Pei jiaming (10 risultati)
Lingua: Inglese
Editore: Springer, 2026
- Brossura
Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 60,57
Spedizione gratuitaSpedito in U.S.A.Quantità: 10 disponibili
Condizione: Brand New. New. Delivery takes 25-30 days. Excellent Customer Service.
Lingua: Inglese
Editore: Springer, 2026
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 60,59
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer, 2026
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 76,29
EUR 3,45 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer, Springer, 2026
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 58,39
EUR 60,98 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Federated Learning for Smart Mobility: Towards Secure, Efficient, and Sustainable Transportation explores how federated learning (FL) reshapes the future of intelligent transportation and the Internet of Things (IoT). As data privacy and communica…tion efficiency become pressing challenges, FL offers a distributed and privacy-preserving paradigm for model training across vehicles, sensors, and edge devices without sharing raw data.This SpringerBrief provides a concise yet comprehensive overview of FL s role in building next-generation smart mobility systems. It covers the fundamentals of FL and IoT infrastructures, introduces emerging applications in autonomous driving, traffic prediction, and vehicular networks, and presents selected case studies from academia and industry. The book also discusses key technical challenges including data heterogeneity, system scalability, and privacy protection and highlights future directions integrating FL with edge intelligence, 6G communication, and blockchain technologies.Written by active researchers in the fields of federated learning, wireless communication, and intelligent transportation, this book serves as a valuable reference for scientists, graduate students, and professionals in AI, IoT, and smart city development. It bridges theoretical advances with practical insights, guiding readers toward secure, efficient, and sustainable mobility solutions.
Lingua: Inglese
Editore: Springer, 2026
- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 50,40
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Federated Learning for Smart Mobility | Towards Secure, Efficient, and Sustainable Transportation System | Jiaming Pei (u. a.) | Taschenbuch | xiv | Englisch | 2026 | Springer | EAN 9789819561599 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, Berlin, Springer, 2026
- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,49
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Federated Learning for Smart Mobility: Towards Secure, Efficient, and Sustainable Transportation explores how federated learning (FL) reshapes the future of intelligent transportation and the Internet of Things (IoT). As data priva…cy and communication efficiency become pressing challenges, FL offers a distributed and privacy-preserving paradigm for model training across vehicles, sensors, and edge devices without sharing raw data.This SpringerBrief provides a concise yet comprehensive overview of FL s role in building next-generation smart mobility systems. It covers the fundamentals of FL and IoT infrastructures, introduces emerging applications in autonomous driving, traffic prediction, and vehicular networks, and presents selected case studies from academia and industry. The book also discusses key technical challenges including data heterogeneity, system scalability, and privacy protection and highlights future directions integrating FL with edge intelligence, 6G communication, and blockchain technologies.Written by active researchers in the fields of federated learning, wireless communication, and intelligent transportation, this book serves as a valuable reference for scientists, graduate students, and professionals in AI, IoT, and smart city development. It bridges theoretical advances with practical insights, guiding readers toward secure, efficient, and sustainable mobility solutions. 104 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2026
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 76,21
EUR 7,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2026
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 78,36
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2026
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 66,70
EUR 43,18 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Federated Learning for Smart Mobility: Towards Secure, Efficient, and Sustainable Transportation explores how federated learning (FL) reshapes the future of intelligent transportation and the Internet of Things (IoT). As data privacy and communication efficiency become pressing challenges,…FL offers a distributed and privacy-preserving paradigm for model training across vehicles, sensors, and edge devices without sharing raw data.This SpringerBrief provides a concise yet comprehensive overview of FLs role in building next-generation smart mobility systems. It covers the fundamentals of FL and IoT infrastructures, introduces emerging applications in autonomous driving, traffic prediction, and vehicular networks, and presents selected case studies from academia and industry. The book also discusses key technical challengesincluding data heterogeneity, system scalability, and privacy protectionand highlights future directions integrating FL with edge intelligence, 6G communication, and blockchain technologies.Written by active researchers in the fields of federated learning, wireless communication, and intelligent transportation, this book serves as a valuable reference for scientists, graduate students, and professionals in AI, IoT, and smart city development. It bridges theoretical advances with practical insights, guiding readers toward secure, efficient, and sustainable mobility solutions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Lingua: Inglese
Editore: Springer, Springer Jan 2026, 2026
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,49
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Federated Learning for Smart Mobility: Towards Secure, Efficient, and Sustainable Transportation explores how federated learning (FL) reshapes the future of intelligent transportation and the Internet of Things (IoT). As data privacy a…nd communication efficiency become pressing challenges, FL offers a distributed and privacy-preserving paradigm for model training across vehicles, sensors, and edge devices without sharing raw data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 120 pp. Englisch.
