La ludification des environnements d’apprentissage humain est une approche de plus en plus utilisée pour répondre au manque de motivation des apprenants. Or, plusieurs résultats de recherche montrent que les apprenants ont des sensibilités différentes face aux mécaniques de jeu qui leur sont proposées. Nos travaux de thèse partent du constat que les systèmes de ludification actuels ne prennent pas en compte la diversité des préférences individuelles. Nous proposons de traiter la problématique de l’adaptation des éléments ludiques aux profils des apprenants suivant leurs caractéristiques en tant que joueurs. Nous nous inspirons d’approches existantes dans le domaine des jeux afin de proposer un modèle générique permettant d’adapter les fonctionnalités ludiques selon les profils de joueur des apprenants. Nos contributions théoriques s’articulent autour de deux grands axes. Premièrement, nous proposons de concevoir les fonctionnalités ludiques comme des épiphytes, des systèmes distincts de l’environnement d’apprentissage qui peuvent être activés indépendamment pour chaque utilisateur. Nous avons construit un framework décrivant ce qu’est une Fonctionnalité Épiphyte Ludique (FEL) adaptative. Il est accompagné d’un guide de conception de fonctionnalités à destination des concepteurs de systèmes ludifiés. Deuxièmement, nous proposons un processus d’adaptation dynamique qui fonctionne suivant deux opérations : la sélection des fonctionnalités d’après le profil de joueur et l’évolution du profil de joueur d’après ses interactions avec les fonctionnalités ludiques. Ces opérations sont basées sur un modèle formalisant les liens entre les fonctionnalités ludiques et les types de joueurs des profils. Nous avons implanté les modèles proposés dans un environnement en ligne d’apprentissage de l’orthographe appelé Projet Voltaire. Selon une approche itérative, nous avons organisé trois expérimentations pour évaluer le système proposé. La première a permis de valider l’implémentation du modèle d’adaptation et du modèle de Fonctionnalité Épiphyte Ludique auprès d’un public de collégiens. Les deux expérimentations suivantes se sont déroulées auprès d’un public adulte avec respectivement 67 et 266 participants. Elles étaient centrées sur l’évaluation du modèle d’adaptation et de son impact sur la motivation des apprenants. Elles ont d’une part montré que le modèle d’adaptation peut s’appuyer sur un jugement d’experts pour faire le lien entre les fonctionnalités et les types de joueurs supportés. D’autre part, les résultats ont validé le fait que proposer aux apprenants des fonctionnalités adaptées à leur profil a un impact positif significatif sur leur motivation et sur leur temps d’utilisation de l’environnement d’apprentissage. / Gamification of learning environments is becoming a widely used approach to address the lack of learner motivation. However, several research results show that learners have different sensitivities to the proposed game mechanics. In our thesis work, we state that the current gamification systems do not take into account the diversity of individual preferences. We propose to address the issue of the adaptation of playful elements to the learners’ profiles according to their characteristics as players. We base our work on existing approaches in the gaming area in order to provide a generic model for the adaptation of gaming features according to the player profile of the learners. Our theoretical contributions are structured around two main axes. Firstly, we propose to design fun features like epiphytes, systems that are distinct from the learning environment and can be activated independently for each user. We built a framework describing what an Epiphytic Gaming Feature (EGF) is. It comes with a gaming features design guide to help the designers of gamification systems. Secondly, we propose a dynamic adaptation process that works in two steps: the selection of gaming features based on the player profile, and the updating of the player profile according to the user’s interactions with the gaming features. These operations are based on a model that formalizes the links between gaming features and player types. We implemented the proposed models in an online learning environment of French spelling called Projet Voltaire. We conducted three experiments to evaluate the proposed system, according to an iterative process. The first experiment was used to validate the implementation of the adaptation model and the Epiphytic Gaming Feature with an audience of middle school students. The following two experiments were conducted with a public of adults, with 67 and 266 participants respectively. They were focused on the evaluation of the adaptation model and its impact on learner motivation. They showed that the adaptation model can be based on expert judgements to make the link between gaming features and player types. Moreover, the results confirmed that providing the learners with gaming features that are adapted to their player profile has a significant positive impact on their motivation and their usage time of the learning environment.

