dc.date.accessioned | 2022-08-09T12:05:18Z | |
dc.date.available | 2022-08-09T12:05:18Z | |
dc.date.issued | 2022 | |
dc.identifier | doi:10.17170/kobra-202205166179 | |
dc.identifier.uri | http://hdl.handle.net/123456789/14040 | |
dc.language.iso | eng | eng |
dc.publisher | kassel university press | |
dc.rights | Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.subject | big data analytics | eng |
dc.subject | robotic process automation | eng |
dc.subject | RPA | eng |
dc.subject | data science | eng |
dc.subject | cloud-computing | eng |
dc.subject | Internet of Things (IoT) | eng |
dc.subject | artificial intelligence | eng |
dc.subject | disruptive innovation | eng |
dc.subject | unmanned aircraft systems | eng |
dc.subject | extended reality | eng |
dc.subject | energy industry | eng |
dc.subject | regenerative energy systems | eng |
dc.subject | European energy exchanges | eng |
dc.subject | digitalization | eng |
dc.subject | digital transformation | eng |
dc.subject | digital business models | eng |
dc.subject | data protection | eng |
dc.subject | smart city | eng |
dc.subject.ddc | 004 | |
dc.subject.ddc | 330 | |
dc.subject.ddc | 650 | |
dc.title | Innovations and artificial intelligence along the energy industry value chain | eng |
dc.type | Buch | |
dcterms.abstract | The immense transformation of the energy industry away from centralized to decentralized energy supply, in particular using renewable energies and comprehensive digitization, will radically change the value chain of the energy industry. Smart meters and smart grids, for example, can accelerate existing business processes in the energy industry to an unprecedented degree. Topics such as big data analytics, robotic process automation (RPA), data science, cloud computing, Internet of Things (IoT) and artificial intelligence (AI), among others, will find their way into the day-to-day business of energy utilities and bring about groundbreaking changes at a high pace of digitalization. This publication aims to provide a first insight into the upcoming paradigm shift in the energy industry and aims to highlight the upcoming change in the energy industry value chain, which will be characterized by disruptive innovations and artificial intelligence (AI) on the one hand, and by the imperative of respecting data privacy and ensuring data security on the other hand. The book is divided into two main sections: Part I highlights the fundamentals of the classic primarily analog energy industry (chapters 2–8), while Part II addresses the paradigm shift that will be characterized by innovations, technologies and digital business models in the energy industry (chapters 9–12). | eng |
dcterms.accessRights | open access | |
dcterms.creator | Krebs, Heinz-Adalbert | |
dcterms.creator | Hagenweiler, Patricia | |
dcterms.extent | XXXIV, 776 Seiten | |
dc.publisher.place | Kassel | |
dc.relation.isbn | 978-3-7376-1050-6 | |
dc.subject.swd | Innovation | ger |
dc.subject.swd | Technische Innovation | ger |
dc.subject.swd | Künstliche Intelligenz | ger |
dc.subject.swd | Robotic Process Automation | ger |
dc.subject.swd | Cloud Computing | ger |
dc.subject.swd | Energiewirtschaft | ger |
dc.subject.swd | Energiewende | ger |
dc.subject.swd | Wertschöpfungskette | ger |
dc.subject.swd | Datenschutz | ger |
dc.subject.swd | Datensicherung | ger |
dc.title.subtitle | taking into account data security and data protection | eng |
dc.type.version | publishedVersion | |
kup.iskup | true | |
kup.order | https://www.genialokal.de/Produkt/Heinz-Adalbert-Krebs-Patricia-Hagenweiler/Innovations-and-artificial-intelligence-along-the-energy-industry-value-chain-taking-into-account-data-security-and-data-protection_lid_47281970.html | |
kup.price | 169,00 | |
kup.subject | Wirtschaftswissenschaft | |
kup.typ | Monographie | |
kup.institution | FB 07 / Wirtschaftswissenschaften | |
kup.binding | Hardcover | |
kup.size | 17 x 24 cm | |
ubks.epflicht | true | |
ubks.relation.translation | doi:10.17170/kobra-202012152522 | |