University projects


J.J. Strossmayer University of Osijek approved seven projects to the Faculty of Electrical Engineering with the aim of encouraging young researchers (assistant professors) to conduct researches and publish papers.


    Project leader: Dr. Krešimir Grgić, Assistant Professor

Wireless sensor networks (WSN) rapid development and their possible application area expansion naturally create the need for their interconnection with other types of networks predominantly based on the Internet protocol. Since IP-based networks started transition from the IPv4 to the IPv6 protocol, there is a need for the IPv6 protocol implementation into the WSN.

The main project goal is to successfully implement the IPv6 protocol into wireless sensor network environment through the entire protocol stack (including communication, routing and security mechanisms). Furthermore, the aim is to test performances of the implemented networking mechanisms in such environment.

The expected project result is to establish full connectivity and to integrate the IPv6-based WSN within the global IP network acquiring satisfying WSN performance (possible real-time operation). Verification and validation of the project results will be carried out by checking the connectivity with sensor nodes from the IP environment in addition to the performance comparison with the conventional WSN (without implemented the Internet protocol).

IPv6 protocol successful implementation into the WSN without performance degradation will enable their simple integration with other IP-based networks and significantly extend their practical application possibilities.


     Project leader: Dr. Tomislav Keser, Assistant Professor

The computer vision technology is the backbone of visual information processing based on computer systems. Nowadays, many technical and technological processes, in order to achieve their goals, are relatively automated. Furthermore, their control algorithms are developed for processing tasks in both 1D and 2D domain. The algorithms are designed for linear processing of 1D data and 2D visual data as moving or still images. Being a direct consequence of automation level increasing, the control domain shifts from 1D processing into 2D processing stressing the need of raising the quality and quantity of production. On the one hand, 1D data processing can easily identify and design the required power of a computer system using linear interpolation modules of the data quantity and the time required to process them. On the other hand, 2D data image processing requires non-linear growth of computing power creating a problem in a computer control system design. One of the most adequate solutions, in economic and practical terms, is the control algorithms adaptation in terms of parallelized data processing in parallel and/or pseudo-parallel computer systems.

The aim of this research is to investigate the possibility of using and adapting the existing algorithms for image processing to work in real-time using graphics processor computer systems and operational assessment of ceramic tiles visual quality. In addition, the goal is to investigate and validate the graphical computer system application aiming at processing 2D data in terms of determining the processing acceleration compared to a classical CPU oriented computer system. Those systems that use graphics processing subsystems to process data for specific purposes already exist being mostly based on Nvidia CUDA technology. The research is based on the AMD opponent APP technology usage, which is, according to the researchers of this project, unfairly neglected being the more adequate solution for certain tasks than the aforementioned technology, which this study will prove.


Project leader: Dr. Mario Vranješ, Assistant Professor

Owing to the development of video technology and broadband Internet, the users have at their disposal a variety of applications that include watching of network transmitted videos (video conferences, video on demand, IPTV, remote video surveillance, etc.). However, the price of these applications is still too high for most users. In order to save the network resources (lower transmission cost), it is necessary to compress the video; however, it reduces the video quality. User devices (TV, PC, tablet, mobile phone, etc.) have different screen sizes. Subsequently, the same video does not look the same on each of them. Furthermore, the video content can also be very different. In addition, the access to the applications should be provided from any location (different transmission conditions). Therefore, it is necessary to optimize the spatial and temporal resolution of the video and adjust them to the transmission conditions together with the device the video is displayed on. This saves the network resources, reduces the applications price while the video quality remains almost the same.

One of the aims of the project is to create new improved computer algorithms for:

(1) spatial and temporal video rescaling in order to adjust it to the size of the screen where it is displayed and to the current transmission conditions;

(2) quality assessment of rescaled and network transmitted video.

New algorithms will lead to the project’s main goal - optimizing the network resources usage when watching videos on different devices in different transmission conditions (lower costs and lower power consumption). Additionally, the study should result in the reduction of the amount of resources needed for the video transmission to a variety of user devices at different locations, reduction of the costs of such applications and lower power consumption making these applications ​​available to a larger number of users. Simultaneously, the network resources surplus could be used for other purposes.