Avec le besoin grandissant pour des modèles d’analyse automatiques de vidéos, le suivi visuel d’objets est devenu une tache primordiale dans le domaine de la vision par ordinateur. Un algorithme de suivi dans un environnement non contraint fait face à de nombreuses difficultés: changements potentiels de la forme de l’objet, du fond, de la luminosité, du mouvement de la camera, et autres. Dans cette configuration, les méthodes classiques de soustraction de fond ne sont pas adaptées, on a besoin de méthodes de détection d’objet plus discriminantes. De plus, la nature de l’objet est a priori inconnue dans les méthodes de tracking génériques. Ainsi, les modèles d’apparence d’objets appris off-ligne ne peuvent être utilisés. L’évolution récente d’algorithmes d’apprentissage robustes a permis le développement de nouvelles méthodes de tracking qui apprennent l’apparence de l’objet de manière en ligne et s’adaptent aux variables contraintes en temps réel. Dans cette thèse, nous démarrons par l’observation que différents algorithmes de suivi ont différentes forces et faiblesses selon l’environnement et le contexte. Afin de surmonter les variables contraintes, nous démontrons que combiner plusieurs modalités et algorithmes peut améliorer considérablement la performance du suivi global dans les environnements non contraints. Plus concrètement, nous introduisant dans un premier temps un nouveau framework de sélection de trackers utilisant un critère de cohérence spatio-temporel. Dans ce framework, plusieurs trackers indépendants sont combinés de manière parallèle, chacun d’entre eux utilisant des features bas niveau basée sur différents aspects visuels complémentaires tel que la couleur, la texture. En sélectionnant de manière récurrente le tracker le plus adaptée à chaque trame, le système global peut switcher rapidement entre les différents tracker selon les changements dans la vidéo. Dans la seconde contribution de la thèse, le contexte de scène est utilisé dans le mécanisme de sélection de tracker. Nous avons conçu des features visuelles, extrait de l’image afin de caractériser les différentes conditions et variations de scène. Un classifieur (réseau de neurones) est appris grâce à ces features de scène dans le but de prédire à chaque instant le tracker qui performera le mieux sous les conditions de scènes données. Ce framework a été étendu et amélioré d’avantage en changeant les trackers individuels et optimisant l’apprentissage. Finalement, nous avons commencé à explorer une perspective intéressante où, au lieu d’utiliser des features conçu manuellement, nous avons utilisé un réseau de neurones convolutif dans le but d’apprendre automatiquement à extraire ces features de scène directement à partir de l’image d’entrée et prédire le tracker le plus adapté. Les méthodes proposées ont été évaluées sur plusieurs benchmarks publiques, et ont démontré que l’utilisation du contexte de scène améliore la performance globale du suivi d’objet. / With the increasing need for automated video analysis, visual object tracking became an important task in computer vision. Object tracking is used in a wide range of applications such as surveillance, human-computer interaction, medical imaging or vehicle navigation. A tracking algorithm in unconstrained environments faces multiple challenges : potential changes in object shape and background, lighting, camera motion, and other adverse acquisition conditions. In this setting, classic methods of background subtraction are inadequate, and more discriminative methods of object detection are needed. Moreover, in generic tracking algorithms, the nature of the object is not known a priori. Thus, off-line learned appearance models for specific types of objects such as faces, or pedestrians can not be used. Further, the recent evolution of powerful machine learning techniques enabled the development of new tracking methods that learn the object appearance in an online manner and adapt to the varying constraints in real time, leading to very robust tracking algorithms that can operate in non-stationary environments to some extent. In this thesis, we start from the observation that different tracking algorithms have different strengths and weaknesses depending on the context. To overcome the varying challenges, we show that combining multiple modalities and tracking algorithms can considerably improve the overall tracking performance in unconstrained environments. More concretely, we first introduced a new tracker selection framework using a spatial and temporal coherence criterion. In this algorithm, multiple independent trackers are combined in a parallel manner, each of them using low-level features based on different complementary visual aspects like colour, texture and shape. By recurrently selecting the most suitable tracker, the overall system can switch rapidly between different tracking algorithms with specific appearance models depending on the changes in the video. In the second contribution, the scene context is introduced to the tracker selection. We designed effective visual features, extracted from the scene context to characterise the different image conditions and variations. At each point in time, a classifier is trained based on these features to predict the tracker that will perform best under the given scene conditions. We further improved this context-based framework and proposed an extended version, where the individual trackers are changed and the classifier training is optimised. Finally, we started exploring one interesting perspective that is the use of a Convolutional Neural Network to automatically learn to extract these scene features directly from the input image and predict the most suitable tracker.

