2016
DOI: 10.1155/2016/7283831
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Context-Aware Mobile Sensors for Sensing Discrete Events in Smart Environment

Abstract: Over the last few decades, several advancements in the field of smart environment gained importance, so the experts can analyze ideas for smart building based on embedded systems to minimize the expense and energy conservation. Therefore, propelling the concept of smart home toward smart building, several challenges of power, communication, and sensors’ connectivity can be seen. Such challenges distort the interconnectivity between different technologies, such as Bluetooth and ZigBee, making it possible to pro… Show more

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Cited by 7 publications
(2 citation statements)
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“…The proposed Viterbi-based Context-Aware Mobile Sensing mechanism optimizes sensing decisions by adaptively deciding when to trigger the sensors. For contextbased mobile sensing in smart building, [231] exploits low power sensors and proposes a model that enhances communication, data processing, and analytics. In [232], the authors propose a multidimensional context-aware social network architecture for MCS applications.…”
Section: Theoretical Work Operational Research and Optimizationmentioning
confidence: 99%
“…The proposed Viterbi-based Context-Aware Mobile Sensing mechanism optimizes sensing decisions by adaptively deciding when to trigger the sensors. For contextbased mobile sensing in smart building, [231] exploits low power sensors and proposes a model that enhances communication, data processing, and analytics. In [232], the authors propose a multidimensional context-aware social network architecture for MCS applications.…”
Section: Theoretical Work Operational Research and Optimizationmentioning
confidence: 99%
“…These sensors are connected through wireless communication to perform several tasks such as sensing, recognizing, and monitoring. These tasks are used in many applications, for example, object tracking [2], intruder detection [3], indoor fire detection [4] and human localization as well as activity recognition in indoor environments [5,6].…”
Section: Introductionmentioning
confidence: 99%