The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
A Collaborative Internet of Things Architecture for Smart Cities and Environmental Monitoring
Open accessAbstract
The collaborative Internet of Things (C-IoT) is an emerging paradigm that involves many communities with the idea of cooperating in data gathering and service sharing. Many fields of application, such as smart cities and environmental monitoring, use the concept of crowdsensing in order to produce the amount of data that such Internet of Things (IoT) scenarios need in order to be pervasive. In this paper we introduce an architecture, namely SenSquare, able to handle both the heterogeneous data sources coming from open IoT platform and crowdsensing campaigns, and display a unified access to users. We inspect all the facets of such a complex system, spanning over issues of different nature: we deal with heterogeneous data classification, mobile crowdsensing management for environmental data, information representation, and unification, IoT service composition and deployment. We detail our proposed solution in dealing with such tasks and present possible methods for meeting open challenges. Finally, we demonstrate the capabilities of SenSquare through both a mobile and a desktop client.
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Cites
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Cited by
Internet of Things is a revolutionary approach for future technology enhancement: a review
Kumar, S., Tiwari, P., & Zymbler, M. (2019) · Journal of Big Data · doi:10.1186/s40537-019-0268-2 · Cited by 1,253
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
Capponi, A., Fiandrino, C., Kantarci, B., Foschini, L., Kliazovich, D., & Bouvry, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2914030 · Cited by 594
Internet of Things applications: A systematic review
Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019) · Computer Networks · doi:10.1016/j.comnet.2018.12.008 · Cited by 589
Future Trends and Current State of Smart City Concepts: A Survey
Kirimtat, A., Krejcar, O., Kertesz, A., & Tasgetiren, M. F. (2020) · IEEE Access · doi:10.1109/access.2020.2992441 · Cited by 452
Hamid, R. A., Albahri, A. S., Alwan, J. K., Al-qaysi, Z. T., Albahri, O. S., Zaidan, A. A., Alnoor, A., Alamoodi, A. H., & Zaidan, B. B. (2021) · Computer Science Review · doi:10.1016/j.cosrev.2020.100337 · Cited by 273
Metadata
- Authors
- Montori, F., Bedogni, L., & Bononi, L.
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-04
- Volume
- 5
- Issue
- 2
- Pages
- 592-605
- ISSN
- 2327-4662 (ISSN-L)
- OpenAlex
- W2729523886
- Cited by
- 282
- References
- 30
- FWCI
- 35.51
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
