[go: up one dir, main page]

skip to main content
10.1145/3274895.3274914acmconferencesArticle/Chapter ViewAbstractPublication PagesgisConference Proceedingsconference-collections
short-paper

Geofences in the sky: herding drones with blockchains and 5G

Published: 06 November 2018 Publication History
  • Get Citation Alerts
  • Abstract

    Unmanned aerial vehicles (UAVs), typically also referred to as drones, are gaining popularity and becoming ubiquitous. As the number of drones in the sky rapidly grows, managing the expected high-volume air traffic is becoming a critical challenge. It is essential to prevent collisions, and to protect the public from nuisances like noise or invasion of privacy, and shield from hazards like falling debris. UAV traffic management should comply with regulation, spatiotemporal constraints and limitations of drones. Spatiotemporal constraints could be no-flight zones or areas where drone flight times are restricted. Drone limitations could refer to their speed, flight range, telecommunication capabilities, etc. Furthermore, managing air traffic for UAVs is very different from managing the traffic of self-driving ground vehicles. First, there are no clearly-marked roads in the sky. Second, some UAVs cannot hover and must have a cleared flight path. Third, air traffic should be managed in a 3-dimensional space. In this paper we present a vision of air-traffic control based on geofencing. We discuss three operation modes: centralized, decentralized and a hybrid of the two other modes. We present some of the challenges involved in drone traffic control and illustrate how geofencing could be a useful tool for that, while leveraging the emerging 5G networking technology.

    References

    [1]
    Jeffrey G Andrews, Stefano Buzzi, Wan Choi, Stephen V Hanly, Angel Lozano, Anthony CK Soong, and Jianzhong Charlie Zhang. 2014. What will 5G be? IEEE Journal on selected areas in communications 32, 6 (2014), 1065--1082.
    [2]
    Elli Androulaki et al. 2018. Hyperledger fabric: a distributed operating system for permissioned blockchains. In Proc. of the 13th EuroSys Conference. ACM, 30.
    [3]
    Jessica R Cauchard, Kevin Y Zhai, James A Landay, et al. 2015. Drone & me: an exploration into natural human-drone interaction. In Proc. of the 2015 ACM international joint conference on pervasive and ubiquitous computing. 361--365.
    [4]
    Konstantinos Christidis and Michael Devetsikiotis. 2016. Blockchains and smart contracts for the internet of things. IEEE Access 4 (2016), 2292--2303.
    [5]
    Tamraparni Dasu, Yaron Kanza, and Divesh Srivastava. 2017. Geotagging IP Packets for Location-Aware Software-Defined Networking in the Presence of Virtual Network Functions. In Proc. of the 25th ACM SIGSPATIAL International Conf. on Advances in Geographic Information Systems. ACM.
    [6]
    Tamraparni Dasu, Yaron Kanza, and Divesh Srivastava. 2018. Unchain your blockchain. In Proc. Symposium on Foundations and Applications of Blockchain.
    [7]
    Yossi Gilad, Rotem Hemo, Silvio Micali, Georgios Vlachos, and Nickolai Zeldovich. 2017. Algorand: Scaling byzantine agreements for cryptocurrencies. In Proceedings of the 26th Symposium on Operating Systems Principles. ACM, 51--68.
    [8]
    Ralf Hartmut Güting, Michael H Böhlen, Martin Erwig, Christian S Jensen, Nikos A Lorentzos, Markus Schneider, and Michalis Vazirgiannis. 2000. A foundation for representing and querying moving objects. ACM Transactions on Database Systems (TODS) 25, 1 (2000), 1--42.
    [9]
    Ralf Hartmut Güting and Markus Schneider. 2005. Moving objects databases. Elsevier.
    [10]
    Javier Irizarry, Masoud Gheisari, and Bruce N Walker. 2012. Usability assessment of drone technology as safety inspection tools. Journal of Information Technology in Construction (ITcon) 17, 12 (2012), 194--212.
    [11]
    Kakuya Iwata. 2013. Research of Cargo UAV for civil transportation. Journal of Unmanned System Technology 1, 3 (2013), 89--93.
    [12]
    Yaron Kanza. 2016. Location corroborations by mobile devices without traces. In Proc. of the 24th ACM SIGSPATIAL International Conf. on Advances in Geographic Information Systems.
    [13]
    Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008).
    [14]
    Svetlana Potyagaylo, Omri Rand, and Yaron Kanza. 2010. Motion Planning for an Autonomous Helicopter in a GPS-denied Environment. In Proceedings of the American Helicopter Society 66Th Annual Forum, Phoenix, AZ, USA. AHS.
    [15]
    Svetlana Potyagaylo, Omri Rand, and Yaron Kanza. 2012. Targeted Autonomous Indoor Flight of a Rotary-Wing MAV. In Proc. of American Helicopter Society 68th Annual Forum.
    [16]
    Sandro Rodriguez Garzon and Bersant Deva. 2014. Geofencing 2.0: Taking Location-based Notifications to the Next Level. In Proc. of the International Joint Conf. on Pervasive and Ubiquitous Computing. ACM.
    [17]
    Giuseppe Salvo, Luigi Caruso, and Alessandro Scordo. 2014. Urban traffic analysis through an UAV. Procedia - Social & Behavioral Sciences 111 (2014), 1083--1091.
    [18]
    Stefan Saroiu and Alec Wolman. 2009. Enabling new mobile applications with location proofs. In Proc. of the 10th Workshop on Mobile Computing Systems and Applications. ACM.
    [19]
    Anmol Sheth, Srinivasan Seshan, and David Wetherall. 2009. Geo-fencing: Confining Wi-Fi coverage to physical boundaries. In International Conference on Pervasive Computing. Springer, 274--290.
    [20]
    A Prasad Sistla, Ouri Wolfson, Sam Chamberlain, and Son Dao. 1997. Modeling and querying moving objects. In Data Engineering, 1997. Proceedings. 13th International Conference on. IEEE, 422--432.
    [21]
    Stephen Statler. 2016. Geofencing: Everything You Need to Know. In Beacon Technologies. Springer, 307--316.
    [22]
    Jianqiu Xu and Ralf Hartmut Güting. 2013. A generic data model for moving objects. Geoinformatica 17, 1 (2013), 125--172.

