Azure Cloud Services for Smart City Development : Microsoft Azure as a Smart City Ecosystem
Lähteinen, Joonas (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202504298182
https://urn.fi/URN:NBN:fi:amk-202504298182
Tiivistelmä
Smart cities represent the future of urban living, where digital technologies, data analytics and Internet of Things (IoT) devices are seamlessly integrated into city infrastructure and operations. The goal of smart cities is to enhance efficiency in urban services, improve the quality of life for residents and create more responsive, connected and adaptive environments that can meet the evolving demands of growing populations. This research focuses on the software development aspects of smart city systems, exploring data validation techniques, system architecture and the implementation of scalable solutions within the Azure cloud ecosystem.
A key area of investigation is the role of cloud-based services in managing vast amounts of real-time data generated by smart city infrastructures. The research explores data ingestion, validation and processing techniques, ensuring that information collected from IoT sensors and other sources is accurate, secure and reliable. Additionally, the research explores how digital twins can be integrated into smart city ecosystems, allowing for real-time simulations and predictive analytics that support better decision-making in urban management. The focus on digital twins was on traffic simulation, since improving traffic flow is a key objective in smart city development projects.
The research also addresses cybersecurity challenges in large-scale smart city systems, highlighting the risks associated with interconnected infrastructures, expanding attack surfaces and data privacy concerns. Security strategies and best practices are analyzed, emphasizing the importance of robust threat detection, risk mitigation and compliance with regulatory frameworks. Furthermore, the research discusses ethical considerations, particularly the implications of mass data collection, surveillance and the responsible implementation of smart city technologies.
A key area of investigation is the role of cloud-based services in managing vast amounts of real-time data generated by smart city infrastructures. The research explores data ingestion, validation and processing techniques, ensuring that information collected from IoT sensors and other sources is accurate, secure and reliable. Additionally, the research explores how digital twins can be integrated into smart city ecosystems, allowing for real-time simulations and predictive analytics that support better decision-making in urban management. The focus on digital twins was on traffic simulation, since improving traffic flow is a key objective in smart city development projects.
The research also addresses cybersecurity challenges in large-scale smart city systems, highlighting the risks associated with interconnected infrastructures, expanding attack surfaces and data privacy concerns. Security strategies and best practices are analyzed, emphasizing the importance of robust threat detection, risk mitigation and compliance with regulatory frameworks. Furthermore, the research discusses ethical considerations, particularly the implications of mass data collection, surveillance and the responsible implementation of smart city technologies.