IOT has the power to transform industries and enhance people's lives. However, resolving the
growing concerns about energy usage is necessary for its widespread adoption. Because
nanotechnology makes it possible to manufacture self-powered gadgets, low-power circuits,
high-performance batteries, and sophisticated sensors, it offers a method to build an IoT
ecosystem that uses less energy. With thousands of devices connected and vast amounts of data
being generated, Internet of Things(IoT) is quickly changing how we live and work. However,
energy consumption is a serious obstacle to this rapid increase. The energy needed to power
these devices, gather and analyze data, and keep the network linked is increasing along with the
number of connected devices. Thankfully, there are promising ways to increase energy efficiency
throughout the IoT ecosystem thanks to nanotechnology. IoTs' potential lies in its capacity to
smoothly incorporate gadgets into our everyday routines. These devices do, however, have high
energy requirements. By increasing the sensitivity of IoT sensors, nanotechnology is opening the
door to the possibility of more precise, accurate, and useful data collecting. Numerous new
opportunities for IoT applications across different industries are made possible by the capacity to
identify and measure even the smallest changes in the environment or target characteristic. The
increased sensitivity provided by sensors enabled by nanotechnology has the potential to

transform data collection and propel the development of IoT, from facilitating early disease
detection to streamlining industrial operations and safeguarding the environment.
Keywords: Nanotechnology, IoT, Sensitivity, Energy efficiency, advanced sensors,

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1. Liyakat KS, Liyakat KK. Nanomedicine as a potential therapeutic approach to COVID-19. Int J Appl Nanotechnol. 2023;9(2):27-35.

2. Alabdulatif A, Thilakarathne NN, Lawal ZK, Fahim KE, Zakari RY. Internet of nano-things (IoNT): a comprehensive review from architecture to security and privacy challenges. Sensors. 2023;23(5):2807.

3. Ralls AM, Leong K, Clayton J, Fuelling P, Mercer C, Navarro V, et al. The role of lithium-ion batteries in the growing trend of electric vehicles. Materials (Basel). 2023;16(17):6063.

4. Opris I, Lebedev MA, Pulgar VM, Vidu R, Enachescu M, Casanova MF. Nanotechnologies in neuroscience and neuroengineering. Front Neurosci. 2020;14:33.

5. Mohanraj I, Ashokumar K, Naren JJ. Field monitoring and automation using IoT in agriculture domain. Procedia Comput Sci. 2016;93:931-9.

6. Hotkar PR, Kulkarni V, Kamble P, Kazi KS. Implementation of low power and area efficient carry select adder. Int J Res Eng Sci Manag. 2019;2(4):183-4.

7. Ramkumar B, Kittur HM. Low-power and area-efficient carry select adder. IEEE Trans Very Large Scale Integr (VLSI) Syst. 2011;20(2):371-5.

8. Liyakat KK. Blynk IoT-powered water pump-based smart farming. Recent Trends Semicond Sensor Technol. 2024;1(1):8-14.

9. Narayana Rao TV, Yellu KR. Preventing drunken driving accidents using IoT. Int J Adv Res Comput Sci. 2017;8(3):[pages not specified].

10. Atlam HF, Walters RJ, Wills GB. Internet of nano things: security issues and applications. In: Proceedings of the 2nd International Conference on Cloud and Big Data Computing; 2018 Aug 3; [location not specified]. p. 71-7.

11. Mehdipour-Ataei S. Polymers and clean energy. Iran Polym J. 2022;31(1):5-6.

12. Liyakat KK. Review of biopolymers in agriculture application: an eco-friendly alternative. Int J Compos Constit Mater. 2024;10(1):50-62.

13. Lage-Rivera S, Ares-Pernas A, Abad MJ. Last developments in polymers for wearable energy storage devices. Int J Energy Res. 2022;46(8):10475-98.

14. Zhuang X, Wang F, Hu X. Biodegradable polymers: a promising solution for green energy devices. Eur Polym J. 2024;204:112696.

15. Kosgiker GM. Satellite sensing for sea level monitoring: a transformative approach to understanding climate change. J Microw Eng Technol. 2025;12(1):33-41.

16. Prasad DS, Jyothi P, Suryanarayana G, Mohanty SN. Algorithms to mitigate cyber security threats by employing intelligent machine learning models in the design of IoT-aided drones. In: Drone Technology: Future Trends and Practical Applications. 2023. p. 257-300.

