Nanomaterial Embedded in Sensor Technology: A New Era of Sensing Solutions

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume :15 | Issue : 01 | Page : –
By
vector

K Kazi,

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

Abstract document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_131012’);});Edit Abstract & Keyword

The emergence of nanotechnology has catalyzed remarkable advances in sensor technology, leading to the development of highly sensitive and selective devices critical for wide range of uses, from environmental monitoring to biomedical diagnostics. Nanomaterials, characterized by unique physical and chemical properties at the nanoscale, serve as effective building blocks for these sensors. This article explores the incorporation of nanomaterials in sensor technology, detailing their operational mechanisms, benefits, and challenges. It investigates various types of nanomaterial-based sensors and highlights their potential in enhancing the performance, efficiency, and accuracy of detection systems. Furthermore, it addresses the future directions and implications of this integration for scientific research and industry. Ultimately, the future of nanomaterials and sensors technology is bright, with potential applications set to transform industries and improve quality of life. Continued investment in research and development, coupled with robust regulatory frameworks, will be essential to fully unlock this transformative potential while addressing safety and ethical considerations. As we advance further into the nanotechnology era, it is crucial to harness its abilities responsibly to ensure sustainable and equitable progress.

 

Keywords: Nanomaterials, Nanotechnology, IoT, Sensors, sensitivity, chemical

[This article belongs to Journal of Nanoscience, NanoEngineering & Applications (jonsnea)]

How to cite this article:
K Kazi. Nanomaterial Embedded in Sensor Technology: A New Era of Sensing Solutions. Journal of Nanoscience, NanoEngineering & Applications. 2025; 15(01):-.
How to cite this URL:
K Kazi. Nanomaterial Embedded in Sensor Technology: A New Era of Sensing Solutions. Journal of Nanoscience, NanoEngineering & Applications. 2025; 15(01):-. Available from: https://journals.stmjournals.com/jonsnea/article=2025/view=0

References
document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_ref_131012’);});Edit