L'estimation de la pose humaine et la reconnaissance des activités humaines sont des étapes importantes dans de nombreuses applications comme la robotique, la surveillance et la sécurité, etc. Actuellement abordées dans le domaine, ces tâches ne sont toujours pas résolues dans des environnements non-coopératifs particulièrement. Ces tâches admettent de divers défis comme l'occlusion, les variations des vêtements, etc. Les méthodes qui exploitent des images de profondeur ont l’avantage concernant les défis liés à l'arrière-plan et à l'apparence, pourtant, l’application est limitée pour des raisons matérielles. Dans un premier temps, nous nous sommes concentrés sur la reconnaissance des actions complexes depuis des vidéos. Pour ceci, nous avons introduit une représentation spatio-temporelle indépendante du point de vue. Plus précisément, nous avons capturé le mouvement de la personne en utilisant un capteur de profondeur et l'avons encodé en 3D pour le représenter. Un descripteur 3D a ensuite été utilisé pour la classification des séquences avec la méthodologie bag-of-words. Pour la deuxième partie, notre objectif était l'estimation de pose articulée, qui est souvent une étape intermédiaire pour la reconnaissance de l'activité. Notre motivation était d'incorporer des informations à partir de capteurs multiples et de les fusionner pour surmonter le problème de l'auto-occlusion. Ainsi, nous avons proposé un modèle de flexible mixtures-of-parts multi-vues inspiré par la méthodologie classique de structure pictural. Nous avons démontré que les contraintes géométriques et les paramètres de cohérence d'apparence sont efficaces pour renforcer la cohérence entre les points de vue, aussi que les paramètres classiques. Finalement, nous avons évalué ces nouvelles méthodes sur des datasets publics, qui vérifie que l'utilisation de représentations indépendantes de la vue et l'intégration d'informations à partir de points de vue multiples améliore la performance pour les tâches ciblées dans le cadre de cette manuscrit. / Estimating human pose and recognizing human activities are important steps in many applications, such as human computer interfaces (HCI), health care, smart conferencing, robotics, security surveillance etc. Despite the ongoing effort in the domain, these tasks remained unsolved in unconstrained and non cooperative environments in particular. Pose estimation and activity recognition face many challenges under these conditions such as occlusion or self occlusion, variations in clothing, background clutter, deformable nature of human body and diversity of human behaviors during activities. Using depth imagery has been a popular solution to address appearance and background related challenges, but it has restricted application area due to its hardware limitations and fails to handle remaining problems. Specifically, we considered action recognition scenarios where the position of the recording device is not fixed, and consequently require a method which is not affected by the viewpoint. As a second prob- lem, we tackled the human pose estimation task in particular settings where multiple visual sensors are available and allowed to collaborate. In this thesis, we addressed these two related problems separately. In the first part, we focused on indoor action recognition from videos and we consider complex ac- tivities. To this end, we explored several methodologies and eventually introduced a 3D spatio-temporal representation for a video sequence that is viewpoint independent. More specifically, we captured the movement of the person over time using depth sensor and we encoded it in 3D to represent the performed action with a single structure. A 3D feature descriptor was employed afterwards to build a codebook and classify the actions with the bag-of-words approach. As for the second part, we concentrated on articulated pose estimation, which is often an intermediate step for activity recognition. Our motivation was to incorporate information from multiple sources and views and fuse them early in the pipeline to overcome the problem of self-occlusion, and eventually obtain robust estimations. To achieve this, we proposed a multi-view flexible mixture of parts model inspired by the classical pictorial structures methodology. In addition to the single-view appearance of the human body and its kinematic priors, we demonstrated that geometrical constraints and appearance- consistency parameters are effective for boosting the coherence between the viewpoints in a multi-view setting. Both methods that we proposed was evaluated on public benchmarks and showed that the use of view-independent representations and integrating information from multiple viewpoints improves the performance of action recognition and pose estimation tasks, respectively.

