Multiple Region of Interest Coverage in Camera Sensor Networks for Tele-Intensive Care Units

Camera sensor networks (CSNs) are gradually being used in a tele-intensive care unit (tele-ICU), providing useful patient information to remote intensivists. Intensivists wish to focus on different regions of interest (RoIs) containing their patients. We consider a situation where preinstalled camer...

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Vydáno v:IEEE transactions on industrial informatics Ročník 12; číslo 6; s. 2331 - 2341
Hlavní autoři: Bo Cheng, Lin Cui, Weijia Jia, Wei Zhao, Gerhard, P. Hancke
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Camera sensor networks (CSNs)
Cameras
healthcare
Heuristic algorithms
Heuristic methods
Intensive care
Medical services
multiple RoI coverage (MRC)
Optimization
Patient monitoring
Performance degradation
Performance evaluation
Polynomials
Sensors
tele-intensive care unit (tele-ICU)
Telemedicine
ISSN:1551-3203, 1941-0050
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Shrnutí:Camera sensor networks (CSNs) are gradually being used in a tele-intensive care unit (tele-ICU), providing useful patient information to remote intensivists. Intensivists wish to focus on different regions of interest (RoIs) containing their patients. We consider a situation where preinstalled camera sensors' locations remain static and they can change the fields of view only by rotating orientations, while the RoIs are dynamically changed in location and size because of changes in the number of patients and care unit configuration. Therefore, an important issue is how to enhance the coverage of these RoIs by controlling the camera sensors' orientations. Previous studies on coverage optimization either focus on single area coverage or point(s) coverage. However, ignoring those multiple RoIs or simply treating them as points can cause unwanted coverage, resulting in performance degradation. In this paper, we investigate a novel multiple RoI coverage (MRC) problem in a CSN-based tele-ICU, aiming to maximize the lowest coverage ratio of all RoIs. The MRC problem is nondeterministic polynomial-time hard, so we propose an efficient heuristic algorithm MRC-Priority to solve it. We have implemented a CSN testbed to evaluate the performance of our proposed algorithm. Experimental results show that our proposed algorithm can improve the lowest coverage ratio up to 200% as compared with existing solutions.
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2016.2574305