06408nam a22005415i 4500 978-3-031-63989-0 DE-He213 20251030112637.0 cr nn 008mamaa 240719s2024 sz | s |||| 0|eng d 9783031639890 978-3-031-63989-0 10.1007/978-3-031-63989-0 doi TK5105.5-5105.9 UKN bicssc COM043000 bisacsh UKN thema Mobile and Ubiquitous Systems: Computing, Networking and Services [electronic resource] : 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14–17, 2023, Proceedings, Part I / edited by Arkady Zaslavsky, Zhaolong Ning, Vana Kalogeraki, Dimitrios Georgakopoulos, Panos K. Chrysanthis. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XX, 550 p. 209 illus., 178 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 1867-822X ; 593 -- 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. 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. Computer networks . 60157 Computer Communication Networks. 65689 Zaslavsky, Arkady. editor. (orcid)0000-0003-1990-5734 https://orcid.org/0000-0003-1990-5734 edt http://id.loc.gov/vocabulary/relators/edt 80881 Ning, Zhaolong. editor. (orcid)0000-0002-7870-5524 https://orcid.org/0000-0002-7870-5524 edt http://id.loc.gov/vocabulary/relators/edt 80882 Kalogeraki, Vana. editor. (orcid)0000-0002-6421-9947 https://orcid.org/0000-0002-6421-9947 edt http://id.loc.gov/vocabulary/relators/edt 80883 Georgakopoulos, Dimitrios. editor. (orcid)0000-0001-7880-2140 https://orcid.org/0000-0001-7880-2140 edt http://id.loc.gov/vocabulary/relators/edt 80884 Chrysanthis, Panos K. editor. (orcid)0000-0001-7189-9816 https://orcid.org/0000-0001-7189-9816 edt http://id.loc.gov/vocabulary/relators/edt 80885 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031639883 Printed edition: 9783031639906 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 1867-822X ; 593 68121 https://doi.org/10.1007/978-3-031-63989-0 ZDB-2-SCS ZDB-2-SXCS ZDB-2-LNS 61737 61737