Internet of Things Connectivity Using Millimetre Wave: A Study

Year : 2025 | Volume : 12 | Issue : 02 | Page : 18 30
    By

    Nikat Rajak Mulla,

  • Kazi Kutubuddin Sayyad Liyakat,

  1. Student, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
  2. Professor and Head, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

Internet of Things(IoT) is undergoing rapid development, which is connecting millions of devices and causing sectors to undergo transformation. On the other hand, given this increase, the constraints of conventional wireless communication technologies are being stretched to their limits. Millimetre wave, often known as mmWave, is a high-frequency band that has the potential to revolutionise Internet of Things connectivity by providing much higher capacity levels and lower latency levels. Microwave (mmWave) is positioned to become an essential component of the future generation of IoT ecosystems, despite the fact that it is still in its early phases of application. The frequency range that extends from 30 to 300 GHz is generally referred to as millimetre waves. A significantly greater spectrum is available with mmWave frequencies, in contrast to the lower frequencies that are utilised in Wi-Fi and cellular networks. This enormous bandwidth makes it possible to transmit data at substantially quicker speeds, making it a great choice for applications that require high throughput and communication in real time. IoT is continuously expanding, which necessitates an ever-increasing bandwidth in order to support the vast number of linked devices and the data-intensive applications that they run. Millimetre wave (mmWave) technology has become the focus of interest in recent years due to the pursuit of greater data rates and lower latency. Conventional sub-6 GHz frequencies have proven to be effective in meeting these requirements. mmWave, which operates in the region of 30 to 300 GHz, provides access to a large spectrum of resources and has the potential to achieve speeds of multiple gigabits per second. But deploying mmWave in IoT poses its own set of design issues. Enhanced IoT communication is the focus of this study, which delves into the essential stages required in overcoming these hurdles and utilising the power of millimetre wave technology.

Keywords: Millimetre wave, internet of things, bandwidth, spectrum, mmWaves, high-frequency

[This article belongs to Journal of Microwave Engineering and Technologies ]

How to cite this article:
Nikat Rajak Mulla, Kazi Kutubuddin Sayyad Liyakat. Internet of Things Connectivity Using Millimetre Wave: A Study. Journal of Microwave Engineering and Technologies. 2025; 12(02):18-30.
How to cite this URL:
Nikat Rajak Mulla, Kazi Kutubuddin Sayyad Liyakat. Internet of Things Connectivity Using Millimetre Wave: A Study. Journal of Microwave Engineering and Technologies. 2025; 12(02):18-30. Available from: https://journals.stmjournals.com/jomet/article=2025/view=215480


References

1. Randive AB, Gaikwad SK, Khadake SB, HM M. Biodiesel: A Renewable Source of Fuel. Int J Adv Res Sci Commun Technol. 2024 Dec; 4(3): 225–240.

2. Mulani AO, Bang AV, Birajadar GB, Deshmukh AB, Jadhav HM, Liyakat KK. IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming. Ann Agri-Bio Res. 2024; 29(2): 71–86.

3. Dudgikar AB, Ingalgi AA, Jamadar AG, Swami OR, Khadake SB, Moholkar SV. Intelligent battery swapping system for electric vehicles with charging stations locator on IoT and cloud platform. Int J Adv Res Sci Commun Technol. 2023 Jan; 3(1): 204–8.

4. Veena C, Sridevi M, Liyakat KK, Saha B, Reddy SR, Shirisha N. HEECCNB: An efficient IoT- cloud architecture for secure patient data transmission and accurate disease prediction in healthcare systems. In 2023 IEEE Seventh International Conference on Image Information Processing (ICIIP). 2023 Nov 22; 407–410.

5. Liyakat KK. Detecting malicious nodes in IoT networks using machine learning and artificial neural networks. In 2023 IEEE International Conference on Emerging Smart Computing and Informatics (ESCI). 2023 Mar 1; 1–5.

6. Kasat K, Shaikh N, Rayabharapu VK, Nayak M, Liyakat KK. Implementation and recognition of waste management system with mobility solution in smart cities using Internet of Things. In 2023 IEEE Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). 2023 Aug 23; 1661–1665.

7. Prasad KR, Karanam SR, Ganesh D, Liyakat KK, Talasila V, Purushotham P. AI in public-private partnership for IT infrastructure development. J High Technol Manag Res. 2024 May 1; 35(1): 100496.

