INTERNET RZECZY I MODELE UCZENIA GŁĘBOKIEGO WZRÓWNOWAŻONYM ROZWOJU INTELIGENTNYCH MIAST
INTERNET OF THINGS AND DEEP LEARNING MODELS FOR SUS-TAINABLE DEVELOPMENT OF SMART CITIES

Summary/Abstract: The aim of the article is to characterize the directions of sustainable development of smart cities based on the use of the Internet of Things and deep learning models. According to the author, such a strategy creates a great opportunity to avoid the crisis in large cities resulting from the negative effects of the pandemic, urban density, climate change and environmental pollution. There is a gap in the literature on the subject, because there are no clear concepts on how to use selected technologies for the sustainable development of smart cities. For the above reasons, the article considers the strategies of using the Internet of Things and deep learning based on neural networks to increase the efficiency of the city's functioning and improve the quality of life of residents, while caring for the natural environment. An integrated city management system with the use of intelligent and ecological technologies has been characterized. The role and importance of the Internet of Things has been described in the context of managing critical city resources. On the other hand, issues related to deep learning models were presented in terms of the possibility of improving prediction and predicting results. Considerations on a special case of a deep learning architecture based on artificial neural networks (ANN) are presented. Recursive ANNs of the LSTM class were verified in terms of financial investments on the stock exchange. Finally, conclusions and planned future work were presented. The conclusions drawn on the basis of the conducted research clearly indicate that the IoT and deep learning models play an important role in the sustainable development of smart cities.

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