Jan Lešetický
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jan Lešetický has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Jan Sedláček
Faculty of Engineering; Czech University of Life Sciences Prague, Kamycka 129, 16500 Prague, Czech Republic
1 shared publication Ján Lacko
1 shared publicationM. Olmr
Czech University of Life Sciences Prague , Faculty of Engineering , Prague , Czech Republic
1 shared publication- Martin Libra
Faculty of Engineering, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic
1 shared publication - Martin Olmr1 shared publication
- Martin Pačes
Department of Chemical Engineering and Center for Nonlinear Dynamics of Chemical and Biological Systems, Prague Institute of Chemical Technology, Technická 5, CZ‐16628 Prague, Czech Republic
1 shared publication
Latest Publications
- Open Access
- 22 July 2026
- Published by Elsevier in Journal of Innovation & Knowledge
Ludic knowledge transfer: How immersive games enable cultural and sustainability learning
- 22 July 2026
- Published by Elsevier in Journal of Innovation & Knowledge
Open AccessLudic knowledge transfer: How immersive games enable cultural and sustainability learning
- Open Access
- 15 March 2022
- Published by Czech Academy of Agricultural Sciences in Research in Agricultural Engineering
- Vol. 68 (3) , 142-149
Monitoring the movement of housed animals by means of wireless technology
Monitoring the movement of housed animals by means of wireless technology | Martin Olmr, Marek Pačes, Jan Lešetický, Miroslav Přikryl | Agricultural Journals
- 15 March 2022
- Published by Czech Academy of Agricultural Sciences in Research in Agricultural Engineering
- Vol. 68 (3) , 142-149
Open AccessMonitoring the movement of housed animals by means of wireless technology
Monitoring the movement of housed animals by means of wireless technology | Martin Olmr, Marek Pačes, Jan Lešetický, Miroslav Přikryl | Agricultural Journals
- Open Access
- 1 September 2019
- Published by Ceska zemedelska univerzita v Praze in Scientia Agriculturae Bohemica
- Vol. 50 (3) , 203-210
Detection of Animal Occurrence Using an Unmanned System
In recent decades, there has been an increase in the work speed and breadth of agricultural technology used to mow grasses. This modernization has resulted in a decline in wildlife. There are several conventional ways to prevent these losses. The most well-known and simplest technique is to search for wild animals using dogs and a phalanx. The dogs are trained to systematically search the area and drive the animals out. Efficiency is increased when visiting a site regularly, thus disturbing the animals, which are then consequently less likely to fawn. The effectiveness of the swarm line depends on the number of participants involved. The recommended spacing is set at 1–3 m. An effective modern means seems to be the use of an unmanned system and thermal cameras. This article presents a proof of concept of a detection system that is capable of detecting the object searched for in grassy vegetation with more than 96% success, regardless of the flight level. The study contributes to automated detection based on the basic principles of threshold.
- 1 September 2019
- Published by Ceska zemedelska univerzita v Praze in Scientia Agriculturae Bohemica
- Vol. 50 (3) , 203-210
Open AccessDetection of Animal Occurrence Using an Unmanned System
In recent decades, there has been an increase in the work speed and breadth of agricultural technology used to mow grasses. This modernization has resulted in a decline in wildlife. There are several conventional ways to prevent these losses. The most well-known and simplest technique is to search for wild animals using dogs and a phalanx. The dogs are trained to systematically search the area and drive the animals out. Efficiency is increased when visiting a site regularly, thus disturbing the animals, which are then consequently less likely to fawn. The effectiveness of the swarm line depends on the number of participants involved. The recommended spacing is set at 1–3 m. An effective modern means seems to be the use of an unmanned system and thermal cameras. This article presents a proof of concept of a detection system that is capable of detecting the object searched for in grassy vegetation with more than 96% success, regardless of the flight level. The study contributes to automated detection based on the basic principles of threshold.
- Open Access
Monitoring of Defects of a Photovoltaic Power Plant Using a Drone
Drone infrared camera monitoring of photovoltaic (PV) power plants allows us to quickly see a large area and to find the worst defects in PV panels, namely cracked PV cells with broken contacts. Roofs are suitable for the integration of PV power plants into buildings. The power plant at the Czech University of Life Sciences in Prague, which was monitored by this method, does not show any significant defects, and the produced electric energy exceeds the expected values. On the contrary, the PV power plant in Ladná has visible defects, and the data monitoring system Solarmon-2.0 also indicates defects. Our newly developed data monitoring system Solarmon-2.0 has been successfully used in 65 PV power plants in the Czech Republic and in many PV power plants throughout the world. Data are archived and interpreted in our dispatch area at the Czech University of Life Sciences in Prague. The monitoring system can report possible failure(s) if the measured amount of energy differs from the expected value(s). The relation of the measured values of PV power to the PV panel temperature is justified, which is consistent with the physical theory of semiconductors.
Open AccessMonitoring of Defects of a Photovoltaic Power Plant Using a Drone
Drone infrared camera monitoring of photovoltaic (PV) power plants allows us to quickly see a large area and to find the worst defects in PV panels, namely cracked PV cells with broken contacts. Roofs are suitable for the integration of PV power plants into buildings. The power plant at the Czech University of Life Sciences in Prague, which was monitored by this method, does not show any significant defects, and the produced electric energy exceeds the expected values. On the contrary, the PV power plant in Ladná has visible defects, and the data monitoring system Solarmon-2.0 also indicates defects. Our newly developed data monitoring system Solarmon-2.0 has been successfully used in 65 PV power plants in the Czech Republic and in many PV power plants throughout the world. Data are archived and interpreted in our dispatch area at the Czech University of Life Sciences in Prague. The monitoring system can report possible failure(s) if the measured amount of energy differs from the expected value(s). The relation of the measured values of PV power to the PV panel temperature is justified, which is consistent with the physical theory of semiconductors.