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Intelligent Recognition of the Smartphone User's Activity
Pustka, Michal ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
This thesis deals with real-time human activity recognition (eg, running, walking, driving, etc.) using sensors which are available on current mobile devices. The final product of this thesis consists of multiple parts. First, an application for collecting sensor data from mobile devices. Followed by a tool for preprocessing of collected data and creation of a data set. The main part of the thesis is the design of convolutional neural network for activity classification and subsequent use of this network in an Android mobile application. The combination of previous parts creates a comprehensive framework for detection of user activities. Finally, some interesting experiments were made and evaluated (eg, the influence of specific sensors on detection precision).
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Platform for Safe File Transfer among Mobile Devices
Pustka, Michal ; Kešner, Filip (referee) ; Minařík, Miloš (advisor)
The thesis deals with safe files transfer among mobile devices . The first part of this thesis is the analysis and review of current solutions for transferring files among mobile devices and complex security solutions for Android operating system. The second part describes the design and evaluation of several concepts for encrypted files transfer among groups of regular users and outside the company or institution . One of the concepts for file transfer among users was chosen for implementation on the Android platform . The last part of the thesis describes the problems that can occur during the implementation , their solution , and finally the verification and validation of the concept itself .
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Intelligent Recognition of the Smartphone User's Activity
Pustka, Michal ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
This thesis deals with real-time human activity recognition (eg, running, walking, driving, etc.) using sensors which are available on current mobile devices. The final product of this thesis consists of multiple parts. First, an application for collecting sensor data from mobile devices. Followed by a tool for preprocessing of collected data and creation of a data set. The main part of the thesis is the design of convolutional neural network for activity classification and subsequent use of this network in an Android mobile application. The combination of previous parts creates a comprehensive framework for detection of user activities. Finally, some interesting experiments were made and evaluated (eg, the influence of specific sensors on detection precision).
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|
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Platform for Safe File Transfer among Mobile Devices
Pustka, Michal ; Kešner, Filip (referee) ; Minařík, Miloš (advisor)
The thesis deals with safe files transfer among mobile devices . The first part of this thesis is the analysis and review of current solutions for transferring files among mobile devices and complex security solutions for Android operating system. The second part describes the design and evaluation of several concepts for encrypted files transfer among groups of regular users and outside the company or institution . One of the concepts for file transfer among users was chosen for implementation on the Android platform . The last part of the thesis describes the problems that can occur during the implementation , their solution , and finally the verification and validation of the concept itself .
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