Internet of Robotic Things in Battlefield Applications: A Novel Study

Year : 2024 | Volume : | : | Page : –
By

Dr. Kazi Kutubuddin Sayyad Liyakat,

  1. Professor and Head, Engineering, Brahmdevdada Mane Institute of Technology, Solapur (MS), Maharashtra, India

Abstract

A new era in military operations is promised by the integration of the Internet of Robotic Things into combat applications, which will provide creative solutions that improve situational awareness, efficiency, and safety. To ensure that the use of these technologies is both responsible and efficient, the potential advantages must be weighed against technological difficulties and ethical issues. It will be crucial going forward for military organisations to continue being proactive and adaptive in handling the intricacies that come with this technology change. The Internet of Robotic Things stands at the forefront of military innovation, offering promising enhancements to battlefield operations. As technology evolves, it is imperative to address the myriad challenges that accompany these advancements. By focusing on enhancing autonomous capabilities, establishing interoperability, securing cyber environments, and navigating ethical considerations, the future of IoRT in the battlefield promises to be both profound and transformative. Continuous collaboration among technologists, military leaders, and policymakers will be essential in achieving a future where IoRT systems can operate safely and efficiently, ultimately redefining modern warfare.

Keywords: IoRT, Battlefield, military, Cybersecurity, Artificial Intelligence, KSK approach,

How to cite this article: Dr. Kazi Kutubuddin Sayyad Liyakat. Internet of Robotic Things in Battlefield Applications: A Novel Study. Journal of Nuclear Engineering & Technology. 2024; ():-.
How to cite this URL: Dr. Kazi Kutubuddin Sayyad Liyakat. Internet of Robotic Things in Battlefield Applications: A Novel Study. Journal of Nuclear Engineering & Technology. 2024; ():-. Available from: https://journals.stmjournals.com/jonet/article=2024/view=167365

