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Sharma, Pawankumar
- The Digital Carbon Footprint: Threat to an Environmentally Sustainable Future
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1 Dept. of Computer and Information Systems, University of the Cumberlands, KY, US
1 Dept. of Computer and Information Systems, University of the Cumberlands, KY, US
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AIRCC's International Journal of Computer Science and Information Technology, Vol 14, No 3 (2022), Pagination: 19-29Abstract
With digitalization at its peak, every online action we take has an environmental impact. There is a growing concern about the world's ever-increasing carbon emission due to technological advancement. The vast majority of human actions have been proved harmful to the environment. This effect has been mostly tied to available carbon emissions. On the other hand, recent findings have raised awareness of digital carbon emissions. These harmful emissions represent the available CO2 emissions rate resulting from generic digitization concepts. The advancement of technology has considerably contributed to CO2 emissions. This study paper discusses the total effects of carbon emissions. It also shows the rates of carbon emissions caused by the tech industry worldwide. The article describes how digital services have boosted carbon emissions and the number of regions affected by the higher rates. The study focuses on the relationship between carbon emissions and digitization, remedies to the problem, and an overall analysis of the global digital carbon footprint.Keywords
Digitalization, Digital carbon footprint, CO2 emission, Global warming, NARDL Approach, FD & CO2 emission nexus, Sustainability.References
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- Active Noise Cancellation in Microsoft Teams Using AI & NLP Powered Algorithms
Abstract Views :138 |
PDF Views:72
Authors
Affiliations
1 School of Computer and Information Science, University of the Cumberlands, KY, US
2 Department of Computer and Information Science, University of the Cumberlands, KY, US
1 School of Computer and Information Science, University of the Cumberlands, KY, US
2 Department of Computer and Information Science, University of the Cumberlands, KY, US
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 15, No 1 (2023), Pagination: 31-42Abstract
The normal method for analyzing technology is formulating many search queries to extract patent datasets and filter the data physically. The purpose of filtering the collected data is to remove noise to guarantee accurate information analysis. With the advancement in technology and machine learning, the work of physical analysis of the patent can be programmed so the system can remove noise depending on the results based on the previous data. Microsoft team generates a new artificial intelligence model that provides solutions on how individuals respond to speakers. Microsoft team, workplace, Facebook, and Google collected data from many active users hence developing artificial intelligence to minimize distracting background noise, barking and typing during the call.Keywords
Artificial Intelligence, NLP, Microsoft Teams, Speech Identification, Video Call, Video Signal Data, Machine Learning.Full Text
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