Localization Context-Aware Models for Wireless Sensor Network

Abstract

Wireless sensor networks (WSNs) are emerging as the key technology to support the Internet of Things (IoT) and smart objects. Small devices with low energy consumption and limited computing resources have wide use in many applications and different fields. Nodes are deployed randomly without a priori knowledge of their location. However, location context is a fundamental feature necessary to provide a context-aware framework to information gathered from sensors in many services such as intrusion detection, surveillance, geographic routing/forwarding, and coverage area management. Nevertheless, only a little number of nodes called anchors are equipped with localization components, such as Global Positioning System (GPS) chips. Worse still, when sensors are deployed in an indoor environment, GPS serves no purpose. This chapter surveys a variety of state-of-the-art existing localization techniques and compares their characteristics by detailing their applications, strengths, and challenges. The specificities and enhancements of the most popular and effective techniques are as well reported. Besides, current research directions in localization are discussed.

An Accurate Anchor-Free Contextual Received Signal Strength Approach Localization in a Wireless Sensor Network

“…Anchor-based methods rely on nodes with known positions to assist in the localization process, offering high accuracy but often at the cost of reduced flexibility and increased operational expenses. In contrast, anchor-free methods, which do not depend on predefined anchor positions, offer greater flexibility and scalability, making them increasingly popular in dynamic and large-scale deployment scenarios [ 3 , 4 , 5 ].…”

Gaussian-newton Localization Through Multilateration Algorithm for Wireless Sensor Networks

“…The ANs in WSNs are equipped with GPS chips but it has disadvantages in indoor applications and networks deployed in hard to reach areas. Therefore, localization algorithms that are independent of GPS information are essential in computing the locations of sensor nodes [1].…”