Monitoring of Wild Animal Species in the Czech Republic

AbstractIn the paper, the method of data collection, processing and visualization of the occurrence of non-indigenous and endangered animal species in the Czech Republic is described. Our new software enables easy data entry about the observation of monitored species to the expert public. The data obtained is then used by expert and scientific institutions in order to search for optimal solutions of nature protection and population management and results are open to the public.This analytic and software solution was developed by the Department of Information Technologies, Czech University of Life Sciences; the data has been also used by the Forestry and Wood Faculty and the Faculty of Life Sciences

Machine Learning-Based Plant Detection Algorithms to Automate Counting Tasks Using 3D Canopy Scans

This study tested whether machine learning (ML) methods can effectively separate individual plants from complex 3D canopy laser scans as a prerequisite to analyzing particular plant features. For this, we scanned mung bean and chickpea crops with PlantEye (R) laser scanners. Firstly, we segmented the crop canopies from the background in 3D space using the Region Growing Segmentation algorithm. Then, Convolutional Neural Network (CNN) based ML algorithms were fine-tuned for plant counting. Application of the CNN-based (Convolutional Neural Network) processing architecture was possible only after we reduced the dimensionality of the data to 2D. This allowed for the identification of individual plants and their counting with an accuracy of 93.18% and 92.87% for mung bean and chickpea plants, respectively. These steps were connected to the phenotyping pipeline, which can now replace manual counting operations that are inefficient, costly, and error-prone. The use of CNN in this study was innovatively solved with dimensionality reduction, addition of height information as color, and consequent application of a 2D CNN-based approach. We found there to be a wide gap in the use of ML on 3D information. This gap will have to be addressed, especially for more complex plant feature extractions, which we intend to implement through further research. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Methods of collecting and processing of data in www environment

The thesis deals with theoretical basis for the dissertation. Firstly, the terms data, information and knowledge are characterized. Then, the current state and development of web technologies on client and server side is explored. Moreover, the analysis of current state of art deals with Content Management Systems and their approach to information content management. Besides that, contemporary research papers in the desired field were studied. On the whole, forthcoming methodical procedure and a dissertation hypotheses are proposed

Methods of collecting and processing of data in www environment

The thesis deals with theoretical basis for the dissertation. Firstly, the terms data, information and knowledge are characterized. Then, the current state and development of web technologies on client and server side is explored. Moreover, the analysis of current state of art deals with Content Management Systems and their approach to information content management. Besides that, contemporary research papers in the desired field were studied. On the whole, forthcoming methodical procedure and a dissertation hypotheses are proposed

Mitigation of Social Exclusion in Regions and Rural Areas – E-learning with Focus on Content Creation and Evaluation

Study materials and learning in general is moving online nowadays. The paper deals with lifelong learning of socially disadvantaged people. Inhabitants of rural areas represent a substantial group there. The fundamental disproportion of digital divide emerges in combination with other factors, which impacts generally. The problem requires a solution then. The main target groups selected for the study are women on maternity leave, seniors and unemployed school graduates. One of the main focuses was on educational materials and their creation and sharing. Several researches such as semi-structured interviews and surveys have been made among the groups. The results show several requirements for e-learning systems and materials. Taking the everything into account, prototype e-learning applications have been developed (web and mobile)

Cloven-hoofed animals spatial activity evaluation methods in Doupov Mountains in the Czech Republic

The focus of the project „Collection and interpretation of positional data“ is placed on the use of positional data (or the information about a moving object) in the scientific research and educational activities in various fields such as environmental science, logistics, spatial data infrastructure, information management, and others. The objective of this effort is to create an universal model for collection and presentation of moving objects data retrieved through GPS (Global Positioning System), and to verify the model in practice. Several different approaches to process and visualize data about sika deer (Cervus nippon) spatial movements in Doupov Mountains are described in the paper. The data base is represented with large data files created through the cooperation of the Faculty of Forestry and Wood Sciences at the Czech University of Life Sciences in Prague and the Military Forests and Estates of the Czech Republic, a state-owned enterprise. Pieces of knowledge introduced in this paper resulted from solution of an institutional research intention. Internal grant agency of the Faculty of Economics and Management, Czech University of Life Sciences in Prague, grant no. 20121043, „Sběr a interpretace pozičních dat“. The results of the cloven-hoofed animals spatial activity evaluation methods will be available for Research Program titled “Economy of the Czech Agriculture Resources and Their Efficient Use within the Framework of the Multifunctional Agri-food Systems” of the Czech Ministry of Education, Youth and Sports number VZ MSM 6046070906

