Smart City Gnosys
Smart city article details
| Title | Socialized Learning For Smart Cities: Cognitive Paradigm, Methodology, And Solution |
|---|---|
| ID_Doc | 52080 |
| Authors | Zhao, YF; Liu, ZC; Qiu, C; Li, XH; Wang, XF; Hu, QH |
| Year | 2021 |
| Published | IEEE WIRELESS COMMUNICATIONS, 28, 5 |
| DOI | http://dx.doi.org/10.1109/MWC.111.2100023 |
| Abstract | Along with the unprecedented boom of 5G, the Internet of Things (IoT), and artificial intelligence, smart cities are making a great clamor. When billions of IoT devices are streaming in the smart city, realizing low-latency and high-bandwidth services has a significant impact on the benefits of smart cities. Thus, managing resources efficiently and intelligently to meet various service requirements has become a challenge for smart cities. With the rapid development of machine intelligence, it can be considered that many machines constitute a machine society just like that of human beings. Inspired by the efficient and collaborative operation mechanism of human society, we propose a socialized learning scheme to address various needs in smart cities (e.g., reasonable resource allocation). Specifically, we present the socialized learning scheme from three perspectives. First, we design a cognitive paradigm of socialized learning to enlighten the long-term vision of applying learning-based resource management to smart cities, with comprehensive discussions of three dimensions consisting of architecture, decision, and knowledge. Second, we also probe the socialized learning methodology including socialized training and socialized inference. It highlights social relationships and introduces a series of technologies to realize social relations within and across layers. Finally, we give a socialized learning solution for solving the practical resource allocation problem in smart cities, thereby jointly improving decision accuracy and reducing training costs. Illustrative simulations are provided to show the effectiveness of the proposed scheme. |
| Author Keywords | Training; Costs; Smart cities; Collaboration; Resource management; Internet of Things; Probes |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
59493  | 0.889 | Ahlers, D; Driscoll, P; Löfström, E; Krogstie, J; Wyckmans, A | Understanding Smart Cities As Social Machines | PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'16 COMPANION) (2016) |
| 13108 | 0.887 | Karger E.; Rothweiler A.; Brée T.; Ahlemann F. | Building The Smart City Of Tomorrow: A Bibliometric Analysis Of Artificial Intelligence In Urbanization | Urban Science, 9, 4 (2025) |
| 49915 | 0.885 | Dustdar S.; Nastic S.; Šcekic O. | Smart Cities: The Internet Of Things, People And Systems | Smart Cities: The Internet of Things, People and Systems (2017) |
| 35880 | 0.885 | Kumar, H; Tanweer, S; Agarwal, P; Rao, NS | Machine Learning And Artificial Intelligence Based Energy Efficient Smart Cities : A Concise Survey | JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 46, 3 (2025) |
| 49568 | 0.882 | Aishwarya R.I.; Asimithaa K.; Eunice J. | Smart Cities For The Future: A Data Science Approach | Cyber security and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities (2025) |
| 25991 | 0.882 | Samui P.; Guharay A.; Mahmoudi E. | Facets Of A Smart City: Computational And Experimental Techniques For Sustainable Urban Development | Facets of a Smart City: Computational and Experimental Techniques for Sustainable Urban Development (2022) |
| 20653 | 0.882 | Hashem I.A.; Siddiqa A.; Alaba F.A.; Bilal M.; Alhashmi S.M. | Distributed Intelligence For Iot-Based Smart Cities: A Survey | Neural Computing and Applications, 36, 27 (2024) |
| 29678 | 0.882 | Shehayeb D.; Tawfik M.; Elsayed M.; Emad S.; Halawa E. | Humanizing Smart Cities: A Preconception To A Better Life For All | 2023 2nd International Conference on Smart Cities 4.0, Smart Cities 4.0 2023 (2023) |
| 49290 | 0.881 | Kirwan C.; Zhiyong F. | Smart Cities And Artificial Intelligence: Convergent Systems For Planning, Design, And Operations | Smart Cities and Artificial Intelligence: Convergent Systems for Planning, Design, and Operations (2020) |
| 19456 | 0.88 | Ahmad K.; Maabreh M.; Ghaly M.; Khan K.; Qadir J.; Al-Fuqaha A. | Developing Future Human-Centered Smart Cities: Critical Analysis Of Smart City Security, Data Management, And Ethical Challenges | Computer Science Review, 43 (2022) |