A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 7 Issue 5
Sep.  2020

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 6.171, Top 11% (SCI Q1)
    CiteScore: 11.2, Top 5% (Q1)
    Google Scholar h5-index: 51, TOP 8
Turn off MathJax
Article Contents
Abenezer Girma, Niloofar Bahadori, Mrinmoy Sarkar, Tadewos G. Tadewos, Mohammad R. Behnia, M. Nabil Mahmoud, Ali Karimoddini and Abdollah Homaifar, "IoT-Enabled Autonomous System Collaboration for Disaster-Area Management," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1249-1262, Sept. 2020. doi: 10.1109/JAS.2020.1003291
Citation: Abenezer Girma, Niloofar Bahadori, Mrinmoy Sarkar, Tadewos G. Tadewos, Mohammad R. Behnia, M. Nabil Mahmoud, Ali Karimoddini and Abdollah Homaifar, "IoT-Enabled Autonomous System Collaboration for Disaster-Area Management," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1249-1262, Sept. 2020. doi: 10.1109/JAS.2020.1003291

IoT-Enabled Autonomous System Collaboration for Disaster-Area Management

doi: 10.1109/JAS.2020.1003291
Funds:  This work was supported partially by Air Force Research Laboratory, the Office of the Secretary of Defense (OSD) (FA8750-15-2-0116), the National Science Foundation (NSF) (1832110), and the National Institute of Aerospace and Langley (C16-2B00-NCAT)
More Information
  • Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits cause delays in response time, resulting in fatality and property damage. In this paper, we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster. The framework consists of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), a cloud-based remote control station (RCS). A light-weight message queuing telemetry transport (MQTT) based communication is adopted for facilitating collaboration between autonomous systems. To effectively work under unfavorable disaster conditions, antenna tracker is developed as a tool to extend network coverage to distant areas, and mobile charging points for the UAVs are also implemented. The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language (AADL). Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols, and the implemented UAV control mechanisms are functioning properly. Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.

     

