Citizens of the city of Sarajevo and of other industrial cities are faced with a record number of days of increased pollution. In the winter months, the city of Sarajevo faces a large number of days of pollution caused mainly by the use of fossil fuels in individual houses for heating purposes. The current situation can be changed by the massive use of energy from renewable sources such as solar energy. This paper aims to evaluate the potential of solar energy in the city of Sarajevo. The use of Geographic Information Systems (GIS) represents the most significant technological and conceptual approach to spatial data analysis. Using existing models for calculating incoming solar radiation integrated in the GRASS GIS and SAGA GIS software, we achieved the goal and calculated the results for solar energy potential in the city of Sarajevo and presented them for the specific settlements. The model was implemented on the basis of created Digital Elevation Model (DEM) from Google Earth – free datasets, using techniques to collect and convert data with different software. Comparative results of selected model research are evaluated using the collected solar irradiance values from the meteorological stations, other research results, and the solar energy potential estimated via the Photovoltaic GIS Information System (PVGIS).

The outbreak of COVID-19 is a public health emergency that caused disastrous results in many countries. The global aim is to stop transmission and prevent the spread of the disease. To achieve it, every country needs to scale up emergency response mechanisms, educate and actively communicate with the public, intensify infected case finding, contact tracing, monitoring, quarantine of contacts, and isolation of cases. Responding to an emergency requires efficient collaboration and a multi-skilled approach (medical, information, statistical, political, social, and other expertise), which makes it hard to define one interface for all. As actors from different perspectives and domain backgrounds need to address diverse functions, the possibility to exchange available information quickly would be desirable. Geoportal provides an entry point to access a variety of data (geospatial data, epidemiological data) and could be used for data discovery, view, download, and transformation. It helps to deal with challenges like data analysis, confirmed cases geocoding, recognition of disease dynamics, vulnerable groups identification, and capacity mapping. Predicting and modeling the spread of infection, along with application support for communication and collaboration, are the biggest challenges. In response to all these challenges, we have established the Epidemic Location Intelligence System (ELIS) using open-source software components in the cloud, as a working platform with all the required functionalities.

ABSTRACT The Online Biomass Potential Atlas is a tool primarily intended for geo-visualisation of biomass data from the Biomass Potential Monitoring System in Bosnia and Herzegovina. However, its role does not have to end here. By developing a functional extension, it can offer an environment for the location analysis of potential biomass users and sources of unused biomass potential. This paper describes an approach for developing tool with such functionality, based on spatial interaction modelling. Determining the optimal location for biogas plants in the region covered by the administrative units of two cantons in Bosnia and Herzegovina is considered as a case study. Based on the analysis conducted in the case study, the feasibility of applying this tool has been demonstrated.

Between March 5 and July 25, 2020, the total number of SARS-CoV-2 confirmed cases in Bosnia and Herzegovina (BH) was 10 090 corresponding to a cumulative incidence rate of 285.7 per 100 000 population. Demographic and clinical information on all the cases along with exposure and contact information was collected using a standardized case report form. In suspected SARS-CoV-2 cases, respiratory specimens were collected and tested by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) assay. The dynamic of the outbreak was summarized using epidemiological curves, instantaneous reproduction number Rt and interactive choropleth maps for geographical distribution and spread. The rate of hospitalization was 14.0% (790/5646) in Federation of Bosnia and Herzegovina (FBH) and 6.2% (267/4299) in Republic of Srpska (RS). The death rate was 2.2% (122/5646) in FBH and 3.6% in the RS (155/4299). After the authorities lifted mandatory quarantine restrictions, the basic reproduction number increased from 1.13 on May, the 20th to 1.72 on May the 31st. The outbreak concerns both entities, Federation of Bosnia and Herzegovina and Republika Srpska, and it is more pronounced in those aged 20-44 years. It is important to develop the communication and emergency plan for the SARS-CoV-2 outbreak in BH, including the mechanisms to allow the ongoing notification and updates at the national level.

