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Electronic module for acoustic detection
Maršál, Martin ; Klusáček, Jan (referee) ; Havránek, Zdeněk (advisor)
This diploma thesis deals with the design and implementation of an electronic module for acoustic detection. The module has the task of detecting a predetermined acoustic signals through them learned classification model. The module is used mainly for security purposes. To identify and classify the proposed model using machine learning techniques. Given the possibility of retraining for a different set of sounds, the module becomes a universal sound detector. With acoustic sound using the digital MEMS microphone, for which it is designed and implemented conversion filter. The resulting system is implemented into firmware microcontroller with real time operating system. The various functions of the system are realized with regard to the possible optimization (less powerful MCU or battery power). The module transmits the detection results of the master station via Ethernet network. In the case of multiple modules connected to the network to create a distributed system, which is designed for precise time synchronization using PTP protocol defined by the IEEE-1588 standard.
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Embedded Sound Detector
Maršál, Martin ; Gutman, Jiří (referee) ; Hynčica, Ondřej (advisor)
In this bachelor thesis I describe how to create a sound recognition system. System aims to detect two types of sounds (hand clap and the sound of the smoke detector). The sound of hand clap user before first using learns to hand clap own type. The sound of the smoke detector is pre-defined by the type of alarm. Evaluation of sounds is done based on Fourier series. The system parameters are set according to the requirements of specificity and sensitivity.
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Embedded Sound Detector
Maršál, Martin ; Gutman, Jiří (referee) ; Hynčica, Ondřej (advisor)
In this bachelor thesis I describe how to create a sound recognition system. System aims to detect two types of sounds (hand clap and the sound of the smoke detector). The sound of hand clap user before first using learns to hand clap own type. The sound of the smoke detector is pre-defined by the type of alarm. Evaluation of sounds is done based on Fourier series. The system parameters are set according to the requirements of specificity and sensitivity.
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Electronic module for acoustic detection
Maršál, Martin ; Klusáček, Jan (referee) ; Havránek, Zdeněk (advisor)
This diploma thesis deals with the design and implementation of an electronic module for acoustic detection. The module has the task of detecting a predetermined acoustic signals through them learned classification model. The module is used mainly for security purposes. To identify and classify the proposed model using machine learning techniques. Given the possibility of retraining for a different set of sounds, the module becomes a universal sound detector. With acoustic sound using the digital MEMS microphone, for which it is designed and implemented conversion filter. The resulting system is implemented into firmware microcontroller with real time operating system. The various functions of the system are realized with regard to the possible optimization (less powerful MCU or battery power). The module transmits the detection results of the master station via Ethernet network. In the case of multiple modules connected to the network to create a distributed system, which is designed for precise time synchronization using PTP protocol defined by the IEEE-1588 standard.
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