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.

Monitoring the movement of housed animals by means of wireless technology | Martin Olmr, Marek Pačes, Jan Lešetický, Miroslav Přikryl | Agricultural Journals

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.