The research covers the areas of IoT technologies, systems and applications. Research will include advanced sensor network technologies as well as their energy efficiency, and advanced techniques to increase reliability and throughput in RFID systems.

Research in the field of the Internet of Things (IoT) is focused on finding energy-efficient solutions for sensor systems that aim to reduce consumption and thus increase the life of most battery-powered devices. Commercial IoT solutions as well as advanced IoT prototypes based on Low Power Wide Area technologies (eg LoRaWAN) as well as Bluetooth Low Energy (BLE) technology will be intensively tested. It is planned to develop models based on deep and machine learning techniques on the basis of which changes in the environment can be accurately detected, such as the occupation of parking lots or changes in soil moisture. Emphasis will be placed on the development of energy-efficient software and hardware solutions that would result in a reduction of cost of the sensor device. With this in mind, emphasis will be placed on the development of an autonomous IoT device.

The research of methods that enable the increase of transmission speed in passive RFID technologies and the development of IoT architectures can be divided into three phases. The first phase involves the simulation of a passive RFID tag with the possibility of testing the properties of multilevel modulation procedures using appropriate coding. Also, as part of the first phase, the performance of bistatic communication systems on the system simulation models developed so far will be investigated. Using existing and procuring new equipment, a series of measurements are planned with the aim of characterizing the performance of IoT architectures. The second phase would involve the development of codes for multilevel modulation in passive RFID technology. The third phase would involve the development of a passive tag prototype with multilevel modulation and the testing of properties in real conditions with the application of appropriate coding.

Research in the field of deep learning, cloud computing and data analytics will involve connecting all three fields in order to develop models over diverse and large data sources. The field of bioinformatics is the research area of the doctoral dissertation in which deep learning methods as well as high-performance computer resources will be used to develop new and improve existing methods in the field of bioinformatics.