L’innovation industrielle tend vers des produits de plus en plus complexes de type mécatronique qui combine des domaines pluridisciplinaires. Les processus de conception de ces produits fait appel aux compétences d’acteurs issus des différents métiers et la création des différentes facettes des constituants nécessite l’utilisation d’outils spécialisés; pour autant il n’existe pas de véritable intégration globale au sein du système d'information permettant une gestion intégrée des différents savoir-faire et domaines de compétence malgré la capacité de certains systèmes comme le PLM. Ce travail présente une méthode de résolution générique. L'objet du présent document est de définir une approche globale pour l'intégration des données des systèmes mécatroniques dans un système PLM en utilisant une modélisation spécifique basé sur la caractérisation du cycle de vie et l'utilisation de SysML. Les premiers essais d’implémentation au sein du PLM Windchill, nous ont permis de valider qu’il était possible d’intégrer, avec une structure sémantique, des liens entre des objets métiers pluridisciplinaires. / Industrial innovation aims towards more complex Mecatronics products which combine multidisciplinary domains. The design process of these products leans on several multi-business. The creation of components' facets requires the use of specialized tools. However there is no real global integration within the information system allowing an integrated management of various know-how and fields of expertise, in spite of capabilities certain systems as PLM. This work presents a generic resolution method. The object of this paper is to present a global approach for the integration of Mecatronics systems into a PLM system using a specific modeling. The first implementation tests within Windchill PLM system shows that it was possible to integrate with a semantic structure, links between multidisciplinary business objects.

Graduation theses attends to the problems of the floatation of an e-commerce. The forepart of the work creates theoretical solution, the individual chapters are attended to the introduction of the problems of an e-commerce, floatation and the development of an e-commerce, the advantages and the disadvantages of these activities, marketing and security. The practical part of this work attends to the analyse of electronic background and the aplication of theoretical solutions while the implementation of e-commerce. The part of the practical part is the personal research of public and the proposition of marketing, technical and technological processes. At the close is implemented the valuation of economical impacts on the business of a small firm.

This thesis focuses on the problematics of CRM system solution for the public limited company KONZULTA Brno. It assesses the current condition and proposes effective solutions for the database systems for the company KONZULTA Brno, plc.

