Relevant bibliographies by topics / Infrastructure intelligente

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Infrastructure intelligente'

Author: Grafiati
Published: 26 April 2025

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Journal articles on the topic "Infrastructure intelligente"

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Zhu, Guangyu, Fuquan Zhao, Haokun Song, and Zongwei Liu. "Cost Analysis of Vehicle-Road Cooperative Intelligence Solutions for High-Level Autonomous Driving: A Beijing Case Study." Journal of Advanced Transportation 2024 (January 23, 2024): 1–22. http://dx.doi.org/10.1155/2024/6170743.

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The development of the vehicle-road cooperative intelligence can effectively resolve the current technical impediment and cost quandary associated with high-level autonomous driving. Nevertheless, the intelligent infrastructure entails initial deployment costs and ongoing energy consumption and maintenance costs, necessitating a comprehensive and quantitative analysis of the costs of intelligent infrastructure and the corresponding changes in comprehensive costs. The cost evaluation model for the cooperative intelligent system is designed in this paper, considering the corresponding intelligent infrastructure layout scheme for different road types within the technical framework. The intelligent configuration and corresponding cost transfer from roadside to vehicle side under the synergy effect is also analyzed. Using Beijing as a case study, the results indicate that the deployment of intelligent infrastructure will effectively reduce acquisition and usage costs of high-level intelligent vehicles and achieve a greater “reuse” effect by serving more intelligent connected vehicles (ICVs). Compared to the vehicle intelligence, collaborative intelligence will reduce cumulative total costs by more than ¥200 billion from 2023 to 2050, even with the inclusion of intelligent infrastructure’s costs.
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Rahman, Mir Mehedi, Bishwo Prakash Pokharel, Sayed Abu Sayeed, Sujan Kumar Bhowmik, Naresh Kshetri, and Nafiz Eashrak. "riskAIchain: AI-Driven IT Infrastructure—Blockchain-Backed Approach for Enhanced Risk Management." Risks 12, no. 12 (December 19, 2024): 206. https://doi.org/10.3390/risks12120206.

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In the evolving landscape of cybersecurity, traditional information technology (IT) infrastructures often struggle to meet the demands of modern risk management frameworks, which require enhanced security, scalability, and analytical capabilities. This paper proposes a novel artificial intelligence (AI)–driven IT infrastructure backed by blockchain technology, specifically designed to optimize risk management processes in diverse organizational environments. By leveraging artificial intelligence for predictive analytics, anomaly detection, and data-driven decision-making, combined with blockchain’s secure and immutable ledger for data integrity and transparency, the proposed infrastructure offers a robust solution to existing challenges in risk management. The infrastructure is adaptable and scalable to support a variety of risk management methodologies, providing a more secure, efficient, and intelligent system. The findings highlight significant improvements in the accuracy, speed, and reliability of risk management, underscoring the infrastructure’s capability to proactively address emerging cyber threats. To ensure the proposed model effectively addresses the most critical issues, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique will be used to analyze and evaluate the interrelationships among the existing critical factors. This approach evaluates the interrelationships and impacts of these factors, verifying the model’s comprehensiveness in managing organizational risk. This study lays the foundation for future research aimed at refining AI-driven infrastructures and exploring their broader applications in enhancing organizational cybersecurity.
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Venkatesh Kata. "Intelligent cloud automation: Leveraging AI and machine learning for enhanced cloud management." World Journal of Advanced Research and Reviews 26, no. 1 (April 30, 2025): 295–301. https://doi.org/10.30574/wjarr.2025.26.1.1094.

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Artificial Intelligence and Machine Learning are fundamentally transforming cloud computing infrastructure, introducing unprecedented capabilities for intelligent, adaptive, and autonomous system management. This article delves into the profound technological metamorphosis occurring in computational ecosystems, highlighting the transition from static, predetermined infrastructure models to dynamic, self-optimizing environments. Intelligent cloud automation represents a revolutionary paradigm that enables predictive maintenance, sophisticated resource allocation, and autonomous problem resolution. By integrating advanced machine learning algorithms, quantum computing principles, and probabilistic computational models, cloud infrastructures can now anticipate, respond, and optimize themselves with minimal human intervention. The article illuminates the complex technological landscape where neural network architectures, reinforcement learning, and anomaly detection systems converge to create intelligent computational platforms that transcend traditional management approaches.
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Zhang, Jiayi. "Digital Infrastructure and Corporate Intelligence." Advances in Economics, Management and Political Sciences 175, no. 1 (April 10, 2025): 142–51. https://doi.org/10.54254/2754-1169/2025.21987.

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With continuous progress in information technology, the construction of digital infrastructure has become a key force in promoting corporate intelligence. This study in-depth explores and analyzes the mechanism by which digital infrastructure promotes the intelligent transformation of enterprises. The research finds that digital infrastructure significantly promotes the intelligence of enterprises, and technology spillover, talent cultivation, and market orientation significantly enhance the positive effect of digital infrastructure on corporate intelligence. The research conclusion points out that digital infrastructure is the cornerstone for enterprises to explore the potential of intelligence. Enterprises should actively embrace digital transformation and inject strong momentum into the intelligent transformation of enterprises through formulating forward-looking technical strategies and upgrading plans. Looking to the future, the deep integration of digital infrastructure and corporate intelligence will drive the innovation of the entire economic ecosystem and have a profound impact on the sustainable development of enterprises and the competitive pattern of the industry.
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Sherrill, John T., and Michael J. Salvo. "Automated infrastructures." Communication Design Quarterly 10, no. 2 (July 2022): 22–31. http://dx.doi.org/10.1145/3507857.3507860.