  • loading
  • 1 https://github.com/Abeni18/IoT-Enabled-Autonomous-UAV-UGV
    2 https://clearpathrobotics.com/jackal-small-unmanned-ground-vehicle/
    3 https://www.vicon.com
    4 https://www.ibm.com/cloud
    5 https://mosquitto.org/
    6 https://osate.org/
    7 https://www.wireshark.org/
  • [1]
    P. Pace, G. Aloi, G. Caliciuri, and G. Fortino, “A mission-oriented coordination framework for teams of mobile aerial and terrestrial smart objects,” Mobile Netw. Appl., vol. 21, no. 4, pp. 708–725, Aug. 2016. doi: 10.1007/s11036-016-0726-4
    [2]
    O. Briante, V. Loscri, P. Pace, G. Ruggeri, and N. R. Zema, “Comvivor: An evolutionary communication framework based on survivors’ devices reuse,” Wirel. Per. Commun., vol. 85, no. 4, pp. 2021–2040, Dec. 2015. doi: 10.1007/s11277-015-2888-y
    [3]
    M. Erdelj and E. Natalizio, “UAV-assisted disaster management: Applications and open issues,” in Proc. Int. Conf. Computing, Networking and Communications, Kauai, USA, 2016, pp. 1–5.
    [4]
    K. Nagatani, S. Kiribayashi, Y. Okada, K. Otake, K. Yoshida, S. Tadokoro, T. Nishimura, T. Yoshida, E. Koyanagi, M. Fukushima, and S. Shinji Kawatsuma, “Gamma-ray irradiation test of electric components of rescue mobile robot quince,” in Proc. IEEE Int. Symp. Safety, Security, and Rescue Robotics, Kyoto, Japan, 2011, pp. 56–60.
    [5]
    M. Li, K. J. Lu, H. Zhu, M. Chen, S. W. Mao, and B. Prabhakaran, “Robot swarm communication networks: Architectures, protocols, and applications,” in Proc. 3rd Int. Conf. Communications and Networking in China, Hangzhou, China, 2008, pp. 162–166.
    [6]
    I. Kassabalidis, M. A. El-Sharkawi, R. J. Marks, P. Arabshahi, and A. A. Gray, “Swarm intelligence for routing in communication networks,” in Proc. IEEE Global Telecommunications Conf., San Antonio, USA, 2001, pp. 3613–3617.
    [7]
    S. B. Hadj, S. Rekhis, N. Boudriga, and A. Bagula, “A cloud of UAVs for the delivery of a sink as a service to terrestrial WSNs,” in Proc. 14th Int. Conf. Advances in Mobile Computing and Multi Media, Singapore, 2016, pp. 317–326.
    [8]
    V. Sharma and R. Kumar, “Cooperative frameworks and network models for flying ad hoc networks: A survey,” Concurr. Comput. Pract. Exp., vol. 29, no. 4, pp. e3931, Feb. 2017. doi: 10.1002/cpe.3931
    [9]
    X. Li, D. N. Guo, H. R. Yin, and G. Wei, “Drone-assisted public safety wireless broadband network,” in Proc. IEEE Wireless Communications and Networking Conf. Workshops, New Orleans, USA, 2015, pp. 323–328.
    [10]
    N. Bezzo, B. Griffin, P. Cruz, J. Donahue, R. Fierro, and J. Wood, “A cooperative heterogeneous mobile wireless mechatronic system,” IEEE/ASME Trans. Mech., vol. 19, no. 1, pp. 20–31, Feb. 2012.
    [11]
    F. Flammini, C. Pragliola, and G. Smarra, “Railway infrastructure monitoring by drones,” in Proc. Int. Conf. Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & Int. Transportation Electrification Conf., Toulouse, France, 2016, pp. 1–6.
    [12]
    T. Yokotani and Y. Sasaki, “Comparison with HTTP and MQTT on required network resources for IoT,” in Proc. Int. Conf. Control, Electronics, Renewable Energy and Communications, Bandung, Indonesia, 2016, pp. 1–6.
    [13]
    N. Naik, “Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP,” in Proc. IEEE Int. Systems Engineering Symp., Vienna, Austria, 2017, pp. 1–7.
    [14]
    H. J. Yu and Y. Yang, “Latency analysis of automobile ABS based on AADL,” in Proc. Int. Conf. Industrial Control and Electronics Engineering, Xi’an, China, 2012, pp. 1835–1838.
    [15]
    M. Munoz, “Space systems modeling using the architecture analysis & design language (AADL),” in Proc. IEEE Int. Symp. Software Reliability Engineering Workshops, Pasadena, USA, 2013, pp. 97–98.
    [16]
    T. Zhang, Y. C. Jiang, J. D. Ye, C. Jing, and H. M. Qu, “An AADL model-based safety analysis method for flight control software,” in Proc. Int. Conf. Computational Intelligence and Communication Networks, Bhopal, India, 2014, pp. 1148–1152.
    [17]
    J. Penders, L. Alboul, U. Witkowski, A. Naghsh, J. Saez-Pons, S. Herbrechtsmeier, and M. El-Habbal, “A robot swarm assisting a human fire-fighter,” Adv. Robot., vol. 25, no. 1−2, pp. 93–117, 2011. doi: 10.1163/016918610X538507