Usability of IoT and Open Data Repositories for Analyzing Water Pollution. A Case Study in the Czech Republic

Recently, the process of data opening has intensified, especially thanks to the involvement of many institutions that have not yet shared their data. Some entities provided data to the public long before the trend of open data was pushed to a wider level, but many institutions have only engaged in this process recently thanks to a systemic state-level effort to make data repositories available to the public. Therefore, there are many new potential sources of data available for research, including the area of water management. This article analyses the current state of available data in the Czech Republic—their content, structure, format, availability, costs and other indicators that affect the usability of these data for independent researchers in the area of water management. The case study was conducted to ascertain the levels of accessibility and usability of data in open data repositories and the possibilities of obtaining data from IoT (Internet of Things) devices such as networked sensors where required data is either not available from existing sources, too costly, or otherwise unsuitable for the research. The goal of the underlying research was to assess the impact/ratio of various watershed factors based on monitored indicators of water pollution in a model watershed. Such information would help propose measures for reducing the volume of pollution resulting in increased security in terms of available drinking water for the capital city Prague

Possibilities of Using Social Networks as Tools for Integration of Czech Rural Areas - Survey 2021

This paper deals with the use of social networks in agricultural enterprises and focuses mainly on their role and share in increasing the competitiveness of agricultural enterprises in the market. Primary data were obtained from an extensive survey of the development of information and communication technologies in agricultural enterprises, which was conducted in the first quarter of 2021 throughout the Czech Republic (“Survey 2021”). The research was primarily focused on capturing current trends in the use of ICT with emphasis on selected key areas (broadband, social networks, communication tools, regional Internet portals, used hardware categories, used software, mobile communications, Internet of Things, data storage and security, social networks, etc.). This survey builds on previous extensive surveys conducted by the Department of Information Technologies, Faculty of Electrical Engineering, CULS in Prague in several phases since 1999, with the last stage being conducted in 2017. Some surveys were conducted in cooperation with the Ministry of Agriculture of Czech Republic. Compared to recent years, the survey includes new domains, such as the use of the Internet of Things in plant and animal production, data storage and security, the impact of the Covid-19 pandemic on the company's core operations, etc. The survey was prepared, conducted and administered by the Department of Information Technology, Faculty of Economics and Management, University of Life Sciences Prague

Internet of Things (IoT) in Agriculture - Selected Aspects

Article analyzes chosen aspects of Internet of Things (IoT) in general and in regards to its specific uses in agriculture, which is one of the areas where IoT is commonly implemented. It serves as a primary delve into the issues of IoT as part of the grant received from Internal Grant Agency of Faculty of Economics and Management at CULS Prague called “Potential use of the Internet of Things, with emphasis on rural development and agrarian sector”. Article overviews IoT equipment categorization, platforms, standards and network solutions. It focuses on network infrastructure, which is the foundation for IoT implementation. The specific environmental conditions of Czech Republic are also taken into account. Lastly, basic development trends of IoT are defined

Evaluation of Frequencies for the IoT Telemetry in Smart Agriculture

The IoT is becoming a widely known technology for the gathering of telemetry data, while mostly the concept of Smart cities is usually seen as the most challenging area for implementation. The different situations can be found in the smart agriculture concept, where different requirements and especially conditions exist. The purpose of this paper is to make an overview of IoT frequency bands available, with special focus on the situation in the EU, their theoretical usability and, using experimental measurements of typical background noise in different bands and calculations of transmission reliability on expected distance, estimate the practical usability of those technologies in the smart agriculture, compared to the smart city’s requirements. Most of the IoT installations outside 5G systems are in the 900 MHz band, but is this wellsuitable for smart agriculture