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As artificial intelligence (AI) automates technical and dialogic processes, technical communicators produce value through articulating complex problems, facilitating new forms of participation, and managing user-generated content via experience architecture. Automated and intelligent agents are least able to grasp the context of experiences, requiring human input/feedback for maximum performance. The examples we trace both prepare communities to embrace AI as part of the available information infrastructure and create an automated infrastructure of intelligent augmented action. Following Star's anthropological investigation of infrastructure, we analyze organizational examples where rhetoric entangles AI, automation, generative design, additive manufacturing, gift labor, and assembly lines.
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Spragins, J. "Converging Infrastructures: Intelligent Transportation and the National Information Infrastructure [New Books]." IEEE Network 10, no. 6 (November 1996): 3. http://dx.doi.org/10.1109/mnet.1996.546348.

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Liu, Zongwei, Haokun Song, Hong Tan, Han Hao, and Fuquan Zhao. "Evaluation of the Cost of Intelligent Upgrades of Transportation Infrastructure for Intelligent Connected Vehicles." Journal of Advanced Transportation 2022 (January 18, 2022): 1–15. http://dx.doi.org/10.1155/2022/5841373.

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Intelligent connected vehicles (ICVs) have become the focus and development direction of the automobile industry. As a flexible intelligent terminal, ICVs will become a necessary part of the intelligent transportation system. The routes of developing ICVs based on “vehicle to X” (V2X) can effectively alleviate the demands of vehicles for intelligent functions and cut related research costs, accelerating commercialization of ICVs and leading to many social benefits. At present, China has made it clear to develop ICVs based on V2X, which requires simultaneous intelligent upgrades of vehicles and transportation infrastructure. Therefore, intelligent upgrades of transportation infrastructure must match the functional requirements of ICVs. In addition, the investment in intelligent upgrades of transportation infrastructure is mainly from the government, so the costs must be controlled reasonably to find the most cost-effective upgrade route. In this paper, the types of intelligent transportation infrastructures were determined by sorting out the demands of ICVs for transportation infrastructure, and the deployment methods and upgrade routes of intelligent transportation infrastructures were designed. Then, the cost evaluation model for intelligent upgrade of transportation infrastructures was established, based on which, the cost evaluation of different intelligent upgrade routes of transportation infrastructure was carried out in closed highway and open urban road scenarios to determine the optimal route. Besides, the key elements affecting the cost of transportation infrastructure upgrades were identified, and their impact degrees on transportation infrastructure upgraded were analyzed by scenario analysis. The results show that the intelligent transportation infrastructure for advanced ICVs mainly includes communication base stations, roadside units (RSUs), vision sensors, millimeter-wave radars, laser radars (LiDARs), meteorological sensors, intelligent signal machines, edge computing servers, and cloud computing centers. The route of deploying primary intelligent transportation infrastructure at first and then directly upgrading them to advanced level can well match the functional requirements of ICVs on the basis of lower costs. The costs of RSUs, LIDARS, and edge computing servers as well as data transmission rate of 5G are key elements affecting the costs of intelligent upgrades of transportation infrastructure.
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VASYLKIVSKYI, Mikola, Ganna VARGATYUK, and Olga BOLDYREVA. "INTELLIGENT RADIO INTERFACE WITH THE SUPPORT OF ARTIFICIAL INTELLIGENCE." Herald of Khmelnytskyi National University. Technical sciences 217, no. 1 (February 23, 2023): 26–32. http://dx.doi.org/10.31891/2307-5732-2023-317-1-26-32.

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The peculiarities of the implementation of the 6G intelligent radio interface infrastructure, which will use an individual configuration for each individual subscriber application and flexible services with lower overhead costs, have been studied. A personalized infrastructure consisting of an AI-enabled intelligent physical layer, an intelligent MAC controller, and an intelligent protocol is considered, followed by a potentially novel AI-based end-to-end (E2E) device. The intelligent controller is investigated, in particular the intelligent functions at the MAC level, which may become key components of the intelligent controller in the future. The joint optimization of these components, which will provide better system performance, is considered. It was determined that instead of using a complex mathematical method of optimization, it is possible to use machine learning, which has less complexity and can adapt to network conditions. A 6G radio interface design based on a combination of model-driven and data-driven artificial intelligence is investigated and is expected to provide customized radio interface optimization from pre-configuration to self-learning. The specifics of configuring the network scheme and transmission parameters at the level of subscriber equipment and services using a personalized radio interface to maximize the individual user experience without compromising the throughput of the system as a whole are determined. Artificial intelligence is considered, which will be a built-in function of the radio interface that creates an intelligent physical layer and is responsible for MAC access control, network management optimization (such as load balancing and power saving), replacing some non-linear or non-convex algorithms in receiver modules or compensation of shortcomings in non-linear models. Built-in intelligence has been studied, which will make the 6G physical layer more advanced and efficient, facilitate the optimization of structural elements of the physical layer and procedural design, including the possible change of the receiver architecture, will help implement new detection and positioning capabilities, which, in turn, will significantly affect the design of radio interface components. The requirements for the 6G network are defined, which provide for the creation of a single network with scanning and communication functions, which must be integrated into a single structure at the stage of radio interface design. The specifics of carefully designing a communication and scanning network that will offer full scanning capabilities and more fully meet all key performance indicators in the communications industry are explored.
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Hu, Limingyue, Jingjing Wu, Xiang Li, Bingyi Li, Huiyu Shan, and Ranran Zhang. "Intelligent transport construction solutions in the form of new infrastructure." Highlights in Business, Economics and Management 47 (February 8, 2025): 244–50. https://doi.org/10.54097/gqa4g367.

