Mobile and Ubiquitous Systems: Computing, Networking and Services: 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14-17, 2023, Proceedings, Part I

by Arkady Zaslavsky (Editor), Zhaolong Ning (Editor), Vana Kalogeraki (Editor), Dimitrios Georgakopoulos (Editor), Panos K. Chrysanthis (Editor)

Overview

These two-volume proceedings constitute the refereed post-conference proceedings of the 20th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2023, held in Melbourne, Australia, during November 14-17, 2023.

 

The 65 papers presented in these proceedings were carefully reviewed and selected from 161 submissions. The conference papers are organized in topical sections on:

 

Part I - Tracking and Detection; IoT; Federated learning; Networks; Activity recognition; Security Management; Urban/Mobile Crowdsensing.

Part II - Urban/Mobile Crowdsensing; Edge computing; Crowdsourcing, Platforms and localization; Activity recognition and prediction; AI and machine learning; Mobile edge and fog computing; Mobile augmented reality and applications for mobile computing; interaction technologies; AutoQuitous workshop.

Product Details

ISBN-13:	9783031639890
Publisher:	Springer-Verlag New York, LLC
Publication date:	07/18/2024
Series:	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , #593
Sold by:	Barnes & Noble
Format:	eBook
File size:	75 MB
Note:	This product may take a few minutes to download.

Table of Contents

.- Tracking and Detection.

.- NoD: Lightweight Continuous Neighbor Discovery on Everyday Devices.

.- Decentralized Collaborative Inertial Tracking.

.- High-Performance Features in Generalizable Fingerprint- based Indoor Positioning.

.- SCORE: Scalable Contact Tracing Over Uncertain Trajectories.

.- IoT.

.- FaultBit : Generic and Efficient Wireless Fault Detection Using the Internet of Things.

.- DeepHeteroIoT: Deep Local and Global Learning over Heterogeneous IoT Sensor Data.

.-  Federated Reinforcement Learning for Automated LoRaWAN Management in Industrial IoT.

.- A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications.

.- LOADHoC: Towards the Automatic local Distribution of Computation using Existing IoT Devices.

.- E-Go Bicycle Intelligent Speed Adaptation System for Catching the Green Light.

.- Federated Learning.

.-  FedGCS: Addressing Class Imbalance in Long-Tail Federated Learning.

.- FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning.

.- RADEAN: A Resource Allocation Model Based on Deep Reinforcement Learning and Generative Adversarial Networks in Edge Computing.

.- Networks.

.-  A Stream Data Service Framework for Real-time Vehicle Companion Discovery.

.- KS-Autoformer: An Autoformer-based SOC Prediction Framework for Electric Vehicles.

.-  Deep Reinforcement Learning-based Multi-Node Collaborative Task Offloading Optimization in 6G
Space-Air-Ground Integrated Networks.

.-  Securing Wireless Communication in Critical Infrastructure: Challenges and Opportunities.

.- Activity Recognition.

.- Cross-user activity recognition via temporal relation optimal transport.

.- SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning.

.- A Novel Method for Wearable Activity Recognition with Feature Evolvable Streams.

.-  Let’s Vibrate with Vibration: Augmenting Structural Engineering with Low-Cost Vibration Sensing.

.- Security Management.

.- Research on Data Drift and Class Imbalance in Android Malware detection.

.- Reputation-based Dissemination of Trustworthy Information in VANETs.

.- Reputation Systems for Supply Chains: The Challenge of Achieving Privacy Preservation.

.- Data Management in Appendable-block Blockchains: A Case Study for IT Life-cycle Management.

.- Exploiting the Potential Anomaly Detection in Automobile Safety Data with Multi-type Neural Network.

.- Urban/Mobile Crowdsensing.

.- HAUM3: A Height Aware Urban Map Matching Mechanism.

.- A resource-efficient approach of GNSS activation for pedestrian monitoring.