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.

Dr Kazi Kutubuddin S. L.,

Dr. G M Kosgiker,
- Professor, Department of Electronics and Telecommunication Engineering, Brahmadanda Mane Institute of Technology, Solapur, Maharashtra, India
- Professor, Department of Electronics and Telecommunication Engineering, Brahmadanda Mane Institute of Technology, Solapur, Maharashtra, India
Abstract
document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_147019’);});Edit Abstract & Keyword
Satellite sensing becomes an essential tool for risk assessment and management as coastal communities continue to struggle with the numerous threats posed by climate change. By using this technology, environmental scientists, legislators, and urban planners may make better judgements that will result in coastal towns that are safer and more resilient. A major advancement in reducing the effects of extreme weather, environmental degradation, and rising sea levels has been made with the incorporation of satellite data into urban planning and disaster preparedness initiatives. Resilience and adaptation are not just choices; they are essentials, and satellite sensing offers the means to successfully achieve them. Sea level monitoring has been revolutionized by satellite sensing, which provides vital information that helps us comprehend how climate change affects sea levels worldwide. Satellite observations will become ever more important as technology develops to support climate resilience plans and assist vulnerable people worldwide. A new era in environmental monitoring is being fostered by the combination of cutting-edge sensing techniques, teamwork, and improved data accessibility, all of which are crucial for preserving the future of our planet.
Keywords: Satellite Sensing, Sea level, Climate change, coastal areas, environmental study.
[This article belongs to Journal of Microwave Engineering and Technologies (jomet)]
Dr Kazi Kutubuddin S. L., Dr. G M Kosgiker. Satellite Sensing for Sea Level Monitoring: A Transformative Approach to Understanding Climate Change. Journal of Microwave Engineering and Technologies. 2025; 12(01):-.
Dr Kazi Kutubuddin S. L., Dr. G M Kosgiker. Satellite Sensing for Sea Level Monitoring: A Transformative Approach to Understanding Climate Change. Journal of Microwave Engineering and Technologies. 2025; 12(01):-. Available from: https://journals.stmjournals.com/jomet/article=2025/view=0
References
- Mahmoudi, A. Flah and L. Sbita, “Prototype design of a compact plug-in solar electric vehicle application for smart power management architecture,” 2017 International Conference on Green Energy Conversion Systems (GECS), Hammamet, Tunisia, 2017, pp. 1-4, doi: 10.1109/GECS.2017.8066162.
- Khandelwal and J. Kumar, “Applications of AI for Power Electronics and Drives Systems: A Review,” 2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Vellore, India, 2019, pp. 1-6, doi: 10.1109/i-PACT44901.2019.8960123.
- 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
- M. Mallad, et al, “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.
- 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
- A 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
- Khadake 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. Https://Repo.Ijiert.Org/Index.Php/Ijiert/Article/View/910 .
- 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. Https://Doi.Org/10.48175/Ijarsct-13048.
- Karale Nikita, Jadhav Supriya, et al, (2020). Design of Vehicle system using CAN Protocol, International Journal of Research in Applied science and Engineering Technology, 8(V), pp. 1978 – 1983, http://doi.org/10.22214/ijraset.2020.5321.
- Kazi Sultanabanu Sayyad Liyakat,(2023m). 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 .
- Kazi Kutubuddin Sayyad Liyakat. (2023k). Home Automation System Based on GSM. Journal of VLSI Design Tools & Technology. 13(3): 7–12p. https://doi.org/10.37591/jovdtt.v13i3.7877 .
- 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
- 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.
- 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
- 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
- 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
- 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
- Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, Bokoro PN, Sharma R. Explainable AI for healthcare 5.0: opportunities and challenges. IEEE Access. 2022 Aug 8;10:84486-517. Veena, M. Sridevi, 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
- 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
- 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
- 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, (2024c). 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
- Yang CC. Explainable artificial intelligence for predictive modeling in healthcare. Journal of healthcare informatics research. 2022 Jun;6(2):228-39.

Journal of Microwave Engineering and Technologies
| Volume | 12 |
| Issue | 01 |
| Received | 13/12/2024 |
| Accepted | 18/12/2024 |
| Published | 10/01/2025 |