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With the advent of the new infrastructure era, new infrastructures such as 5G, AI, BeiDou Navigation and IOT will bring great changes to the transport industry, driving it towards intelligence and digitalization. As an important part of the development of new infrastructure, the transport industry has become a key factor in driving the country towards ecology, digitalization, intelligence, high speed, transformation of old and new dynamics and symmetrical economic structure. Smart light poles are an important part of smart city construction, combining multiple functions in one, including small base stations, video surveillance, LED information screens, environmental sensors, IP broadcasting sound poles and charging posts. This new type of information infrastructure can provide accurate data services for urban governance through edge-cloud collaboration, and provide low-latency support for multi-scene linkage. In the new situation, the study of how to plan and build intelligent traffic light poles is an important part of the transport industry's contribution to the national information development strategy, and is a new topic of great significance for the transport industry's research.
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Braga, Vasili. "DECENTRALISED AUTONOMOUS SOCIETY THROUGH LARGE LANGUAGE MODELS’ BASED AGENTS: A PATHWAY TO EMPOWER SMALL COMMUNITIES." Journal of Engineering Science 30, no. 3 (November 2, 2023): 99–120. http://dx.doi.org/10.52326/jes.utm.2023.30(3).07.

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This paper explores the concept of Decentralized Autonomous Society through the lens of Large Language Models focusing on the transformative potential of integrating these technologies. The paper on the role of Large Language Models based agents in providing a versatile, responsive, and contextually intelligent resource within a Decentralized Autonomous Society, fostering intellectual exploration, assisting in complex tasks, and aiding real-time problem solving. One delves into their integration with Decentralized Autonomous Society infrastructures, including robotic and automated systems. While promising, the integration of Large Language Models and their agents into a Decentralized Autonomous Society poses several challenges, including infrastructure and connectivity limitations, information accuracy, artificial intelligence bias, privacy and data security, and ethical concerns. This paper critically discusses these issues and proposes potential solutions. Through the lens of the Decentralized Autonomous Society construct, the paper considers the future possibilities and implications of artificial intelligence, where self-sustaining, digitally-empowered communities leverage artificial intelligence as a cornerstone of their collective intelligence.
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Dissertations / Theses on the topic "Infrastructure intelligente"

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Marquet, Clément. "Binaire béton : Quand les infrastructures numériques aménagent la ville." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT036.

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Comment la ville est-elle aménagée par et avec les technologies numériques ? Pour répondre à cette question, la thèse analyse dans un même mouvement les conséquences urbaines des infrastructures informationnelles et physiques du numérique. Elle mobilise pour cela les cadres méthodologiques et analytiques des Infrastructures Studies, de la sociologie des techniques et de l’innovation et de la sociologie des problèmes publics. D’un point de vue empirique, elle propose de faire un pas de côté vis-à-vis des grandes expérimentations médiatisées de la « ville intelligente » pour étudier des transformations plus diffuses, quotidiennes, générées par les technologies numériques. Elle se compose ainsi de deux études de cas : d’une part, elle suit un programme de développement de services connectés destinés à améliorer l’accessibilité d’un réseau de transport francilien pour les personnes à mobilité réduite, d’autre part, elle analyse l’implantation discrète de nombreux data centers à Plaine Commune, au nord de la métropole parisienne, et les troubles qui s’en sont suivis localement. Le travail d’enquête articule plusieurs observations participantes, une quarantaine d’entretiens, une revue de presse ainsi que l’analyse de documents internes aux organisations. La thèse montre comment la logique d’instantanéité, de « temps réel », généralement au centre des promesses associées à la ville numérique, réclame une disponibilité accrue des travailleur.se.s, des données et des serveurs. Ainsi, dans l’entreprise de transport, les projets d’amélioration du service voyageur par l’intermédiaire des smartphones confrontent les agents de gare au double impératif de la relation face à face et des alertes du périphérique connecté. Les données cartographiques sur lesquelles reposent les services connectés, souvent prises pour acquises, nécessitent aux organisations d’inventer des collaborations inédites pour assurer leur production et leur maintenance. Les serveurs nécessaires au fonctionnement de la société numérique sont accumulés, protégés et entretenus dans des data centers, imposants bâtiments qui se concentrent géographiquement, bouleversent les environnements où ils s’implantent, décontenancent les élu.e.s et dérangent les riverain.e.s. La logique de temps réel pèse ainsi sur l’organisation sociale et spatiale des villes, et invite à repenser le développement urbain des infrastructures numériques en termes de travail, de maintenance et d’environnement – à la différence de ceux, plus couramment mobilisés, d’imaginaires sociotechniques, de promesses d’optimisation et des modèles urbains
How is the city developed by and with digital technologies? To answer this question, the thesis analyses in a single movement the urban consequences of the information and physical infrastructures of digital technology. To this end, it mobilizes the methodological and analytical frameworks of Infrastructure Studies, the sociology of techniques and innovation and the sociology of public problems. From an empirical point of view, it proposes to take a step back from the major mediatized experiments of the "smart city" to study more diffuse, everyday transformations generated by digital technologies. It consists of two case studies: on the one hand, it follows a programme to develop connected services to improve the accessibility of a Paris Region transport network for people with reduced mobility, and on the other hand, it analyses the discreet establishment of numerous data centres in Plaine Commune, in the north of the Parisian metropolitan area, and the resulting local unrest. The fieldwork includes several participating observations, about 40 interviews, a press review and the analysis of internal documents of the organizations. The thesis shows how the logic of immediacy, of "real time", generally at the centre of the promises associated with the digital city, requires an increased availability of workers, data and servers. Thus, in the transport company, projects to improve passenger service via smartphones confront station agents with the dual imperative of the face-to-face relationship and the alerts of the connected device. The cartographic data on which connected services are based, often taken for granted, require organizations to invent new collaborations to ensure their production and maintenance. The servers necessary for the functioning of the digital society are accumulated, protected and maintained in data centres, imposing buildings that are geographically concentrated, disrupt the environments in which they are located, disconcert elected officials and disturb residents. The logic of real time thus weighs on the social and spatial organization of cities, and invites us to rethink the urban development of digital infrastructures in terms of work, maintenance and the environment - unlike those, more commonly mobilized, of socio-technical imaginaries, promises of optimization and urban models
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Bouallaga, Anouar. "Gestion énergétique d’une infrastructure de charge intelligente de véhicules électriques dans un réseau de distribution intégrant des énergies renouvelables." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10043/document.