Made available in DSpace on 2016-04-18T12:12:29Z (GMT). No. of bitstreams: 4 Monica Mendonca Maria1.pdf: 763444 bytes, checksum: d5fe5f8d60e9e7bd08aecfc0a88b8198 (MD5) Monica Mendonca Maria2.pdf: 1212194 bytes, checksum: b5f0b63d350777866e3955220d604827 (MD5) Monica Mendonca Maria3.pdf: 1656626 bytes, checksum: c2a9d642d2e4d86b7409ce54aabebe89 (MD5) Monica Mendonca Maria4.pdf: 2215429 bytes, checksum: 64893a7cd54a8d0497c2dc13776f74e4 (MD5) Previous issue date: 2009-02-04 / This dissertation presents the technology within BIM and its implication in the architectural and engineering design process. Since the 60 s, aerospace and automotive industries have already revolutionized the way of project with the CAD, and manufacture with the assembly lines. In AEC, the CAD became BIM, a new way of project, build and manage, from conception till life cycle building. This brought a project and construction time reduction, cost and environmental impacts decrease foreseen in LEED and merged in BIM. / Este trabalho objetiva apresentar a tecnologia contida no BIM e suas implicações no processo de projeto da arquitetura e engenharia civil. A partir de 1960, as indústrias, aeronáutica e automotiva, já haviam revolucionado a forma de projetar com o CAD, e de fabricar com as linhas de montagem. Na Arquitetura, Engenharia e Construção, o CAD está evoluindo para o BIM (Building Information Modeling), uma forma de projetar, construir e gerenciar, da concepção ao habite-se, aplicável a todo o ciclo de vida da edificação. Dessa forma houve não só uma redução no tempo de projeto e construção, mas também em custos e impactos ambientais previstos em normas internacionais incorporadas ao BIM.

Les sources de données multimédias provenant de divers domaines (médical, tourisme, commerce, art et culture, etc.) sont devenues incontournables sur le web. L’accès à ces sources multimédias dans les systèmes distribués pose de nouveaux problèmes en raison de nombreux paramètres : volumétrie, diversité des interfaces, format de représentation, localisation, etc. En outre, l’exigence de plus en plus forte des utilisateurs et des applications à vouloir intégrer la sémantique dans la recherche d’information pose de nouvelles questions à résoudre. Pour prendre en compte cette nouvelle complexité, nous nous intéressons dans notre travail de recherche aux solutions d’intégration de données basées sur les services web. Dans cette thèse, nous proposons une approche orientée service pour la recherche sémantique de contenus multimédia. Nous avons appelé cette approche SeSaM (Semantic Search of Multimedia content). SeSaM repose sur la définition d’un nouveau type de services accédant aux contenus multimédias, qui est les services MaaS (Multimedia as a Services). Elle est basée sur un processus en deux phases : description et découverte des services MaaS. En ce qui concerne la description de services MaaS, nous avons défini le langage SA4MaaS (Semantic Annotation for MaaS services), qui est une extension de SAWSDL (recommandation W3C). L’idée principale de ce langage est l’intégration, en plus de la sémantique métier, de la sémantique de l’information multimédia dans la description des services MaaS. En ce qui concerne la découverte de services MaaS, nous avons proposé un nouveau matchmaker MaaS-MX (MaaS services Matchmaker) adapté au modèle de description des MaaS. MaaS-MX est composé de deux étapes primordiales : appariement métier et appariement multimédia. L’appariement métier consiste à comparer la description métier des services et de la requête, tandis que l’appariement multimédia compare la description multimédia des services et de la requête. L’approche a été prototypée et évaluée dans deux domaines différents : médical et tourisme. Les résultats indiquent que l’utilisation de l’appariement métier et l’appariement multimédia a considérablement amélioré les performances des systèmes de recherche de données multimédias. / Multimedia data sources from various fields (medical, tourism, trade, art and culture, etc.) became essential on the web. Accessing to multimedia data in distributed systems poses new challenges due to many system parameters: volume, diversity of interfaces, representation format, location, etc. In addition, the growing needs of users and applications to incorporate semantics in the information retrieval pose new issues. To take into account this new complexity, we are interested in our research of data integration solutions based on web services. In this thesis, we propose an approach-oriented service for the semantic search of multimedia content. We called this approach SeSaM (Semantic Search of Multimedia content). SeSaM is based on the definition of a new pattern of services to access multimedia content, which is the MaaS services (Multimedia as a Services). It is based on a two-phase process: description and discovery of MaaS services. As for the MaaS services description, we have defined the SA4MaaS language (Semantic Annotation for MaaS services), which is an extension of SAWSDL (W3C recommendation). The main idea of this language is the integration, in addition to business domain semantic, of multimedia information semantics in the MaaS services description. As for the MaaS service discovery, we have proposed a new matchmaker MaaS-MX (MaaS services Matchmaker) adapted to the MaaS services description model. MaaS-MX is composed of two essential steps: domain matching and multimedia matching. Domain matching consists in comparing the business domain description of MaaS services and the query, whereas multimedia matching compares the multimedia description of MaaS services and the query. The approach has been implemented and evaluated in two different domains: medical and tourism. The results indicate that using both domain and multimedia matching considerably improves the performance of multimedia data retrieving systems.

