Modernizing Public Services: Leveraging the Microsoft Tech Stack in Digital Transformation
Abstract
— Scientific interest in the adaption in industrial domains is growing as a result of the Internet of Things' quick design and development advancements. The influence of dispersed new technologies, the topology of the industrial Internet of things, and the resource limitations associated with industrial 5.0 security are to blame. The fourth industrial revolution, known as the Industrial Internet of Things (IIoT), focuses on profits while enhancing productivity, dependability, and competitiveness. IIoTenabled technology has been studied and employed in a variety of studies, but additional investigation is needed to fully grasp the promise and challenges they present. Machine learning, or ML, helps promote the adoption of the Internet of Things (IoT) by autonomously identifying patterns in data and generating meaningful insights from massive amounts of observed data. To effectively serve governments, enterprises, and customers on their own, the Internet of Things (IoT) requires Machine Learning (ML). The Internet of Things collects environment data and employs powerful algorithms for automated human-driven decisionmaking processes. The machine learning and Internet of Things research is organised and assessed according to data, application, and industry perspectives. We review relevant studies and investigate how the Internet of Things and Artificial Intelligence (AI) may make our surroundings smarter. Our analysis includes a number of cutting-edge approaches. We also discuss distributed computing, trivial learning, deep learning, networked automobiles, managing pandemics, and the Internet of Things. Concerns about technological advances, individuals, businesses, and society as a whole surround the Internet of Things. Gaining knowledge about IoT usage can extend and enhance society's quality of life. In order to compare results of different machine learning techniques coupled with the Internet of Things, we also look at a case study.
Keywords
Digital Transformation, Public Services, Microsoft Tech Stack, ASP.NET Core, SQL Server DB, Azure, Legacy Systems, Data Security, Cloud Computing, AI-driven Automation, Data Analytics