Hybrid Localization Algorithm for Accurate Indoor Estimation based IoT Services
The Internet of Things (IoT) has been known to have several applications which have a significant and direct effect on our everyday life as an emerging services such as tracking, monitoring and positioning services. One of the most prominent services was Localization where several algorithms have been utilized for different localization issues and based on different measurement methods. However, these presented algorithm would have a major two drawback points represented by the lower accuracy or the higher implementation cost. Meanwhile, Indoor environment was another significant challenge facing these algorithms due to several complexities related with such environments. As a result, in this paper it has been proposed a localization algorithm known as (HILA). Such algorithm would be worked based on the measurement of both Received Signal Strength (RSS) and Angle-of-Arrival (AoA). The results obtained from our HILA showed a significant higher accuracy with indoor environment localization and the average ranging error (0.04, 0.17) for the overall estimated locations.