AUTONOMOUS EXPERIMENTAL SYSTEM AND SOFTWARE FOR SOUND OBJECT DETECTION AND NOTIFICATION - CHYHIN, VASYL; PAZYNIUK, MYHAILO (Herald of Khmelnytskyi National University. Technical sciences, 2023)
An experimental system and software have been created to detect the object with sending the notification about its detection. ASUS TS-10 Mini PC and Synco Mic-M3 type microphone were used. A real-time sound analysis software was created using a C++ programming language with a usage of open-source application named ‘Frequency Analyzer’ was developed. Fast Fourier Transform algorithm was used to expand a sound wave to Fourier series. Herewith such functions as entering threshold sound intensity value, with a notification sending, and signal duration value to cut off unnecessary sounds were introduced. A python-application was created to send notification when the object is detected using Flask library to receive the requests from Sound Analysis application. Herewith a python-telegram-bot library was used to automate sending messages to the telegram chat. Python-application was deployed on the Heroku cloud environment, which allows to comfortably manage the application, its version, and requests to send the message. At the heart of the sound analysis software lies the ingenious application of the Fast Fourier Transform (FFT) algorithm. This algorithm acts as a mathematical cornerstone, effectively converting intricate sound waves into comprehensible Fourier series representations. This transformation allows for a deeper understanding of the audio input, enabling the system to discern key patterns and anomalies. The created experimental system and software stand as a testament to innovation in object detection through sound analysis. By leveraging cutting-edge hardware, meticulous programming, and strategic integrations, the system provides a robust and efficient solution. In parallel to the sound analysis software, a complementary Python application was ingeniously devised to facilitate instant notifications upon object detection. Leveraging the Flask library, this application orchestrates seamless communication between the sound analysis software and external systems. This integration ensures that detection events trigger immediate notifications, enabling real-time awareness and response.