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International audience; During successive industrial revolutions, the objective has not only been for industry to improve and satisfy its direct needs, it has also been to improve society’s standard of living and make life easier for the consumer. Therefore, economic growth should always go hand in hand with each industrial revolution. The medical industry, energy conservation and, in particular, production technologies will be transformed through new value chain models. Globalization, urbanization, demographic change and energy transformation are the transforming forces estimating the technological impetus for a better identification of solutions for a world on the move. In recent years, successive revolutions have made remarkable contributions to a person’s quality of life, safety, industrial economy, comfort and health. This work aims at improving the energy consumption of buildings. To achieve this goal, we have created a Digital Twin that accurately reflects the behavior and characteristics of a future or existing building. To reproduce a copy of the future or existing building, we chose to use the Autodesk REVIT solution to meet several constraints. These have a significant influence on the energy behavior of the building.

Everyday more and more accidents between vehicles accrue mainly because of poorly visible road signs, that is why it is important to have a system that can help drivers for safer driving. In order to improve road safety and significantly reduce the risk of these accidents, numerous works have been undertaken in computer vision. In this paper, we propose a contribution to this issue by taking advantage of the remarkable results of deep convolutional neural networks in computer vision. We propose an automatic recognition system of road signs based on a modified model inspired by LeNet model. The results obtained by comparison of LeNet model and two proposed modified models on the German traffic dataset is about 99% accuracy which is promising compared to the state-of-the-art results.

In the industrial world, a trend towards connected, robotic and intelligent factories is on the rise to face competition from countries with low production costs. The industrial revolution ‘Industry 4.0’ is considerably reducing the boundaries between the physical and digital worlds. This has given rise to interconnected factories in which people, machines and products interact with each other using smart sensors. This paper presents a comparison between a pulse-modulated Discrete Wavelet Packet Transform (DWPT) system and an Orthogonal Frequency Division Multiplexing (OFDM) multicarrier modulation system in a noisy industrial propagation environment. This to provide an alternative to conventional high-rate wireless communication systems using an Industrial Internet of Thing (IIoT).

The internet of things represents the next phase of the digital revolution that will transform the lives of consumers. While the Internet does not usually extend beyond the electronic world, connected objects represent the extension of the Internet to things and places. The purpose of this article is to present the different uses of IoT in finance and to analyze the impact of digital trends and IoT on the procedural scheme of a traditional bank. It would be interesting to gather the different types of digital trends that similarly impact processes of a bank. We will treat these trends in the same way to carry out the digital transformation using these new techniques.

This article presents the simulation, validation and implementation of a temperature sensor based on RO (Ring Oscillator) in order to carry out a thermal study for the detection and localization of thermal peaks in an integrated circuit (CI). The input temperature, angles, distance as well as certain frequencies will be obtained using the GDS (gradient Direction Sensor) method based on RO. In this work, a simulation with the ModelSIM tool as well as the technological validation of the degree of integration with the NCLAUNCH Cadence tool and check this type of fully digital temperature sensor includes a number of exact inverters that can be logically inserted. In addition, a DE1 FPGA cyclone of the V 5CSEMA5F31C6 family is used for implementation. Before the transition to FPGA board implementation and verification, the use of the VHDL code and its bench test is required to describe three inverters that form a ring oscillator, in order to validate the results obtained after the synthesis Quartus Prime. This document provides a solution to thermal constraints and local overheating in the design of complex systems, which has been a major concern for designing integrated circuits.

The Coronavirus epidemic first appeared in Wuhan-China on December, 31st, 2019 This has put the world's hospitals, clinics, testing laboratories and health administrations under pressure As of April, 04th, 2020, the World Health Organization reported more than 167515 confirmed cases in more than 100 countries worldwide The diagnosis of the epidemic will increase the burden on overburdened testing laboratories Several screening methods have been proposed in parallel in order to facilitate and, above all, to make rapid diagnosis easier At this level, X-Ray images seem to be a good accompanying solution for emerging countries to help rapid screening The solution proposed in this paper consists on a collaborative and smart platform based on the Convolutional Neural Network for Classification and Detection namely VGG16 The platform ensures the fast download of the X-Ray image, with the entry of the patient's personal information followed by the launch of a 5 seconds test The platform generates, as a result, a PDF file containing all patient information © 2020 The Authors Published by Elsevier B V