  1. Halli UM. Nanotechnology in IoT Security. J Nanoscience Nanoengineering Appl. 2022;12(3):11–6.
  2. Wale AD, Rokade D, et al. Smart Agriculture System using IoT. Int J Innov Res Technol. 2019;5(10):493–7.
  3. Halli UM. Nanotechnology in E-Vehicle Batteries. Int J Nanomater Nanostruct. 2022;8(2):22–7.
  4. Hotkar PR, Kulkarni V, et al. Implementation of Low Power and Area Efficient Carry Select Adder. Int J Res Eng Sci Manage. 2019;2(4):183–4.
  5. Sayyad Liyakat KK. Nanotechnology Application in Neural Growth Support System. Nano Trends J Nanotechnol Appl. 2022;24(2):47–55.
  6. Mishra SB, et al. Nanotechnology’s Importance in Mechanical Engineering. J Fluid Mech Mech Des. 2024;6(1):1–9.
  7. Sayyad Liyakat KK. Blynk IoT-Powered Water Pump-Based Smart Farming. Recent Trends Semiconductor Sens Technol. 2024;1(1):8–14.
  8. Sayyad Liyakat S. IoT-based Alcohol Detector using Blynk. J Electron Des Technol. 2024;1(1):10–5.
  9. Sayyad Liyakat KS. Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. J Nanoscience Nanoengineering Appl. 2023;13(2):17–26. doi:10.37591/jonsnea.v13i2.1464.
  10. Dhanwe SS, et al. AI-driven IoT in Robotics: A Review. J Mech Robot. 2024;9(1):41–8..
  11. Patil SS, et al. Research on AI Applications in Cloud Computing. Int J Cloud Comput Appl. 2023;5(3):56–63.
  12. Shah AV, et al. Image Processing for Disease Detection in Agriculture. J Comput Vis AI. 2023;3(4):78–85.
  13. Sayyad Liyakat S. Low-Cost Autonomous Drone with AI. J Aeronaut Aerosp Eng. 2023;2(2):112–8.
  14. Kulkarni PR, et al. Role of Blockchain in Secure IoT. J Cyber Secur Trends. 2023;4(1):34–40.
  15. Mishra SB, et al. Advancements in Nanomaterials for Biomedical Applications. Biomed Mater Res J. 2023;6(2):45–53.
  16. Sayyad Liyakat KK. IoT-based Garbage Monitoring System. Int J Innov Res Technol. 2024;6(1):23–8.
  17. Rao P, et al. Graphene-Based Sensors for Environmental Monitoring. Sensors J Adv Mater Appl. 2024;8(3):14–22.
  18. Sayyad Liyakat S. Self-Healing Materials with Nanotechnology. Nano Trends J Nanotechnol Appl. 2024;25(1):57–64.
  19. Patil AS, et al. Energy Harvesting Techniques in IoT Devices. J Smart Energy Sustain Dev. 2023;7(2):19–26.
  20. Sayyad Liyakat S. Blynk-based Weather Monitoring System. IoT Tech Trends J. 2024;2(1):9–15.
  21. Kazi Kutubuddin Sayyad Liyakat. Review of Biopolymers in Agriculture Application: An Eco-Friendly Alternative. Int J Compos Constit Mater. 2024;10(1):50–62.
  22. Kazi Kutubuddin Sayyad Liyakat. Railway Health-Monitoring Using KSK Approach: Decision-Making Using AIIoT Approach in Railways. J Controller Converters. 2024;9(3):1–10. Available from: https://matjournals.net/engineering/index.php/JCC/article/view/1047
  23. K K Sayyad Liyakat. Impact of Nanotechnology on Battlefield Welfare: A Study. Int J Nanobiotechnol. 2024;10(2):19–32.
  24. Sultanabanu Sayyad Liyakat. Nanotechnology in Healthcare Applications: A Study. Int J Nanobiotechnol. 2024;10(2):48–58.
  25. Kazi Kutubuddin Sayyad Liyakat. Internet of Battlefield Things: An IoBT-Inspired Battlefield of Tomorrow. J Telecommun Switch Syst Netw. 2024;11(3):11–19.
  26. Sunil B. Mishra. AI-Driven-IoT (AIIoT)-Based Decision Making in Manufacturing Processes in Mechanical Engineering. J Mech Robot. 2024;9(2):27–38.
  27. Sunil B. Mishra. AI-Driven-IoT (AIIoT)-Based Decision-Making in Molten Metal Processing. J Ind Mech. 2024;9(2):45–56.
  28. Kazi Kutubuddin Sayyad Liyakat. Impact of Nanotechnology on Battlefield Welfare: A Study. Int J Nanobiotechnol. 2024;10(2):19–32.
  29. Kazi Sultanabanu Sayyad Liyakat, Kazi Kutubuddin Sayyad Liyakat. Nanosensors in Agriculture Field: A Study. Int J Appl Nanotechnol. 2024;10(2):12–22. Available from: https://journalspub.com/publication/ijan-v10i02-11625/
  30. Kazi Kutubuddin Sayyad Liyakat. Nanotechnology in Space Study. Int J Appl Nanotechnol. 2024;10(2):39–46. Available from:
  31. Liyakat KKS. Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata SK, Sethi S, Gao XZ, editors. Intelligent Systems. ICMIB 2023. Lecture Notes in Networks and Systems. Vol. 728. Singapore: Springer; 2024. p. 179–90. Available from: https://doi.org/10.1007/978-981-99-3932-9_12
  32. Pradeepa M, et al. Student Health Detection Using a Machine Learning Approach and IoT. 2022 IEEE 2nd Mysore Subsection International Conference (MysuruCon); 2022. Available from: https://ieeexplore.ieee.org/document/9972445
  33. Liyakat KKS. 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. p. 1–5. Available from: https://doi.org/10.1109/ESCI56872.2023.10099544
  34. Kasat K, Shaikh N, Rayabharapu VK, Nayak M. 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. p. 1661–5. Available from: https://doi.org/10.1109/ICAISS58487.2023.10250690
