Abstract
The most commonly seen things on streets in any city are vehicles. However, most of them are used to transport people or goods. What if they also carry resources and capabilities for sensing, communications, computing, storage, and intelligence (SCCSI)? We would have a web of sensors to monitor the city, a network of powerful communicators to transport data around, a grid of computing power to conduct data analytics and machine learning (ML), a network of distributed storage to buffer/cache data/job for optimization, and a set of movable AI/ML toolboxes made available for specialized smart applications. This perspective article presents information on leveraging SCCSI-empowered vehicles to design such a service network, simply called SCCSI network, to help build a smart city with a cost-effective and sustainable solution. It showcases how multi-dimensional technologies - namely, sensing, communications, computing, storage, and intelligence - converge to a unifying technology to solve grand challenges for resource demands from emerging large-scale applications. Thus, with SCCSI-empowered vehicles on the ground, over the air, and on the sea, SCCSI networks can make resources and capabilities on the move, practically pushing SCCSI services to the edge! We hope this article serves as a spark to stimulate more disruptive thinking to address grand challenges of paramount importance.
| Original language | English |
|---|---|
| Pages (from-to) | 200-206 |
| Number of pages | 7 |
| Journal | IEEE Communications Society Magazine |
| Volume | 63 |
| Issue number | 4 |
| Early online date | 27 Sept 2024 |
| DOIs | |
| Publication status | Published - Apr 2025 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 1979-2012 IEEE.
Funding
This work was supported in part by the Hong Kong SAR Government under the Global STEM Professorship and Research Talent Hub, and the Hong Kong Jockey Club under the Hong Kong JC STEM Lab of Smart City (Ref.: 2023-0108). The work of Y. Deng was also supported in part by the National Natural Science Foundation of China under Grant No. 62301300. The work of X. Chen was supported in part by HKU-SCF FinTech Academy R&D Funding.