References

  • Megha Nagrale, Rahul S. Pol, Ganesh B. Birajadar, Altaf O. Mulani, (2024). Internet of Robotic Things in Cardiac Surgery: An Innovative Approach, African Journal of Biological Sciences, Vol 6, Issue 6, pp. 709-725 doi: 33472/AFJBS.6.6.2024.709-725 Available at: https://www.afjbs.com/issue-content/internet-of-robotic-things-in-cardiac-surgery-an-innovative-approach-784
  • Liyakat, K.K.S. (2024). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. ICMIB 2023. Lecture Notes in Networks and Systems, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
  • M Pradeepa, et al. (2022). Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2nd Mysore sub section International Conference (MysuruCon), Available at: https://ieeexplore.ieee.org/document/9972445
  • K. S. Liyakat. (2023).Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks, 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2023, pp. 1-5, doi:10.1109/ESCI56872.2023.10099544. Available at: https://ieeexplore.ieee.org/document/10099544/
  • Kasat, N. Shaikh, V. K. Rayabharapu, M. Nayak. (2023). Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1661-1665, doi: 10.1109/ICAISS58487.2023.10250690 . Available at: https://ieeexplore.ieee.org/document/10250690/
  • Liyakat, K.K.S. (2023). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Shukla, P.K., Mittal, H., Engelbrecht, A. (eds) Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4577-1_3
  • Kazi, K. (2024a). AI-Driven IoT (AIIoT) in Healthcare Monitoring. In T. Nguyen & N. Vo (Eds.), Using Traditional Design Methods to Enhance AI-Driven Decision Making(pp. 77-101). IGI Global. https://doi.org/10.4018/979-8-3693-0639-0.ch003 available at: https://www.igi-global.com/chapter/ai-driven-iot-aiiot-in-healthcare-monitoring/336693
  • Kazi, K. (2024b). Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In L. D., N. Nagpal, N. Kassarwani, V. Varthanan G., & P. Siano (Eds.), E-Mobility in Electrical Energy Systems for Sustainability (pp. 295-320). IGI Global. https://doi.org/10.4018/979-8-3693-2611-4.ch014 Available at: https://www.igi-global.com/gateway/chapter/full-text-pdf/341172
  • Kazi, K. S. (2024a). Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In M. Garcia & R. de Almeida (Eds.), Transformative Approaches to Patient Literacy and Healthcare Innovation(pp. 112-135). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch006 Available at: https://www.igi-global.com/chapter/computer-aided-diagnosis-in-ophthalmology/342823
  • Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
  • Priya Mangesh Nerkar, Bhagyarekha Ujjwalganesh Dhaware. (2023). Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning, Journal of Advanced Zoology, 2023, Volume 44, Special Issue -2, Page 3673:3686.  Available at: https://jazindia.com/index.php/jaz/article/view/1695
  • Neeraja, R. G. Kumar, M. S. Kumar, K. K. S. Liyakat and M. S. Vani. (2024), DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp. 589-594, doi: 10.1109/IC2PCT60090.2024.10486714. Available at: https://ieeexplore.ieee.org/document/10486714
  • Sayyad Liyakat, (2024). Explainable AI in Healthcare. In: Explainable Artificial Intelligence in healthcare System, editors: Anitha Kamaraj, Debi Prasanna Acharjya. ISBN: 979-8-89113-598-7. DOI: https://doi.org/10.52305/GOMR8163
  • Liyakat Kazi, K. S. (2024). ChatGPT: An Automated Teacher’s Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning(pp. 1-20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
  • Veena, M. Sridevi, K. K. S. Liyakat, B. Saha, S. R. Reddy and N. Shirisha,(2023). HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 407-410, doi: 10.1109/ICIIP61524.2023.10537627. Available at: https://ieeexplore.ieee.org/document/10537627
  • Rajendra Prasad, Santoshachandra Rao Karanam (2024). AI in public-private partnership for IT infrastructure development, Journal of High Technology Management Research, Volume 35, Issue 1,May 2024, 100496. https://doi.org/10.1016/j.hitech.2024.100496
  • Kazi, K. S. (2024b). IoT Driven by Machine Learning (MLIoT) for the Retail Apparel Sector. In T. Tarnanidis, E. Papachristou, M. Karypidis, & V. Ismyrlis (Eds.),Driving Green Marketing in Fashion and Retail (pp. 63-81). IGI Global. https://doi.org/10.4018/979-8-3693-3049-4.ch004
  • Kutubuddin Kazi, (2024a). Machine Learning (ML)-Based Braille Lippi Characters and Numbers Detection and Announcement System for Blind Children in Learning, In Gamze Sart (Eds.), Social Reflections of Human-Computer Interaction in Education, Management, and Economics, IGI Global. https://doi.org/10.4018/979-8-3693-3033-3.ch002
  • Kazi, K. S. (2024). Artificial Intelligence (AI)-Driven IoT (AIIoT)-Based Agriculture Automation. In S. Satapathy & K. Muduli (Eds.), Advanced Computational Methods for Agri-Business Sustainability(pp. 72-94). IGI Global. https://doi.org/10.4018/979-8-3693-3583-3.ch005
  • Kazi Kutubuddin, (2024d). Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5367-5374. Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3371&id=8

[21].                     Kazi Kutubuddin, (2024e). A Novel Approach on ML based Palmistry, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5186-5193. Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3344&id=8 [22].                     Kazi Kutubuddin, (2024e). IoT based Boiler Health Monitoring for Sugar Industries, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp. 5178 -5185. Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3343&id=8 [23].                     Liyakat, K.K.S., (2024). Explainable AI in healthcare, Explainable Artificial Intelligence in Healthcare Systems, 2024, pp. 271–284

