Emerging AI and 6G-Based User Localization Technologies for Emergencies and Disasters

Abstract

This paper presents state-of-the-art user localization technologies that can effectively assist the authorities and first responders to localize individuals during emergency and disaster scenarios. Localization is an essential tool that ensures preparedness, response, and coordination between first responders and impacted people. Many of these technologies employ artificial intelligence techniques to improve the localization accuracy using the information collected by a variety of sensing equipment such as sensors, unmanned aerial vehicles, wireless access points, cameras, and smart load meters. The paper also highlights the emerging sixth-generation (6G) wireless technologies such as integrated sensing and localization, THz communications, satellite-based non-terrestrial networks, and reconfigurable intelligent surfaces that can modify the reflection properties of materials to enable device localization. These technologies are expected to play a key role in enabling emergency services. Other localization technologies include WiFi, Bluetooth, radio frequency identification, and long range wide area network. In addition, crowd sensing and smart meter-based non-intrusive load monitoring (NILM) techniques that are supported by deep learning and federated learning techniques are also presented in the context of device localization. To the best of our knowledge, this paper introduces NILM for the first time as a useful technique that can provide information about the inhabitants’ behaviour in residential and commercial buildings to assist in emergency and public safety applications. All the technologies reviewed in this paper can play an effective role in device localization, and are presented to serve as a foundation for researchers to further investigate and conduct research in this domain.

Topics & Concepts