17. Challa K. Enhancing credit risk assessment using AI and big data in modern finance. Am Data Sci J Adv Comput (ADSJAC). 2024;2(1):[pages not specified].

18. Kishor A, Chakraborty C. Artificial intelligence and internet of things based healthcare 4.0 monitoring system. Wirel Pers Commun. 2022;127(2):1615-31.

19. Payalan YF, Guvensan MA. Towards next-generation vehicles featuring the vehicle intelligence. IEEE Trans Intell Transp Syst. 2019;21(1):30-47.

20. Maini E, Venkateswarlu B, Maini B, Marwaha D. Machine learning-based heart disease prediction system for Indian population: an exploratory study done in South India. Med J Armed Forces India. 2021;77(3):302-11.

21. Mahant MA, Vidyullatha P. Predictive data analytics framework based on child and pregnant women health care systems. Metall Mater Eng. 2025;[volume not specified]:1167-81.

22. Fang K, Wang W, Woźniak M, Zhang Q, Yu K, Chen J, et al. Guest editorial: AI-empowered Internet of Things for data-driven psychophysiological computing and patient monitoring. IEEE J Biomed Health Inform. 2024;28(5):2496-9.

23. Liyakat KK, Khadake SB, Chounde AB, Suryagan AA, HM M, Khadatare MR. AI-driven-IoT (AIIoT) based decision making system for high-blood pressure patient healthcare monitoring. In: 2024 Int Conf Sustainable Commun Netw Appl (ICSCNA); 2024 Dec 11; [location not specified]. p. 96-102. IEEE.

24. Kazi KS. AI-powered IoT (AI IoT) for decision-making in smart agriculture: KSK approach for smart agriculture. In: Enhancing Automated Decision-Making through AI. IGI Global Sci Publ; 2025. p. 67-96.

25. Kazi KS. KK approach to increase resilience in Internet of Things: a T-cell security concept. In: Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions. IGI Global Sci Publ; 2025. p. 87-120.

26. Kazi KS, Shinde SS, Nerkar PM, Kazi SS, Kazi VS. Machine learning for brand protection: a review of a proactive defense mechanism. In: Avoiding Ad Fraud and Supporting Brand Safety: Programmatic Advertising Solutions. 2025. p. 175-220.

27. Jain A, Jain N, Verma A, Jain A. Cognitive computing’s role in shaping the future landscape of healthcare. In: 2024 IEEE Int Students’ Conf Electr Electron Comput Sci (SCEECS); 2024 Feb 24; [location not specified]. p. 1-5. IEEE.

28. SilpaRaj M, Kumar RS, Jayakumar K, Gopila M, Kumar SS, Liyakat KK. Scalable Internet of Things enabled intelligent solutions for proactive energy engagement in smart grids: predictive load balancing and sustainable power distribution. In: Int Conf Sustain Innov Comput Eng (ICSICE 2024); 2025 May 23; [location not specified]. p. 1004-16. Atlantis Press.

29. 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;4(2):73-82.

30. Prakash C, Barthwal A, Acharya D. FLOODWALL: a real-time flash flood monitoring and forecasting system using IoT. IEEE Sens J. 2022;23(1):787-99.

31. Setyawan DY, Marjunus R. A novel controlling system for smart farming-based Internet of Things (IoT). Int J Adv Comput Sci Appl. 2024;15(5):[pages not specified].

32. Tushar, Das M, Nagarajan K, Mani GA. Solar-based EV wireless charging system. AIP Conf Proc. 2024;3044(1):030016.

33. Sharman D. Getting real about small wind. Renew Energy Focus. 2010;11(3):38-41.

34. Al Ameri OA, Serhan MA, Lamont LA, El Chaar L. Variable electronic load for testing PV performance. Appl Sol Energy. 2010;46(2):89-96.

35. Bhatti F, Shah MA, Maple C, Islam SU. A novel Internet of Things-enabled accident detection and reporting system for smart city environments. Sensors (Basel). 2019;19(9):2071.

36. Mostofa KZ, Islam MA. Creation of an Internet of Things (IoT) system for the live and remote monitoring of solar photovoltaic facilities. Energy Rep. 2023;9:422-7.

