| Issue |
ITM Web Conf.
Volume 65, 2024
International Conference on Multidisciplinary Approach in Engineering, Technology and Management for Sustainable Development: A Roadmap for Viksit Bharat @ 2047 (ICMAETM-24)
|
|
|---|---|---|
| Article Number | 03015 | |
| Number of page(s) | 5 | |
| Section | Computer Engineering and Information Technology | |
| DOI | https://doi.org/10.1051/itmconf/20246503015 | |
| Published online | 16 July 2024 | |
Towards a Sustainable Future: Enabling Industry with Green Web 3.0, Decentralized AI, and Edge Intelligence
P P Savani University, NH 8, GETCO, Near Biltech, Dhamdod, Kosamba
1* meenakshi.kashyap@ppsu.ac.in
2 raviraj.chaihan@ppsu.ac.in
3 dhruvil7694@gmail.com
4 kishanprajapati0242@gmail.com
Our world is, at a point in terms of the environment. The fashioned industrial approach, which heavily relies on centralized systems and resource-intensive computing is no longer sustainable. This document delves into a way to embrace Green Web 3.0, Decentralized AI and Edge Intelligence to drive the industry to-ward a more sustainable future. Green Web 3.0 challenges the energy nature of blockchain technology by utilizing eco-friendly protocols such as Proof of Stake which reduces energy consumption and lessens environmental impact. Similarly, Decentralized AI empowers distributed systems decreasing dependence, on data centers and promoting efficient resource utilization. Building on this foundation Edge Intelligence enables real-time decision making and data processing at the source reducing data transfer and optimizing energy efficiency. The combination of these technologies has the potential to revolutionize industries. Picture smart factories adjusting production in real-time supply chains supported by networks and renewable energy networks managed by intelligent edge devices.
Key words: Sensors / Cloud / Confidentiality WSN / IoT / Security / IoT Components
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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