  • B. Khadake and V. J. Patil, “Prototype Design & Development of Solar Based Electric Vehicle,” 2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON), Bangalore, India, 2023, pp. 1-7, doi: 10.1109/SMARTGENCON60755.2023.10442455.
  • J. Patil, S. B. Khadake, D. A. Tamboli, H. M. Mallad, S. M. Takpere and V. A. Sawant, “Review of AI in Power Electronics and Drive Systems,” 2024 3rd International conference on Power Electronics and IoT Applications in Renewable Energy and its Control (PARC), Mathura, India, 2024, pp. 94-99, doi: 10.1109/PARC59193.2024.10486488.
  • Suhas B. Khadake. (2021). Detecting Salient Objects of Natural Scene in a Video’s Using Spatio-Temporal Saliency &Amp; Colour Map. JournalNX – A Multidisciplinary Peer Reviewed Journal, 2(08), 30–35. Retrieved from https://repo.journalnx.com/index.php/nx/article/view/1070
  • Suhas B. Khadake, Prof. Sudarshan P. Dolli, Mr. K. S. Rathod, Mr. O. P. Waghmare, & Mr. A. V. Deshpande. (2021). An Overview Of Intelligent Traffic Control System Using Plc And Use Of Current Data Of Vehicle Travels. JournalNX – A Multidisciplinary Peer Reviewed Journal, 1–4. Retrieved from https://repo.journalnx.com/index.php/nx/article/view/739
  • J. Patil, S. B. Khadake, D. A. Tamboli, H. M. Mallad, S. M. Takpere and V. A. Sawant, “A Comprehensive Analysis of Artificial Intelligence Integration in Electrical Engineering,” 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), Lalitpur, Nepal, 2024, pp. 484-491, doi: 10.1109/ICMCSI61536.2024.00076.
  • Khadake, S., Kawade, S., Moholkar, S., Pawar, M. (2024). A Review of 6G Technologies and Its Advantages Over 5G Technology. In: Pawar, P.M., et al.Techno-societal 2022. ICATSA 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-34644-6_107
  • Balkrishna Dudgikar, A Ahmad Akbar Ingalgi, A Gensidha Jamadar et al., “Intelligent battery swapping system for electric vehicles with charging stations locator on IoT and cloud platform”, International Journal of Advanced Research in Science Communication and Technology, vol. 3, no. 1, pp. 204-208, January 2023. DOI: 10.48175/IJARSCT-7867. Available at: https://ijarsct.co.in/Paper7867.pdf
  • B. Khadake , Prajakta. V. Padavale , Priyanka. M. Dhere , Bharati. M. Lingade., “Automatic Hand Dispenser and Temperature Scanner for Covid-19 Prevention” , International Journal of Advanced Research in Science Communication and Technology, vol. 3, no. 2, pp. 362-367,  June 2023. DOI: 10.48175/IJARSCT-11364.
  • Suhas .B. (2021). Detecting Salient Objects In A Video’s By Usingspatio-Temporal Saliency & Colour Map. International Journal of Innovations in Engineering Research and Technology, 3(8), 1-9. Available at:https://repo.ijiert.org/index.php/ijiert/article/view/910
  • Suhas B khadake , Pranita J Kashid , Asmita M Kawade , Santoshi V Khedekar , H. M. Mallad., “Electric Vehicle Technology Battery Management – Review”, International Journal of Advanced Research in Science Communication and Technology, vol. 3, no. 2, pp. 319-325, September 2023. Available at: https://doi.org/10.48175/ijarsct-13048.
  • Machha Babitha, C Sushma, et al, “Trends of Artificial Intelligence for online exams in education”, International journal of Early Childhood special Education, 2022, Vol 14, Issue 01, pp. 2457-2463.
  • J. Sirisha Devi, Mr. B. Sreedhar, et al, “A path towards child-centric Artificial Intelligence based Education”, International Journal of Early Childhood special Education, 2022, Vol 14, Issue 03, pp. 9915-9922.
  • D. Sreenivasulu, Dr. J. Sirishadevi, et al, “Implementation of Latest machine learning approaches for students Grade Prediction”, International Journal of Early Childhood special Education, 2022, Vol 14, Issue 03, pp. 9887-9894
  • K. P. Pardeshi et al, “Development of Machine Learning based Epileptic Seizureprediction using Web of Things (WoT)” , NeuroQuantology, 2022, Vol 20, Issue 8, pp. 9394- 9409
  • K. P. Pardeshi et al, “Implementation of Fault Detection Framework for Healthcare Monitoring System Using IoT, Sensors in Wireless Environment”, Telematique, 2022, Vol 21, Issue 1, pp. 5451 – 5460