Aim The damage caused by the COVID-19 pandemic has made the prevention of its further spread at the top of the list of priorities of many governments and state institutions responsible for health and civil protection around the world. This prevention implies an effective system of epidemiological surveillance and the application of timely and effective control measures. This research focuses on the application of techniques for modelling and geovisualization of epidemic data with the aim of simple and fast communication of analytical results via geoportal. Methods The paper describes the approach applied through the project of establishing the epidemiological location-intelligence system for monitoring the effectiveness of control measures in preventing the spread of COVID-19 in Bosnia and Herzegovina. Results Epidemic data were processed and the results related to spatio-temporal analysis of the infection spread were presented by compartmental epidemic model, reproduction number R, epi-curve diagrams as well as choropleth maps for different levels of administrative units. Geovisualization of epidemic data enabled the release of numerous information from described models and indicators, providing easier visual communication of the spread of the disease and better recognition of its trend. Conclusion The approach involves the simultaneous application of epidemic models and epidemic data geovisualization, which allows a simple and rapid evaluation of the epidemic situation and the effects of control measures. This contributes to more informative decision-making related to control measures by suggesting their selective application at the local level.

This paper shows how to integrate data from enterprise database with spatial data, publish them together to online interactive map, and enable public users to perform analysis in simple web interface. The fact, that this is a public site, where users are not known in advanced and not trained, calls for importance of usability and intuitive user interface design. Also, system administrators are not willing to invest a lot of time in learning the basics of a system, and data providers need effective geoportals to enable access to spatial data and services via the Internet. All these needs should be reconciled during the implementation of the solution. Due to increasing interest of forestry and agricultural organizations in spatial data infrastructure (SDI) development and public users' needs for biomass data web presentation and analysis in Bosnia and Herzegovina, as case study is used the project of Biomass Potential Database with Online Atlas development. Additionally, here is proposed application of the geoportal using online atlas as spatial decision support tool.

E-Learning solutions for Computer Aided Design (CAD) require high quality graphics for positive impact and high satisfaction. Software tools used for hands-on CAD laboratory exercises depend on dedicated Graphics Processing Unit (GPU) to deal with complex graphics processing needed to visualize virtual models in real-time. It is challenging to offer the same level of experience to remote users as they usually cannot afford laboratory-level hardware with dedicated GPU nor such hardware can be provided to them as part of their e-Learning experience. In this paper, grouping of average CAD laboratory workstations in pairs is proposed in order to create remote stations capable of performing required CAD graphics processing for remote users while streaming it over the network for a near real-time experience. Remote station captures video and utilizes hardware HEVC encoding, as common capability of high-end dedicated GPUs, to perform low bitrate video streaming with sub-second latency. The remote station concept enables cost-effective extension of average conventional CAD laboratory to an e-Learning remote laboratory for up to 50% additional remote users in respect to the total number of the laboratory workstations.

Online courses have potential to reach broader audience when compared to traditional learning methods, as they can be made instantly available to groups of students dispersed over wide range of locations and time zones. Some learning topics are easily adopted to this online environment, while others may be challenging to implement as online courses due to their specific requirements and associated cost. If mastering certain topic requires hands-on experience then online course must be made interactive to match the experience of a traditional instructor-led class. Otherwise, online course will be perceived as unsatisfactory and lacking positive impact. Computer Aided Design (CAD) training requires both high performance Graphics Processing Unit (GPU) and hands-on experience with specific CAD software. Both these requirements are difficult to meet on a remote student computer without additional cost. In this paper, grouping CAD workstations into cells is proposed in order to perform required graphics processing using existing hardware and software resources available in an average CAD laboratory. Proposed cell framework uses video capture and GPU hardware encoding to stream the content to the remote students while capturing their interactive feedback for the near real-time hands-on experience. The framework requires single capture card per cell and utilizes 20% of the resources for the cell overhead processing. Remaining 80% of workstations are fully available to the online students and instructors.

Different methodologies are used to assess the potential for using high efficiency cogeneration for cooling and heating. They are mostly adapted to the availability of data and tools for their analytical processing. This paper presents the approach applying location intelligence as a tool that allows using geospatial analysis algorithms and geovisualization of its results. Due to the extremely large amount of data and the dependence of the results on their accuracy and the level of aggregation, the initial methodology of the analytical process implied two steps: wide scale mapping by the ”top down” method, and local mapping by “bottom up” method. However, in order to overcome the problem of regional disparities of quality and the existence of spatial data, certain adaptations of the initial methodology have been made considering the need for a single analytical approach for the entire area of interest. Randomized control of the obtained results indicate that applied geospatial algorithms satisfy the required level of accuracy and reliability of the final methodology.