A multimode SoC FPGA-based acoustic camera for wireless sensor networks

Acoustic cameras allow the visualization of sound sources using microphone arrays and beamforming techniques. The required computational power increases with the number of microphones in the array, the acoustic images resolution, and in particular, when targeting real-time. Such computational demand leads to a prohibitive power consumption for Wireless Sensor Networks (WSNs). In this paper, we present a SoC FPGA based architecture to perform a low-power and real-time accurate acoustic imaging for WSNs. The high computational demand is satisfied by performing the acoustic acquisition and the beamforming technique on the FPGA side. The hard-core processor enhances and compresses the acoustic images before transmitting to the WSN. As a result, the WSN manages the supported configuration modes of the acoustic camera. For instance, the resolution of the acoustic images can be adapted on-demand to satisfy the available network's BW while performing real-time acoustic imaging. Our performance measurements show that acoustic images are generated on the FPGA in real time with resolutions of 160x120 pixels operating at 32 frames-per-second. Nevertheless, higher resolutions are achievable thanks to the exploitation of the hard-core processor available in SoC FPGAs such as Zynq

Review on the Modeling of Electrostatic MEMS

Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices

[poster] Tentoonstelling: De Belgische reglementaire vuurwapens sedert 1830 : 15 september - 15 december 1988 /

Bijzondere collectie

Élaboration et caractérisation de technologies microsystèmes avancées (structures d'actionnement tridimensionnelles et résonateurs électromécaniques à entrefer latéral nanométrique)

Le développement des technologies microsystèmes depuis le milieu des années quatre-vingt a permis d'entrevoir de nouvelles voies de miniaturisation aux fonctions de capteurs et d'actionneurs intégrés. Le principal attrait de ces technologies est de s'appuyer sur des techniques déjà éprouvées en microélectronique afin de fabriquer des composants capables de combiner maîtrise du transport électronique et contrôle du mouvement à l'échelle nanométrique. Parmi ces techniques, le micro-usinage de surface du silicium permet une fabrication de masse et donc l'utilisation en parallèle de ces dispositifs pour un faible coût. Dans le cadre de cette thèse, deux utilisations clés du micro-usinage de surface. La première s'appuie sur un transfert de technologie entre l'IEMN et l'Université de Tokyo pour la réalisation d'actionneurs intégrés de type SDA (Scratch Drive Actuators). Ces actionneurs ont été utilisés pour l'assemblage tridimensionnel de structures grâce au flambage de poutres de support. Le procédé de fabrication, ainsi qu'une technique originale de gravure anisotrope du polysilicium en film mince sont présentés, avant de détailler le processus d'auto-assemblage qui a permis d'élever des plateaux mobiles à 90 micromètres hors du plan du substrat. Un actionnement électrostatique de large amplitude (+ ou - 15 degrés en rotation) est caractérisé et modélisé dans le but d'appliquer ces micro-actionneurs à grande déflexion à un système d'optique adaptative, dont un démonstrateur est présenté en dernier lieu. La seconde voie d'étude concerne la réalisation par micro-usinage de surface de structures résonantes appliquées au traitement de signal en haute fréquence. un enchaînement original d'étapes technologiques assure la réalisation de transducteurs électrostatiques [...].LILLE1-BU (590092102) / SudocSudocFranceF

A New Method for Acoustic Priority Vehicle Detection Based on a Self-Powering Triboelectric Acoustic Sensor Suitable for Low-Power Wireless Sensor Networks

Traffic congestion is, on a daily basis, responsible for a significant amount of economic and social costs. One of the critical examples is the obstruction of priority vehicles during fast trajectories, which potentially costs lives and property in case of delay that is too great. By means of visual sensing methods, solutions and schedules have already been proposed for adjusting traffic light sequences depending on a priority vehicle’s position. However, these mechanisms are computation and power intensive. Deploying and powering a large-scale network will have a crucial economical cost. Furthermore, these devices will not always have access to sufficient power. To provide a solution, we developed an acoustic and self-powered device that can detect priority vehicles and can be cost effectively deployed to define a sensor network. The device combines the detection of priority vehicles and the harvesting of sound energy through triboelectrification. This paper will introduce the use of triboelectric energy harvesting, specifically in a self-powered wireless sensor network for priority vehicle detection. Furthermore, it shows how to increase the power performance of such a generator. Finally, the results are analyzed

Les T.O.C. et leurs traitements

AMIENS-BU Santé (800212102) / SudocSudocFranceF

Open Sensing System for Long Term, Low Cost Water Quality Monitoring

Water is a major preoccupation for our generation since it is crucial in keeping a healthy ecosystem and supporting biodiversity. The state of aquatic systems and water bodies needs to be continuously monitored to make informed decisions and trigger sanitation when necessary. However, observing and tracking the evolution of many water bodies without disturbing and polluting the biotopes is expensive, not scalable, and thus, infeasible. This article presents a way to make sustainable measurements using a new low-cost, open-source, and autonomous monitoring system deployable in a broad network. The smart buoy is deployed and controlled by a central unit that uses lab-graded sensors to measure ambient factors. The custom electronic board offers sustainable electronics integration emphasizing power path and network connectivity. The smart buoy showed an average power consumption of 1.8 mA and a cost of 932 euros per device. Currently, five spots have been monitored, which allowed the understanding of why biological events, such as a massive fish death, occurred. The system is easily expandable and can be used in various applications to increase the knowledge of the underwater ecosystem