04621nam 22006975 450 991062725920332120230810231552.0981-19-5244-210.1007/978-981-19-5244-9(MiAaPQ)EBC7088308(Au-PeEL)EBL7088308(CKB)24846065700041(DE-He213)978-981-19-5244-9(PPN)26495825X(EXLCZ)992484606570004120220916d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierTowards Net-Zero Targets Usage of Data Science for Long-Term Sustainability Pathways /by Neha Sharma, Prithwis Kumar De1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (258 pages)Advances in Sustainability Science and Technology,2662-6837Print version: Sharma, Neha Towards Net-Zero Targets Singapore : Springer,c2022 9789811952432 Includes bibliographical references and index.Chapter 1. Climate Change and AI in the Financial, Energy, Domestic and Transport Sectors -- Chapter 2. Role of Banking Sector in Climate Change – Literature Review and Data Preparation -- Chapter 3. Application of Machine Learning to Predict Climate Change Consequences due to Investments by Banks in Fossil Fuel Sectors -- Chapter 4. Effect of Non-Renewable Energy Sources on Climate Change in India- Literature Review and Data Preparation -- Chapter 5. Using Machine Learning to Predict the Effect of Non-Renewable Energy Sources on Climate Change in India -- Chapter 6. Impact of Household Emissions on Climate Change in India – Literature Review and Data Preparation -- Chapter 7. Use of Unsupervised Learning Algorithms to Segment Indian States based on Primary Energy Household Emissions -- Chapter 8. Application of Machine Learning in Climate Change for Transport Sector – Literature Review and Data Preparation -- Chapter 9. Application of Machine Learning to Predict CO2 Emission from Transport Sector to Mitigate Climate Change -- Chapter 10. Carbon Emission Calculator: Impact of AI on Climate Change.This book discusses the use of technology, data science and open data to achieve the net-zero carbon emissions target set up by the Paris Agreement on climate change. There have been many discussions around sustainability and climate change solutions to mitigate the negative impact. However, using technology levers to tackle climate challenges is rarely seen as the most significant catalyst. The available research in this field is generally qualitative in nature, where technology and data have not yet been leveraged. By using AI/ML, the book predicts the climate change consequences arising due to investment in fossil fuel sectors, estimates CO2 emissions from the transport sector, forecasts average land temperature due to non-renewable sources of energy, and segments Indian states on the basis of household carbon emissions. The researchers, policymakers, students, teachers, educational institutions, governments, regulators, companies, international organizations, etc., will benefit immensely by referring to this book. Moreover, the endeavour of this book is to provide a decarbonized environment and a better tomorrow to the next generation.Advances in Sustainability Science and Technology,2662-6837Computational intelligenceSustainabilityArtificial intelligenceArtificial intelligenceData processingMachine learningComputational IntelligenceSustainabilityArtificial IntelligenceData ScienceMachine LearningComputational intelligence.Sustainability.Artificial intelligence.Artificial intelligenceData processing.Machine learning.Computational Intelligence.Sustainability.Artificial Intelligence.Data Science.Machine Learning.363.73874561Sharma Neha(Of Tufts University. School of Medicine),1277233De Prithwis KumarMiAaPQMiAaPQMiAaPQBOOK9910627259203321Towards Net-Zero targets3010176UNINA