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Research Topics in Context-Aware Computing for IoT

Research Topics in Context-Aware Computing for IoT

PhD Thesis Topics in Context-Aware Computing for IoT

   The context-aware computing models connect the realistic IoT information to the ambient intelligence through various computing strategies. It adapts human situations to the smart world by using hardware and software. Generally, the contexts are classified into core and domain-specific. The core contexts are general for all IoT applications, whereas the domain-specific contexts are only used in specific domains. The acquisition, understanding, abstraction, and reorganization are the main concerns that context-aware computing faces. The context is classified under five physical categories, computing, user, temporal and structural.
   Additionally, three methods are used to build the context-aware computing models, which are application-level context models, implicit context models, and explicit context models. Quality of Context (QoC) plays a key role in context-aware computing of IoT. The QoC context metrics are used to accomplish the desired level of performance in IoT-based applications.