Made available in DSpace on 2016-04-04T18:31:31Z (GMT). No. of bitstreams: 1 Ana Cristina Pereira de P Assolari.pdf: 1062992 bytes, checksum: 86b8f894fb835cd2496911a4689155b6 (MD5) Previous issue date: 2011-02-11 / IT and Telecommunication Managers need to be on top of rnarket trends so they rnay proceed to necessary changes and improvement on their network in order to keep up with business challenges and ensure the future of the cornpany, The decision making related to network migration should not be rnade without a consistent and reliable method that would support the decision taken, protecting the managers and companies from risks and losses. This paper has the objective to propose the usage of multicriteria decision making methodology, with focus on the MACBETH method in arder to support the network migration, based on information extracted from the financiai reports published on the public internet. This paper will show the study of two companies that have m igrated to MPLS in the last five years, buildlng the MACBETH Model from information present on the Financiai Report at the time of contract was signed and validating the information extracted with executives from the commercial and technical departments who lived through that period in the company. Within this scenario it can be verified that MACBETH Method once provided with the correct information that reflects the period the cornpany is living rnay help executives to decide if they should migrate ar not migrate their network / Gestores de telecomunica??es e TI precisam estar sempre atentos aos rumos da organiza??o e com isso procederem a mudan?as necess?rias nas estruturas e redes de comunica??o que subsidiam os neg?cios da empresa. A tomada de decis?o a respeito da migra??o de tecnologias n?o dever ser efetuada sem um m?todo consistente que as subsidie, livrando o gestor de riscos e preju?zos empresariais que podem ser minjmizados quando uma abordagem estruturada elencando os principais crit?rios a serem considerados ? utilizada. Este trabalho tem como objetivo propor o uso de metodologia para tomada de decis?o multicrit?rio, com foco no m?todo MACBETH, para subsidiar a migra??o de plataformas de redes de telecomunica??es. Com base em informa??es oriundas de boletins financeiros disponibilizados publicamente na Internet. O trabalho analisa duas empresas que migraram para plataforma MPLS, construindo a estrutura do m?todo MACBETH a partir das informa??es obtidas nos boletins financeiros dessas organiza??es e validando a an?lise com dados obtidos de gerentes das ?reas comerciais e de tecnologias que vivenciaram esse per?odo. Dentro desse quadro, considerou-se que o m?todo MACBETH, uma vez alimentado com informa??es corretas que reflitam o momento da empresa, pode orientar gestores a decidirem se devem ou n?o proceder ? migra??o de suas bases tecnol?gicas

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Att, Secretaria de Registro on 2011-12-28T12:09:43Z (GMT) / Submitted by Regiane Relva Romano (regiane@vip-systems.com.br) on 2012-01-04T01:31:23Z No. of bitstreams: 1 Tese Regiane Relva Romano - Versao Final Entregue.pdf: 4264628 bytes, checksum: 5cde922f780d99b751abbf306d16f982 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2012-01-04T11:12:52Z (GMT) No. of bitstreams: 1 Tese Regiane Relva Romano - Versao Final Entregue.pdf: 4264628 bytes, checksum: 5cde922f780d99b751abbf306d16f982 (MD5) / Made available in DSpace on 2012-01-04T11:16:03Z (GMT). No. of bitstreams: 1 Tese Regiane Relva Romano - Versao Final Entregue.pdf: 4264628 bytes, checksum: 5cde922f780d99b751abbf306d16f982 (MD5) Previous issue date: 2011-12-09 / Este trabalho objetivou identificar as principais tecnologias disponíveis de TI (Tecnologia da Informação) e de AIDC (Identificação e Captura Automática de Dados) para a área de varejo de autosserviço, para