    [18]
    R. Ventura and P. U. Lima, “Search and rescue robots: The civil protection teams of the future,” in Proc. 3rd Int. Conf. Emerging Security Technologies. Lisbon, Portugal, 2012, pp. 12–19.
    [19]
    A. Ollero, J. Alcazar, F. Cuesta, F. Lopez-Pichaco, and C. Nogales, “Helicopter teleoperation for aerial monitoring in the comets multi-UAV system,” in Proc. 3rd IARP Workshop on Service, Assistive and Personal Robots, Madrid, Spain, 2003.
    [20]
    J. H. Hong, B. C. Min, J. M. Taylor, V. Raskin, and E. T. Matson, “NL-based communication with firefighting robots,” in Proc. IEEE Int. Conf. Systems, Man, and Cybernetics. Seoul, South Korea, 2012, pp. 1461–1466.
    [21]
    L. Gupta, R. Jain, and G. Vaszkun, “Survey of important issues in UAV communication networks,” IEEE Communications Surveys &Tutorials, vol. 18, no. 2, pp. 1123–1152, 2016.
    [22]
    E. P. De Freitas, T. Heimfarth, I. F. Netto, C. E. Lino, C. E. Pereira, A. M. Ferreira, F. R. Wagner, and T. Larsson, “UAV relay network to support WSN connectivity,” in Proc. Int. Congr. Ultra Modern Telecommunications and Control Systems, Moscow, Russia, 2010, pp. 309–314.
    [23]
    W. T. L. Teacy, J. Nie, S. McClean, and G. Parr, “Maintaining connectivity in UAV swarm sensing,” in Proc. IEEE Globecom Workshops, Miami, USA, 2010, pp. 1771–1776.
    [24]
    D. Orfanus, E. P. de Freitas, and F. Eliassen, “Self-organization as a supporting paradigm for military UAV relay networks,” IEEE Commun. Lett., vol. 20, no. 4, pp. 804–807, Apr. 2016. doi: 10.1109/LCOMM.2016.2524405
    [25]
    G. Fortino, W. Russo, C. Savaglio, W. M. Shen, and M. C. Zhou, “Agent-oriented cooperative smart objects: From IoT system design to implementation,” IEEE Trans. Syst. Man Cybern. Syst., vol. 48, no. 11, pp. 1939–1956, Nov. 2018. doi: 10.1109/TSMC.2017.2780618
    [26]
    C. Savaglio, M. Ganzha, M. Paprzycki, C. Bǎdicǎ, M. Ivanović, and G. Fortino, “Agent-based internet of things: State-of-the-art and research challenges,” Future Generat. Comput. Syst., vol. 102, pp. 1038–1053, Jan. 2020. doi: 10.1016/j.future.2019.09.016
    [27]
    K. Sundaresan, E. Chai, A. Chakraborty, and S. Rangarajan, “Skylite: End-to-end design of low-altitude UAV networks for providing LTE connectivity,” arXiv preprint arXiv: 1802.06042, 2018.
    [28]
    S. A. R. Naqvi, S. A. Hassan, H. Pervaiz, and Q. Ni, “Drone-aided communication as a key enabler for 5G and resilient public safety networks,” IEEE Commun. Mag., vol. 56, no. 1, pp. 36–42, Jan. 2018. doi: 10.1109/MCOM.2017.1700451
    [29]
    W. S. Shi, H. B. Zhou, J. L. Li, W. C. Xu, N. Zhang, and X. M. Shen, “Drone assisted vehicular networks: Architecture, challenges and opportunities,” IEEE Netw., vol. 32, no. 3, pp. 130–137, May/Jun. 2018. doi: 10.1109/MNET.2017.1700206
    [30]
    A. Girma, X. Y. Yan, and A. Homaifar, “Driver identification based on vehicle telematics data using LSTM-recurrent neural network,” arXiv preprint arXiv: 1911.08030, 2019.
    [31]
    A. Girma, S. Amsalu, A. Workineh, M. Khan, and A. Homaifar, “Deep learning with attention mechanism for predicting driver intention at intersection,” arXiv preprint arXiv: 2006.05918, 2020.
    [32]
    S. W. Zhang, Y. Zeng, and R. Zhang, “Cellular-enabled UAV communication: A connectivity-constrained trajectory optimization perspective,” IEEE Trans. Commun., vol. 67, no. 3, pp. 2580–2604, Mar. 2019. doi: 10.1109/TCOMM.2018.2880468
    [33]
    A. Orsino, A. Ometov, G. Fodor, D. Moltchanov, L. Militano, S. Andreev, O. N. C. Yilmaz, T. Tirronen, J. Torsner, G. Araniti, A. Iera, M. Dohler, and Y. Koucheryavy, “Effects of heterogeneous mobility on D2D- and drone-assisted mission-critical MTC in 5G,” IEEE Commun. Mag., vol. 55, no. 2, pp. 79–87, Feb. 2017. doi: 10.1109/MCOM.2017.1600443CM
    [34]
    D. Wu, X. Sun, and N. Ansari, “An FSO-based drone assisted mobile access network for emergency communications,” IEEE Trans. Netw. Sci. Eng., 2019.
    [35]
    A. Trotta, M. Di Felice, F. Montori, K. R. Chowdhury, and L. Bononi, “Joint coverage, connectivity, and charging strategies for distributed UAV networks,” IEEE Trans. Robot., vol. 34, no. 4, pp. 883–900, Aug. 2018. doi: 10.1109/TRO.2018.2839087
