the last few years, one of the most prominent paradigms for urban sensing. The citizens actively participate in the sensing process by contributing data with their mobile devices. To produce data, citizens sustain costs, that is, the mobile devices consume energy for sensing and reporting operations. This chapter emphasizes the role of energy management in MCS by assessing the performance of multiple data-collection frameworks and presents the applicability of MCS in a smart public street lighting scenario. | |
| dc.publisher | Elsevier | |
| dc.relation.ispartofseries | Micro and Nano Technologies | |
| dc.title | Chapter 32 - Crowdsensing architectures for smart cities | |
| dc.type | book part | |
| dc.identifier.url | http://www.sciencedirect.com/science/article/pii/B978012819870400030X | |
| dc.book.title | Nanosensors for Smart Cities | |
| dc.page.final | 542 | |
| dc.page.initial | 527 | |
| dc.subject.keyword | Mobile crowdsensing | |
| dc.subject.keyword | urban sensing | |
| dc.subject.keyword | smart cities | |
| dc.subject.keyword | energy efficiency | |
| dc.subject.keyword | data collection | |
| dc.description.refereed | TRUE | |
| dc.description.status | pub | |
| dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/2109 | |
