Drones as internet of video things front-end sensors: challenges and opportunities
Tóm tắt
Internet of Video Things (IoVT) has become an emerging class of IoT systems that are equipped with visual sensors at the front end. Most of such visual sensors are fixed one whereas the drones are considered flying IoT nodes capable of capturing visual data continuously while flying over the targets of interest. With such a dynamic operational mode, we can imagine significant technical challenges in sensor data acquisition, information transmission, and knowledge extraction. This paper will begin with an analysis on some unique characteristics of IoVT systems with drones as its front end sensors. We shall then discuss several inherent technical challenges for designing drone-based IoVT systems. Furthermore, we will present major opportunities to adopt drone-based IoVT in several contemporary applications. Finally, we conclude this paper with a summary and an outlook for future research directions.
Tài liệu tham khảo
Chen CW. Internet of video things: next-generation IoT with visual sensors. IEEE Internet Things J. 2020;7(8):6676–85. https://doi.org/10.1109/JIOT.2020.3005727.
Genc H, Zu Y, Chin T, Halpern M, Reddi VJ. Flying IoT: toward low-power vision in the sky. IEEE Micro. 2017;37(6):40–51. https://doi.org/10.1109/MM.2017.4241339.
Mishra B, Garg D, Narang P, Mishra V. Drone-surveillance for search and rescue in natural disaster. Computer Commun. 2020;156:1–10. https://doi.org/10.1016/j.comcom.2020.03.012 (ISSN 0140-3664).
Narang M, Liu W, Gutierrez J, Chiaraviglio L. A cyber physical buses-and-drones mobile edge infrastructure for large scale disaster emergency communications. In: 2017 IEEE 37th international conference on distributed computing systems workshops (ICDCSW), Atlanta, GA; 2017. p. 53–60. https://doi.org/10.1109/ICDCSW.2017.41
Khalid NIM, Zakaria SNAS, Yusoff Z, Marzukhi S. Ensuring communication for command and control in Search and Rescue (SAR) operations using smart phones for audio, video and monitoring functions. In: 2016 international conference on information and communication technology (ICICTM), Kuala Lumpur; 2016. p. 15–18. https://doi.org/10.1109/ICICTM.2016.7890768.
Wang J, et al. Edge-based live video analytics for drones. IEEE Internet Comput. 2019;23(4):27–34. https://doi.org/10.1109/MIC.2019.2909713.
Chen P, Dang Y, Liang R, Zhu W, He X. Real-Time Object Tracking on a Drone With Multi-Inertial Sensing Data. IEEE Trans Intell Transp Syst. 2018;19(1):131–9. https://doi.org/10.1109/TITS.2017.2750091.
Sato M, Iwase M. Semi-autonomous flight control of forestry-use drone. In: 2019 58th annual conference of the society of instrument and control engineers of Japan (SICE), Hiroshima, Japan; 2019. p. 1232-1235. https://doi.org/10.23919/SICE.2019.8859900
Yamamoto N, Uchida N. Improvement of image processing for a collaborative security flight control system with multiple drones. In: 2018 32nd international conference on advanced information networking and applications workshops (WAINA), Krakow; 2018. p. 199–202. https://doi.org/10.1109/WAINA.2018.00087
Ki M, Cha J, Lyu H. Detect and avoid system based on multi sensor fusion for UAV. In: 2018 international conference on information and communication technology convergence (ICTC), Jeju; 2018. p. 1107–1109. https://doi.org/10.1109/ICTC.2018.8539587
Chen W, Liu J, Guo H, Kato N. Toward robust and intelligent drone swarm: challenges and future directions. IEEE Netw. 2020;34(4):278–83. https://doi.org/10.1109/MNET.001.1900521.
Yanmaz E, Yahyanejad S, Rinner B, Hellwagner H, Bettstetter C. Drone networks: communications, coordination, and sensing. Ad Hoc Netw. 2018;68:1–15. https://doi.org/10.1016/j.adhoc.2017.09.001 (ISSN 1570-8705).
Molla DM, Badis H, Desta AA, George L, Berbineau M. SDR-based reliable and resilient wireless network for disaster rescue operations. In: 2019 international conference on information and communication technologies for disaster management (ICT-DM), Paris, France; 2019. p. 1–7. https://doi.org/10.1109/ICT-DM47966.2019.9032987.