  35. Liyakat KKS. Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Shukla PK, Mittal H, Engelbrecht A, editors. Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Singapore: Springer; 2023. p. 25–40. Available from: https://doi.org/10.1007/978-981-99-4577-1_3
  36. Kazi K. AI-Driven IoT (AIIoT) in Healthcare Monitoring. In: Nguyen T, Vo N, editors. Using Traditional Design Methods to Enhance AI-Driven Decision Making. Hershey, PA: IGI Global; 2024. p. 77–101. Available from: https://doi.org/10.4018/979-8-3693-0639-0.ch003
  37. Kazi K. Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In: L D, Nagpal N, Kassarwani N, Varthanan GV, Siano P, editors. E-Mobility in Electrical Energy Systems for Sustainability. Hershey, PA: IGI Global; 2024. p. 295–320. Available from: https://doi.org/10.4018/979-8-3693-2611-4.ch014
  38. Kazi KS. Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In: Garcia M, de Almeida R, editors. Transformative Approaches to Patient Literacy and Healthcare Innovation. Hershey, PA: IGI Global; 2024. p. 112–35. Available from: https://doi.org/10.4018/979-8-3693-3661-8.ch006
  39. Magadum PK. Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems. Grenze Int J Eng Technol. 2024;10(1):2074–80.
  40. Nerkar PM, Dhaware BU. Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning. J Adv Zool. 2023;44(Special Issue 2):3673–86. Available from:
  41. Neeraja P, Kumar RG, Kumar MS, Liyakat KKS, Vani MS. 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. p. 589–94. Available from: https://doi.org/10.1109/IC2PCT60090.2024.10486714
  42. Liyakat KKS. Explainable AI in Healthcare. In: Kamaraj AA, Acharjya DP, editors. Explainable Artificial Intelligence in Healthcare System. 2024. ISBN: 979-8-89113-598-7. Available from: https://doi.org/10.52305/GOMR8163
  43. Kazi LKS. ChatGPT: An Automated Teacher’s Guide to Learning. In: Bansal R, Chakir A, Ngah AH, Rabby F, Jain A, editors. AI Algorithms and ChatGPT for Student Engagement in Online Learning. Hershey, PA: IGI Global; 2024. p. 1–20. Available from: https://doi.org/10.4018/979-8-3693-4268-8.ch001
  44. Veena C, Sridevi M, Liyakat KKS, Saha B, Reddy SR, Shirisha N. 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. p. 407–10. Available from: https://doi.org/10.1109/ICIIP61524.2023.10537627
  45. Prasad KR, Karanam SR. AI in Public-Private Partnership for IT Infrastructure Development. J High Technol Manag Res. 2024;35(1):100496.
  46. Kazi KS. IoT Driven by Machine Learning (MLIoT) for the Retail Apparel Sector. In: Tarnanidis T, Papachristou E, Karypidis M, Ismyrlis V, editors. Driving Green Marketing in Fashion and Retail. Hershey, PA: IGI Global; 2024. p. 63–81.
  47. Kazi KK. 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. Available from: https://doi.org/10.4018/979-8-3693-3033-3.ch002
  48. Kazi KS. 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. Available from: https://doi.org/10.4018/979-8-3693-3583-3.ch005
  49. Kutubuddin K. Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors. Grenze Int J Eng Technol. 2024;10(2):5367–74. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3371&id=8
  50. Kutubuddin K. A Novel Approach on ML-Based Palmistry. Grenze Int J Eng Technol. 2024;10(2):5186–93.
  51. Kutubuddin K. IoT-Based Boiler Health Monitoring for Sugar Industries. Grenze Int J Eng Technol. 2024;10(2):5178–85. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3343&id=8
  52. Kazi KS. Machine Learning-Based Pomegranate Disease Detection and Treatment. In: Zia Ul Haq M, Ali I, editors. Revolutionizing Pest Management for Sustainable Agriculture. Hershey, PA: IGI Global; 2024. p. 469–98. Available from: https://doi.org/10.4018/979-8-3693-3061-6.ch019
  53. Liyakat K. IoT Technologies for the Intelligent Dairy Industry: A New Challenge. In: Thandekkattu S, Vajjhala N, editors. Designing Sustainable Internet of Things Solutions for Smart Industries. Hershey, PA: IGI Global; 2025. p. 321–50. Available from: https://doi.org/10.4018/979-8-3693-5498-8.ch012
  54. Liyakat KK. Heart Health Monitoring Using IoT and Machine Learning Methods. In: Shaik A, editor. AI-Powered Advances in Pharmacology. Hershey, PA: IGI Global; 2025. p. 257–82. Available from: https://doi.org/10.4018/979-8-3693-3212-2.ch010
  55. Sayyad KK. AI-Powered-IoT (AIIoT)-Based Decision-Making System for BP Patient’s Healthcare Monitoring: KSK Approach for BP Patient Healthcare Monitoring. In: Aouadni S, Aouadni I, editors. Recent Theories and Applications for Multi-Criteria Decision-Making. Hershey, PA: IGI Global; 2025. p. 205–38. Available from: https://doi.org/10.4018/979-8-3693-6502-1.ch008
  56. Kazi KS. AI-Driven-IoT (AIIoT)-Based Decision Making in Drones for Climate Change: KSK Approach. In: Aouadni S, Aouadni I, editors. Recent Theories and Applications for Multi-Criteria Decision-Making. Hershey, PA: IGI Global; 2025. p. 311–40. Available from: https://doi.org/10.4018/979-8-3693-6502-1.ch011
