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Crowd tracking and monitoring middleware via Map-Reduce
- Publication Year :
- 2022
-
Abstract
- This paper presents the design, implementation, and operation of a novel distributed fault-tolerant middleware. It uses interconnected WSNs that implement the Map-Reduce paradigm, consisting of several low-cost and low-power mini-computers (Raspberry Pi). Specifically, we explain the steps for the development of a novice, fault-tolerant Map-Reduce algorithm which achieves high system availability, focusing on network connectivity. Finally, we showcase the use of the proposed system based on simulated data for crowd monitoring in a real case scenario, i.e., a historical building in Greece (M. Hatzidakis' residence).The technical novelty of this article lies in presenting a viable low-cost and low-power solution for crowd sensing without using complex and resource-intensive AI structures or image and video recognition techniques.<br />Comment: 18 pages, 7 figures, 4 tables, 23 references, This is an Accepted Manuscript of an article published by Taylor & Francis Group in the International Journal of Parallel, Emergent & Distributed Systems on 2022, available online: http://www.tandfonline.com/10.1080/17445760.2022.2034163
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2201.09550
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1080/17445760.2022.2034163