Abstract
Nowadays, monitoring of people and events is a common matter in the street, in the industry or at home, and acoustic event detection is commonly used. This increases the knowledge of what is happening in the soundscape, and this information encourages any monitoring system to take decisions depending on the measured events. Our research in this field includes, on one hand, smart city applications, which aim is to develop a low cost sensor network for real time noise mapping in the cities, and on the other hand, ambient assisted living applications through audio event recognition at home. This requires acoustic signal processing for event recognition, which is a challenging problem applying feature extraction techniques and machine learning methods. Furthermore, when the techniques come closer to implementation, a complete study of the most suitable platform is needed, taking into account computational complexity of the algorithms and commercial platforms price. In this work, the comparative study of several platforms serving to implement this sensing application is detailed. An FPGA platform is chosen as the optimum proposal considering the application requirements and taking into account time restrictions of the signal processing algorithms. Furthermore, we describe the first approach to the real-time implementation of the feature extraction algorithm on the chosen platform.
Highlights
Monitoring all kind of human activities has never been as common as today, when it is usual to have many sensors spread along the city, some factories or even our homes
Grup de Recerca en Tecnologies Mèdia (GTM) is involved in two projects related to audio event detection
We conclude that the Basys-3 Field Programmable Gate Array (FPGA) platform is a good trade-off between cost and features for the audio detection algorithm implementation
Summary
Monitoring all kind of human activities has never been as common as today, when it is usual to have many sensors spread along the city, some factories or even our homes. The Grup de Recerca en Tecnologies Mèdia (GTM) has conducted several research projects in the study of acoustic signal processing and event recognition for different applications. GTM is involved in two projects related to audio event detection. GTM develops in the project an Anomalous Event Detection Algorithm in order to avoid the noise computation of any other event but the traffic noise to calculate the noise maps of the city [7]. The second project, named HomeSound (2014-SGR-0590), consists of programming a low-cost GPU platform [8] for the audio event detection of fifteen in-home common sounds (e.g., water, walking, glass breaking, dog barking, etc.). The real-time implementation of the conducted projects in GTM led us to the study of the best hardware platform in terms of efficiency and cost to implement these algorithms. The conclusions of this first approach to the real—time low cost Field Programmable Gate Array (FPGA) proposal are enumerated
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