Context-aware IoT search engine through fuzzy clustering: Search space restructuring and query resolution mechanisms

Abstract

As the technological landscape of ubiquitous computing continues to develop and increase in the variety of objects being connected to sensors, a number of smart applications and services are being evolved that offer consumer-centric functionalities and solutions across different sectors. Therefore the search for sensors with capacity to provide most meaningful facts becomes paramount. Leveraging the inherent contextual metadata associated with sensor deployments and user applications can facilitate the systematic identification and removal of redundant or obsolete sensor infrastructure within large-scale organizational environments. This work proposes a novel approach that incorporates the principles of fuzzy context oriented seek algorithm that maps the submitted user question to the maximum appropriate sensors available within the search space. We have used the weighted fuzzy c-way cluster set of rules to institution sensors of similar houses into one cluster. So, the consumer query is channeled to the most relevant cluster. We have performed experiments and as compared the end result with the existing search algorithm noted inside the literature to uplift its performance.