Exploiting partial reconfiguration through PCIe for a microphone array network emulator

The current Microelectromechanical Systems (MEMS) technology enables the deployment of relatively low-cost wireless sensor networks composed of MEMS microphone arrays for accurate sound source localization. However, the evaluation and the selection of the most accurate and power-efficient network’s topology are not trivial when considering dynamic MEMS microphone arrays. Although software simulators are usually considered, they consist of high-computational intensive tasks, which require hours to days to be completed. In this paper, we present an FPGA-based platform to emulate a network of microphone arrays. Our platform provides a controlled simulated acoustic environment, able to evaluate the impact of different network configurations such as the number of microphones per array, the network’s topology, or the used detection method. Data fusion techniques, combining the data collected by each node, are used in this platform. The platform is designed to exploit the FPGA’s partial reconfiguration feature to increase the flexibility of the network emulator as well as to increase performance thanks to the use of the PCI-express high-bandwidth interface. On the one hand, the network emulator presents a higher flexibility by partially reconfiguring the nodes’ architecture in runtime. On the other hand, a set of strategies and heuristics to properly use partial reconfiguration allows the acceleration of the emulation by exploiting the execution parallelism. Several experiments are presented to demonstrate some of the capabilities of our platform and the benefits of using partial reconfiguration

Design exploration and performance strategies towards power-efficient FPGA-based achitectures for sound source localization

Many applications rely on MEMS microphone arrays for locating sound sources prior to their execution. Those applications not only are executed under real-time constraints but also are often embedded on low-power devices. These environments become challenging when increasing the number of microphones or requiring dynamic responses. Field-Programmable Gate Arrays (FPGAs) are usually chosen due to their flexibility and computational power. This work intends to guide the design of reconfigurable acoustic beamforming architectures, which are not only able to accurately determine the sound Direction-Of-Arrival (DoA) but also capable to satisfy the most demanding applications in terms of power efficiency. Design considerations of the required operations performing the sound location are discussed and analysed in order to facilitate the elaboration of reconfigurable acoustic beamforming architectures. Performance strategies are proposed and evaluated based on the characteristics of the presented architecture. This power-efficient architecture is compared to a different architecture prioritizing performance in order to reveal the unavoidable design trade-offs

Diseño de nodo inalámbrico para procesamiento de voz en prevención de violencia sexual

Este Trabajo Fin de Grado surge de la necesidad de reducir, pero sobre todo prevenir, el alto índice de violencia y agresiones sexuales contra las mujeres que existe en cualquier región del mundo. Para ello, se diseña un sistema de grabación de audio en modo continuo (streaming) y de envío mediante un protocolo inalámbrico, Bluetooth® Low Energy (BLE), a un teléfono móvil; lo que permite incorporar la detección de pánico en la voz y poder alertar, a través de un dispositivo portable, de un ataque o agresión que se esté produciendo contra la usuaria. Por otra parte, se ha aprovechado el sistema de adquisición de audio realizado, para diseñar y desarrollar un sistema que optimice y depure las grabaciones realizadas, en una cámara anecoica, para el entrenamiento de los algoritmos que detectan estrés en la voz. Se han definido dos protocolos para la comunicación en dicho sistema, uno inalámbrico mediante Bluetooth® Low Energy (BLE), y otro alámbrico mediante un cable USB de 10 metros de alcance. La realización de este Trabajo Fin de Grado ha tenido una duración de 10 meses, y de forma resumida y muy general, se puede sostener que se ha conseguido unificar el trabajo en los niveles altos de abstracción, generación de algoritmos para el procesamiento de audio, con los más bajos, y cercanos a las capas físicas y de enlace, para la adquisición, preprocesado y transmisión de dicho audio, a través de los componentes electrónicos y los protocolos de comunicación más actuales y demandados en las aplicaciones tecnológicas de redes de sensores (MEMS, Bluetooth® Low Energy..).This Final Degree Project arises from the need to reduce, but above all prevent, the high rate of violence and sexual aggression against women that exists in any region of the world. For this reason, a streaming audio recording system is designed and sent via Bluetooth® Low Energy (BLE) to a mobile phone, which allows the incorporation of panic detection in the voice to alert through a portable device, of an attack or aggression that is occurring against the user. On the other hand, the audio acquisition system has been used to design and develop a system that optimizes and debugs the recordings made in an anechoic chamber for the training of the algorithms that detect voice stress. Two protocols have been defined for communication in this system, one wireless via Bluetooth® Low Energy (BLE), and another wired via a 10-meter USB cable. The achievement of this Final Degree Project has lasted 10 months, and in a summarized and very general way, we can say that it has been possible to unify the work in the high levels of abstraction, generation of algorithms for the audio processing, with the lowest and closest ones to the phisical and connection layers, for the acquisition, preprocessing and transmission of this one, through the most current electronic components and communication protocols demanded in the technological applications of sensor networks (MEMS, Bluetooth® Low Energy ..).Ingeniería Electrónica Industrial y Automátic

A Low-Power MEMS Microphone Array for Wireless Acoustic Sensors

In this article we present the design of a low-power MEMS microphone array for wireless sensors. The array is used as part of a device that performs acoustic Angle-Of-Arrival (AOA) measurements. The power consumption of this design is lower than that of comparable designs. Each of the 4 analog channels (each with a microphone and amplifier) can be turned on or off (standby) separately. The power consumption is 1.8 mW per channel, and about 0.13 ??W in standby. For a single AOA detection cycle (array activation, audio sampling, AOA computation), the energy consumption is 6.02 mJ. When consecutive AOA detections are performed, the energy cost per detection converges to 3.20 mJ. The AOA accuracy corresponds with the expectations. With a mean error of 4??, this is lower than that of comparable designs.status: publishe