Abstract
Machine learning (ML) has already gained the attention of the researchers involved in smart city (SC) initiatives, along with other advanced technologies such as IoT, big data, cloud computing, or analytics. In this context, researchers also realized that data can help in making the SC happen but also, the open data movement has encouraged more research works using machine learning. Based on this line of reasoning, the aim of this paper is to conduct a systematic literature review to investigate open data-based machine learning applications in the six different areas of smart cities. The results of this research reveal that: (a) machine learning applications using open data came out in all the SC areas and specific ML techniques are discovered for each area, with deep learning and supervised learning being the first choices. (b) Open data platforms represent the most frequently used source of data. (c) The challenges associated with open data utilization vary from quality of data, to frequency of data collection, to consistency of data, and data format. Overall, the data synopsis as well as the in-depth analysis may be a valuable support and inspiration for the future smart city projects.
Highlights
Mining into our dataset with the challenges meet for different types of machine learning applications, we have discovered 25 out of the total deep learning based applications have encountered problems related to data utilization
Machine learning already gave the measure of its value and usefulness
artificial intelligence (AI) and machine learning become a core part of businesses, either private or public, around the world
Summary
The quoted analysis states the fuzziness of the SC concept, while there is not a generally agreed definition in the literature; the SC concept is frequently described as many-sided, multidimensional, complex, widespread, or fuzzy, while being used in inconsistent ways [2,4,5,6] Having all these different opinions, we have decided to combine the ‘intelligent city’ perspective with the multidimensional view of the smart city in our research. 2020 indicated that AI is applied in many smart cities’ areas such as education, security, transport, energy, environment, health, land use, and urban governance [7] They conclude that learning-based AI, known as machine learning (ML) has a greater potential to solve SC problems than rules-based AI. We have chosen to investigate the ‘intelligent city’ fostered by the impulse generated by the development of machine learning applications
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