Name
Abstract | ||
|---|---|---|
With the development of Internet of Things (IoT), heterogeneous sensory data appears everywhere in our lives. Unlike traditional sensory data, heterogeneous sensory data often involves variety modalities of data in one set, so that it is called as the multi-modal sensory data in this paper. The appearance of such data making it possible to monitor more complicated objects and improve monitoring accuracy. However, due to lack of integration model for multi-modal sensory data, most of the existing sensory data management algorithms only consider single modal sensory data, resulting in insufficient utilization of sensory data. Thus, we propose a model for integrating the heterogeneous sensory data generated in a IoT system based on Hidden Markov Process in the paper. The distributed algorithm for constructing such a model is then presented. The integration model can be applied to many applications, while we take the cooperative event detection as an example for illustration. The extensive theoretical analysis and experimental results show that all the proposed algorithms are efficient and effective . |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.comnet.2018.11.032 | Computer Networks |
Keywords | Field | DocType |
Heterogeneous,Multi-Modal sensory data,Internet of things,Integration | Modalities,Computer science,Internet of Things,Distributed algorithm,Sensory system,Hidden markov process,Data management,Modal,Distributed computing | Journal |
Volume | ISSN | Citations |
150 | 1389-1286 | 1 |
PageRank | References | Authors |
0.35 | 26 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siyao Cheng | 1 | 438 | 22.59 |
| Yingshu Li | 2 | 671 | 53.71 |
| Zhi Tian | 3 | 115 | 14.04 |
| Wei Cheng | 4 | 811 | 106.56 |
| Xiuzhen Cheng | 5 | 3238 | 210.23 |