Artificial Intelligence of Things and Systems
Description
This volume constitutes the proceedings of Third International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2025, held in Lanzhou, China, during August 15-17, 2025.
The 37 full papers included in this book were carefully reviewed and selected from 88 submissions. These papers discuss the integration of AI into IoT (AIoT) and its impact across a wide range of economic and social domains, driving the transformation of traditional industries into a new era of intelligence that goes beyond mere digitization and connectivity.
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Content
.- IMU-Accelerated Image Stitching: Fast and Artifact-Free Panorama Construction.
.- Intrusion Detection for Unmanned Aerial Vehicle Systems with Deep Reinforcement Learning.
.- Seeing from Within: Ego-Centric 3D Orientation Prediction for Autonomous Driving.
.- Tag in Bloom: Fast RFID Membership via Software-Defined Readers.
.- FedDEK: Federated Domain-Incremental Learning via Expert Knowledge Construction.
.- An Accurate Indoor Depth Estimation Method Based on Iterative Pose Refinement.
.- A Dynamic Stress Assessment Framework via Multi-Scale Feature Fusion.
.- Regularized Offline Reinforcement Learning for Energy Efficient Urban Rail Transit System Control.
.- P2MFDS: A Privacy-Preserving Multimodal Fall Detection System for Elderly People in Bathroom Environments.
.- Enhancing Indoor Trajectory Tracking with XGBoost-Based Classification on mmWave Radar Point Clouds.
.- Towards Large-scale Wireless Sensing in Smart Buildings Using LoRa Signals.
.- Wi-CLIP:Toward Zero-Shot Air Gesture Recognition Based on RF-Text Foundation Model.
.- Object Size Classification in Garbage Disposal Sensing System Using Monocular Depth Estimation.
.- Memory-Aware Structured Pruning for DL with Joint Optimization of L1-norm and Peak Memory.
.- SAULC: Semantic-Driven Adaptive Method for UAV-LEO Satellite Communication.
.- A Low Migration and Low Energy Consumption Fog Computing Workflow Scheduling Framework for Multiple Constraints.
.- A Method for Recognition and Analysis of Industrial Sewing Machine Operating States Based on Edge Computing.
.- Trustworthy Distributed Decision-making for Multi-view Sensing Data.
.- From Sparse Labels to Accurate Models: Active Semi-Supervised Learning for mmWave Radar Target Classification.
.- Runtime Heterogeneous Sensor Selection with Data Reuse in Multi-Device Environments.
.- Can Time-Series Foundation Models Enhance Wireless Sensing Data Analytics? An Empirical Study.
.- DGA-Based Power Transformer Fault Diagnosis via Knowledge Distillation of Large Language Model.
.- GraphSAGE-Enhanced Reinforcement Learning for Optimizing Load-Aware Microservice Deployment.
.- STCL-Dynamic Sparsity-driven Transition Feature Replay Continual Learning for Edge Devices.
.- Towards On-device NPU-Friendly Neural Network Operator Optimization.
.- AIGC in Mobile Edge Networks: A Survey.
.- Large Language Models-Driven Personalized Adaptation Framework for Intelligent Agents.
.- Learning-based Taxi Selection for Opportunistic Street Parking Sensing.
.- Eye-PPG: Remote PPG Signal Generation for Heart-rate Estimation and User Identification in Virtual Reality.
.- Temporal Decision-Making Optimization for Intelligent Agents withGradually Clarified Objectives.
.- A LoRa Positioning Algorithm Based on the Integration of Kalman Filtering and Neural Networks and Its Implementation.
.- MSGR-DCM:Multi-Scale Graph Relational Learning and DC-Mamba for Multivariate Time Series Anomaly Detection in Industrial Control Systems.
.- A Review on Temporal Knowledge Graph Completion in The Context of Internet of Things and Industrial Security.
.- Federated Learning for AIoT Security: Current Advances and Future Challenges.
.- Lightweight Chaos-Based Image Encryption Algorithm for the Internet of Things.
.- Image Watermarking Encryption Algorithm for IoT Utilizing Chaotic Neural Network.
.- BluePLP: Dynamic Vulnerability Patching for Heterogeneous BLE Devices.