IOT has the power to transform industries and enhance people's lives. However, resolving the
growing concerns about energy usage is necessary for its widespread adoption. Because
nanotechnology makes it possible to manufacture self-powered gadgets, low-power circuits,
high-performance batteries, and sophisticated sensors, it offers a method to build an IoT
ecosystem that uses less energy. With thousands of devices connected and vast amounts of data
being generated, Internet of Things(IoT) is quickly changing how we live and work. However,
energy consumption is a serious obstacle to this rapid increase. The energy needed to power
these devices, gather and analyze data, and keep the network linked is increasing along with the
number of connected devices. Thankfully, there are promising ways to increase energy efficiency
throughout the IoT ecosystem thanks to nanotechnology. IoTs' potential lies in its capacity to
smoothly incorporate gadgets into our everyday routines. These devices do, however, have high
energy requirements. By increasing the sensitivity of IoT sensors, nanotechnology is opening the
door to the possibility of more precise, accurate, and useful data collecting. Numerous new
opportunities for IoT applications across different industries are made possible by the capacity to
identify and measure even the smallest changes in the environment or target characteristic. The
increased sensitivity provided by sensors enabled by nanotechnology has the potential to

transform data collection and propel the development of IoT, from facilitating early disease
detection to streamlining industrial operations and safeguarding the environment.
Keywords: Nanotechnology, IoT, Sensitivity, Energy efficiency, advanced sensors,

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Liyakat KS, Liyakat KK. Nanomedicine as a potential therapeutic approach to COVID-19. Int J Appl Nanotechnol. 2023;9(2):27-35.

2. Alabdulatif A, Thilakarathne NN, Lawal ZK, Fahim KE, Zakari RY. Internet of nano-things (IoNT): a comprehensive review from architecture to security and privacy challenges. Sensors. 2023;23(5):2807.

3. Ralls AM, Leong K, Clayton J, Fuelling P, Mercer C, Navarro V, et al. The role of lithium-ion batteries in the growing trend of electric vehicles. Materials (Basel). 2023;16(17):6063.

4. Opris I, Lebedev MA, Pulgar VM, Vidu R, Enachescu M, Casanova MF. Nanotechnologies in neuroscience and neuroengineering. Front Neurosci. 2020;14:33.

5. Mohanraj I, Ashokumar K, Naren JJ. Field monitoring and automation using IoT in agriculture domain. Procedia Comput Sci. 2016;93:931-9.

6. Hotkar PR, Kulkarni V, Kamble P, Kazi KS. Implementation of low power and area efficient carry select adder. Int J Res Eng Sci Manag. 2019;2(4):183-4.

7. Ramkumar B, Kittur HM. Low-power and area-efficient carry select adder. IEEE Trans Very Large Scale Integr (VLSI) Syst. 2011;20(2):371-5.

8. Liyakat KK. Blynk IoT-powered water pump-based smart farming. Recent Trends Semicond Sensor Technol. 2024;1(1):8-14.

9. Narayana Rao TV, Yellu KR. Preventing drunken driving accidents using IoT. Int J Adv Res Comput Sci. 2017;8(3):[pages not specified].

10. Atlam HF, Walters RJ, Wills GB. Internet of nano things: security issues and applications. In: Proceedings of the 2nd International Conference on Cloud and Big Data Computing; 2018 Aug 3; [location not specified]. p. 71-7.

11. Mehdipour-Ataei S. Polymers and clean energy. Iran Polym J. 2022;31(1):5-6.

12. Liyakat KK. Review of biopolymers in agriculture application: an eco-friendly alternative. Int J Compos Constit Mater. 2024;10(1):50-62.

13. Lage-Rivera S, Ares-Pernas A, Abad MJ. Last developments in polymers for wearable energy storage devices. Int J Energy Res. 2022;46(8):10475-98.

14. Zhuang X, Wang F, Hu X. Biodegradable polymers: a promising solution for green energy devices. Eur Polym J. 2024;204:112696.

15. Kosgiker GM. Satellite sensing for sea level monitoring: a transformative approach to understanding climate change. J Microw Eng Technol. 2025;12(1):33-41.

16. Prasad DS, Jyothi P, Suryanarayana G, Mohanty SN. Algorithms to mitigate cyber security threats by employing intelligent machine learning models in the design of IoT-aided drones. In: Drone Technology: Future Trends and Practical Applications. 2023. p. 257-300.

