Abstract
Context-awareness develops smart, intelligent IoT devices that can adapt to changing needs and act autonomously on behalf of the user. The main challenge of context-aware internet of things is to interpret the context effectively. There is an abundance of CAIOT in literature. Understanding of the meaning of the context is, however, almost ignored. Misinterpretation of context can lead to an incorrect decision that motivates to develop a system that emphasis context reasoning and decision making using the fuzzy Bayesian approach. The current investigation aims to build a context-aware IoT system using occupancy detection for energy management. The performance evaluation for the proposed system uses data collected in the tutorial room to detect occupancy. Extensive experiments highlight the utility of the proposed approach, which significantly reduces energy than the traditional ON/OFF usage pattern through customer access via mobile phone or personal computer.
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