Advances in Sensory Systems for Unmanned Underwater Vehicles: A Preliminary Review

  • 1 AGH university of Krakow, Poland


Unmanned underwater vehicles (UUVs) are gaining traction in various fields, from oceanographic research to defence applications, due to their versatility and autonomy. This preliminary study explores the integration of Internet of Things (IoT) technology and beamforming techniques to enhance the sensory capabilities of UUVs. The study delves into the evolving landscape of sensory systems, emphasising the incorporation of IoT to enable seamless data exchange, real-time monitoring and adaptive decision making. It also examines the use of beamforming techniques in directional sonar sensing, highlighting their role in improving target detection, localisation and tracking capabilities in underwater environments. By synthesising current research and technological trends, this review provides valuable insights into the synergistic integration of IoT and beamforming techniques to enhance the capabilities of UUV sensor systems for diverse applications.



  1. Balestrieri, E., Daponte, P., de Vito, L., & Lamonaca, F. (2021). Sensors and Measurements for Unmanned Systems: An Overview. Sensors, 21(4).
  2. Kabanov, A., & Kramar, V. (2022). Marine Internet of Things Platforms for Interoperability of Marine Robotic Agents: An Overview of Concepts and Architectures. Journal of Marine Science and Engineering, 10(9).
  3. Zhang, W., Wei, S., Teng, Y., Zhang, J., Wang, X., & Yan, Z. (2017). Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method. Sensors, 17(12).
  4. Liu, W., & Weiss, S. (2010). Wideband beamforming: concepts and techniques. John Wiley & Sons.
  5. Luo, J., Han, Y., & Fan, L. (2018). Underwater Acoustic Target Tracking: A Review. Sensors, 18(1).
  6. Bovio, E., Cecchi, D., & Baralli, F. (2006). Autonomous underwater vehicles for scientific and naval operations. Annual Reviews in Control, 30(2), 117–130.
  7. Zhufeng, L., Xiaofang, L., Na, W., & Qingyang, Z. (2022). Present status and challenges of underwater acoustic target recognition technology: A review. Frontiers in Physics, 10, 1044890.
  8. Jahanbakht, M., Xiang, W., Hanzo, L., & Azghadi, M. R. (2021). Internet of underwater things and big marine data analytics—a comprehensive survey. IEEE Communications Surveys & Tutorials, 23(2), 904–956.
  9. Gannot, S., & Cohen, I. (2008). Adaptive beamforming and postfiltering. Springer Handbook of Speech Processing, 945–978.
  10. al Kassir, H., Zaharis, Z. D., Lazaridis, P. I., Kantartzis, N. v, Yioultsis, T. v, & Xenos, T. D. (2022). A review of the state of the art and future challenges of deep learning-based beamforming. IEEE Access, 10, 80869–80882

Article full text

Download PDF