Integrating Sustainable Technology, Artificial Intelligence, and Advanced Communication Networks for Climate Change and Disaster Management

Authors

  • Supreet Kaur Associate Professor, Department of Computer Science Engineering, Khalsa College of Engineering and Technology, Amritsar, India
  • Jasleen Kaur Student,Department of Computer Science Engineering, Khalsa College of Engineering and Technology, Amritsar, India
  • Prince Kumar Student,Department of Computer Science Engineering, Khalsa College of Engineering and Technology, Amritsar, India
  • Anmol Preet Kour Student,Department of Computer Science Engineering, Khalsa College of Engineering and Technology, Amritsar, India
  • Priya Kumari Student,Department of Computer Science Engineering, Khalsa College of Engineering and Technology, Amritsar, India

Abstract

Since the start of the 21st century, the issues of climate change and disaster management have become major areas of concern in the world. The main factors responsible for the environmental imbalance that is taking place are rapid industrialization, urbanization without limits, and over-exploitation of natural resources. As a result, the weather is becoming more and more erratic and severe. In addition to becoming more frequent, the power of floods, droughts, cyclones and wildfires is also increasing. There are new problems in the world, and these problems can only be solved by new solutions.

 

The main factors which could have been the leading role in controlling the situation during the good times are sustainable technologies, smart monitoring systems and AI-driven prediction models. These resources are designed to ‘slow down’ the threats, attract the readiness and make the response easier. The report is about how the use of eco-friendly technologies, prediction AI and communication systems can provide the disaster management with the improvements they require.

References

Adeel A, Gogate M, Farooq S, Ieracitano C, Dashtipour K, Larijani H, Hussain A. A survey on the role of wireless sensor networks and IoT in disaster management. 86

Rolnick D, Donti PL, Kaack LH, Kochanski K, Lacoste A, Sankaran K, Ross AS, Milojevic-Dupont N, Jaques N, Waldman-Brown A, Luccioni AS. Tackling climate change with machine learning. ACM Computing Surveys (CSUR). 2022 Feb 8;55(2):1 96.

Oh Y, Seo M, Kim D, Seo J. Prototype-oriented Unsupervised Change Detection for Disaster Management. arXiv preprint arXiv:2310.09759. 2023 Oct 15.

Zhao S, Xiong Z, Zhao J, Zhu XX. ExEBench: Benchmarking Foundation Models on Extreme Earth Events. arXiv preprint arXiv:2505.08529. 2025 May 13.

Lavell A. Unpacking climate change adaptation and disaster risk management: Searching for the links and the differences: A conceptual and epistemological critique and proposal. IUCN-FLACSO Project on Climate Change Adaptation and Disaster Risk Reduction. 2011.

Lavell A, Oppenheimer M, Diop C, Hess J, Lempert R, Li J, Myeong S. Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the intergovernmental panel on climate change (IPCC). 2012;3:25-64.

Denis-Loupot A. Disaster Risk Reduction and Climate Change Adaptation-Pathways for policy coherence in Sub-Saharan.

Pollner J, Kryspin-Watson J, Nieuwejaar S. Disaster risk management and climate change adaptation in Europe and central Asia. Washington, DC: World Bank; 2010.

Arnell NW. The implications of climate change for emergency planning. International Journal of Disaster Risk Reduction. 2022 Dec 1;83:103425

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Published

2026-01-16

Issue

Vol. 12 (2025): (Special Issue) Journal of Advanced Research in Medical Science & Technology

Section

Research Article

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Copyright (c) 2026 Supreet Kaur, Jasleen Kaur, Prince Kumar, Anmol Preet Kour, Priya Kumari

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.