    [36]
    I. Kovacs, R. Amorim, H. C. Nguyen, J. Wigard, and P. Mogensen, “Interference analysis for UAV connectivity over LTE using aerial radio measurements,” in Proc. IEEE 86th Vehicular Technology Conf., Toronto, Canada, 2017, pp. 1–6.
    [37]
    O. S. Oubbati, A. Lakas, F. Zhou, M. Günesş, N. Lagraa, and M. B. Yagoubi, “Intelligent UAV-assisted routing protocol for urban VANETs,” Comput. Commun., vol. 107, pp. 93–111, Jul. 2017. doi: 10.1016/j.comcom.2017.04.001
    [38]
    X. Y. Yan, M. Razeghi-Jahromi, A. Homaifar, B. A. Erol, A. Girma, and E. Tunstel, “A novel streaming data clustering algorithm based on fitness proportionate sharing,” IEEE Access, vol. 7, pp. 184985–185000, Jun. 2019. doi: 10.1109/ACCESS.2019.2922162
    [39]
    G. Fortino, C. Savaglio, C. E. Palau, J. S. de Puga, M. Ganzha, M. Paprzycki, M. Montesinos, A. Liotta, and M. Llop, “Towards multi-layer interoperability of heterogeneous IoT platforms: The INTER-IOT approach,” in Integration, Interconnection, and Interoperability of IoT Systems, R. Gravina, C. E. Palau, M. Manso, A. Liotta, and G. Fortino, Eds. Cham, Germany: Springer, 2018, pp. 199–232.
    [40]
    N. H. Motlagh, T. Taleb, and O. Arouk, “Low-altitude unmanned aerial vehicles-based internet of things services: Comprehensive survey and future perspectives,” IEEE Internet Things J., vol. 3, no. 6, pp. 899–922, Dec. 2016. doi: 10.1109/JIOT.2016.2612119
    [41]
    Y. Zhou, N. Cheng, N. Lu, and X. S. Shen, “Multi-UAV-aided networks: Aerial-ground cooperative vehicular networking architecture,” IEEE Veh. Technol. Mag., vol. 10, no. 4, pp. 36–44, Dec. 2015. doi: 10.1109/MVT.2015.2481560
    [42]
    J. P. Dash, G. D. Pearse, and M. S. Watt, “UAV multispectral imagery can complement satellite data for monitoring forest health,” Remote Sens., vol. 10, no. 8, pp. 1216, Aug. 2018. doi: 10.3390/rs10081216
    [43]
    N. Goddemeier, K. Daniel, and C. Wietfeld, “Role-based connectivity management with realistic air-to-ground channels for cooperative UAVs,” IEEE J. Sel. Areas Commun., vol. 30, no. 5, pp. 951–963, Jun. 2012. doi: 10.1109/JSAC.2012.120610
    [44]
    Y. Ham, K. K. Han, J. J. Lin, and M. Golparvar-Fard, “Visual monitoring of civil infrastructure systems via camera-equipped unmanned aerial vehicles (UAVs): A review of related works,” Vis. Eng., vol. 4, no. 1, pp. 1–8, 2016. doi: 10.1186/s40327-015-0029-z
    [45]
    C. B. Luo, J. Nightingale, E. Asemota, and C. Grecos, “A UAV-cloud system for disaster sensing applications,” in Proc. IEEE 81st Vehicular Technology Conf., Glasgow, UK, 2015, pp. 1–5.
    [46]
    Jackal unmanned ground vehicle. [Online]. Available: https://clearpathrobotics.com/jackal-small-unmanned-ground-vehicle.
    [47]
    Z. Benić, P. Piljek, and D. Kotarski, “Mathematical modelling of unmanned aerial vehicles with four rotors,” Interdiscip. Descript. Complex Syst., vol. 14, no. 1, pp. 88–100, Jan. 2016. doi: 10.7906/indecs.14.1.9
    [48]
    M. Behniapoor, Z. Yuan, A. Hailemichael, K. Vinh, B. Bowles, A. Karimoddini, and A. Homaifar, “Development of a micro aerial vehicle,” in Proc. World Automation Congr., Rio Grande, Puerto Rico, 2016, pp. 1–6.
    [49]
    J. Baichtal, Building Your Own Drones: A Beginners’ Guide to Drones, UAVs, and ROVs. Indianapolis, Indiana: Que Publishing, 2015.
    [50]
    G. H. T. Navajas and S. R. Prada, “Building your own quadrotor: A mechatronics system design case study,” in Proc. III Int. Congr. Engineering Mechatronics and Automation, Cartagena, Colombia, 2014, pp. 1–5.
    [51]
    A. Mashood, M. Mohammed, M. Abdulwahab, S. Abdulwahab, and H. Noura, “A hardware setup for formation flight of UAVs using motion tracking system,” in Proc. 10th Int. Symp. Mechatronics and its Applications, Sharjah, United Arab Emirates, 2015, pp. 1–6.
    [52]
    S. Al Habsi, M. Shehada, M. Abdoon, A. Mashood, and H. Noura, “Integration of a vicon camera system for indoor flight of a parrot AR drone,” in Proc. 10th Int. Symp. Mechatronics and its Applications, Sharjah, United Arab Emirates, 2015, pp. 1–6.
    [53]
    N. Michael, D. Mellinger, Q. Lindsey, and V. Kumar, “The GRASP multiple micro-UAV testbed,” IEEE Robot. Automat. Mag., vol. 17, no. 3, pp. 56–65, Sept. 2010. doi: 10.1109/MRA.2010.937855