    Cited By

    View all
    • (2024)Air Traffic Controllers' Perspectives on Unmanned Aerial Vehicles Integration into Non-Segregated AirspaceJournal of Aviation10.30518/jav.14757358:2(153-165)Online publication date: 27-Jun-2024
    • (2024)Drones as a service (DaaS) for 5G networks and blockchain-assisted IoT-based smart city infrastructureCluster Computing10.1007/s10586-024-04354-1Online publication date: 17-Apr-2024
    • (2023)Blockchain Technology for Secure Communication and Formation Control in Smart Drone SwarmsFuture Internet10.3390/fi1510034415:10(344)Online publication date: 19-Oct-2023
    • Show More Cited By

    Index Terms

    1. Geofences in the sky: herding drones with blockchains and 5G

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
      November 2018
      655 pages
      ISBN:9781450358897
      DOI:10.1145/3274895
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 06 November 2018

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. 5G networks
      2. IoT
      3. UAV
      4. blockchain
      5. drone
      6. geofencing
      7. traffic control

      Qualifiers

      • Short-paper

      Conference

      SIGSPATIAL '18
      Sponsor:

      Acceptance Rates

      SIGSPATIAL '18 Paper Acceptance Rate 30 of 150 submissions, 20%;
      Overall Acceptance Rate 220 of 1,116 submissions, 20%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)54
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 07 Aug 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Air Traffic Controllers' Perspectives on Unmanned Aerial Vehicles Integration into Non-Segregated AirspaceJournal of Aviation10.30518/jav.14757358:2(153-165)Online publication date: 27-Jun-2024
      • (2024)Drones as a service (DaaS) for 5G networks and blockchain-assisted IoT-based smart city infrastructureCluster Computing10.1007/s10586-024-04354-1Online publication date: 17-Apr-2024
      • (2023)Blockchain Technology for Secure Communication and Formation Control in Smart Drone SwarmsFuture Internet10.3390/fi1510034415:10(344)Online publication date: 19-Oct-2023
      • (2023)Planning Wireless Backhaul Links by Testing Line of Sight and Fresnel Zone ClearanceACM Transactions on Spatial Algorithms and Systems10.1145/35173829:1(1-30)Online publication date: 12-Jan-2023
      • (2023)Unmanned Aerial Vehicles Traffic Management Solution Using Crowd-Sensing and BlockchainIEEE Transactions on Network and Service Management10.1109/TNSM.2022.320181720:1(201-215)Online publication date: Mar-2023
      • (2023)Unmanned Aerial Vehicles for Air Pollution Monitoring: A SurveyIEEE Internet of Things Journal10.1109/JIOT.2023.329050810:24(21687-21704)Online publication date: 15-Dec-2023
      • (2023)Cost-efficient blockchain application to secure data transmission in heterogeneous FANETs2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51644.2023.10060385(1139-1142)Online publication date: 8-Jan-2023
      • (2023)A comprehensive survey on security, privacy issues and emerging defence technologies for UAVsJournal of Network and Computer Applications10.1016/j.jnca.2023.103607213(103607)Online publication date: Apr-2023
      • (2022)Geo-Fencing Location Based Services Using Sentiment AnalysisInternational Journal of Advanced Research in Science, Communication and Technology10.48175/IJARSCT-3357(600-603)Online publication date: 30-Apr-2022
      • (2022)Airspace Geofencing and Flight Planning for Low-Altitude, Urban, Small Unmanned Aircraft SystemsApplied Sciences10.3390/app1202057612:2(576)Online publication date: 7-Jan-2022
      • Show More Cited By

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media