Hostname: page-component-89b8bd64d-shngb Total loading time: 0 Render date: 2026-05-06T10:34:17.637Z Has data issue: false hasContentIssue false
  • English
  • Français

Wireless vision-based digital media fixed-point DSP processor depending robots for natural calamities

Published online by Cambridge University Press:  15 March 2024

S. Mary Joans Open the ORCID record for S. Mary Joans [Opens in a new window] ,
N. Gomathi  and
P. Ponsudha
S. Mary Joans*
Affiliation:
Department of Electronics and Communication Engineering, Velammal Engineering College, Anna University, Chennai, Tamil Nadu, India
N. Gomathi
Affiliation:
Department of Computer Science and Engineering, Vel Tech University, Chennai, Tamil Nadu, India
P. Ponsudha
Affiliation:
Department of Electronics and Communication Engineering, Velammal Engineering College, Anna University, Chennai, Tamil Nadu, India
*
Corresponding author: S. Mary Joans; Email: ecehod@velammal.edu.in
Get access Rights & Permissions [Opens in a new window]

Abstract

Natural calamities are affecting many parts of the world. Natural disasters, terrorist attacks, earthquakes, wildfires, floods and all unpredicted phenomena. Disasters cause emergency conditions, so imperative to coordinate the prompt delivery of essential services to the sufferers. Often, disasters lead many people to perish by becoming trapped inside, but many more also perish as a result of individuals receiving rescue either too late or not at all. The implementation and design of a Receiver module utilizing Davinci code processor DVM6437, Wireless camera receiver, Zigbee Transceiver and Global Positioning System (GPS) is proposed in this manuscript for Wireless Vision-based Semi-Autonomous rescue robots that are employed in rough terrain. The receiver side’s Zigbee transceiver module eliminates the limitations of tele-operating rescue robots by enabling the control station to receive GPS data signals and aids in robot management by sending control signals wirelessly. Half and full-duplex communication are supported by the Davinci processor DVM6437, a digital media fixed-point DSP processor that relies on Very Long Instruction Words. It includes an extensive instruction set that is ideal for real-time salvage operations. DVM processor is coded utilizing MATLAB Simulink. MATLAB codes and Simulink blocks are employed under Embedded IDE link.

Keywords

Davinci code Processor- DVM 6437wireless cameraZigbee TransceiverGlobal Positioning Systemrescue robot

