Mobile Networks and Applications

, Volume 21, Issue 2, pp 352–366 | Cite as

GreenBikeNet: an Intelligent Mobile Application with Green Wireless Networking for Cycling in Smart Cities

  • Osama M. F. Abu-Sharkh
  • Zaid Dabain


In this paper, we introduce a mobile application with intelligent systems to provide services for cyclists and enhance their cycling experiences in smart cities. The application utilizes smartphones and low-power ZigBee technology for ad-hoc networking. Since ZigBee chipsets have not been included yet in recent smartphones, we develop a Smartphone-ZigBee embedded system that we use in building a mobile application for low-power low-bandwidth wireless ad-hoc networking with acceptable ranges. Cyclists can join either public networks or create their own private networks to exchange information and utilize several developed services. For voice communication between cyclists, we develop a multilingual voice communication system with an innovative smart spectrum and energy management approach. A sender cyclist can speak in his own language while being translated and heard in a clear voice by the receiver cyclist in another language with an acceptable delay less than 1 s. We also develop an intelligent geo-localization system that utilizes smartphone’s GPS receiver to provide real-time geo-locations and speeds of all cyclists connected to the same network on a visual interactive map. The latter system adaptively manages the number of visits to the GPS receiver according to various system parameters to reduce power consumption. Moreover, we develop an emergency system that provides a platform for efficient collaboration between cyclists in emergency conditions. To ensure safety of cyclists, all our services are accessed vocally. Furthermore, we provide an energy harvesting system using the movement of the bike for power generation.


