Internet of Things Group

Team leader
Krzysztof Grochla
Team members
Konrad Połys
Michał Gorawski
Rafał Marjasz
Anna Strzoda
Mohammed Nasereddin
Yuting Ma
Viacheslav Kovtun
Zbigniew Laskarzewski
Artur Frankiewicz
Radosław Nowak

Our team specializes in Internet of Things (IoT) research, with emphasis on wireless communication and network protocols. We design and analyze the performance of network protocols, address issues related to interoperability, and the semantic description of data and operation of IoT systems. In addition, we investigate auto-configuration, energy consumption minimization, and localization in embedded devices.

We specialize in:

  • -LP WAN networks, participating in the works of the LoRa Alliance (including the Relay / D2D Task Force);
  • -Indoor localization using UWB and BLE AoA.

We also work on applying artificial intelligence and machine learning to analyze data generated by IoT devices to assist in detecting anomalies such as water leaks or device failures. In cooperation with the industry, we have developed algorithms to increase the accuracy of UWB and BLE indoor localization systems, analyzed measurements from large LoRa networks to identify problem sources, and developed tools for automatic network reconfiguration in response to a failure and to assist in network design.

We have extensive experience working with various technologies and platforms. We specialize in the design and implementation of systems based on technologies such as LoRa, LTE, WiFi, and heterogeneous networks. In our projects, we also work with mesh networks, which are becoming increasingly popular in the IoT world, due to their ability to self-regulate, scalability, and reliability.

We have completed the following projects:

  1. "Optimization and Load Balancing in Next Generation Wireless Networks"
  2. "Dynamic wireless framework for Smart City IoT infrastructure"
  3. "HybridMeshMeet: development of a hybrid system for neighborhood relation detection based on mesh network for MILES industry"
  4. "Integrated system for epidemiological threat analysis and business process management supported by personnel and corporate asset location techniques" (PL)
  5. "Augmented Intelligence Ecosystem for Water Distribution Network Analysts" (PL)

Submitted
In Press

2026

Published

2026

2025

2024

Wyświetlanie 1 - 25 z 171