LiDAR Technology for Human Activity Recognition: Outlooks and Challenges

Omar Rinchi, Hakim Ghazzai, Ahmad Alsharoa, Yehia Mahmoud Massoud

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The smart and autonomous learning and recognition of human activities will certainly lead to an incredible progression for several applications and services in public healthcare, education, entertainment, safety and security, and more. With the recent advances in artificial intelligence, signal processing, and computational capabilities, light detection and ranging (LiDAR) technology can play an instrumental role to revamp current human activity recognition (HAR) systems. In this magazine, we investigate the potential of using LiDAR sensors as a novel technology enabling complex and real-time HAR applications. We first overview the HAR categories and the existing state-of-the-art technologies: video-based cameras, depth sensors, wearable devices, and WiFi. Afterward, we delve into the integration of LiDAR technology to perform HAR applications. Then, we discuss the advantages and drawbacks of utilizing LiDAR technology for HAR and compare it with the existing techniques. Finally, we discuss the challenges that need to be addressed to enable advanced LiDAR-based HAR applications.
Original languageEnglish (US)
Pages (from-to)143-150
Number of pages8
JournalIEEE Internet of Things Magazine
Volume6
Issue number2
DOIs
StatePublished - Jun 6 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-06-14

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