Department of Computer Engineering

Artificial Intelligence
of Things Research Lab

We develop innovative algorithms, protocols and methodologies based on Artificial Intelligence, focusing on IoT data analytics, fog computing, edge computing, and complex event processing.

259+
Publications
6,161
Citations
h = 38
h-index
24+
Projects

About the Lab

Research at the Artificial Intelligence of Things (AIoT) Lab aims to develop innovative algorithms, protocols and methodologies based on Artificial Intelligence, focusing on IoT data analytics, fog computing, edge computing, and complex event processing.

Our work facilitates data collection, data analysis, system design and presentation in the field of IoT. The lab collaborates with leading industry partners and research institutions including TUBITAK, ASELSAN, and Roketsan.

Led by Prof. Suat Özdemir at Hacettepe University's Department of Computer Engineering, our team brings together researchers from multiple Turkish universities to advance the frontiers of AI-driven networked systems.

Hacettepe University AIoT Lab

Research Areas

Internet of Things (IoT)

Scalable technologies, architectures, and analytics frameworks for collecting, processing, monitoring, and deriving meaningful insights from large-scale sensor and device ecosystems.

Artificial Intelligence (AI)

Intelligent algorithms and AI-driven models for prediction, optimization, automation, and data analytics across IoT, healthcare, transportation, environmental monitoring, and financial systems.

Fog & Edge Computing

Distributed computation architectures that bring AI processing closer to IoT data sources for reduced latency.

Security & Privacy

Secure data aggregation, privacy-preserving protocols, and threat detection for wireless sensor and IoT networks.

Smart Grids

Fog-computing-based smart grid architectures with AI-driven energy management and privacy-preserving metering.

NTN

Federated & Distributed Learning for Collaborative Intelligence in Non-Terrestrial Networks (NTN)

NGIoT

Digital Twin-Driven Task Offloading for Next-Generation IoT Networks.

Complex Event Processing

Real-time rule extraction and anomaly detection engines for heterogeneous IoT environments.

259+
Publications
6,161
Total Citations
38
h-index
96
i10-index