Name
Abstract | ||
|---|---|---|
Mobile phones, vehicles, appliances, and other types of devices have sensors in the last few years. On the good side, this makes the world increasingly interconnected every day. However, this interconnection generates Big Data that cannot be processed using traditional tools because of its volume, variety, and speed. This paper contributes with a review of mobile sensing systems, including their applications, shortcomings, and opportunities. A taxonomy covering the different systems revised is proposed. Moreover, the main characteristics of mobile sensing architectures are explained and research-related works are studied into the context of these characteristics. Multi-agent systems (MASs) are considered as a perfect match to create large-scale, multi-device, and multi-purpose mobile sensing systems with the potential of obtaining information from heterogeneous devices, open sources, and social networks. Finally, the paper also contributes with the overview of a MAS architecture that aims to leverage these features while the studied dimensions observed in the reviewed literature are covered. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s10115-019-01346-1 | Knowledge and Information Systems |
Keywords | Field | DocType |
Mobile sensing, Multi-agent systems, Human agent societies, Social computing | Data mining,Mobile sensing,Architecture,Social network,Computer science,Multi-agent system,Social computing,Interconnection,Big data,Distributed computing | Journal |
Volume | Issue | ISSN |
62 | 1 | 0219-1377 |
Citations | PageRank | References |
1 | 0.35 | 55 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco Laport-López | 1 | 1 | 0.35 |
| Emilio Serrano | 2 | 121 | 12.53 |
| Javier Bajo | 3 | 1451 | 118.96 |
| Andrew T. Campbell | 4 | 8958 | 759.66 |