Diploma thesis describes direction finding principles for passive localization of emitting source. Direction finding system with one rotating antenna was chosen with triangulation calculation of emitter position. Input parameters are position of measurement point and direction of maximum signal receiving level. A suitable digital compass module and GPS receiver module for this measurement was chosen. For this purpose was created a graphic user interface, which allow user to communicate with external devices and control spectrum analyzer. Results of measurements are displayed at map, together with area of possible positions of transmitter. Receiving Yagi antenna is placed on rotator and whole system is placed on roof of car. Whole system was construct and results of measurement are discuss here.

The diploma thesis in theoretical part focuses on LPWAN in general, meaning the low power wireless device falling into IoT category with a focus on LoRaWAN. The second half of the theoretical part focuses on describing localization techniques and principles in general and selection of one suitable technique for implementation in LoRaWAN. The practical part focuses on the proper HW customizations to enable the localization in this network. There are also described all the steps needed to build the whole working LoRaWAN network. The TDoA localization algorithm is described, the functionality is verified by simulation and also by testing under real conditions. In the end, the results are explained, the shortcomings of the technology are described and finally a suggestion for improvement is provided.

The aim of this term project was to analyze wireless indoor localization. It contains analysis of some wireless localization techniques such as Time of Arrival or Time Difference of Arrival. The paper also describes the system of SEWIO Company. Main part of the master’s thesis is description, design and implementation of the Kalman filter. The Kalman filter is used to improve two-dimensional positional data and synchronization of anchors (devices for finding a position of an object in SEWIO system). There are described a few system models for the Kalman filter.

Professors who manage large classes are unrealistically expected to grade each student fairly and accurately. Even with all of the technological advancements that have occurred in the past thirty years, very little progress has been made in classroom management, and as a result, professors are not equipped with enough tools to successfully manage large class sizes. Because radio frequency identification (RFID) technology is making its way into student issued identification cards, there is an opportunity to use it as a tool to aid professors in the classroom. The focus of this paper is to discover the most effective system that can be implemented as a classroom management instrument. Through multi criteria analysis, several different infrastructures are examined and compared to determine the best alternative. The result of an effective system leads to a reduction in time spent taking attendance, an increase in student performance, an increase in the fairness and accuracy of recording classroom participation, and an enhanced professor-student relationship.