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La crise énergétique et environnementale ont promu le gouvernement à prendre des mesures vigoureuses pour stimuler la transition énergétique et accélérer la croissance verte. Dans cette politique, les véhicules électriques (VE) constituent à terme une réelle réponse aux problématiques actuelles. Leur insertion dans le système électrique a poussé l’ensemble des acteurs et notamment les gestionnaires de réseaux de distribution à privilégier une modernisation des réseaux électriques. Assimilée à la thématique des Smart Grids, la thèse vise à apporter des éléments de réflexion au concept de la gestion de la demande appliquée aux VE. La première partie de ce travail expose une méthodologie d’évaluation de l’impact technico-économique des VE sur les réseaux de distribution HTA/BTA. Ensuite, pour soulever cette problématique, une prospection des services du pilotage de charge orientés réseaux et marché est menée en deuxième partie. Une démarche d’analyse des pistes de valorisation a permis de dégager les services à forte contribution économique. A ce titre, une méthodologie de conception de stratégies de supervision optimisées est proposée. Son application a permis de tirer des conclusions sur la valorisation financière et environnementale des effacements de charges de VE. Les résultats de simulation sont employés pour une étude de rentabilité technico-économique. Ensuite, le comportement des réseaux de distribution face aux algorithmes de supervision est étudié par une approche de co-simulation. Enfin, les principes Smart Grids sont analysés et validés via des expérimentations réalisées sur un démonstrateur hybride interfaçant un simulateur temps réel avec du matériel physique
Energy and environmental crisis have prompted the government to take strong measures to stimulate energy transition and accelerate green growth. In this context, electric vehicles (EVs) are considered as a real solution to deal with the current problems. Their integration into the electrical system promotes distribution system operators to develop smart solutions in this field. Concerning the Smart Grids concept, the present work aims to provide answers to a wide range of questions for demand side management program using plug-in EVs charging strategies. The first section of this PhD project, presents a methodology to assess technical and economic impacts of EVs charging on Medium and Low voltage distribution networks. Afterwards, analyses about the competitive EVs load management ancillary services are conducted in the third chapter. By comparing potential and opportunities of each ones, three ancillary services for electricity market contribution were selected. In this context, a methodology for designing energy management strategies is proposed. The latter is applied to the selected ancillary services to assess the financial contribution of the developed strategies. Environmental aspects and Wind-to-Vehicle concept are also evaluated. Furthermore, thanks to a co-simulation interface, the interactions between supervision strategies and real distribution networks are analyzed. The last section presents a Hardware-in-the-loop demonstrator using a real time simulator, smart meters and EVs charging stations. Through experiments, communication constraints and Smart Grids principles are evaluated and validated
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Shil, Manash. "Designing and simulating a Car2X communication system using the example of an intelligent traffic sign." Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-161679.

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The thesis with the title “Designing and simulating a Car2X communication system using the example of an intelligent traffic sign” has been done in Chemnitz University of Technology in the faculty of Computer Science. The purpose of this thesis is to define a layered architecture for Infrastructure to Vehicle (I2V) communication and the implementation of a sample intelligent traffic sign (variable speed limit) application for a Car2X communication system. The layered architecture of this thesis is defined based on three related projects. The application is implemented using the defined layered architecture. Considering the availability of hardware, the implementation is done using the network simulator OMNET++. To check the feasibility of the application three scenarios are created and integrated with the application. The evaluation is done based on the result log files of the simulation which show that the achieved results conform with the expected results, except some minor limitations.
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Zurawski, Maciej. "An infrastructure mechanism for dynamic ontology-based knowledge infrastructures." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/3291.

