Detecting Context Inconsistencies in Context-aware IoT Applications

Abstract

The Internet of Things (IoT) is a rapidly growing technology that is transforming various domains such as smart homes, smart cities, healthcare, and transportation. IoT is the system of interconnected devices connecting to the internet to transfer and receive data with each other. IoT has developed in the number of context-aware applications where IoT applications automatically response to events triggered by contextual information, hence this feature can enhance user experience and facilitate the system with intelligent decision-making.  IoT context aware applications are heavily rely on the contextual information to operate intelligently, therefore there is the growing demand for robust solutions to address the challenge of context inconsistencies. Inaccurate, incomplete or mismatched context readings from multiple sensors, is termed as context inconsistency. This context inconsistency in IoT applications can arise due to several factors, such as sensor noise, communication errors, and conflicting data from different sources. These inconsistencies can lead to inaccurate data processing, which can result in poor decision making and may cause damage in terms of time, labor, cost and even cause life threats. To address this critical issue, in this paper we propose an approach that detects context inconsistency in IoT. Further, the implementation of the proposed system is also presented in the paper.