Pedwarn-Enhancement of Pedestrian Safety Using Mobile Application

  • N. MalathyEmail author
  • S. Sabarish Nandha
  • B. Praveen
  • K. Pravin Kumar
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)


Mobile phones usages are emerging as fast as the evolution of a man. Starting from the sunrise to sunset people are constantly using the mobile phone. It has more features like gaming, music, camera, alarm, etc. and people are using it to perform their day-to-day tasks. Even though the mobile phone has a lot of benefits, it also leads to life threatening problems due to pedestrian collision. The probability of such incidents may happen, when the pedestrians are not taking their eyes form the mobile phone while walking or crossing the road, so they met with an accident which causes serious injuries. To avoid such happenings and to notify the pedestrians about the obstacles, a mobile application called Pedwarn is developed with the help of built in phone sensors like accelerometer sensor, gyroscope sensor. It provides solutions to the problem without prior knowledge of the surroundings by calculating the distance to the nearby objects with phone speakers and microphones. The obstacles are detected within 2–4 m. Its accuracy is also strengthened by using the visual detector which will capture the images of the surrounding with the rear camera. Pedwarn is evaluated using variety of environmental settings and in different devices which are common in our day to day surroundings. The power consumed by each and every component is measured periodically of about one hour. Averages of Pedwarn measurements is noted that, its detection accuracy is 95% higher and 2%.


Pedwarn Pedestrian safety Mobile application 


  1. 1.
    Lim, J., Amado, A., Sheehan, L., Van Emmerik, R.E.: Dual task interference during walking: the effects of texting on situational awareness and gait stability. Elsevier Gait Posture 42(4), 466–471 (2015)CrossRefGoogle Scholar
  2. 2.
    Nasar, J.L., Troyer, D.: Pedestrian injuries due to mobile phone use in public places. Accid. Anal. Prev. 57, 91–95 (2013)CrossRefGoogle Scholar
  3. 3.
    Chinese City Creates a Cell Phone Lane for Walkers (2017).
  4. 4.
    Wang, T., Cardone, G., Corradi, A., Torresani, L., Campbell, A.T.: WalkSafe: a pedestrian safety application for mobile phone users who walk and talk while crossing roads. In: Proceedings of ACM International Workshop Mobile Computer System Application, pp. 5:1–5:6 (2012)Google Scholar
  5. 5.
    Jain, S., Borgiattino, C., Ren, Y., Gruteser, M., Chen, Y., Chiasserini, C.F.: LookUp: enabling pedestrian safety services via shoe sensing. In: Proceedings of ACM 1st International Conference on Mobile Systems, Applications, and Services, pp. 257–271 (2015)Google Scholar
  6. 6.
    Hincapie-Ramos, J.D., Irani, P.: Crashalert: enhancing peripheral alertness for eyes-busy mobile interaction while walking. In: Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems, pp. 3385–3388 (2013)Google Scholar
  7. 7.
  8. 8.
    Borenstein, J., Koren, Y.: The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Trans. Robot. Autom. 7(3), 278–288 (1991)CrossRefGoogle Scholar
  9. 9.
    Minguez, J.: The obstacle-restriction method for robot obstacle avoidance in difficult environments. In: Proceedings of IEEE International Conference on Intelligent Robots and Systems, pp. 2284–2290 (2005)Google Scholar
  10. 10.
    Philomin, V., Duraiswami, R., Davis, L.: Pedestrian tracking from a moving vehicle. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 350–355 (2000)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • N. Malathy
    • 1
    Email author
  • S. Sabarish Nandha
    • 1
  • B. Praveen
    • 1
  • K. Pravin Kumar
    • 1
  1. 1.Department of Information TechnologyMepco Schlenk Engineering College (Autonomous)SivakasiIndia

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