Swarm of Mobile Robots for Security Surveillance Based on Android Smartphone and Firebase

Authors

  • Afdhal Kurniawan Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11530, Indonesia
  • Alexander A. S. Gunawan Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11530, Indonesia
  • Boby Hartanto Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11530, Indonesia
  • Aditya Mili Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11530, Indonesia
  • Widodo Budiharto Professor, Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11530, Indonesia

Keywords:

Android, Firebase, Microcontroller, Swarm Robot

Abstract

A swarm of mobile robots is an approach used to coordinate large numbers of mobile robots for accomplishing specific tasks. This study utilizes swarm robots in a security surveillance scenario. The research involves the development of an affordable mobile robot based on an IOIO board. To enable its integration into swarm robot systems, the robot must be enhanced with communication capabilities, and an algorithm must be implemented to coordinate multiple robots. The robots should be able to communicate with each other both locally and online. An OpenWrt-based router is employed as the local network communication backbone. Firebase, a cloud based IoT database service, is also utilized as a platform for online communication. The design of the swarm robot system allows a user to monitor and assign tasks to the system remotely. Once connected to a local network, the swarm robots can operate and coordinate autonomously. The mobile robot should have a camera capable of identifying people and detecting motion, making it suitable for security surveillance applications. The experiments successfully demonstrated the swarm robot system's effectiveness in performing security surveillance tasks.

Downloads

Download data is not yet available.

References

N. Oros and J. L. Krichmar, “Smartphone Based Robotics: Powerful, Flexible and Inexpensive Robots for Hobbyists, Educators, Students and Researchers,” Irvine, USA, 2013. [Online]. Available: https://pdfs.semanticscholar.org/1e4f/371b9509dac7b649a473a0b95c39f0bfd63a.pdf

S. Wilson et al., “Pheeno, A Versatile Swarm Robotic Research and Education Platform,” IEEE Robot Autom Lett, vol. 1, pp. 884–891, 2016.

S. Monk, Making Android Accessories with IOIO, 1st ed. Sebastopol, CA 95472: O’Reilly Media, Inc., 2012.

S. Gobel, R. Jubeh, S.-L. Raesch, and A. Zundorf, “Using the Android Platform to control Robots,” RiE 2011, 2011, [Online]. Available: http://www.innoc.at/fileadmin/user_upload/_temp_/RiE/Proceedings/65.pdf

E. B. B. Gyebi, M. Hanheide, and G. Cielniak, “Affordable mobile robotic platforms for teaching computer science at African universities,” 2015.

F. Arvin, J. Espinosa, B. Bird, A. West, S. Watson, and B. Lennox, “Mona: an Affordable Open-Source Mobile Robot for Education and Research,” J Intell Robot Syst, vol. 94, no. 3–4, pp. 761–775, Jun. 2019, doi: 10.1007/s10846-018-0866-9.

C. E. Palazzi, M. Brunati, and M. Roccetti, “An OpenWRT solution for future wireless homes,” in 2010 IEEE International Conference on Multimedia and Expo, IEEE, Jul. 2010, pp. 1701–1706. doi: 10.1109/ICME.2010.5583223.

J. Azeta et al., “An Android Based Mobile Robot for Monitoring and Surveillance,” Procedia Manuf, vol. 35, pp. 1129–1134, 2019, doi: 10.1016/j.promfg.2019.06.066.

Y. Yan, S. Cosgrove, E. Blantont, S. Y. Ko, and L. Ziarek, “Real-Time Sensing on Android,” in Proceedings of the 12th International Workshop on Java Technologies for Real-time and Embedded Systems, New York, NY, USA: ACM, Oct. 2014, pp. 67–75. doi: 10.1145/2661020.2661026.

L. Moroney, “The Firebase Realtime Database,” in The Definitive Guide to Firebase, Berkeley, CA: Apress, 2017, pp. 51–71. doi: 10.1007/978-1-4842-2943-9_3.

R. Raj and A. Kos, “A Comprehensive Study of Mobile Robot: History, Developments, Applications, and Future Research Perspectives,” Applied Sciences, vol. 12, no. 14, p. 6951, Jul. 2022, doi: 10.3390/app12146951.

R. Siegwart and I. R. Nourbakhsh, Introduction to Autonomous Mobile Robots. USA: Bradford Company, 2004.

C.-L. Shih and L.-C. Lin, “Trajectory Planning and Tracking Control of a Differential-Drive Mobile Robot in a Picture Drawing Application,” Robotics, vol. 6, no. 3, p. 17, Aug. 2017, doi: 10.3390/robotics6030017.

G. Dudek and M. Jenkin, Computational Principles of Mobile Robotics. Cambridge University Press, 2010. doi: 10.1017/CBO9780511780929.

K. Shojaei, A. M. Shahri, A. Tarakameh, and B. Tabibian, “Adaptive trajectory tracking control of a differential drive wheeled mobile robot,” Robotica, vol. 29, no. 3, pp. 391–402, 2011, doi: 10.1017/S0263574710000202.

Dr. Sandip Kadam. (2014). An Experimental Analysis on performance of Content Management Tools in an Organization. International Journal of New Practices in Management and Engineering, 3(02), 01 - 07. Retrieved from http://ijnpme.org/index.php/IJNPME/article/view/27

Sheeba, T. B. ., Hemanth, S. V. ., Devaraj, V. ., Arularasan, A. N. ., & Gopianand, M. . (2023). Digital Hash Data Encryption for IoT Financial Transactions using Blockchain Security in the Cloud. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4s), 129–134. https://doi.org/10.17762/ijritcc.v11i4s.6316

Downloads

Published

21.09.2023

How to Cite

Kurniawan, A. ., Gunawan, A. A. S. ., Hartanto, B. ., Mili, A. ., & Budiharto, W. . (2023). Swarm of Mobile Robots for Security Surveillance Based on Android Smartphone and Firebase. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 810–815. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3614

Issue

Section

Research Article