An ML-Based Solution in the Transformation towards a Sustainable Smart City
[ 1 ] Instytut Technologii Materiałów, Wydział Inżynierii Mechanicznej, Politechnika Poznańska | [ P ] employee
2024
scientific article
english
- artificial intelligence
- machine learning
- data processing
- smart sustainable city
- Social Internet of Things
- 6G
- Industry 5.0
EN The rapid development of modern information technology (IT), power supply, communication and traffic information systems and so on is resulting in progress in the area of distributed and energy-efficient (if possible, powered by renewable energy sources) smart grid components securely connected to entire smart city management systems. This enables a wide range of applications such as distributed energy management, system health forecasting and cybersecurity based on huge volumes of data that automate and improve the performance of the smart grid, but also require analysis, inference and prediction using artificial intelligence. Data management strategies, but also the sharing of data by consumers, institutions, organisations and industries, can be supported by edge clouds, thus protecting privacy and improving performance. This article presents and develops the authors’ own concept in this area, which is planned for research in the coming years. The paper aims to develop and initially test a conceptual framework that takes into account the aspects discussed above, emphasising the practical aspects and use cases of the Social Internet of Things (SIoT) and artificial intelligence (AI) in the everyday lives of smart sustainable city (SSC) residents. We present an approach consisting of seven algorithms for the integration of large data sets for machine learning processing to be applied in optimisation in the context of smart cities.
14.09.2024
8288-1 - 8288-25
Article Number: 8288
CC BY (attribution alone)
open journal
final published version
at the time of publication
100
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