Building Environments Where AI Never Stops in Reality.
We research technologies where systems understand service intent, autonomously configure resources, and maintain AI service quality.
Core Research Framework
We research intelligent systems where distributed AIoT devices automatically compose, deploy, and reconfigure their service functions to match user intent and maintain optimal state.
Intelligent Networking & Systems
Our intelligent networking & systems research designs the system and network environments that keep AI services running without interruption. We study self-healing architectures that understand user intent and autonomously optimize themselves, spanning intent-based networking, Edge AI deployment, and distributed AIoT environments.
Representative Papers
- 1
Intent-Based Autonomous Networking for Multi-Domain Mobile IoT
IEEE TNSM (2025)
- 2
Deep Reinforcement Learning for Dynamic Resource Allocation in 6G Networks
IEEE ICC 2024 (2024)
- 3
LPWAN Framework for Industrial IoT Applications
IEEE Access (2023)
Data Intelligence
Our data intelligence research builds data-driven learning frameworks that allow systems to recognize their own state and anticipate problems. Through network data analysis, pattern recognition, and anomaly detection, we cultivate the intelligence needed to respond proactively to changing environments.
Representative Papers
- 1
Federated Learning Optimization for Edge Networks
IEEE ICC 2024 (Best Paper) (2024)
- 2
Communication-Efficient Federated Learning with Adaptive Aggregation
IEEE TNSM (2024)
- 3
Privacy-Preserving Deep Learning for IoT Data Analytics
IEEE Access (2023)
Intelligent Services
Our intelligent services research develops user-centric AI services that stay reliable even as their environment shifts. Built on Edge AI running on embedded boards, we bring IoT applications, smart city solutions, mobile services, and computer vision systems into real-world deployment.
Representative Papers
- 1
GNN-Based Anomaly Detection for Industrial IoT Networks
IEEE Access (2025)
- 2
AI-Based Monitoring System for Wildlife Conservation
Sensors (2022)
- 3
Deep Learning Noise Analysis for Smart Factory Predictive Maintenance
KICS (2024)
Ongoing Projects
AIκΈ°λ° μ€λ§νΈμν° ν΄λ¦° μμ€ν κ°λ° / Development of AI-based clean systems of a smart city
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Structural Connectivity
At INSLAB, no research area exists in isolation. The DATA, SYSTEM, and SERVICE pillars interact organically, with AI technology as the core driving force behind our intelligent solutions.