A Survey of Indoor and Outdoor UAV-Based Target Tracking Systems: Current Status, Challenges, Technologies, and Future Directions

Mohannad Alhafnawi, Haythem A. Bany Salameh, Ala'eddin Masadeh, Haitham Al-Obiedollah, Moussa Ayyash, Reyad El-Khazali, Hany Elgala

    Research output: Contribution to journalArticlepeer-review

    32 Scopus citations

    Abstract

    Due to their distinctive features, unmanned aerial vehicles (UAVs) have been recently exploited to support a wide range of applications. The features include low maintenance cost, compact size, and excellent capability of maneuvering. In particular, UAVs have the potential capabilities to support different technologies such as Internet-of-things (IoT) devices, sensors, cameras, and systems, thus, performing civilian, target tracking, industrial, and military applications. Specifically, target tracking has been recently configured as one of the most attractive applications of UAVs. With this, UAVs estimate and detect the behavior or locate a moving or a stationary item. Accordingly, several research efforts have been conducted to investigate the promising capabilities of UAVs in target-tracking missions, including indoor and outdoor tracking missions. This paper surveys UAV-based target tracking and monitoring for indoor and outdoor environments, where the deployment scenarios of such UAV-based systems are characterized and investigated. Furthermore, we discuss a set of practical design challenges of UAV-based target tracking systems, and thus, we provide a set of potential solutions to deal with these challenges. Specifically, we present a set of recent enabling technologies that might be integrated into UAV target tracking systems, including machine learning (ML), cloud computing, and emerging fifth-generation (5G) technologies. We also demonstrate a use-case scenario in which ML is used to facilitate indoor target tracking and monitoring. Finally, future research directions are outlined that can help in improving the efficiency of the UAV-based target-tracking systems.

    Original languageBritish English
    Pages (from-to)68324-68339
    Number of pages16
    JournalIEEE Access
    Volume11
    DOIs
    StatePublished - 2023

    Keywords

    • artificial intelligence (AI)
    • drones
    • indoor/outdoor deployment
    • Target tracking systems
    • uncertain movement

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