People
Ing. Jan Procházka

Ing. Jana Kaliková, Ph.D.; Ing. Jan Procházka

The project focuses on experimental research into the dynamics of Wi-Fi signals passing through various materials and the analysis of mobile device behavior during Probe Request frame transmissions. The primary goal is to collect real-world data and link it to the principles of signal propagation in material environments from a theoretical physics perspective. This approach provides a detailed insight into mobile device behavior within the context of passive mobile crowdsensing and contributes to optimizing the use of Wi-Fi technologies, particularly in the transportation sector, such as the placement of sensors at transit stops or within vehicles. The project leader has been extensively researching the modeling and testing of passive mobile crowdsensing technologies in transportation environments. This includes estimating passenger numbers, detecting individuals at transit stops, and modeling traffic flows to optimize public transportation. Her previous research has demonstrated the effectiveness of this technology and revealed its broad application potential. For valid project results, it is essential to create extensive datasets based on real measurements, reliable data, and their integration with theoretical physics. The project involves experiments with transmitter and receiver placements around obstacles, examining the effects of various materials, varying distances, and the use of different types of antennas. Data, particularly RSSI (Received Signal Strength Indication) values, in relation to other parameters, will be analyzed and processed using the Python programming language. Custom algorithms and scripts, as well as Python extensions for Excel, will be utilized. Another part of the project involves creating a perfectly shielded environment for measuring the frequency of Probe Request frame transmissions, enabling a detailed analysis of differences between devices, operating systems, and applications. The first part of the research focuses on analyzing

2025 - 2025

Studentská grantová soutěž ČVUT - SGS25/069/OHK2/1T/16

Ing. Marek Kalika, Ph.D.; Ing. Jan Krčál, Ph.D.; Ing. Alena Kubáčová

In this two-year project, we are focusing on the development of an innovative sensor for passive mobile crowdsensing, its software configuration, and the creation of a methodology for optimal processing and analysis of acquired data. The main objective is to create a dynamic model that will be used to optimize various aspects of public mass transportation and its monitoring. In the first year of the project, we will concentrate on assembling and testing the sensor using Raspberry Pi 5 and developing customized software for data collection and filtering. The sensor will be specifically designed for efficient passive capture of Probe Requests from Wi-Fi frames of mobile devices of passengers and will be capable of storing, filtering, and sending preprocessed data to a server. The second year of the project is dedicated to the analysis of gathered data and the creation of a model for real-world use in public transportation systems. The goal is to efficiently identify passengers, create their travel routes, and establish transportation flows. During this process, emphasis will be placed on recognizing device types based on MAC addresses, incorporating MAC address randomization, and using de-randomization algorithms for more accurate device identification. Possible collaboration with the Institute of Logistics and Transportation Management at the Faculty of Transportation and the Institute of Microelectronic Applications brings additional value to the project in terms of expertise and the opportunity to implement results in a real-world environment. This ensures that the research will not be purely theoretical but will also have a practical impact. The project results will be presented at international conferences and published in prestigious scientific journals, allowing for the dissemination of knowledge and increasing the visibility and significance of the research. This effort will contribute to strengthening the position of the Faculty of Transportation as an in

2024 - 2025

Studentská grantová soutěž ČVUT - SGS24/105/OHK2/2T/16

Ing. Marek Kalika, Ph.D.; Ing. Jan Procházka

The project "Qualification of objects using FMCW radars to increase safety in the external environment" responds to current challenges in the field of autonomous vehicles, where optical sensors are often used to detect obstacles. These sensors are effective in ideal lighting and climate conditions, but their functionality is limited in more demanding conditions, such as poor lighting conditions or extreme climatic conditions. This project presents FMCW radar technology as a possible solution to these limitations, as radar sensors are not dependent on light conditions. The goal of the project is the development and implementation of FMCW radar systems capable of identifying and classifying objects in various outdoor environments. The benefit is a possible increase in the safety of traffic participants in outdoor environments such as industrial sites and spaces where different traffic flows meet people or animal creatures. The project focuses on the implementation of radar sensors that are able to distinguish objects. The emphasis is placed on the integration of radar systems into existing security and monitoring systems, including the development of algorithms for the processing and analysis of radar data. With the goal of creating technologies to create a safe environment where autonomous vehicles and other agents can coexist without the need for physical separation. The output of this project is the creation of a separate technology that can recognize at least three types of objects and, at the same time, classify their movement.

