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Digital Twin Technology: A Comprehensive Review

Digital Twin Technology: A Comprehensive Review
Authors:-Malithi R. Abayadeera, G.U. Ganegoda

Abstract-This review explores Digital Twin technology’s evolution since 2003, beyond replicating physical entities to encompass data ecosystems and service relationships. Analyzing its inception, growth, and multifaceted uses, the review illuminates Digital Twins’ transformative role in modern sectors. It delves into their impact on manufacturing, healthcare, smart cities, defence, agriculture, and utilities, showcasing their ability to enhance decision-making and operational efficiencies. Yet, significant obstacles hinder Digital Twin adoption, including IT infrastructure establishment, data quality assurance, privacy concerns, and ethical implications. These challenges obstruct the full realization of Digital Twins’ potential benefits. The study concludes by outlining critical avenues for future research, emphasizing standardization, data quality, privacy preservation, trust-building, and cross-domain applications. Bridging these gaps is vital for harnessing the true potential of Digital Twins in revolutionizing industries. This review aims to present a comprehensive view of Digital Twins, highlighting their benefits, challenges, and the imperative for further research to unlock their transformative impact.

DOI: 10.61137/ijsret.vol.10.issue4.199

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Foreseeing Maximum and Minimum Temperatures by Integrating Several Machine Learning Programs While Assessing Their Performance

Foreseeing Maximum and Minimum Temperatures by Integrating Several Machine Learning Programs While Assessing Their Performance
Authors:-Pintu Pal, Deblina Banerjee, Subhodeep Moitra

Abstract-Global warming has led to a boost in both optimum and minima temperatures. So, in this situation, precise prediction of maximum and minimum temperatures plays a very pivotal role in studying various factors related to human comfort, agriculture, ecological and environmental developments, and other causes. We investigated the effectiveness and varied capabilities of data-driven algorithms to anticipate the maximum and lowest temperatures of the third day in accordance with the meteorological situations of the preceding two days in a row.

DOI: 10.61137/ijsret.vol.10.issue4.198

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