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Both semantic web applications and individuals are in need of knowledge infrastructures that can be used in dynamic and distributed environments where autonomous entities create knowledge and build their own view of a domain. The prevailing view today is that the process of ontology evolution is difficult to monitor and control, so few efforts have been made to support such a controlled process formally involving several ontologies. The new paradigm we propose is to use an infrastructure mechanism that processes ontology change proposals from autonomous entities while maintaining user-defined consistency between the ontologies of these entities. This makes so called semantic autonomy possible. A core invention of our approach is to formalise consistency constraints as so called spheres of consistency that define 1) knowledge regions within which consistency is maintained and 2) a variable degree of proof-bounded consistency within these regions. Our infrastructure formalism defines a protocol and its computational semantics, as well as a model theory and proof theory for the reasoning layer of the mechanism. The conclusion of this thesis is that this new paradigm is possible and beneficial, assuming that the knowledge representation is kept simple, the ontology evolution operations are kept simple and one proposal is processed at a time.
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Haque, Mesbah 1972. "Intelligent parking management infrastructure design." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/8032.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.
Includes bibliographical references (leaf 71).
This thesis discusses the different components required to build and design a prototype for the Intelligent Parking Management (IPM) infrastructure. Different aspects of the hardware and software components used to build the prototype is also discussed in the thesis along with discussion of business and marketing strategies for the viability of the solution for commercial use. A prototype solution was built using hardware and software components. The prototype was tested for real-time parking meter availability information for both general web customers and smart device users such as PDA with wireless access and Smart Phone mobile devices using 3G technologies. The tests were conducted in a controlled environment with simulation data for real parking meters. The IPM prototype solution infrastructure built was able to provide real-time parking information. The information was accessible via the Internet through standard browsers and 3G enable Smart Phones. The integration between the hardware and software components and the IPM infrastructure design prototype was enabled through various technologies such as Microsoft .NET platform, Microsoft SQL Server 2000, Microsoft Mobile Internet toolkit, DTS, ASP.NET and ADO.NET. The thesis discusses these technologies and their interconnectivity within the IPM infrastructure.
by Mesbah Haque.
M.Eng.
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Gray, Matthew Konefal. "Infrastructure for an intelligent kitchen." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/61540.

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Thesis (S.M.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1999.
Includes bibliographical references (leaves 66-67).
In a world of growing numbers of "things that think", a software infrastructure for managing complex systems of these things is a necessity. This paper presents such a software system, Hive. Hive is a decentralized distributed mobile agents platform, addressing the requirements of a infrastructure for "things that think". Hive addresses the need for ways to manage highly heterogeneous sets of devices, methods for describing and discovering resources, and an approach toward constructing applications. To effectively evaluate this architecture, the particular testbed of a networked kitchen is examined. The kitchen provides a dynamic and compelling application domain to explore the Hive system. The kitchen described in this paper is capable of assisting a user in the preparation of recipes, through use of a variety of sensing and actuation technologies. In addition to the kitchen, a number of other Hive-based systems are discussed, including a networked jukebox and a localization infrastructure for wearables. Hive is evaluated in the context of the networked kitchen and these other applications. Hive is compared to other distributed software systems, in particular Jini. Finally, areas for future work are suggested, in both the Hive infrastructure and the networked kitchen application.
by Matthew Konefal Gray.
S.M.
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Eberhart, Andreas. "Ontology-based infrastructure for intelligent applications." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=972319662.

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Liu, Zihuai. "Artificial intelligence infrastructure into material attributes insights." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126909.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 57-60).
The development of a biopharmaceutical manufacturing process involves an assessment of all possible sources of variation throughout each of the unit operations in the drive toward six sigma manufacturing. The primary goal of this project is to develop a novel way to assess the variation in raw materials attributes throughout the life-cycle of the material and gain insights about the correlation between material variation to process performance and product quality. This thesis focuses on understanding the impact raw materials have on unit operations within biopharmaceutical manufacturing processes through machine learning techniques. To evaluate the impact of raw material attributes on process performance and exclude the variations explained by process operating parameters, a modeling framework is developed and tested. The framework contains three steps: (1) fitting models with only process operating data, (2) fitting models with process operating data and batch number information, (3) fitting models with process operating and raw material attributes data. By comparing the performance measurements from 3 different models, insights of correlations between raw materials and process outcomes could be obtained.
by Zihuai Liu.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
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Fleet, Charles O'Bryan 1977. "Candidate system architecture for intelligent itegrated infrastructure." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/80931.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.
Includes bibliographical references (leaves 41-42).
by Charles O'Bryan Fleet.
M.Eng.
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Dadashi, Nastaran. "Human factors of future rail intelligent infrastructure." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/13157/.