17. Challa K. Enhancing credit risk assessment using AI and big data in modern finance. Am Data Sci J Adv Comput (ADSJAC). 2024;2(1):[pages not specified].

18. Kishor A, Chakraborty C. Artificial intelligence and internet of things based healthcare 4.0 monitoring system. Wirel Pers Commun. 2022;127(2):1615-31.

19. Payalan YF, Guvensan MA. Towards next-generation vehicles featuring the vehicle intelligence. IEEE Trans Intell Transp Syst. 2019;21(1):30-47.

20. Maini E, Venkateswarlu B, Maini B, Marwaha D. Machine learning-based heart disease prediction system for Indian population: an exploratory study done in South India. Med J Armed Forces India. 2021;77(3):302-11.

21. Mahant MA, Vidyullatha P. Predictive data analytics framework based on child and pregnant women health care systems. Metall Mater Eng. 2025;[volume not specified]:1167-81.

22. Fang K, Wang W, Woźniak M, Zhang Q, Yu K, Chen J, et al. Guest editorial: AI-empowered Internet of Things for data-driven psychophysiological computing and patient monitoring. IEEE J Biomed Health Inform. 2024;28(5):2496-9.

23. Liyakat KK, Khadake SB, Chounde AB, Suryagan AA, HM M, Khadatare MR. AI-driven-IoT (AIIoT) based decision making system for high-blood pressure patient healthcare monitoring. In: 2024 Int Conf Sustainable Commun Netw Appl (ICSCNA); 2024 Dec 11; [location not specified]. p. 96-102. IEEE.

24. Kazi KS. AI-powered IoT (AI IoT) for decision-making in smart agriculture: KSK approach for smart agriculture. In: Enhancing Automated Decision-Making through AI. IGI Global Sci Publ; 2025. p. 67-96.

25. Kazi KS. KK approach to increase resilience in Internet of Things: a T-cell security concept. In: Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions. IGI Global Sci Publ; 2025. p. 87-120.

26. Kazi KS, Shinde SS, Nerkar PM, Kazi SS, Kazi VS. Machine learning for brand protection: a review of a proactive defense mechanism. In: Avoiding Ad Fraud and Supporting Brand Safety: Programmatic Advertising Solutions. 2025. p. 175-220.

27. Jain A, Jain N, Verma A, Jain A. Cognitive computing’s role in shaping the future landscape of healthcare. In: 2024 IEEE Int Students’ Conf Electr Electron Comput Sci (SCEECS); 2024 Feb 24; [location not specified]. p. 1-5. IEEE.

28. SilpaRaj M, Kumar RS, Jayakumar K, Gopila M, Kumar SS, Liyakat KK. Scalable Internet of Things enabled intelligent solutions for proactive energy engagement in smart grids: predictive load balancing and sustainable power distribution. In: Int Conf Sustain Innov Comput Eng (ICSICE 2024); 2025 May 23; [location not specified]. p. 1004-16. Atlantis Press.

29. 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;4(2):73-82.

30. Prakash C, Barthwal A, Acharya D. FLOODWALL: a real-time flash flood monitoring and forecasting system using IoT. IEEE Sens J. 2022;23(1):787-99.

31. Setyawan DY, Marjunus R. A novel controlling system for smart farming-based Internet of Things (IoT). Int J Adv Comput Sci Appl. 2024;15(5):[pages not specified].

32. Tushar, Das M, Nagarajan K, Mani GA. Solar-based EV wireless charging system. AIP Conf Proc. 2024;3044(1):030016.

33. Sharman D. Getting real about small wind. Renew Energy Focus. 2010;11(3):38-41.

34. Al Ameri OA, Serhan MA, Lamont LA, El Chaar L. Variable electronic load for testing PV performance. Appl Sol Energy. 2010;46(2):89-96.

35. Bhatti F, Shah MA, Maple C, Islam SU. A novel Internet of Things-enabled accident detection and reporting system for smart city environments. Sensors (Basel). 2019;19(9):2071.

36. Mostofa KZ, Islam MA. Creation of an Internet of Things (IoT) system for the live and remote monitoring of solar photovoltaic facilities. Energy Rep. 2023;9:422-7.