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Mobile application for an intelligent beekeeping system
Pecár, Martin ; Myška, Vojtěch (referee) ; Kiac, Martin (advisor)
The aim of this thesis is to design and create an application which will allow beekeepers to manage their hives with a mobile phone.The reason for this is centralisation and clarification of all colected data from visits to the hive, where this data could be later used to create statistics.Furthermore, this app contains ways to notify the beekeeper that there is a need of intervention with the hive using their own alerts and statistics of selected properties of a hive. The result of this work is the previously described application.
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Intelligent beekeeping system
Hrubý, Jan ; Zeman, Václav (referee) ; Kiac, Martin (advisor)
The aim of this thesis is to design and develop an intelligent beekeeping system that can measure the frequency in the colony, the weight of the hive to monitor the loss or to inform the beekeeper if the bees are carrying honey. Furthermore, the security of the hive against theft is also being considered. Communication between multiple intelligent beekeeping systems is important for the functionality. This is why part of the work focuses on choosing the best possible communication, taking into consideration battery consumption and reliability. In this work, a many-to-one communication system of modules is used, which means that the number of hives can be freely expanded without affecting the functionality of the system. The resulting system is powered by a combination of battery and solar panels.
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Advanced analysis of moving objects in transport
Hora, Adam ; Dejdar, Petr (referee) ; Kiac, Martin (advisor)
This thesis solves the problem of monitoring objects from live streams or camera recordings. The aim is also to create your own data set usable in solving traffic situations and analysis for object recognition and classification. The YOLO method with OpenCV support was used for evaluation purposes. The result is a program in which road recordings can be inserted or live broadcasts can be used from a camera positioned so that it captures the road. The output of the program is to find out the number of motor vehicles at any given moment and the average number of vehicles that were on the road during given periods of time. The videos from which the data set is created were provided by the thesis supervisor. The main benefit of this work is the ability to monitor traffic density at given time intervals.
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Control Of Laboratory Processes Using Modern Methods Of Image Processin
Kiac, Martin
The thesis deals with the image processing and detection of specific objects in the image. The main objective of this work is to implement a algoritm for the control of pipetting processes based on images from the camera. In this thesis is used for image processing an open source computer vision library OpenCV and for pipette detection is used convolutional neural network. The proposed solution is still in development process. The following article describes the issue and the results of the thesis solution.
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Wireless robot control using mobile platform
Matuška, Jakub ; Kiac, Martin (referee) ; Přinosil, Jiří (advisor)
This bachelor’s thesis deals with design and implementation of an application for robot’s omnidirectional movement control using mobile platform. Implementation includes an Android application, used as user interface, as well as robot–side Python program for controlling movement and sending RTP stream to Android application. User can control robot’s movement using two virtual joysticks. Raspberry Pi was used as the control unit. The application has security module. Pipeline-based multimedia framework named GStreamer was used to implement RTP steaming. This paper describes necessary theory first and then introduces basic building blocks used in creation process of the application.
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Advanced analysis of moving objects in the image
Medynskyi, Ivan ; Sikora, Pavel (referee) ; Kiac, Martin (advisor)
This work focuses on image processing using the OpenCV library and detecting moving objects in video using convolutional neural networks. The resulting application can detect moving objects in video or in real time and includes a user interface that allows the user to easily control the application. Part of this application is the YOLO convolutional model, which is designed to detect moving objects.
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Image data segmentation using deep neural networks
Hrdý, Martin ; Myška, Vojtěch (referee) ; Kiac, Martin (advisor)
The main aim of this master’s thesis is to get acquainted with the theory of the current segmentation methods, that use deep learning. Segmentation neural network that will be capable of segmenting individual instances of the objects will be proposed and created based on theoretical knowledge. The main focus of the segmentation neural network will be segmentation of electronic components from printed circuit boards.
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IoT system for gardening
Mlčák, Petr ; Kiac, Martin (referee) ; Caha, Tomáš (advisor)
The thesis deals with the design and creation of a weather station suitable for gardeners. The created device is able to measure temperature, pressure, humidity, amount of precipitation, wind speed and direction, UV index and also temperature and soil moisture at several depths. The weather station is powered by a battery with auxiliary charging from a photovoltaic panel. The thesis is divided into several parts. The theoretical part describes the individual physical principles of measurement of the considered physical quantities. Subsequently, a comparison of available sensors is made and then a final selection is made. The third part deals with the design and implementation of the hardware circuitry including the creation of the PCB. In this section, the holders of each sensor are also designed for printing on a 3D printer, which are then printed. The fourth section deals with software design issues, which is described in more detail. Finally, the whole weather station is assembled, wired and the functionality of all components is verified by sending the measured data to Thingspeak.
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Object detection in video using neural networks and Android application
Mikulec, Vojtěch ; Kiac, Martin (referee) ; Myška, Vojtěch (advisor)
This master’s thesis deals with the implementation of functional solution for classifying road users using mobile device with Android operating system. The goal is to create Android application which classifies vehicles in real time using rear-facing camera and saves timestamps of classification. Testing is performed mostly with own, diversely modificated dataset. Five models are trained and their performance is measured in dependence on hardware. The best classification performance is from pretrained MobileNet model where transfer learning with 6 classes of own dataset is used – 62,33 %. The results are summarized and a method for faster and more accurate traffic analysis is proposed.
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Utilization Of Modern Image Processing Methods In Control Of Laboratory Processes
Kiac, Martin
The thesis deals with the processing and detection of specific objects in the image on the Android mobile platform. The main objective of this work is to implement a mobile application for the control of pipetting processes based on images from a camera of a mobile device. In this thesis is used for image processing an open source computer vision library OpenCV. The proposed solution was subsequently implemented on the Android platform using the Android Studio development environment. The following article describes the issue and the results of the thesis solution.
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