Face aux défis actuels liés à la conception de capteurs d'images à forte résolution comme la limitation de la consommation électrique, l'augmentation du flux de données ainsi que le traitement de données associé, on propose, à travers cette thèse, un capteur d'image novateur asynchrone à échantillonnage non uniforme.Ce capteur d’images asynchrone est basé sur une matrice de pixels événementiels qui intègrent un échantillonnage non uniforme par traversée de niveaux. Contrairement aux imageurs conventionnels, où les pixels sont lus systématiquement lors de chaque trame, les pixels événementiels proposés sont consultés que lorsqu’ils contiennent une information pertinente. Cela induit un flux de données réduit et dépendant de l’image.Pour compléter la chaîne de traitement des pixels, on présente également une architecture numérique de lecture dédiée conçue en utilisant de la logique asynchrone et destinée à contrôler et à gérer le flux de données des pixels événementiels. Ce circuit de lecture numérique permet de surmonter les difficultés classiques rencontrées lors de la gestion des demandes simultanées des pixels événementiels sans dégrader la résolution et le facteur de remplissage du capteur d’images. En outre, le circuit de lecture proposé permet de réduire considérablement les redondances spatiales dans une image ce qui diminue encore le flux de données.Enfin, en combinant l'aspect échantillonnage par traversée de niveau et la technique de lecture proposée, on a pu remplacer la conversion analogique numérique classique de la chaîne de traitement des pixels par une conversion temps-numérique (Time-to-Digital Conversion). En d'autres termes, l'information du pixel est codée par le temps. Il en résulte une diminution accrue de la consommation électrique du système de vision, le convertisseur analogique-numérique étant un des composants les plus consommant du système de lecture des capteurs d'images conventionnels / In order to overcome the challenges associated with the design of high resolution image sensors, we propose, through this thesis, an innovative asynchronous event-driven image sensor based on non-uniform sampling. The proposed image sensor aims the reduction of the data flow and its associated data processing by limiting the activity of our image sensor to the new captured information.The proposed asynchronous image sensor is based on an event-driven pixels that incorporate a non-uniform sampling crossing levels. Unlike conventional imagers, where the pixels are read systematically at each frame, the proposed event-driven pixels are only read when they hold new and relevant information. This induces a reduced and scene dependent data flow.In this thesis, we introduce a complete pixel reading sequence. Beside the event-driven pixel, the proposed reading system is designed using asynchronous logic and adapted to control and manage the flow of data from event pixels. This digital reading system overcomes the traditional difficulties encountered in the management of simultaneous requests for event pixels without degrading the resolution and fill factor of the image sensor. In addition, the proposed reading circuit significantly reduces the spatial redundancy in an image which further reduces the data flow.Finally, by combining the aspect of level crossing sampling and the proposed reading technique, we replaced the conventional analog to digital conversion of the pixel processing chain by a time-to-digital Conversion (TDC). In other words, the pixel information is coded by time. This results in an increased reduction in power consumption of the vision system, the analog-digital converter being one of the most consuming reading system of conventional image sensors components

<p dir="ltr">In the ever-advancing landscape of technology, emerging technologies have emerged as<br>powerful catalysts for innovation across various domains. These technologies, situated at<br>the nexus of the physical and digital realms, hold tremendous potential for revolutionizing<br>industries, improving our quality of life, and addressing global challenges. Central to har-<br>nessing this potential is the efficient exchange of data and the processing of information, a<br>pivotal linchpin that underpins the success of emerging technologies.</p><p dir="ltr"><br>The thesis titled ”Empowering Emerging Technologies through Energy-Efficient Commu-<br>nication and In-Sensor Computing” delves into a critical facet of this technological revolution.<br>It explores the central role of energy-efficient communication and in-sensor computing in un-<br>locking the full potential of emerging technologies. This comprehensive exploration unfolds<br>across three distinct chapters, each addressing an essential aspect of the research undertaken.<br>The first two chapters are dedicated to the realm of wearable technology, where we delve<br>into the intricacies of Human Body Communication (HBC). Chapter 2 meticulously models<br>the human body, focusing on Galvanic excitation and termination, which are fundamental<br>to understanding communication within this unique domain. In Chapter 3, we introduce<br>a novel method employing resonance through the human body to enhance wearable device<br>functionality and efficiency, shedding light on its innovative potential.</p><p dir="ltr"><br>The fourth chapter takes us into the world of machine vision and computer vision, where<br>we unveil an ingenious solution—an ADC-less in-sensor image edge detection scheme. This<br>pioneering approach not only advances the field but also enables enhanced image processing<br>and analysis within sensors, thereby fostering the growth of machine vision applications.<br>This thesis represents a substantial contribution to the fields of HBC and in-sensor com-<br>puting. It models the Galvanic body channel, explores resonance-based power delivery and<br>communication, and demonstrates the importance of in-sensor image edge detection. Fur-<br>thermore, it presents a hardware-based CMOS image sensor capable of real-time edge image<br>extraction, enhancing computational efficiency while reducing latency.<br>As we embark on this intellectual journey, we invite the reader to delve deeper into the<br>realms of emerging technologies, energy-efficient communication, and in-sensor computing.</p><p dir="ltr">By the culmination of this thesis, it is our hope that the insights garnered from this re-<br>search will empower emerging technologies, inspire further innovation, and usher in a more<br>sustainable and technologically empowered future.</p>