International audience

Nowadays, the Industrial Internet of Things (IIoT), plays an important role in transforming industrial environment by opening up a new area for economic growth and competitiveness in digital Industry 4.0. Using intelligent communication system based on IIoT, will help factories to obtain better profits in the industrial manufacturing markets. For this purpose, this article presents performances in terms of binary error rate of a wide-band IIoT multi-users (or sensors) system under an industrial medium. This medium is simulated as a fading channel including industrial noise, through which the robustness of our system will be studied and improved. This multi-users system is based on IDWPT and DWPT for many-to-one applications. To face the harshness of the industrial environment, an error-correcting code is added to the architecture to improve its robustness. Two error-correcting codes are used, convolutional coding and RS code for 8, 16 and 32 multi-sensors system. This will lead to a comparative analysis of the performance between this two coding techniques.

This work is dedicated to present a new pipeline-parallel architecture of Discrete Wavelet Packet Transform (DWPT) for all wavelet family implemented in FPGA technology. The main target of our architecture is to provide an effective performance trade-off, where it significantly increases the throughput with a restricted amount of hardware. In this article, we propose two kinds of configurable architecture: first architecture with a very strict amount of hardware base of pipeline and sharing resource, and the second architecture provide an ultra-high speed by propose P-parallel DWPT and a parallel direct FIR filter under the strategy of pipeline-parallel and sharing resource. The pipeline and the clever sharing of the hardware resources are smartly connect based on low-pass and high-pass filters in the Mallat-tree algorithm. These architectures are fully configurable in synthesis according to parallel degree, the tree depth (number of tree levels), the order of the filters and the filter quantization coefficient. Consequently, the simulation results accelerated to an approximate value of P*(Frequency). Furthermore, the tree depth and filters order has little impact (only due to place and route variations) on throughput. This architecture was synthesized using Altera Quartus prime lite edition targeting an Altera Cyclone IV – (FPGA) and it was developed in VHDL at RTL level modeling.

International audience; The industrial internet of things (IIoT) known as industry 4.0, is the use of internet of things technologies, via the Wireless Sensor Network (WSN), to enhance manufacturing and industrial processes. It incorporates machine learning and big data technologies, to allow machine-to-machine communication that have existed for years in the industrial world. Therefore, it is necessary to propose a robust and functional communication architecture that is based on WSNs, inside factories, in order to show the great interest in the connectivity of things in the industrial environment. In such environment, propagation differs from other conventional indoor mediums, in its large dimensions, and the nature of objects and obstacles inside. Thus, the industrial medium is modeled as a fading channel affected by an impulsive and Gaussian noise. The objective of this paper is to improve robustness and performances of multi-user WSN architecture, based on Discrete Wavelet Transform, under an industrial environment using conventional channel coding and an optimal thresholding receiver.

This work is part of a broader project in the field of wireless sensor networks, in which the wavelet transform is at the core of the transmission functions. Our goal in this paper is to propose a new DWT architecture characterized by a high level of performance and a low cost design. This goal is achieved in particular thanks to the intelligent sharing of hardware resources between the different filters in the DWT algorithm. This paper presents the architectures developped for the first generation Discrete Wavelet Packet Transform (DWPT), based on the Mallat algorithm, and for the second generation DWPT, based on the lifting scheme. These archictures empower us to compute DWPT at high sampling rates (upto 750 Mega-samples per second) while requiring only limited hardware resources and no memory storage between or within the different depth stages of the DWPT / IDWPT (Inverse DWPT) transform.This work is part of a broader project in the field of wireless sensor networks, in which the wavelet transform is at the core of the transmission functions. Our goal in this paper is to propose a new DWT architecture characterized by a high level of performance and a low cost design. This goal is achieved in particular thanks to the intelligent sharing of hardware resources between the different filters in the DWT algorithm. This paper presents the architectures developped for the first generation Discrete Wavelet Packet Transform (DWPT), based on the Mallat algorithm, and for the second generation DWPT, based on the lifting scheme. These archictures empower us to compute DWPT at high sampling rates (upto 750 Mega-samples per second) while requiring only limited hardware resources and no memory storage between or within the different depth stages of the DWPT / IDWPT (Inverse DWPT) transform.

