Search results for "Sensor"
showing 10 items of 4594 documents
A Spatial-Temporal Correlation Approach for Data Reduction in Cluster-Based Sensor Networks
2019
International audience; In a resource-constrained Wireless Sensor Networks (WSNs), the optimization of the sampling and the transmission rates of each individual node is a crucial issue. A high volume of redundant data transmitted through the network will result in collisions, data loss, and energy dissipation. This paper proposes a novel data reduction scheme, that exploits the spatial-temporal correlation among sensor data in order to determine the optimal sampling strategy for the deployed sensor nodes. This strategy reduces the overall sampling/transmission rates while preserving the quality of the data. Moreover, a back-end reconstruction algorithm is deployed on the workstation (Sink)…
Online Non-linear Topology Identification from Graph-connected Time Series
2021
Estimating the unknown causal dependencies among graph-connected time series plays an important role in many applications, such as sensor network analysis, signal processing over cyber-physical systems, and finance engineering. Inference of such causal dependencies, often know as topology identification, is not well studied for non-linear non-stationary systems, and most of the existing methods are batch-based which are not capable of handling streaming sensor signals. In this paper, we propose an online kernel-based algorithm for topology estimation of non-linear vector autoregressive time series by solving a sparse online optimization framework using the composite objective mirror descent…
Accurate Graph Filtering in Wireless Sensor Networks
2020
Wireless sensor networks (WSNs) are considered as a major technology enabling the Internet of Things (IoT) paradigm. The recent emerging Graph Signal Processing field can also contribute to enabling the IoT by providing key tools, such as graph filters, for processing the data associated with the sensor devices. Graph filters can be performed over WSNs in a distributed manner by means of a certain number of communication exchanges among the nodes. But, WSNs are often affected by interferences and noise, which leads to view these networks as directed, random and time-varying graph topologies. Most of existing works neglect this problem by considering an unrealistic assumption that claims the…
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points
2022
In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…
PHASER – A Phase-Shifting Antenna for Low-Power Directional Communication
2017
This paper describes the design and empirical evaluation of PHASER — a mote prototype for low-power directional communication in wireless sensor networks. PHASER has a modular design that includes three components: a low-power radio, an RF signal processing chip, and two off-the-shelf antennas. Directional communication is achieved by splitting the output signal from the low-power radio chip and controlling programmatically the phase of each signal as it transmitted to each antenna. The net effect of controlling the phase of the signals is that they generate patterns of constructive and destructive interference as signals propagate. PHASER is well-suited for wireless sensor networks as it d…
Depth-of-Field Enhancement in Integral Imaging by Selective Depth-Deconvolution
2014
One of the major drawbacks of the integral imaging technique is its limited depth of field. Such limitation is imposed by the numerical aperture of the microlenses. In this paper, we propose a method to extend the depth of field of integral imaging systems in the reconstruction stage. The method is based on the combination of deconvolution tools and depth filtering of each elemental image using disparity map information. We demonstrate our proposal presenting digital reconstructions of a 3-D scene focused at different depths with extended depth of field.
Design of Asymmetric Shift Operators for Efficient Decentralized Subspace Projection
2021
A large number of applications in decentralized signal processing includes projecting a vector of noisy observations onto a subspace dictated by prior information about the field being monitored. Accomplishing such a task in a centralized fashion in networks is prone to a number of issues such as large power consumption, congestion at certain nodes and suffers from robustness issues against possible node failures. Decentralized subspace projection is an alternative method to address those issues. Recently, it has been shown that graph filters (GFs) can be implemented to perform decentralized subspace projection. However, most of the existing methods have focused on designing GFs for symmetr…
Rounding noise effects’ reduction for estimated movement of speckle patterns
2018
The problem of resolution enhancement for speckle patterns analysis-based movement estimation is considered. In our previous publications we showed that this movement represents the corresponding tilt vibrations of the illuminated object and can be measured as a relative spatial shift between time adjacent images of the speckle pattern. In this paper we show how to overcome the resolution limitation obtained when using an optical sensor available in an optical mouse and which measures the Cartesian coordinates of the shift as an integer number of pixels. To overcome such a resolution limitation, it is proposed here to use simultaneous measurements from the same illuminated spot by a few cam…
Ultra-sensitive refractive index sensor using CMOS plasmonic transducers on silicon photonic interferometric platform
2020
Optical refractive-index sensors exploiting selective co-integration of plasmonics with silicon photonics has emerged as an attractive technology for biosensing applications that can unleash unprecedented performance breakthroughs that reaps the benefits of both technologies. However, towards this direction, a major challenge remains their integration using exclusively CMOS-compatible materials. In this context, herein, we demonstrate, for the first time to our knowledge, a CMOS-compatible plasmo-photonic Mach-Zehnder-interferometer (MZI) based on aluminum and Si3N4 waveguides, exhibiting record-high bulk sensitivity of 4764 nm/RIU with clear potential to scale up the bulk sensitivity value…
Baseline design of the filters for the LAD detector on board LOFT
2014
The Large Observatory for X-ray Timing (LOFT) was one of the M3 missions selected for the phase A study in the ESA's Cosmic Vision program. LOFT is designed to perform high-time-resolution X-ray observations of black holes and neutron stars. The main instrument on the LOFT payload is the Large Area Detector (LAD), a collimated experiment with a nominal effective area of ~10 m 2 @ 8 keV, and a spectral resolution of ~240 eV in the energy band 2-30 keV. These performances are achieved covering a large collecting area with more than 2000 large-area Silicon Drift Detectors (SDDs) each one coupled to a collimator based on lead-glass micro-channel plates. In order to reduce the thermal load onto …