Information

Type
Research Article
Information
Robotica , Volume 42 , Issue 5 , May 2024 , pp. 1368 - 1385
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Chen, S. W., Shao, J. Q. and Zhu, H. S., “Technology of internet of things responding to natural disasters,” EAI Endorsed Trans. Internet of Things 7(26), e2 (2021).Google Scholar
Ma, J., Cheng, J. C., Jiang, F., Gan, V. J., Wang, M. and Zhai, C., “Real-time detection of wildfire risk caused by powerline vegetation faults using advanced machine learning techniques,” Adv. Eng. Inform. 44, 101070 (2020).CrossRefGoogle Scholar
Choden, Y., Raj, M., Wangchuk, C., Singye, P. and Muramatsu, K.. “Remote Controlled Rescue Robot Using ZigBee Communication”. In: 2019 IEEE 5th International Conference for Convergence in Technology (I2CT), IEEE (2019) pp. 1–5.Google Scholar
Machaiah, M. D. and Akshay, S., “IoT based human search and rescue robot using swarm robotics,” Int. J. Eng. Adv. Technol. 8(5), 1797–1801 (2019).Google Scholar
Dinh, T. D., Vishnevsky, V., Le, D. T., Kirichek, R. and Koucheryavy, A.. “Determination of Subscribers Coordinates Using Flying Network for Emergencies”. In: 2021 23rd International Conference on Advanced Communication Technology (ICACT), IEEE (2021) pp. 1–10.Google Scholar
Yang, Q. and Parasuraman, R.. “Needs-Driven Heterogeneous Multi-Robot Cooperation in Rescue Missions”. In: IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), IEEE(2020) pp. 252–259.Google Scholar
Behairy, A., El-Rahman, G. I. A., Aly, S. S., Fahmy, E. M. and Abd-Elhakim, Y. M., “Di (2-ethylhexyl) adipate plasticizer triggers hepatic, brain, and cardiac injury in rats: Mitigating effect of Peganumharmala oil,” Ecotox. Environ. Saf. 208, 111620 (2021).CrossRefGoogle Scholar
Çoban, B., Scaparra, M. P. and O’Hanley, J. R., “Use of OR in earthquake operations management: A review of the literature and roadmap for future research,” Int. J. Disast. Risk. Reduct. 65, 102539 (2021).10.1016/j.ijdrr.2021.102539CrossRefGoogle Scholar
Battistuzzi, L., Recchiuto, C. T. and Sgorbissa, A., “Ethical concerns in rescue robotics: A scoping review,” Ethics Inf. Technol. 23(4), 863–875 (2021).CrossRefGoogle Scholar
Azpúrua, H., Rezende, A., Potje, G., Júnior, G. P. D. C., Fernandes, R., Miranda, V. and Freitas, G. M., “Towards semi-autonomous robotic inspection and mapping in confined spaces with the EspeleoRobô,” J. Intell. Robot. Syst. 101, 1–27 (2021).CrossRefGoogle Scholar
Tan, L., Guo, J., Mohanarajah, S. and Zhou, K., “Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices,” Nat. Hazards 107(3), 2389–2417 (2021).CrossRefGoogle Scholar
Nosirov, K. K., Shakhobiddinov, A. S., Arabboev, M., Begmatov, S. and Togaev, O. T., “Specially designed multi-functional search and rescue robot,” Bull. TUIT Manag. Comm. Technol. 2(1), 1–5 (2020).Google Scholar
Wildani, F., Mardiati, R., Mulyana, E. and Setiawan, A. E.. Semi-Autonomous Navigation Robot Using Integrated Remote Control And Fuzzy Logic”. In: 2021 7th International Conference on Wireless and Telematics (ICWT), IEEE (2021) pp. 1–5.Google Scholar
Edlinger, R., Zauner, G. and Zauner, M., “Hazmat label recognition and localization for rescue robots in disaster scenarios,” Electron. Imag. 31(7), 1–6 (2019).Google Scholar
Narayan, S., Aquif, M., Kalim, A. R., Chagarlamudi, D. and Vignesh, M. H.. “Search and Reconnaissance Robot for Disaster Management”. In: Machines, Mechanism and Robotics: Proceedings of iNaCoMM. 2019, Springer Singapore (2022) pp. 187–201.Google Scholar
Soma, P., Jatoth, R. K. and Nenavath, H.. “Implementation of Single Image De-hazing System on DSP TMS320C6748 Processor”. In: Soft Computing: Theories and Applications: Proceedings of SoCTA. 2018 (Springer Singapore, Singapore, 2020) pp. 405–415.Google Scholar
Alam, M. N., Saiam, M., Al-Mamun, A., Rahman, M. M. and Hany, U.. “A Prototype of Multi Functional Rescue Robot Using Wireless Communication”. In: 2021 5th International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), IEEE (2021) pp. 1–5.Google Scholar