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The introduction of highly reliable sensors and remote condition monitoring equipment will change the form and functionality of maintenance and engineering systems within many infrastructure sectors. Process, transport and infrastructure companies are increasingly looking to intelligent infrastructure to increase reliability and decrease costs in the future, but such systems will present many new (and some old) human factor challenges. As the first substantial piece of human factors work examining future railway intelligent infrastructure, this thesis has an overall goal to establish a human factors knowledge base regarding intelligent infrastructure systems, as used in tomorrow’s railway but also in many other sectors and industries. An in-depth interview study with senior railway specialists involved with intelligent infrastructure allowed the development and verification of a framework which explains the functions, activities and data processing stages involved. The framework includes a consideration of future roles and activities involved with intelligent infrastructure, their sequence and the most relevant human factor issues associated with them, especially the provision of the right information in the right quantity and form to the right people. In a substantial fieldwork study, a combination of qualitative and quantitative methods was employed to facilitate an understanding of alarm handling and fault finding in railway electrical control and maintenance control domains. These functions had been previously determined to be of immediate relevance to work systems in the future intelligent infrastructure. Participants in these studies were real railway operators as it was important to capture users’ cognition in their work settings. Methods used included direct observation, debriefs and retrospective protocols and knowledge elicitation. Analyses of alarm handling and fault finding within real-life work settings facilitated a comprehensive understanding of the use of artefacts, alarm and fault initiated activities, along with sources of difficulty and coping strategies in these complex work settings. The main source of difficulty was found to be information deficiency (excessive or insufficient information). Each role requires different levels and amounts of information, a key to good design of future intelligent infrastructure. The findings from the field studies led to hypotheses about the impact of presenting various levels of information on the performance of operators for different stages of alarm handling. A laboratory study subsequently confirmed these hypotheses. The research findings have led to the development of guidance for developers and the rail industry to create a more effective railway intelligent infrastructure system and have also enhanced human factors understanding of alarm handling activities in electrical control.
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Books on the topic "Infrastructure intelligente"

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1926-, Branscomb Lewis M., and Keller James, eds. Converging infrastructures: Intelligent transportation and the National Information Infrastructure. Cambridge, Mass: MIT Press, 1996.

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Negenborn, Rudy R., Zofia Lukszo, and Hans Hellendoorn, eds. Intelligent Infrastructures. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3598-1.

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Kumar Shukla, Vinod, Piyush Maheshwari, Purushottam Sharma, and Sonali Vyas. Computational Intelligence in Urban Infrastructure. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003218715.

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Mishra, Brijesh, Rakesh Kumar Singh, Subodh Wairya, and Manish Tiwari. Intelligent Systems and Smart Infrastructure. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003357346.

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Systems, Intelligent Transportation, ed. Intelligent Transportation Systems infrastructure initiative. [Washington, D.C.]: Intelligent Transportation Systems, Joint Program Office, U.S. Dept. of Transportation, 1997.

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Shah, Jiten, Shriniwas S. Arkatkar, and Pravin Jadhav, eds. Intelligent Infrastructure in Transportation and Management. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6936-1.

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Fries, Ryan, Mashrur Chowdhury, and Jeffrey Brummond. Transportation Infrastructure Security Utilizing Intelligent Transportation Systems. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2008. http://dx.doi.org/10.1002/9780470432853.

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Jeff, Brummond, ed. Transportation infrastructure security utilizing intelligent transportation systems. Hoboken, N.J: John Wiley & Sons, 2008.

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United States. Dept. of Transportation., ed. Operation TimeSaver: Building the intelligent transportation infrastructure. [Washington, D.C.]: U.S. Dept. of Transportation, 1995.

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United States. Dept. of Transportation, ed. Operation TimeSaver: Building the intelligent transportation infrastructure. [Washington, D.C.]: U.S. Dept. of Transportation, 1995.

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Book chapters on the topic "Infrastructure intelligente"

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Striffler, Tobias, Nicola Michailow, Michael Bahr, and Hans D. Schotten. "How Device-to-Device Communication can be used to Support an Industrial Mobile Network Infrastructure." In Technologien für die intelligente Automation, 128–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-59895-5_10.

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Grunau, Sergej, Magnus Redeker, Denis Göllner, and Lukasz Wisniewski. "The Implementation of Proactive Asset Administration Shells: Evaluation of Possibilities and Realization in an Order Driven Production." In Technologien für die intelligente Automation, 131–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64283-2_10.

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AbstractA major benefit of Digital Twins is autonomous decision making. The concept of the Asset Administration Shell (AAS) enables an assets interaction in Industry 4.0 application scenarios and beyond. This article defines and validates implementation possibilities for proactive AASs by integrating their different types in an AAS infrastructure for an order driven production. The proactive AAS execute the VDI/VDE 2193-interaction protocol in a demonstrator. For this purpose suitable AAS submodels for production and storage are modeled.
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Büchter, Marvin, and Sebastian Wolf. "Plug and Work with OPC UA at the Field Level: Integration of Low-Level Devices." In Technologien für die intelligente Automation, 63–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64283-2_5.

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AbstractThe integration of Open Platform Communications Unified Architecture into the field level holds potential to reduce manual configuration efforts by consistent information modelling and a uniform communication protocol. This paper discusses initiatives that are active in this context and reflects the status of the current specification work. The review focuses on the achievability of Quality of Service requirements, the adaption of established automation system concepts and the introduction of new concepts for automation systems at the field level. Using a remote input/output application as an example, we investigate the impact of new concepts for low-level system engineering. It is shown that besides a possible reduction of configuration steps, a loose coupling between the automation application, the used network infrastructure and the used devices can be achieved.
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Qiu, Jie, and Siyue Qiu. "Building Design Intelligent Management System Based on BIM+Artificial Intelligence." In Sustainable Civil Infrastructures, 236–46. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78276-3_24.

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Siraj, Aiman, Vinod Kumar Shukla, Sonali Vyas, and Soumi Dutta. "Artificial Intelligence and Intelligent Transport Systems for Urban Transportation." In Computational Intelligence in Urban Infrastructure, 137–54. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003218715-12.

