Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Optimizing LoRa for Edge Computing with TinyML Pipeline for Channel Hopping
We propose to integrate long-distance LongRange (LoRa) communication solution for sending the data from IoT to the edge computing system, by taking advantage of its unlicensed nature and the potential for open source imp…
Collaborative FilteringEdge-computingSmart Parking with Pixel-Wise ROI Selection for Vehicle Detection Using YOLOv8, YOLOv9, YOLOv10, and YOLOv11
The increasing urbanization and the growing number of vehicles in cities have underscored the need for efficient parking management systems. Traditional smart parking solutions often rely on sensors or cameras for occupa…
Cloud ComputingEdge-computingobject-detectionObject Detection+1EdgeOAR: Real-time Online Action Recognition On Edge Devices
This paper addresses the challenges of Online Action Recognition (OAR), a framework that involves instantaneous analysis and classification of behaviors in video streams. OAR must operate under stringent latency constrai…
Action RecognitionEdge-computingEmbedded Machine Learning for Solar PV Power Regulation in a Remote Microgrid
This paper presents a machine-learning study for solar inverter power regulation in a remote microgrid. Machine learning models for active and reactive power control are respectively trained using an ensemble learning me…
Edge-computingEnsemble LearningEdge Computing for Microgrid via MATLAB Embedded Coder and Low-Cost Smart Meters
In this paper, an edge computing-based machine-learning study is conducted for solar inverter power forecasting and droop control in a remote microgrid. The machine learning models and control algorithms are directly dep…
Edge-computingCharacterizing and Modeling AI-Driven Animal Ecology Studies at the Edge
Platforms that run artificial intelligence (AI) pipelines on edge computing resources are transforming the fields of animal ecology and biodiversity, enabling novel wildlife studies in animals' natural habitats. With eme…
Edge-computingThe Streetscape Application Services Stack (SASS): Towards a Distributed Sensing Architecture for Urban Applications
As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to improve safety, mobility, and quality of l…
Edge-computingMonocular Obstacle Avoidance Based on Inverse PPO for Fixed-wing UAVs
Fixed-wing Unmanned Aerial Vehicles (UAVs) are one of the most commonly used platforms for the burgeoning Low-altitude Economy (LAE) and Urban Air Mobility (UAM), due to their long endurance and high-speed capabilities. …
Collision AvoidanceDeep Reinforcement LearningEdge-computingSemantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
Semantic Edge Computing (SEC) and Semantic Communications (SemComs) have been proposed as viable approaches to achieve real-time edge-enabled intelligence in sixth-generation (6G) wireless networks. On one hand, SemCom l…
Edge-computingJoint Resource Optimization, Computation Offloading and Resource Slicing for Multi-Edge Traffic-Cognitive Networks
The evolving landscape of edge computing envisions platforms operating as dynamic intermediaries between application providers and edge servers (ESs), where task offloading is coupled with payments for computational serv…
Bayesian OptimizationEdge-computingPrivacy PreservingTowards Efficient Model-Heterogeneity Federated Learning for Large Models
As demand grows for complex tasks and high-performance applications in edge computing, the deployment of large models in federated learning has become increasingly urgent, given their superior representational power and …
Edge-computingFederated Learningparameter-efficient fine-tuningAdaptable Embeddings Network (AEN)
Modern day Language Models see extensive use in text classification, yet this comes at significant computational cost. Compute-effective classification models are needed for low-resource environments, most notably on edg…
ClassificationDensity EstimationEdge-computingtext-classification+1FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation
With the rapid development of large language models (LLM), robots are starting to enjoy the benefits of new interaction methods that large language models bring. Because edge computing fulfills the needs for rapid respon…
Edge-computingModel CompressionRobot NavigationQuantum Kernel-Based Long Short-term Memory
The integration of quantum computing into classical machine learning architectures has emerged as a promising approach to enhance model efficiency and computational capacity. In this work, we introduce the Quantum Kernel…
Edge-computingQuantum Machine LearningFederated Continual Learning for Edge-AI: A Comprehensive Survey
Edge-AI, the convergence of edge computing and artificial intelligence (AI), has become a promising paradigm that enables the deployment of advanced AI models at the network edge, close to users. In Edge-AI, federated co…
Continual LearningEdge-computingSurveyMAS-Attention: Memory-Aware Stream Processing for Attention Acceleration on Resource-Constrained Edge Devices
The advent of foundation models have revolutionized various fields, enabling unprecedented task accuracy and flexibility in computational linguistics, computer vision and other domains. Attention mechanism has become an …
Edge-computingSchedulingOptimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsiveness
The growing complexity of the operations of airline reservations requires a smart solution for the adoption of novel approaches to the development of quick, efficient, and adaptive reservation systems. This paper outline…
Distributed ComputingEdge-computingFrom Centralized RAN to Open RAN: A Survey on the Evolution of Distributed Antenna Systems
Next-generation mobile networks require evolved radio access network (RAN) architectures to meet the demands of high capacity, massive connectivity, reduced costs, and energy efficiency, and to realize communication with…
Edge-computingZonal Architecture Development with evolution of Artificial Intelligence
This paper explains how traditional centralized architectures are transitioning to distributed zonal approaches to address challenges in scalability, reliability, performance, and cost-effectiveness. The role of edge com…
Autonomous VehiclesDecision MakingEdge-computingManagement+1STOP: Spatiotemporal Orthogonal Propagation for Weight-Threshold-Leakage Synergistic Training of Deep Spiking Neural Networks
The prevailing of artificial intelligence-of-things calls for higher energy-efficient edge computing paradigms, such as neuromorphic agents leveraging brain-inspired spiking neural network (SNN) models based on spatiotem…
Edge-computing