Biking Cycling IEEE802.15.4 Intelligent systems Smart cities ZigBee 


  1. 1.
    Xiao Y et al (2013) Modeling energy consumption of data transmission over Wi-Fi. IEEE Trans Mob Comput 13(8):1760–1773CrossRefGoogle Scholar
  2. 2.
    Lauridsen M et al (2014) An empirical LTE smartphone power model with a view to energy efficiency evolution. Intel Technol J 18(1):172–193Google Scholar
  3. 3.
    Zhang L (2010) Accurate online power estimation and automatic battery behavior based power model generation for smartphones. The 8th IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis (CODES/ISSS ‘10), Scottsdale, ArizonaGoogle Scholar
  4. 4.
    ZigBee Alliance (2006) ZigBee Specifications, version 1.1.Google Scholar
  5. 5.
    Institute of Electrical and Electronics Engineers Inc., IEEE Std. 802.15.4–2003 (2003) Wireless Medium Access Control (MAC) and Physical Layer (PHY) specifications for Low Rate Wireless Personal Area Networks (LR-WPANs). IEEE Press, NYGoogle Scholar
  6. 6.
    Gössling S, Choi AS (2015) Transport transitions in Copenhagen: comparing the cost of cars and bicycles. Elsevier Ecol Econ 113:106–113CrossRefGoogle Scholar
  7. 7.
    Arancibia D, Savan B, Ledsham T, Bennington M (2015) Economic impacts of cycling in dense urban areas: literature review. Transportation Research Board 94th Annual Meeting, Washington DC, United StatesGoogle Scholar
  8. 8.
    Eisenman SB et al (2009) BikeNet: a mobile sensing system for cyclist experience mapping. ACM Trans Sens Netw 6:6:1–6:39Google Scholar
  9. 9.
    Outram C, Ratti C, Biderman A (2010) The Copenhagen wheel: an innovative electric bicycle system that harnesses the power of real-time information and crowd sourcing. International Exhibition and Conference on Ecologic Vehicles and Renewable Energies (EVER), MonacoGoogle Scholar
  10. 10.
    Shin HY, Un FL, Huang KW (2013) A sensor-based tracking system for cyclist group. 7th International Conference on Complex, Intelligent, and Software Intensive Systems, TaichungGoogle Scholar
  11. 11.
    Reddy S et al (2010) Biketastic: sensing and mapping for better biking. SIGCHI Conference on Human Factors in Computing Systems, New YorkGoogle Scholar
  12. 12.
    Isemann B et al (2014) Chaotic ad-hoc data network-A bike based system for city networks. IEEE Fifth International Conference on Communications and Electronics (ICCE), DanangGoogle Scholar
  13. 13.
    Cespedes S et al (2014) Poster: smart networked bicycles with platoon cooperation. IEEE Vehicular Networking Conference (VNC)Google Scholar
  14. 14.
    Yu KM et al (2009) An event-based wireless navigation and healthcare system for group recreational cycling. 5th International Conference on Mobile Ad-hoc and Sensor Networks (MSN ‘09), FujianGoogle Scholar
  15. 15.
    Gharghan SK, Nordin R, Ismail M (2015) An ultra-low power wireless sensor network for bicycle torque performance measurements. Sensors 15:11741–11768CrossRefGoogle Scholar
  16. 16.
    Kazdaridis G et al (2014) A demonstration of the NITOS BikesNet framework. 2014 I.E. 15th International Conference on Mobile Data Management, BrisbaneGoogle Scholar
  17. 17.
    Nakamura T et al (2012) Proposal of web framework for ubiquitous sensor network and its trial application using NO2 sensor mounted on bicycle. IEEE/IPSJ 12th International Symposium on Applications and the Internet (SAINT), IzmirGoogle Scholar
  18. 18.
    Yang Y, Yeo J, Priya S (2012) Harvesting energy from the counterbalancing (weaving) movement in bicycle riding. Sensors, 10248–10258Google Scholar
  19. 19.
    Weinert J, Ma C, Cherry C (2007) The transition to electric bikes in China: history and key reasons for rapid growth. Springer Transp 34:301–318Google Scholar
  20. 20.
    Ruogu Z, Xiong Y, Xing G, Sun L, Ma J (2010) ZiFi: wireless LAN discovery via ZigBee interference signatures. 16th annual international conference on Mobile computing and networking (MobiCom), New YorkGoogle Scholar
  21. 21.
    Yifan Z, Q Li (2013) HoWiES: a holistic approach to ZigBee assisted WiFi energy savings in mobile devices. 32nd IEEE International Conference on Computer Communications (INFOCOM), TurinGoogle Scholar
  22. 22.
    Tao J, Noubir G, Sheng B (2011) WiZi-Cloud: application-transparent dual ZigBee-WiFi radios for low power internet access. 30th IEEE International Conference on Computer Communications (INFOCOM), ShanghaiGoogle Scholar
  23. 23.
    Olteanu et al (2013) Enabling mobile devices for home automation using ZigBee. 19th International Conference on Control Systems and Computer Science (CSCS), BucharestGoogle Scholar
  24. 24.
    Hu SQ et al (2013) Enabling ZigBee communications in android devices. Adv Mater Res 756–759:2125–2130CrossRefGoogle Scholar
  25. 25.
    Peng B, Wei ZG, Wu T (2014) Corresponding research of android and ZigBee. international conference on Wireless Communication and Sensor Network (WCSN), Wuhan, ChinaGoogle Scholar
  26. 26.
    GNU General Public License version 2, Accessed 20 Feb 2015
  27. 27.
    XBee-PRO Accessed 20 Feb 2015
  28. 28.
    IOIO-OTG Accessed 20 Feb 2015
  29. 29.
    Apertium, Accessed 20 Feb 2015
  30. 30.
    OpenStreetMap Accessed 20 Feb 2015
  31. 31.
    Open Data Commons Open Database License (ODbL). Accessed 20 Feb 2015
  32. 32.
    MapQuest. Accessed 20 Feb 2015
  33. 33.
    Mobile Atlas Creator. Accessed 20 Feb 2015

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Computer Engineering, The King Abdulla II School for EngineeringPrincess Sumaya University for TechnologyAmmanJordan
  2. 2.Department of Software EngineeringRedTroopsAmmanJordan

Personalised recommendations