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Liu, Dong, Xi Cheng, Zheyu Zhang, Zhicheng Liu, and Yumeng Ma. "Intelligent Connected Vehicle Information Security Detection System Based on Artificial Intelligence." In Sustainable Civil Infrastructures, 333–42. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-72509-8_28.

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Yao, Yao. "Utilization of Intelligent LIMS System Based on Artificial Intelligence Algorithm in Environmental Evaluation." In Sustainable Civil Infrastructures, 421–31. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78276-3_42.

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Dadashi, Nastaran, David Golightly, Sarah Sharples, and Richard Bye. "Understanding Alarm Handling: A Case in Railway Electrical Control Systems." In Intelligent Infrastructure, 75–90. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781315587288-6.

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Dadashi, Nastaran, David Golightly, Sarah Sharples, and Richard Bye. "Introducing Human Factors for Remote Condition Monitoring." In Intelligent Infrastructure, 1–12. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781315587288-1.

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Dadashi, Nastaran, David Golightly, Sarah Sharples, and Richard Bye. "Challenges of Remote Condition Monitoring." In Intelligent Infrastructure, 25–40. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781315587288-3.

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Conference papers on the topic "Infrastructure intelligente"

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Tan, Mike Yongjun. "Localized Corrosion Control and Management for Durable Renewable Energy Infrastructure." In CONFERENCE 2025, 1–8. AMPP, 2025. https://doi.org/10.5006/c2025-00148.

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Abstract A huge network of renewable energy infrastructure such as offshore wind farms is currently being built for the emerging renewable energy age, often at remote locations and exposed to complex environments. The durability of these infrastructure assets is often dependent upon localized corrosion because local corrosion damages are likely the sites of local stress concentration and crack initiation. Currently these infrastructures are designed only for approximately 20-25 years of life, which is unsustainable not only from lifecycle assessment point of view, but also for generating significant materials wastage that is often difficult to recycle at remote offshore locations. Therefore, the control of localized corrosion is a prerequisite condition for significantly extending the safe operational life of major renewable energy infrastructure. This paper presents an overview of localized corrosion issues affecting the durability of energy infrastructure and potential approaches to addressing them. It is noted that the detection and monitoring of localized forms of corrosion are essential for preventing premature failure of engineering structures. Future corrosion management will need to incorporate localized corrosion monitoring, predictive modelling, data analytics and artificial intelligence, to enable data driven closed-loop smart corrosion control such as closed-loop cathodic protection.
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Shastry, K. Aditya, Byalalli Jagadish, Vilok C. Bhat, and A. N. Kruthika Chowdary. "Automated Urban Infrastructure Classification Using Aerial Imagery." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721673.

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Almadi, Soloman. "Intelligent Field Infrastructure: Distributed Intelligence and Retention Based System." In SPE Intelligent Energy Conference & Exhibition. Society of Petroleum Engineers, 2014. http://dx.doi.org/10.2118/167826-ms.

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Jiang, Shengfeng, and Lei Jiang. "Enterprise Artificial Intelligence New Infrastructure Standardization and Intelligent Framework Design." In 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, 2021. http://dx.doi.org/10.1109/i-smac52330.2021.9640877.

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Blythe, P. "Future intelligent infrastructure." In 2nd IEE Conference on Automotive Electronics. IEE, 2006. http://dx.doi.org/10.1049/ic:20060580.

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Blythe, P. T., and H. R. Bryan. "Future intelligent infrastructure." In IET Road Transport Information and Control Conference and the ITS United Kingdom Members' Conference (RTIC 2008). Institution of Engineering and Technology, 2008. http://dx.doi.org/10.1049/ic.2008.0766.

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Ramazanov, S. "Intelligent decision-making technologies in the conditions of war threats, dangers and post-war reconstruction of Ukraine." In international scientific-practical conference. MYKOLAYIV NATIONAL AGRARIAN UNIVERSITY, 2024. http://dx.doi.org/10.31521/978-617-7149-78-0-107.

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The report examines the role of intelligent technologies, in particular artificial intelligence, machine learning and big data analysis, in making effective decisions in the face of military threats, hazards and during the post-war recovery of Ukraine. The author highlights the areas of application of these technologies: emergency management, infrastructure reconstruction, evacuation planning, forecasting the consequences of war, and countering disinformation. The author emphasises the need for interdisciplinary cooperation, development of specialised solutions, access to quality data and training. Ethical aspects and cybersecurity issues are outlined. The importance of investing in the development of intelligent technologies to strengthen Ukraine's resilience and security is emphasised
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Focaracci, Alessandro, Luigi Martirano, and Francesca Zacchei. "AI & Smart Tunnel: improving road tunnel resilience by dynamic and predictive risk analysis." In 8th International Conference on Road and Rail Infrastructure, 271–76. University of Zagreb Faculty of Civil Engineering, 2024. http://dx.doi.org/10.5592/co/cetra.2024.1642.