    [54]
    M. Sarkar, A. Homaifar, B. A. Erol, M. Behniapoor, and E. Tunstel, “PIE: A tool for data-driven autonomous UAV flight testing,” J. Intell. Robot. Syst., vol. 98, no. 2, pp. 421–438, May 2020. doi: 10.1007/s10846-019-01078-y
    [55]
    M. R. Kosanovic and M. K. Stojcev, “Connecting wireless sensor networks to internet,” Facta Univ.-Ser:Mech. Eng., vol. 9, no. 2, pp. 169–182, 2011.
    [56]
    U. Hunkeler, H. L. Truong, and A. Stanford-Clark, “MQTT-s—a publish/subscribe protocol for wireless sensor networks,” in Proc. 3rd Int. Conf. Communication Systems Software and Middleware and Workshops, Bangalore, India, 2008, pp. 791–798.
    [57]
    L. Durkop, B. Czybik, and J. Jasperneite, “Performance evaluation of M2M protocols over cellular networks in a lab environment,” in Proc. 18th Int. Conf. Intelligence in Next Generation Networks, Paris, France, 2015, pp. 70–75.
    [58]
    L. Mainetti, L. Patrono, and A. Vilei, “Evolution of wireless sensor networks towards the internet of things: A survey,” in Proc. 19th Int. Conf. Software, Telecommunications and Computer Networks, Split, Croatia, 2011, pp. 1–6.
    [59]
    A. A. Dahoud and M. Fezari, “NodeMCU V3 For fast IoT application development,” [Online]. Available: https://paesaggiaperti.org/alfonso/rioba_tech/raw/branch/master/piattaforma/NodeMCUV3.pdf.
    [60]
    P. H. Feiler, B. A. Lewis, and S. Vestal, “The SAE architecture analysis & design language (AADL) a standard for engineering performance critical systems,” in Proc. IEEE Conf. Computer Aided Control System Design, IEEE Int. Conf. Control Applications, IEEE Int. Symp. Intelligent Control, Munich, Germany, 2006, pp. 1206–1211.
    [61]
    Espressif Systems. Esp8266ex datasheet. [Online]. Available: https://cdn-shop.adafruit.com/product-files/2471/0A-ESP8266__Datasheet__EN_v4.3.pdf.
    [62]
    R. P. Foundation. Raspberry pi 3 model B+. [Online]. Available: https://static.raspberrypi.org/files/product-briefs/Raspberry-Pi-Model-Bplus-Product-Brief.pdf.
    [63]
    Moog Components Group. DBH-0472 models. [Online]. Available: https://www.moog.com/content/dam/moog/literature/MCG/DBH-0472_Model_DtS.pdf.
    [64]
    [65]
    A. Sikora and V. F. Groza, “Fields tests for ranging and localization with time-of-flight-measurements using chirp spread spectrum RF-devices,” in Proc. IEEE Instrumentation & Measurement Technology Conf., Warsaw, Poland, 2007, pp. 1–6.
    [66]
    P. R. Palafox, M. Garzon, J. Valente, J. J. Roldán, and A. Barrientos, “Robust visual-aided autonomous takeoff, tracking, and landing of a small UAV on a moving landing platform for life-long operation,” Appl. Sci., vol. 9, no. 13, pp. 2661, 2019. doi: 10.3390/app9132661

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(16)  / Tables(3)

    Article Metrics

    Article views (1630) PDF downloads(69) Cited by()

    Highlights

    • Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits still cause delays in response time that results in fatality and property damages. In this paper, we proposed and implemented a framework designed to create a collaborative effort between heterogeneous Unmanned Vehicles and first-responders to make search and rescue operations safer and faster.
    • The proposed collaborative heterogeneous autonomous system framework consists of Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), cloud-based Remote-Control Station (RCS) IoT technology, cloud connectivity, and antenna tracker.
    • An effective UAV resource allocation mechanism is implemented using a clustering algorithm technique for maximizing the UAVs’ network coverage area and an antenna tracker is developed to extend network coverage to the UAVs and.
    • A control mechanism for landing UAV on moving UGV platform is implemented for recharging UAVs as well as to transport them.
    • Advanced Architectural Design Language (AADL) is used to analyze and evaluate the end-to-end delay of the proposed framework. To the best of our knowledge, this is the first work that uses AADL for timing analysis in an IoT-enabled autonomous system.

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return