Paiva / Lopes / Yonezawa | Science and Technologies for Smart Cities | Buch | 978-3-030-76062-5 | sack.de

Buch, Englisch, Band 372, 652 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1007 g

Reihe: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Paiva / Lopes / Yonezawa

Science and Technologies for Smart Cities

6th EAI International Conference, SmartCity360°, Virtual Event, December 2-4, 2020, Proceedings
1. Auflage 2021
ISBN: 978-3-030-76062-5
Verlag: Springer International Publishing

6th EAI International Conference, SmartCity360°, Virtual Event, December 2-4, 2020, Proceedings

Buch, Englisch, Band 372, 652 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1007 g

Reihe: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

ISBN: 978-3-030-76062-5
Verlag: Springer International Publishing


This book constitutes the refereed proceedings of the 6 Annual Smart City 360° Summit. Due to COVID-19 pandemic the conference was held virtually.

The volume combines selected papers of seven conferences, namely AISCOVID 2020 - International Conference on AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart-Cities; EdgeIoT 2020 - International Conference on Intelligent Edge Processing in the IoT Era; IC4S 2020 - International Conference on Cognitive Computing and Cyber Physical Systems; CiCom 2020 - International Conference on Computational Intelligence and Communications; S-Cube 2020 - International Conference on Sensor Systems and Software; SmartGov 2020 - International Conference on Smart Governance for Sustainable Smart Cities; and finnally, the Urb-IOT 2020 -International Conference on IoT in Urban Space.

Paiva / Lopes / Yonezawa Science and Technologies for Smart Cities jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart-Cities.- IoT and AI for COVID-19 in Scalable Smart Cities.- Automated Segmentation of COVID-19 Lesion from Lung CT Images using U-Net Architecture.- COVID-19 Patient Care: A Content-Based Collaborative Filtering Using Intelligent Recommendation Systems.- A new Blood Pressure prediction approach using PPG sensors: subject specific evaluation over a long-term period.- 5G network Slicing Technology and its Impact on COVID-19: A Comprehensive Survey.- An Empirical Study of Trilateration and Clustering for Indoor Localization and Trend Prediction.- Covid-19 Detection on CT Scans using Local Binary Pattern and Deep Learning.- Security and privacy issues associated with Coronavirus diagnosis and prognosis Approach for the development of a system for COVID-19 preliminary test.- Application of Distributed Generation for Reduction of Power Losses and Voltage Deviation in Electric Distribution System by Using AI Techniques.-Non-Linear Control Applied to a 3d Printed Hand To Beacon or Not?: Speed Based Probabilistic Adaptive Beaconing Approach for Vehicular Ad-Hoc Networks.- Reduce 802.11 Connection Time Using Offloading and Merging of DHCP layer to MAC layer.- Hybrid Machine Learning Model for Traffic Forecasting.- Labeling News Article’s Subject Using Uncertainty Based Active Learning.- Intelligent Edge Processing in the IoT Era Environment Monitoring Modules with Fire Detection Capability based on IoT Methodology.- NetButler: Voice-Based Edge/Cloud Virtual Assistant for Home Network Management.- Low-cost LoRa-based IoT Edge Device for Indoor Air Quality Management in Schools.- Technologies for Industrial Internet of Things (IIoT): Guidelines for Edge Computing Adoption in the Industry.- Scalable Approximate Computing Techniques for Latency and Bandwidth Constrained IoT Edge.- Collaborative task processing with Internet of Things (IoT) Clusters.- An Energy Sustainable CPS/IoT Ecosystem.- Inference Performance Comparison of Convolutional Neural Networks on Edge Devices.- Cognitive Computing and Cyber Physical Systems A non-intrusive IoT-based real-time alert system for elderly people monitoring.- A Smartphone Application Designed to Detect Obstacles for Pedestrians’ Safety.- Automatic Generation of Security Requirements for Privacy-Preserving Blockchain-Based Solutions in the Internet of Things.- Assessment of Video Games Players and Teams Behaviour via Sensing and Heterogeneous Data Analysis: Deployment at an eSports Tournament.- A feature-fusion transfer learning method as a basis to support automated smartphone recycling in a circular smart city.- Are Neural Networks Really the Holy Grail? A Comparison of Multivariate Calibration for Low-cost Environmental Sensors.- MOBIUS: Smart Mobility Tracking with Smartphone Sensors.- An Attack-resistant Weighted Least Squares Localization Algorithm Based on RSSI.- Promotion as a Tool of Smart Governance in Cities.- Identity Inclusion: A Digital National Identification for All Computer Vision Assisted Approaches to Detect Street Garbage from Citizen Generated Imagery.- Smart Governance in Urban Mobility Process.- 37 A Framework for GIS-enabled Public Electronic Participation in Municipal Solid Waste Management.- A Crowd-sourced Obstacle Detection and Navigation App for Visually Impaired An ecosystem approach to the design of sensing systems for bicycles Calibration of Low-cost Particulate Matter Sensors with Elastic Weight Consolidation (EWC) as an Incremental Deep Learning Method.- Person-Flow Estimation with Preserving Privacy using Multiple 3D People Counters.- Quality and Reliability Metrics for IoT Systems: A Consolidated View.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.