20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14–17, 2023, Proceedings, Part I Zaslavsky, Arkady. editor. edt http://id.loc.gov/vocabulary/relators/edt Ning, Zhaolong. editor. edt http://id.loc.gov/vocabulary/relators/edt Kalogeraki, Vana. editor. edt http://id.loc.gov/vocabulary/relators/edt Georgakopoulos, Dimitrios. editor. edt http://id.loc.gov/vocabulary/relators/edt Chrysanthis, Panos K. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

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access XX, 550 p. 209 illus., 178 illus. in color. online resource. 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. -- 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. edited by Arkady Zaslavsky, Zhaolong Ning, Vana Kalogeraki, Dimitrios Georgakopoulos, Panos K. Chrysanthis. Computer networks  Computer Communication Networks TK5105.5-5105.9 9783031639890 https://doi.org/10.1007/978-3-031-63989-0 https://doi.org/10.1007/978-3-031-63989-0 240719 20251030112637.0 978-3-031-63989-0