Project leader: Dr. Irena Galić, Assistant Professor

Statistically, cardiovascular diseases are among the most common diseases in developed countries being the most common cause of death in more than 50% of cases. Minimally invasive diagnostic methods for the diagnosis of heart diseases are Computed Tomography (CT) and Nuclear Magnetic Resonance (NMR). In the resulting image, which may be 2D or 3D, internal structure features, e.g. size, shape, density, defects, etc. are well visible. The acquired medical data are organized as a group of cross sections and require visualization. Sophisticated visualization methods provide an insight into the complex behaviour of the heart. Furthermore, they provide localized view of the selected areas within the heart and enable interactive changes to the parts of interest. The goal is to construct a 3D model of the heart based on the 4D CT images of the heart as well as to construct a 3D model of the heart based on the 4D NMR images of the heart. From the resulting 3D model of the heart, a further analysis and modelling of the heart in every stage of the cardiac cycle can be done. The expected result is the video simulation of the heart that can afterwards be upgraded for the purpose of determining the specific properties of the heart and its motion. For the quantitative results analysis and successful 3D heart modelling, MATLAB software package will be used. The software package MATLAB displays all data in the form of matrices, thus being the excellent tool for the results verification. In addition, MATLAB allows graphic manipulations in both 2D and 3D space. Consequently, dangerous cardiovascular diseases will be much easier detected and analysed because modern CT and NMR devices produce more complex and larger data sets which creates the need for efficient and more advanced visualization algorithms.


Project leader: Dr. Zvonimir Klaić, Assistant Professor

In the last few decades, considerable resources have been invested in the rapid development of renewable energy sources and distributed generation in general in the European Union and worldwide. At the same time, power consumption is continuously increasing and loads are becoming more complex which ultimately requires new investments in the distribution network generally accepting the concept of Smart Grids as a solution. A smart grid is a concept containing many elements where monitoring and control of every element in the chain of production, transmission, distribution and final consumption enable much more efficient delivery and the electricity usage. One of the elements of the smart grid efficiency is the ability of real-time demand and supply balancing. This balancing is carried out by consumption monitoring and redistribution of electricity among individual end users according to their needs.

The project aims at modelling and testing capabilities of real-time balancing using smart metering solutions. The model for real-time balancing consumption at the Faculty of Electrical Engineering Osijek is performed by using the smart measurements of photovoltaic power plants production with 10 kWp (renewable source) and measuring the air conditioning devices consumption (final consumption devices). The expected result regarding real-time air conditioners consumption, depending on the level of electricity production in the photovoltaic power plant, is to decrease the peak-to-peak value of the air conditioning devices. Upon the completion of the measurements, the results will be used to simulate and analyze the demand redispatching influence on Osijek local distribution network. The impact of balancing the production and consumption in real-time using the concept of smart grids on the local distribution system will be analyzed by the software EasyPower. The expected result is to optimize the peak value consumption in the analyzed area and to analyze the photovoltaic power plants integration in the electricity distribution system.


     Project leader: Dr. Davor Vinko, Assistant Professor

The existing energy harvesting methods are able to provide (harvest) low instantaneous power from the environment, which is sufficient for ultra-low power electronics. Energy harvesting is especially suitable for the use in systems where the batteries usage is a high cost solution and the power supply network is not available. Good examples are wireless sensor networks (WSNs) which are used to monitor large spatial area. They consist of a number of wireless sensor nodes which are deployed within the monitored area.

The project goal is to develop a prototype of a wireless passive sensor node which solely uses energy harvesting as a power supply. The additional project goal is to enable effective transfer of collected data through the WPSN by optimizing the WPSN’s several segments. The project is expected to prove that it is possible to have reliable operation of the wireless sensor node which is powered solely by energy harvesting methods.


Project leader: Dr. Marinko Barukčić, Assistant Professor

The general aim of the project is to implement and adapt the soft computing methods (Evolutionary Algorithms, Artificial Neural Networks and Fuzzy Inference Systems) in order to solve the optimization and estimation problems in electric power systems and sets. The research will deal with the optimal distributed generation allocation in distributed networks, estimation of the photovoltaic panels equivalent circuit parameters and induction motors. The research will be carried out on the simulation level and verified by comparison to previously provided and afterwards measured results.

According to the previous experience, the soft computing methods usage, which aims at solving the specific problems in electrical engineering, requires the problem dependent and unique adjustments. To paraphrase, the use of these methods in their original form in order to solve the specific problems in electrical engineering do not usually result in satisfactory solutions. On the other hand, the soft computing methods enable estimations taking the uncertainties of the numerical data into consideration. Therefore, the proposed research will result in the adjusted soft computing methods in order to simulate real systems as realistic as possible.