8. Yang CC. Explainable artificial intelligence for predictive modeling in healthcare. J Healthc Inform Res. 2022;6:228–39. doi:10.1007/s41666-022-00114-1. PMID: 35194568.

9. Liyakat KK. Microwave communication in the Internet of things: A study. J RF Microw Commun Technol. 2024;1:38–49.

10. Sayyad Liyakat KK, Konnur RG. Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors. Grenze Int J Eng Technol. 2024 Jun 15; 10: 5368–5374.

11. Kazi S. AI-driven-IoT (AIIoT)-based Jawar leaf disease detection. In: Garwi J, Dzingirai M, Masengu R, editors. Integrating Agriculture, Green Marketing Strategies, and Artificial Intelligence. Hershey (PA): IGI Global; 2025. p. 439–72.

12. Liyakat KK, Kutubuddin K. IoT based boiler health monitoring for sugar industries. In 15th International Conference on Advances in Computing, Control, ad Telecommunication Technologies, ACT 2024. 2024 Jun 15; 2: 5178–5185.

13. Kazi K. AI-driven IoT (AIIoT) in healthcare monitoring. In: Nguyen TVT, Vo NTM, editors. Using Traditional Design Methods to Enhance AI-Driven Decision Making. Hershey (PA): IGI Global Scientific Publishing; 2024. p. 77–101. doi:10.4018/979-8-3693-0639-0.ch003.

14. Kazi K. Modelling and simulation of electric vehicle for performance analysis: BEV and HEV electrical vehicle implementation using Simulink for E-mobility ecosystems. In: Lakshmi D, Nagpal N, Kassarwani N, Varthanan G, Siano P, editors. E-Mobility in Electrical Energy Systems for Sustainability. Hershey (PA): IGI Global Scientific Publishing; 2024. p. 295–320. doi:10.4018/979-8-3693-2611-4.ch014.

15. Kazi KSL. Artificial intelligence (AI)-driven IoT (AIIoT)-based agriculture automation. In: Satapathy S, Muduli K, editors. Advanced Computational Methods for Agri-Business Sustainability. Hershey (PA): IGI Global; 2024. p. 72–94. doi:10.4018/979-8-3693-3583-3.ch005.

16. El Ghati O, Alaoui-Fdili O, Alioua N, Chahbouni O, Bouari W. An overview of the applications of AI-powered visual IoT systems in agriculture. 2023 IEEE International Conference on Advances in Data-Driven Analytics and Intelligent Systems (ADACIS), Marrakesh, Morocco. 2023. p. 1–4. doi:10.1109/ADACIS59737.2023.10424223.

17. Kazi KSL. Computer-aided diagnosis in ophthalmology: A technical review of deep learning applications. In: Garcia MB, Almeida RPP, editors. Transformative Approaches to Patient Literacy and Healthcare Innovation. Hershey (PA): IGI Global; 2024. p. 1–24. doi:10.4018/979-8-3693- 3661-8.ch006.

18. Kazi KSL. IoT driven by machine learning (MLIoT) for the retail apparel sector. In: Tarnanidis TK, Papachristou E, Karypidis M, Ismyrlis V, editors. Driving Green Marketing in Fashion and Retail. Hershey (PA): IGI Global; 2024. p. 63–81. doi:10.4018/979-8-3693-3049-4.ch004.

19. Kazi KSL. Machine learning-driven Internet of medical things (ML-IoMT)-based healthcare monitoring system. In: Souene BO, Chakraborty C, editors. Responsible AI for Digital Health and Medical Analytics. Hershey (PA): IGI Global; 2024. p. 49–86. doi:10.4018/979-8-3693-6294-5.ch003.

20. Kazi KSL. Transformation of agriculture effectuated by artificial intelligence-driven Internet of things (AIIoT). In: Garwi J, Dzingirai M, Masengu R, editors. Integrating Agriculture, Green Marketing Strategies, and Artificial Intelligence. Hershey (PA): IGI Global; 2024. p. 449–84. doi:10.4018/979-8-3693-6468-0.ch015.

21. Liyakat KK, Khadake SB, Tamboli DA, Sawant VA, HM M, Sathe S. AI-Driven-IoT (AIIoT) Based Decision-Making-KSK Approach in Drones for Climate Change Study. In 2024 IEEE 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS). 2024 Dec 12; 1735–1744.

22. Magar SS, Sugandhi AS, Pawar SH, Khadake SB, Mallad HM. Harnessing Wind Vibration, a Novel Approach towards Electric Energy Generation-Review. Int J Adv Res Sci Commun Technol. 2024 Oct; 4(2): 73–82.

