The research area focuses on IoT systems and Wireless Internet technologies, with particular emphasis on Wi-Fi as a pervasive infrastructure for data collection, sensing, and protocol optimization.
With respect to IoT systems, the research spans all layers of the IoT protocol stack. At the application layer, activities concentrate on lightweight messaging protocols such as MQTT, MQTT-SN, and CoAP, addressing large-scale traffic analysis, protocol optimization, interoperability mechanisms, and distributed deployments. This includes the study of publish/subscribe architectures, advanced MQTT features, broker federation strategies, and systematic performance evaluation under realistic and large-scale workloads.
At the data link and connectivity layers, the research investigates short-range and long-range IoT technologies including Zigbee, Matter/Thread, BLE, LoRa/LoRaWAN, and NB-IoT. Activities include comparative performance evaluation, analytical modeling, scalability analysis, and optimization of communication strategies under dense and heterogeneous deployment scenarios.
In the Wi-Fi domain, the primary focus is the application of AI and machine learning techniques to extract high-level information from wireless traffic and physical-layer measurements. This includes localization, presence detection, and people counting through passive Wi-Fi monitoring, as well as learning-based mechanisms to enhance protocol performance, for example through reinforcement learning approaches for adaptive configuration and resource management.
A unifying theme across all activities is network data analysis at scale. The research addresses the design of optimized traffic analysis pipelines, including task-aware compression of network logs, scalable trace processing, and feature extraction mechanisms tailored to specific analytical or forensic objectives. Protocol enhancements are validated through both real-world experimentation and simulation campaigns, supported by embedded hardware programming, firmware development, and the deployment of large-scale experimental testbeds to ensure reproducibility and practical relevance.
The overall goal is to tightly integrate protocol engineering, wireless systems, and data-driven network intelligence, enabling scalable, interoperable, and analytically tractable IoT and Wireless Internet infrastructures.
