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Advances in Industrial Internet of Things, Engineering and Management

Medium: Buch
ISBN: 978-3-030-69707-5
Verlag: Springer International Publishing
Erscheinungstermin: 29.05.2022
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This book presents the trends, challenges, and advances in Internet of Things (IoT) in the areas of industrial management and industrial engineering. The authors look at how smart environments (smart city, smart university, smart regions, smart transportation, etc.) affect the way industrial management and industrial engineering are envisioned, planned, and applied and how engineers must incorporate new ideas and methods now and in the future. Some topics include the impact of ICT on the emergency response vehicle driving time, car accident detecting systems based on machine learning algorithms, smart city platforms based on citizen reporting services, and IoT-based household energy consumption prediction using machine learning. The book brings together contributions from academics and practitioners from around the world to discuss the intersection of IoT, industry and management.


Produkteigenschaften


  • Artikelnummer: 9783030697075
  • Medium: Buch
  • ISBN: 978-3-030-69707-5
  • Verlag: Springer International Publishing
  • Erscheinungstermin: 29.05.2022
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2021
  • Serie: EAI/Springer Innovations in Communication and Computing
  • Produktform: Kartoniert
  • Gewicht: 324 g
  • Seiten: 198
  • Format (B x H x T): 155 x 235 x 12 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Introduction.- Basic Stations Work Optimization in Cellular Communication Network.- The analysis of different materials used for an electric car charger shell under the wind influence.- Impact of ICT on Emergency Response Vehicle Driving Time in a Vicinity of Large Events.- Developing Car Accident Detecting System Based on Machine Learning Algorithms Applied to Video Recordings Data.- Smart City platform based on citizen reporting services.- Stages of  the Virtual Technical Functions Concept Networks Development.- IoT-based Household Energy Consumption Prediction Using Machine Learning.- Management Decision-Making for Logistics Systems Based on a Fuzzy-Neural Model.- Conclusion.