23. Khadake SB, Padavale PV, Dhere PM, Lingade BM. Automatic hand dispenser and temperature scanner for Covid-19 prevention. Int J Adv Res Sci Commun Technol. 2023; 3(2): 362–7.

24. Khadake S, Kawade S, Moholkar S, Pawar M. A review of 6G technologies and its advantages over 5G technology. In: Techno-Societal 2016, International Conference on Advanced Technologies for Societal Applications. Cham: Springer International Publishing; 2022 Dec 9; 1043–1051.

25. Kazi KSL. Machine learning (ML)-based Braille Lippi characters and numbers detection and announcement system for blind children in learning. In: Sart G, editor. Social Reflections of Human-Computer Interaction in Education, Management, and Economics. Hershey (PA): IGI Global; 2024. p. 16–39. doi:10.4018/979-8-3693-3033-3.ch002.

26. Mahant MA, Vidyullatha P. Predictive data analytics framework based on child and pregnant women health care systems. Metall Mater Eng. 2025;:1167–81.

27. Kazi LK, Sayyad K. ChatGPT: An automated teacher’s guide to learning. In: Bansal R, editor. AI Algorithms and ChatGPT for Student Engagement in Online Learning. Hershey (PA): IGI Global Scientific Publishing; 2024. p. 1–20. doi:10.4018/979-8-3693-4268-8.ch001.

28. Kazi KSL. Heart health monitoring using IoT and machine learning methods. In: Shaik A, editor. AI-Powered Advances in Pharmacology. Hershey (PA): IGI Global; 2025. p. 1–26. doi:10.4018/979-8-3693-3212-2.ch010.

29. Liyakat KK. Machine learning approach using artificial neural networks to detect malicious nodes in IoT networks. In International Conference on Machine Learning, IoT and Big Data. Singapore: Springer Nature Singapore; 2023 Mar 10; 123–134.

30. Khatun MA, Chowdhury N, Uddin MN. Malicious nodes detection based on artificial neural network in IoT environments. 2019 22nd International Conference on Computer and Information Technology (ICCIT), Dhaka, Bangladesh. 2019. p. 1–6. doi:10.1109/ICCIT48885.2019.9038563.

31. Kazi KSL. IoT technologies for the intelligent dairy industry: A new challenge. In: Thandekkattu SG, Vajjhala NR, editors. Designing Sustainable Internet of Things Solutions for Smart Industries. Hershey (PA): IGI Global; 2024. p. 321–50. doi:10.4018/979-8-3693-5498-8.ch012.

32. Kazi KSL. AI-driven-IoT(AIIoT)-based decision making in kidney diseases patient healthcare monitoring: KSK approach for kidney monitoring. In: Polat LÖ, Polat O, editors. AI-Driven Innovation in Healthcare Data Analytics. Hershey (PA): IGI Global; 2024. p. 277–306. doi:10.4018/979-8-3693-7277-7.ch009.

33. Kazi KSL. A study on AI-driven Internet of battlefield things (IoBT)-based decision making: KSK approach in IoBT. In: Tariq MU, editor. Merging artificial intelligence with the Internet of Things. Hershey (PA): IGI Global Scientific Publishing; 2025. p. 203–38. doi:10.4018/979-8-3693-8547- 0.ch007.

34. Kazi KSL, Mahant MA. Machine learning-driven Internet of things (MLIoT)-based healthcare monitoring system. In: Wickramasinghe N, editor. Digitalization and the Transformation of the Healthcare Sector. Hershey (PA): IGI Global; 2024. p. 205–36. doi:10.4018/979-8-3693-9641- 4.ch007.

35. Neeraja P, Kumar RG, Kumar MS, Liyakat KK, Vani MS. DL-based somnolence detection for improved driver safety and alertness monitoring. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT). 2024 Feb 9; 5: 589–594.

36. Randive AB, Gaikwad SK, Khadake SB, HM M. Biodiesel: A Renewable Source of Fuel. Int J Adv Res Sci Commun Technol. 2024 Dec; 4(3): 225–240.

37. Khadake SB, Khedekar SV, Kawade AM, Vyavahare SS, Kashid PJ, Chounde Amol B, Mallad HM. Solar Based Electric Vehicle Charging System. Int J Adv Res Sci Commun Technol. 2024 Dec; 4(2): 42–57.