2024 - 2025

Studentská grantová soutěž ČVUT - SGS24/104/OHK2/2T/16

Ing. Jana Kaliková, Ph.D.; Ing. Alena Kubáčová; Ing. Jan Procházka

Znalost programovacího jazyka Python patří v dnešní době mezi stěžejní znalosti každého inženýra. V roce 2022 byla na FD vytvořena intranetová platforma pro podporu online studia základů tohoto programovacího jazyka. Na Fakultě dopravní od 3. semestru studují studenti v rámci specializací. Každá specializace potřebuje jiné znalosti i v rámci programování. Touto platformou bychom chtěli do budoucna poskytnout konkrétní portfolio znalostí pro každou z nich. V roce 2023 se zaměříme na rozšíření kurzu pythonu o kompetence potřebné v rámci studia specializace ITS (inteligentní doprvní systémy) na FD. Hlavním cílem projektu je rozšíření intranetové platformy, která v současné době obsahuje 3 kurzy, o pokročilé nástroje programování v Pythonu se zaměřením na specializaci ITS.

2023 - 2023

The "PPSR" internal calls

Ing. Jana Kaliková, Ph.D.; Ing. Jan Procházka

Crowdsensing and related technologies, such as personal wearable devices, have great potential for growth and application in various fields today due to the availability of modern technologies and technical elements. So far, this issue has been insufficiently scientifically researched or is insufficiently being researched at present, and there are no commercial solutions available for use in common practice. Not only during the current coronavirus crisis, crowdsensing technologies would find wide multidisciplinary applications. They can be used as sources of valuable statistical data on population movements (eg. for transport service planning), access authorization (based on authorization, purchase of tickets, etc.), guidance and navigation (search for a free parking space or guiding a person to the platform according to the purchased ticket) or identification of the number of people present in a certain area (number of people in one vehicle or car, in a waiting room at a railway station, in a shopping center, city center, etc.), as well as for commercial use (amusement parks, etc.) and much more. However, crowdsensing and related technologies (wearable devices, biometrics) can also be used to measure different types of data - ambient air pollution by measuring blood oxygen saturation, anonymous demographic statistics (nationality, age, gender), predictive analysis, measurement and monitoring for medical purposes or, for example, to exchange data between devices that would ensure the retrospective identification of persons who were near a carrier of a dangerous disease, etc. The project aims to identify the most suitable potential applications of these technologies primarily applied to transport issues concerning their contribution to today's society. Subsequently, these applications will be modeled and empirically investigated.

2022 - 2023

Studentská grantová soutěž ČVUT - SGS22/122/OHK2/2T/16

Ing. Jana Kaliková, Ph.D.; Ing. Alena Kubáčová; Ing. Jan Procházka

Bude vytvořena a realizována ucelená platforma - webové prostředí na intranetu FD s přístupem pro všechny zaměstnace a studenty FD. Stránky budou rozděleny do 3 sekcí podle úrovně znalostí. Pro každou sekci budou vytvořeny komplexní výukové materiály pro 14 výukových týdnů cvičení. Kromě základních materiálů budou webové stránky obsahovat množství řešených příkladů k řešené problemtice, interaktivní odkazy na oficiální dokumentaci Pythonu, dále personalizované prostředí pro každého uživatele s možností ukládání svých řešení a v neposlední řadě i diskusní fórum, kde uživatelé budou moci žádat o radu a sdílet své znalosti.

2022 - 2022

The "PPSR" internal calls