  • Vahida, et al, “ Deep Learning, YOLO and RFID based smart Billing Handcart”, Journal of Communication Engineering & Systems, 2023, 13(1), pp. 1-8
  • Karale Aishwarya A, et al, “Smart Billing Cart Using RFID, YOLO and Deep Learning for Mall Administration”, International Journal of Instrumentation and Innovation Sciences, 2023, Vol 8, Issue- 2.
  • Sultanabanu Kazi, Mardanali Shaikh, “Machine Learning in the Production Process Control of Metal Melting” Journal of Advancement in Machines, Volume 8 Issue 2 (2023)
  • Sayyad Liyakat (2023). Smart Motion Detection System using IoT: A NodeMCU and Blynk Framework, Journal of Microelectronics and Solid State Devices, Vol 10, No 3 (2023)
  • Sayyad Liyakat (2024). Blynk IoT-Powered Water Pump-Based Smart Farming, Recent Trends in Semiconductor and Sensor Technology, 1(1), 8-14.
  • Sultanabanu Kazi, et al.(2023), Fruit Grading, Disease Detection, and an Image Processing Strategy, Journal of Image Processing and Artificial Intelligence, 9(2), 17-34.
  • Sultanabanu Sayyad Liyakat (2023). Electronics with Artificial Intelligence Creating a Smarter Future: A Review, Journal of Communication Engineering and Its Innovations, 9(3), 38-42
  • Sultanabanu Sayyad Liyakat (2023). Dispersion Compensation in Optical Fiber: A Review, Journal of Telecommunication Study, 8(3), 14-19.
  • Sultanabanu Sayyad Liyakat (2023). IoT Based Arduino-Powered Weather Monitoring System, Journal of Telecommunication Study, 8(3), 25-31.
  • Sultanabanu Sayyad Liyakat (2023). Arduino Based Weather Monitoring System, Journal of Switching Hub, 8(3), 24-29.
  • K K S Liyakat (2022). Implementation of e-mail security with three layers of authentication, Journal of Operating Systems Development and Trends, 9(2), 29-35
  • Mishra Sunil B., et al. (2024). Nanotechnology’s Importance in Mechanical Engineering, Journal of Fluid Mechanics and Mechanical Design, 6(1), 1-9.
  • Sultanabanu Sayyad Liyakat, (2024). IoT-based Alcohol Detector using Blynk, Journal of Electronics Design and Technology, 1(1), 10-15.
  • Sultanabanu Sayyad Liyakat,(2023). Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. Journal of Nanoscience, Nanoengineering & Applications. 2023; 13(2): 17–26p. DOI: https://doi.org/10.37591/jonsnea.v13i2.1464
  • Mishra Sunil B., et al. (2024). Review of the Literature and Methodological Structure for IoT and PLM Integration in the Manufacturing Sector, Journal of Advancement in Machines, 9(1), 1-5
  • Sayyad Liyakat (2024). Smart Agriculture based on AI-Driven-IoT(AIIoT): A KSK Approach, Advance Research in Communication Engineering and its Innovations, 1(2), 23-32.
  • Mishra Sunil B., et al. (2024). AI-Driven IoT (AI IoT) in Thermodynamic Engineering, Journal of Modern Thermodynamics in Mechanical System, 6(1), 1-8.
  • Sayyad Liyakat,(2023). Intelligent Watering System (IWS) for Agricultural Land Utilising Raspberry Pi. Recent Trends in Fluid Mechanics. 2023; 10(2): 26–31p.
  • Kazi Sultanabanu Sayyad Liyakat, Kazi Kutubuddin Sayyad Liyakat,(2023). Nanomedicine as a Potential Therapeutic Approach to COVID-19. International Journal of Applied Nanotechnology. 2023; 9(2): 27–35p.
  • Sayyad Liyakat, (2023). IoT based Healthcare Monitoring for COVID- Subvariant JN-1, Journal of Electronic Design Technology, Vol 14, No 3 (2023)
  • Chopade Mallikarjun Abhangrao (2024), Internet of Things in Mechatronics for Design and Manufacturing: A Review, Journals of Mechatronics Machine Design and Manufacturing, Vol 6, Issue 1.
  • Sunil Shivaji Dhanwe, et al. (2024). AI-driven IoT in Robotics: A Review, Journal of Mechanical Robotics, 9(1), 41-48.
  • Sayyad Liyakat (2024). IoT and Sensor-based Smart Agriculturing Driven by NodeMCU, Research & Review: Electronics and Communication Engineering, 1(2), 25-33.

 

Ahead of Print Subscription Review Article
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Received July 16, 2024
Accepted July 31, 2024
Published August 16, 2024
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