Kamegawa, T., Akiyama, T., Sakai, S., Fujii, K., Une, K., Ou, E. and Gofuku, A., “Development of a separable search-and-rescue robot composed of a mobile robot and a snake robot,” Adv. Robot. 34(2), 132–139 (2020).CrossRefGoogle Scholar
Nosirov, K., Begmatov, S. and Arabboev, M. “Analog Sensing and Leap Motion Integrated Remote Controller for Search and Rescue Robot System”. In: 2020 International Conference on Information Science and Communications Technologies (ICISCT), IEEE (2020) pp. 1–5.Google Scholar
Ravendran, A., Ponpai, P., Yodvanich, P., Faichokchai, W. and Hsu, C. H.. “Design and development of a low cost rescue robot with environmental adaptability”. In: 2019 International Conference on System Science and Engineering (ICSSE), IEEE (2019) pp. 57–61.Google Scholar
Baldemir, Y., İyigün, S., Musayev, O. and Cenk, U. L. U., “Design and development of a mobile robot for search and rescue operations in debris,” Int. J. Appl. Math. Electron. Comput. 8(4), 133–137 (2020).CrossRefGoogle Scholar
Ullah, K., Mahmood, T. and Garg, H., “Evaluation of the performance of search and rescue robots using T-spherical fuzzy Hamacher aggregation operators,” Int. J. Fuzzy Syst. 22(2), 570–582 (2020).CrossRefGoogle Scholar
Avinash, L. G., “Robotic search and rescue using human detection system,” Turk. J. Comput. Math. Educ. 12(1S), 162–169 (2021).Google Scholar
Punith, K. M., Sumanth, S. and Savadatti, M. A., “Internet rescue robots for disaster management,” Int. J. Wir. Microw. Technol. 11(2), 13–23 (2021).Google Scholar
Alam, S. S., Ahmed, T., Islam, M. S. and Chowdhury, M. M. F., “A smart approach for human rescue and environment monitoring autonomous robot,” Int. J. Mech. Eng. Robot. Res. 10(4), 209–215 (2021).CrossRefGoogle Scholar
Dong, J., Ota, K. and Dong, M., “UAV-based real-time survivor detection system in post-disaster search and rescue operations,” IEEE J. Miniaturizat. Air Space Syst. 2(4), 209–219 (2021).CrossRefGoogle Scholar
Saputra, R. P., Rakicevic, N., Kuder, I., Bilsdorfer, J., Gough, A., Dakin, A. and Kormushev, P., “Resqbot 2.0: An improved design of a mobile rescue robot with an inflatable neck securing device for safe casualty extraction,” Appl. Sci. 11(12), 5414 (2021).CrossRefGoogle Scholar
Habibian, S., Dadvar, M., Peykari, B., Hosseini, A., Salehzadeh, M. H., Hosseini, A. H. and Najafi, F., “Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions,” Robomech J. 8(1), 1–33 (2021).CrossRefGoogle Scholar
Dumbre, S., Jadhav, Y., Mahajan, S. and Sorte, M., “Design and fabrication semi-autonomous search and rescue robot using rocker bogie mechanism,” Int. J. Mech. Dynam. Anal. 7(2), 34–38 ( 2021 ).Google Scholar
Imteaj, A., Chowdhury, M. I. J., Farshid, M. and Shahid, A. R.. “RoboFI: Autonomous Path Follower Robot for Human Body Detection and Geolocalization for Search and Rescue Missions Using Computer Vision and IoT”. In: 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), IEEE(2019) pp. 1–6.Google Scholar
Hilario, J., Balbuena, J., Penaloza, C., Hernandez-Carmona, D., Quiroz, D., Ramirez, J. and Cuellar, F.. “Late Breaking Report-Development of a Mobile Robot for Industrial Plants Inspections Using Computer Vision”. In: 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), IEEE (2019) pp. 108–109.Google Scholar
Nazarova, A. V. and Zhai, M., “The Application of Multi-Agent Robotic Systems for Earthquake Rescue”,” In: Robotics: Industry 4.0 Issues & New Intelligent Control Paradigms (2020) pp. 133–146.CrossRefGoogle Scholar
., “Development of two rescue robots for disaster relief operations in narrow debris,” (4), 399–406 (2015).Google Scholar
Yang, Z., Clemente, M. F., Laffréchine, K., Heinzlef, C., Serre, D. and Barroca, B., “Resilience of social-infrastructural systems: Functional interdependencies analysis,” Sustainability 14(2), 606 (2022).CrossRefGoogle Scholar