Wireless sensor networks (WSN) are considered as a future main platform in many technologies where they are applied in several fields such as industry, medicine, militaries, environmental monitoring and others. In this paper, we propose a new vision of WSN communication based on a new IDWPT / DWPT transformation architecture. In this context, our efforts are devoted, in the begging, to the development of a reconfigurable functional architecture for WSN in both modes: mono-user and multi-users. The functional architecture is based on inverse discrete wavelet packet transform (IDWPT) in the emitter and discrete wavelet packet transform (DWPT) in the receiver. To improve the performance of the proposed functional model, we have launched many simulations under AWGN noise and with different wavelets. Due to the importance of hardware implementation, in the life of WSN, we have also developed in this work a new hardware architecture of DWPT/ IDWPT. This can provide a throughput, configurable and generic architecture. Where we developed this hardware architecture in VHDL at RTL level and implemented in a NexysVideo board (Artix 7 FPGA). A limited amount of hardware was used to achieve high throughput, achieved by intelligent sharing of hardware resources between the low-pass and high-pass filters in the wavelet packet transformation algorithm. In addition, the proposed model was developed without using memory between or within different depths of DWPT / IDWPT transform.

International audience; In contemporary industry, the wireless technologies trend is growing fast, because it will help to reduce cable cost, deployment time, flexibility, enabling wireless monitoring and control systems, and help to be more environment friendly, a huge research effort is done on wireless sensor networks (WSNs), however there are several issues facing the reliability of these wireless systems such that they can be used properly in harsh noisy or dynamic industrial environments, which led to outline the research direction for industrial wireless sensor networks (IWSNs). This article presents performances of a wavelet modulation and channel coding-based architecture of industrial wireless sensor network under an industrial channel. A model of the industrial channel is described, and performances of error correcting codes compared between multiple combinations of reed Solomon and convolutional codes for multiuser applications.

In last few years, several recent developments concern a new proposed techniques of communication for WSN (Wireless Sensors Network) using a complex methods and technics. This network is considered a future platform for many applications like: medical, agriculture, industrial, monitoring and others. The challenge of this work consists in proposing a new design of transceiver for WSN based on IDWPT (Inverse Discrete Wavelet Packet Transform) in emitter and DWPT (Discrete Wavelet Packet Transform) in receiver for mono and multi users using AWGN Channel. We will propose in this paper, a new concept of impulse radio communication for multiband orthogonal communication for UWB (Ultra-wideband) applications. The main objective of this work is to present a new form of pulse communication adapted to low through-put short-range applications and is scalable according to the type of use but also the number of sensors.

Wireless Sensor Networks (WSNs) are used in several areas such as medicine, multimedia and industry. For the last one, WSNs are used for monitoring and control of industrial equipment. Nevertheless, requirements in the industrial systems differ from the general WSN requirements due to the complex environment propagation. In this work, performance for an architecture of wide-band industrial wireless sensor network under an industrial noisy channel is proposed. Transciever for IWSN is based on IDWPT and DWPT for transmitter and receiver respectively for multi user applications. A model of industrial noise is described and BER performance are presented compared with AWGN channel.

A novel low-cost design of communication architecture based on discrete packet wavelet transform is proposed. However, a lot of characteristics as demand for wireless communication systems like high bit rate, high capacity for objective to integrate a high speed data in several domains: industrial, medicine, militaries, and others. This paper present a novel design of architecture based on Inverse Discrete Packet Wavelet Transform (IDPWT) in transmitter and Discrete Packet Wavelet Transform (DPWT) in receiver for multichannel mode of communications. We are testing also a transceiver/receiver in different situation of noise from white Gaussian to worse case like random pulse noise.