Qin Y, Kishk MA, Alouini M-S. Performance evaluation of UAV-enabled cellular networks with battery-limited drones. IEEE Commun Lett. 2020;24(12):2664–8. https://doi.org/10.1109/LCOMM.2020.3013286.
Bouras MA, Farha F, Ning H. Convergence of computing, communication, and caching in Internet of Things. Intell Converged Netw. 2020;1(1):18–36. https://doi.org/10.23919/ICN.2020.0001.
Messous MA, Hellwagner H, Senouci S, Emini D, Schnieders D. Edge computing for visual navigation and mapping in a UAV network. ICC 2020—2020 ieee international conference on communications (ICC), Dublin, Ireland; 2020, p. 1–6. https://doi.org/10.1109/ICC40277.2020.9149087.
Yao J, Ansari N. Online task allocation and flying control in fog-aided internet of drones. IEEE Trans Veh Technol. 2020;69(5):5562–9. https://doi.org/10.1109/TVT.2020.2982172.
Wu D, Sun X, Ansari AN. An FSO-based drone assisted mobile access network for emergency communications. IEEE Trans Netw Sci Eng. 2020;7(3):1597–606. https://doi.org/10.1109/TNSE.2019.2942266.
Drones for deliveries from medicine to post, Packages And Pizza, by Fintan Corrigan, July 2, 2020, https://www.dronezon.com/drones-for-good/drone-parcel-pizza-delivery-service/, Accessed on January 18, 2021
Zubin I, van Arem B, Wiegmans B, van Duin R. Using drones in the last-mile logistics processes of medical product delivery: a feasibility case study in Rotterdam. In: Proceedings of the 99th annual meeting TRB. Transportation Research Board (TRB); 2020. p. 1–17.
Claesson A, Bäckman A, Ringh M, et al. Time to delivery of an automated external defibrillator using a drone for simulated out-of-hospital cardiac arrests vs emergency medical services. JAMA. 2017;317(22):2332–4. https://doi.org/10.1001/jama.2017.3957.
Pulver A, Wei R, Mann C. Locating AED enabled medical drones to enhance cardiac arrest response times. Prehospital Emerg Care. 2016;20(3):378–89. https://doi.org/10.3109/10903127.2015.1115932 (Epub 2016 Feb 6. PMID: 26852822).
Euchi J. Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems? Chin J Aeronaut. 2020. https://doi.org/10.1016/j.cja.2020.06.006 (ISSN 1000-9361).
Iastrebov V, Wong CY, Pang WC, Seet G. Motion tracking drone for extreme sports filming. In: 1st international conference in sports science & technology (ICSST 2014). https://hdl.handle.net/10356/138183
Hebbel-Seeger A, Horky T, Theobalt C. Usage of drones in sports communication—new aesthetics and enlargement of space. Athens J Sports. 2017;4(2):89–106. https://doi.org/10.30958/ajspo.4.2.1.
Karungaru S, Matsuura K, Tanioka H, Wada T, Gotoda N. Ground sports strategy formulation and assistance technology develpoment: player data acquisition from drone videos. In: 2019 8th international conference on industrial technology and management (ICITM), Cambridge, United Kingdom; 2019. p. 322–325. https://doi.org/10.1109/ICITM.2019.8710735.
Elder Akpa, Kazuki Fujisawa, Cedric Konan, Marko Trono, William Brou and Keiichi Yasumoto, CuraCopter—automated player tracking and video curating system by using UAV for sport sessions. IPSJ SIG Technical Report, vol. 2015-MBL-77 No. 7, 2015
Bravo GC, Parra DM, Mendes L, de Jesus Pereira AM. First aid drone for outdoor sports activities. In: 2016 1st international conference on technology and innovation in sports, health and wellbeing (TISHW), Vila Real; 2016. p. 1–5. https://doi.org/10.1109/TISHW.2016.7847781.
Dinesh Kumar G, Jeeva B. Drone Ambulance for Outdoor Sports. Asian J Appl Sci Technol (AJAST). 2017;1(5):44–9.
Lou Y, et al. Front-end smart visual sensing and back-end intelligent analysis: a unified infrastructure for economizing the visual system of city brain. IEEE J Sel Areas Commun. 2019;37(7):1489–503. https://doi.org/10.1109/JSAC.2019.2916488.