38. Sayyad Liyakat KK, Magadum PK. Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems. Grenze Int J Eng Technol. 2024 Jan 22; 10: 2074–2080.

39. Nerkar PM, Dhaware BU, Liyakat KS. Predictive data analytics framework based on heart healthcare system (HHS) using machine learning. J Adv Zool. 2023; 44(2): 3673–3686.

40. Kutubuddin KA, Nerkar PR, Sultanabanu KA. IoT-based skin health monitoring system. Int J Biol Pharm Allied Sci. 2024; 13(11): 5937–50.

41. Khadake SB, Patil VJ. Prototype design & development of solar based electric vehicle. In 2023 IEEE 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON). 2023 Dec 29; 1–7.

42. Khan S, Ahmad A, Ahmad F, Shafaati Shemami M, Saad Alam M, Khateeb S. A comprehensive review on solar powered electric vehicle charging system. Smart Sci. 2018;6:54–79. doi:10.1080/23080477.2017.1419054.

43. Kazi KSL. AI-powered IoT (AI IoT) for decision-making in smart agriculture: KSK approach for smart agriculture. In: Hai-Jew S, editor. Enhancing Automated Decision-Making Through AI. Hershey (PA): IGI Global; 2024. p. 67–96. doi:10.4018/979-8-3693-6230-3.ch003.

44. Kazi KSL. KK approach to increase resilience in Internet of things: A T-cell security concept. In: Darwish D, Charan K, editors. Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions. Hershey (PA): IGI Global; 2024. p. 87–120. doi:10.4018/979-8-3693- 9491-5.ch005.

45. Kazi KSL. Healthcare monitoring system driven by machine learning and Internet of medical things (MLIoMT). In: Kumar VV, Katina PF, Zhao J, editors. Convergence of Internet of Medical Things (IoMT) and Generative AI. Hershey (PA): IGI Global Scientific Publishing; 2025. p. 385–416. doi:10.4018/979-8-3693-6180-1.ch016.

46. Landage SS, Chavan SR, Kokate PA, Lohar SP, Pawar MK, Khadake SB. Solar Outdoor Air Purifier With Air Quality Monitoring System. In Synergies of Innovation: Proceedings of NCSTEM 2023. 2024 Sep; 260–266.

47. Magar SS, Sugandhi AS, Pawar SH, Khadake SB, Mallad HM. Harnessing Wind Vibration, a Novel Approach towards Electric Energy Generation-Review. Int J Adv Res Sci Commun Technol. 2024 Oct; 4(2): 73–82.

48. Khadake SB, Kashid PJ, Kawade AM, Khedekar SV, Mallad HM. Electric vehicle technology battery management–review. Int J Adv Res Sci Commun Technol. 2023 Sep; 3(2): 319–25.

49. Chounde A, Gopnarayan BB, Patil KB, Kamble SS. Human Health Care System: A New Approach towards Life. Grenze Int J Eng Technol. 2024 Jun 15; 10(2): 5487–5494.

50. Khadake Suhas B, Dolli Sudarshan P, Rathod KS, Waghmare OP, Deshpande AV. An Overview of Intelligent Traffic Control System Using Plc and Use of Current Data of Vehicle Travels. JournalNX. 2021 Jan; 1–4.

51. Patil VJ, Mallad HM, Gopnarayan BB, Pati KB. Maximize Farming Productivity through Agriculture 4.0 based Intelligence, with use of Agri Tech Sense Advanced Crop Monitoring System. Grenze Int J Eng Technol. 2024 Jun 15; 10(2): 5127–5134.

52. Khadake SB. Detecting salient objects of natural scene in a video’s using spatio-temporal saliency & colour map. International Journal of Research Publications in Engineering and Technology (IJRPET). 2016; 2(8): 30–5.

53. Patil VJ, Khadake SB, Tamboli DA, Mallad HM, Takpere SM, Sawant VA. Review of AI in power electronics and drive systems. In 2024 IEEE 3rd International conference on Power Electronics and IoT Applications in Renewable Energy and its Control (PARC). 2024 Feb 23; 94–99.

54. Patil VJ, Khadake SB, Tamboli DA, Mallad HM, Takpere SM, Sawant VA. A comprehensive analysis of artificial intelligence integration in electrical engineering. In 2024 IEEE 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI). 2024 Jan 18; 484–491.

Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 13/05/2025
Accepted 14/05/2025
Published 26/06/2025
Publication Time 44 Days
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