  57. Liyakat K. 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 Scientific Publishing; 2025. p. 277–306. Available from: https://doi.org/10.4018/979-8-3693-7277-7.ch009
  58. 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 Scientific Publishing; 2025. p. 205–36. Available from: https://doi.org/10.4018/979-8-3693-9641-4.ch007
  59. Nerkar P, Sultanabanu K. IoT-Based Skin Health Monitoring System. Int J Biol Pharm Allied Sci. 2024;13(11):5937–50. Available from: https://doi.org/10.31032/IJBPAS/2024/13.11.8488
  60. Sayyad KK. 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 Scientific Publishing; 2025. p. 67–96. Available from: https://doi.org/10.4018/979-8-3693-6230-3.ch003
  61. Sayyad (2025f). KK Approach to Increase Resilience in Internet of Things: A T-Cell Security Concept. In D. Darwish & K. Charan (Eds.), Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions (pp. 87-120). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9491-5.ch005
  62. Kazi KS. Machine learning-driven Internet of Medical Things (ML-IoMT)-based healthcare monitoring system. In: Soufiene B, Chakraborty C, editors. Responsible AI for digital health and medical analytics. IGI Global Scientific Publishing; 2025. p. 49-86. doi:10.4018/979-8-3693-6294-5.ch003.
  63. Kazi Kutubuddin. Vehicle health monitoring system (VHMS) by employing IoT and sensors. Grenze Int J Eng Technol. 2024;10(2):5367-5374. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3371&id=8.
  64. Kazi Kutubuddin. A novel approach on ML-based palmistry. Grenze Int J Eng Technol. 2024;10(2):5186-5193. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3344&id=8.
  65. Kazi Kutubuddin. IoT based boiler health monitoring for sugar industries. Grenze Int J Eng Technol. 2024;10(2):5178-5185. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3343&id=8.
  66. Magadum PK. Machine learning for predicting wind turbine output power in wind energy conversion systems. Grenze Int J Eng Technol. 2024;10(1):2074-2080. Available from: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8.
  67. Khadake SB, Patil VJ. Prototype design & development of solar-based electric vehicle. 3rd Int Conf Smart Generation Computing, Communication and Networking (SMART GENCON); 2023 Nov 1-7; Bangalore, India. p. 1-7. doi:10.1109/SMARTGENCON60755.2023.10442455.
  68. Patil VJ, Khadake SB, Tamboli DA, Mallad HM, Takpere SM, Sawant VA. Review of AI in power electronics and drive systems. 3rd Int Conf Power Electronics and IoT Applications in Renewable Energy and Its Control (PARC); 2024 Mar 15-18; Mathura, India. p. 94-99. doi:10.1109/PARC59193.2024.10486488.
  69. Khadake SB. Detecting salient objects of natural scene in a video using spatio-temporal saliency & color map. JNX-A Multidiscip Peer Rev J. 2021;2(8):30-35. Available from: https://repo.journalnx.com/index.php/nx/article/view/1070.
  70. Khadake SB, Dolli SP, Rathod KS, Waghmare OP, Deshpande AV. An overview of intelligent traffic control system using PLC and use of current data of vehicle travels. JNX-A Multidiscip Peer Rev J. 2021;1:1-4. Available from: https://repo.journalnx.com/index.php/nx/article/view/739.
  71. Patil VJ, Khadake SB, Tamboli DA, Mallad HM, Takpere SM, Sawant VA. A comprehensive analysis of artificial intelligence integration in electrical engineering. 5th Int Conf Mobile Computing and Sustainable Informatics (ICMCSI); 2024 Jun 5-7; Lalitpur, Nepal. p. 484-491. doi:10.1109/ICMCSI61536.2024.00076.
  72. Khadake S, Kawade S, Moholkar S, Pawar M. A review of 6G technologies and its advantages over 5G technology. In: Pawar PM, et al., editors. Techno-Societal 2022. ICATSA 2022. Springer; 2024. p. 107. doi:10.1007/978-3-031-34644-6_107.
  73. Dudgikar AB, Ingalgi AA, Jamadar AG, et al. Intelligent battery swapping system for electric vehicles with charging stations locator on IoT and cloud platform. Int J Adv Res Sci Commun Technol. 2023;3(1):204-208. doi:10.48175/IJARSCT-7867. Available from: https://ijarsct.co.in/paper7867.pdf.
  74. 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):362-367. doi:10.48175/IJARSCT-11364. Available from: https://ijarsct.co.in/paper11364.pdf.
  75. Khadake SB. Detecting salient objects in videos by using spatio-temporal saliency & color map. Int J Innov Eng Res Technol. 2021;3(8):1-9. Available from: https://repo.ijiert.org/index.php/ijiert/article/view/910.
  76. Khadake SB, Kashid PJ, Kawade AM, Khedekar SV, Mallad HM. Electric vehicle technology battery management – review. Int J Adv Res Sci Commun Technol. 2023;3(2):319-325. doi:10.48175/IJARSCT-13048.
  77. Khadake SB, Chounde A, Gopnarayan BB, Patil KB, Kamble SS. Human healthcare system: A new approach towards life. Grenze Int J Eng Technol. 2024;10(2):5487-5494.
Regular Issue Subscription Review Article
Volume 15
Issue 01
Received 22/12/2024
Accepted 27/12/2024
Published 04/01/2025
159