Building Robust Context Aware IoT Applications: Methods and Strategies for Detecting and Resolving Context Inconsistencies

The Internet of Things (IoT) has revolutionized connectivity, creating a vast network of interconnected devices that seamlessly exchange and analyze data. Within this dynamic IoT ecosystem, context-aware applications have emerged, enabling autonomous responses to events triggered by contextual information, thereby enhancing user experiences and facilitating intelligent decision-making. However, the utilization of contextual data in IoT applications has introduced a key challenge: context inconsistencies. Context inconsistency is defined as the condition in which contextual data collected from multiple sources is inaccurate, incomplete, or conflicting, leading to incorrect processing that may disrupt the behavior of context-aware applications. Context inconsistencies arise from various factors, including sensor noise, communication errors, and contradictory data sources (e.g., two motion detection sensors located in the same area may report different readings, where one sensor detects one person, and the other sensor detects three people). These inconsistencies can significantly impact the reliability and precision of IoT applications, potentially resulting in erroneous decisions and degraded user experiences. To address this critical concern, this research paper undertakes a comprehensive review of contemporary methodologies developed for detecting and resolving context inconsistencies in IoT environments. This study explores various strategies, discusses their features in detail, and contributes by classifying them into different categories for better understanding. Through a detailed examination of the effectiveness, strengths, and limitations of each classified method, the paper aims to offer valuable insights into managing context inconsistencies in IoT applications. More precisely, this paper serves as a valuable resource for researchers, practitioners, and industry professionals in the IoT domain, providing them with a comprehensive understanding of context inconsistency detection and resolution methods