Mobile and Ubiquitous Systems: Computing, Networking and Services

This book constitutes the proceedings of the 21st International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2024, held in Oslo, Norway, during November 1214, 2024.

The 32 full papers presented in this book were carefully reviewed and selected from 73 submissions. They were organized into the following topical sections: Health, Biomedical Applications, and Human-Centric Computing; IoT, Cybersecurity, and Wireless Communication; Machine Learning, AI, and Smart Systems; Robotics and Autonomous Systems; and Simulation, Optimization, and Specialized Techniques.

Inhalt

.- Health, Biomedical Applications, and Human-Centric Computing.

.- A Preliminary Study on Core Temperature Estimation Using a Neonatal Thermal Model via Backpropagation Algorithm.

.- A Two-Step Deep Neural Network Approach for Real-Time Context-Aware Health Monitoring of Hajj Pilgrims.

.- Environment Independent Fall Detection with WiFi Streams.

.- Real-time mobile health analytics & interventions pipeline to detect acute events in COPD.

.- Wearable-based Fair and Accurate Pain Assessment Using Multi-Attribute Fairness Loss in Convolutional Neural Networks.

.- EEGAmp+: Investigating the Efficacy of Functional Connectivity for Detecting Events in Low Resolution EEG.

.- IoT, Cybersecurity, and Wireless Communication.

.- Resilience Against APTs: A Provenance-based IIoT Dataset for Cybersecurity Research.

.- Verifying Multi-Vendor IoT Deployments using Conditional Tables.

.- Supporting an Ephemeral Shared Dataspace with a BLE connectionless protocol.

.- Adaptive Deployment of Application-level Sensing and Data Processing Pipelines in a Wireless Network of Embedded Devices.

.- Exploiting NLOS Links for Energy-Efficient Opportunistic Routing in IoV.

.- Spatio-Temporal Analysis of Concurrent Networks.

.- VF-RL: A Reinforcement Learning-Based Coverage Improvement in Mobile IoT Networks using Virtual Force.

.- Machine Learning, AI, and Smart Systems.

.- A Service-based Real-time Anomaly Detection Method for Sensor Stream Data.

.- AI Robust Anomaly Localization for DC Microgrid Using Adversarial Autoencoder.

.- DERGB: An Android malware adversarial attack technique based on RGB images.

.- Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity Recognition.

.- Genetic Algorithm Optimization for Mobile Crowd-sensing of On-street Parking.

.- GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes.

.- Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs.

.- Scene Graph driven Context Query Generation: A Focus on Diversity and Situation-Specific Queries.

.- Robotics and Autonomous Systems.

.- A Framework for Devising, Evaluating and Fine-tuning Indoor Tracking Algorithms.

.- CSI Phase Fingerprinting for Indoor Positioning Services using Deep Reinforcement Learning.

.- Automatic Marker Placement Method for Marker-based Virtual Reality.

.- Establishing a Data-Efficient Witness Protocol for Connected Autonomous Vehicles.

.- Real-Time Obstacle Detection and Safe Operation for Industrial Autonomous Mobile Robots.

.- Simulating and Evaluating Search Strategies for Highly Accurate Localization based on Wireless Technologies using Autonomous Unmanned Aerial Vehicles.

.- Simulation, Optimization, and Specialized Techniques.

.- Event-driven Performance Evaluation of Statecharts and MicroPython on ESP32-C3 Platforms.

.- Simulating Urban Pedestrian Flows by Fusing Wide-Area Location Data and Spot Pedestrian Counts.

.- MDMV: A Malware Detection Method based on Memory and Visualization on KVM.

.- Collection Scheduling with Memory Constraints for Low Earth Orbit Satellite Constellations.

.- Smartphone Contact-Object Estimation by Acoustic Sensing Focusing on Abstraction Level.