preencher a lacuna existente na literatura, sobre os benefícios de se usar novas tecnologias no ponto de venda, com vistas a otimizar sua operação. Para tanto, foram estudados os principais processos operacionais de uma loja de varejo de autosserviço, com vistas a identificar como as Tecnologias da Informação (TI) e de Identificação e Captura Automática de Dados (AIDC), poderiam ajudar a melhorar os resultados operacionais e agregar valor ao negócio. Para analisar suas proposições (de que o uso de TI e de AIDC podem ajudar na: redução dos tempos dos processos de retaguarda; redução do número de operações no ponto de venda; prevenção de perdas; redução dos custos e dos tempos para a realização dos inventários; redução do número de funcionários nas lojas; redução do tempo de fila no caixa; redução de rupturas e no aumento da eficiência operacional da loja), foram pesquisados diversos estudos de casos mundiais de empresas do segmento de varejo, que implementaram as tecnologias de AIDC e TI, principalmente a de RFID, para saber quais foram os impactos do uso destas tecnologias em suas operações e, em seguida, foi desenvolvido um Estudo de Caso abrangente, por meio do qual se objetivou entender os benefícios empresariais reais do uso destas tecnologias para o varejo de autosserviço. Como resultado final, foi possível identificar as mudanças nos processos operacionais do varejo de autosserviço, bem como os benefícios gerados em termos de custo, produtividade, qualidade, flexibilidade e inovação. O trabalho também evidenciou os pontos críticos de sucesso para a implementação da TI e das AIDC no varejo, que são: a revisão dos processos operacionais; a correta definição do hardware; dos insumos; do software; das interferências do ambiente físico; da disponibilização dos dados/informações dos produtos; das pessoas/funcionários e dos parceiros de negócios/fornecedores. De maneira mais específica, este trabalho buscou contribuir para o enriquecimento do campo de estudos no segmento de varejo e para o uso da tecnologia da informação, no Brasil, já que o assunto sobre o uso e o impacto de novas tecnologias no ponto de vendas, ainda permanece pouco explorado academicamente. / This study sought to identify the main IT technologies available for the AIDC and retail self-service area, to fill the gap in the literature about the real advantages of using new technologies at the point of sale, in order to optimize its operation. In order to do this, we studied the main operational processes of a self-service retail store bearing in mind to identify how the technologies of Automatic Identification and Data Capture and IT could help to improve the operating results and add value to the business. To analyze these proposals we have surveyed several global case studies of retail companies, which implemented the AIDC and IT technologies to investigate what were the impacts of using these technologies in their operations and then designed a comprehensive and innovative Case Study, through which we sought to understand the real business benefits. As a final result, it was possible to identify the changes and the benefits in terms of cost, productivity, quality, flexibility and innovation. The work also highlighted the critical points of success for the implementation of AIDC and IT Retail, which are: the review of operating processes, the correct definition of the hardware; inputs; software; interferences of the physical environment, the availability of data / information of products, of people / employees and of business partners / suppliers. More specifically, this study sought to contribute to the enrichment of the field studies in the retail segment and for the use of information technology in Brazil, since the issue on the use and impact of new technologies at the point of sales, still remains unexplored academically.