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Technological innovations have led to the tunnel concept evolution from civil works to technological infrastructure, where technology overcomes the geometric-functional limits, increasing its operating capacity. Today, the tunnel system must have the ability to adapt to a scenario in which transportation is based on guided or self-driving cars, with internal combustion engines or electric motors, that safely run through Smart Roads and Smart Tunnels. This implies that the tunnel system must be part of "Intelligent Transport Systems" (ITS), a goal introduced by Directive 2010/40/EU [1]. This paper aims to illustrate the fundamental principles of SCADRA (Supervisory Control Acquisition and Dynamic Risk Analysis) system, developed and implemented thanks to EURAM (EUropean Risk Analysis Method) methodology, and how it can be empowered thanks to Artificial Intelligence (AI). SCADRA system is a supplementary prevention and safety measure for tunnels management, both during normal operation and in emergency conditions, capable of guaranteeing a real-time monitoring of tunnel risk level. Thanks to AI, the system can be enhanced in order to execute a predictive risk analysis, by assessing the tunnel risk level trend according to the data gathered and by adjusting the next prediction to the real-time risk data. Artificial Intelligence (AI) and the Generative AI (Gen AI) are concepts and areas of practical application that are quickly growing, in terms of interest, products and services across multiple sectors. The concept is also relevant to the road, transport and mobility sectors in areas such as infrastructure design, operations and management, but it could be crucial for the safety aspect.
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Bursi, Oreste S., Daniele Zonta, and Manuel Fassin. "Towards intelligent civil infrastructure." In 2015 17th International Conference on Transparent Optical Networks (ICTON). IEEE, 2015. http://dx.doi.org/10.1109/icton.2015.7193408.

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Mathá, Natalia, Konstantin Schekotihin, Matthias Bergner, Doriana Cobârzan, and Marco Hudelist. "Automated Labeling Infrastructure for Failure Analysis." In ISTFA 2022. ASM International, 2022. http://dx.doi.org/10.31399/asm.cp.istfa2022p0036.

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Abstract The development of intelligent assistants helping Failure Analysis (FA) engineers in their daily work is essential to any digitalization strategy. In particular, these systems must solve various computer vision or natural language processing problems to select the most critical information from heterogeneous data, like images or texts, and present it to the users. Modern artificial intelligence (AI) techniques approach these tasks with machine learning (ML) methods. The latter, however, require large volumes of training data to create models to solve the required problems. In most cases, enterprise clouds store vast volumes of data captured while applying various FA methods. Nevertheless, this data is useless for ML training algorithms since it is stored in forms that can only be interpreted by highly-trained specialists. In this paper, we present an approach to embedding an annotation process in the everyday routines of FA engineers. Its services can easily be embedded in existing software solutions to (i) capture and store the semantics of each data piece in machine-readable form, as well as (ii) provide predictions of ML models trained on previously annotated data to simplify the annotation task. Preliminary experiments of the built prototype show that the extension of an image editor used by FA engineers with the services provided by the infrastructure can significantly simplify and speed up the annotation process.
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Reports on the topic "Infrastructure intelligente"

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Balali, Vahid. System-of-Systems Integration for Civil Infrastructures Resiliency Toward MultiHazard Events. Mineta Transportation Institute, August 2023. http://dx.doi.org/10.31979/mti.2023.2245.

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Civil infrastructure systems—facilities that supply principal services, such as electricity, water, transportation, etc., to a community—are the backbone of modern society. These systems are frequently subject to multi-hazard events, such as earthquakes. The poor resiliency of these infrastructures results in many human casualties and significant economic losses every year. An outline of a holistic view that considers how different civil infrastructure systems operate independently and how they interact and communicate with each other is required to have a resilient infrastructure system. More specifically a systems engineering approach is required to enable infrastructure to remain resilient in the case of extreme events, including natural disasters. To address these challenges, this research builds on the proposal that the infrastructure systems be equipped with state-of-the-art sensor networks that continuously record the condition and performance of the infrastructure. The sensor data from each infrastructure are then transferred to a data analysis system component that employs artificial intelligence techniques to constantly analyze the infrastructure’s resiliency and energy efficiency performance. This research models the resilient infrastructure problem as a System of Systems (SoS) comprised of the abovementioned components. It explores system integration and operability challenges and proposes solutions to meet the requirements of the SoS. An integration ontology, as well as a data-centric architecture, is developed to enable infrastructure resiliency toward multi-hazard events. The Federal Emergency Management Agency (FEMA), and infrastructure managers, such as Departments of Transportation (DOTs) and the Federal Highway Administration (FHWA), can learn from and integrate these solutions to make civil infrastructure systems more resilient for all.
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Gbedomon, Rodrigue Castro, Sidol Houngbo, and Fréjus Thoto. Profil de l’agriculture numérique et de l’adaptation aux changements climatiques Cas du Bénin. Centre Africain pour le Développement Equitable, June 2024. http://dx.doi.org/10.61647/aa84576.

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Le Bénin connaît une croissance démographique rapide et une demande alimentaire significative, qui requiert une transformation structurale de l'agriculture par le recours à des technologies agricoles. Les solutions numériques sont en évolution pour améliorer la productivité agricole et renforcer l'adaptation aux changements climatiques dans le secteur agricole. Les nouvelles orientations agricoles en Bénin ont renforcé le rôle du secteur privé dans le domaine. Le Bénin est confronté à des risques climatiques perturbant son agriculture, notamment des précipitations tardives, violentes, sécheresses, la chaleur excessive, les vents violents et l'élévation du niveau de la mer. Le numérique peut aider à surmonter ces défis en renforçant l'information agro-climatique et hydrologique, en favorisant l'adoption d'innovations et de pratiques climato-intelligente. Il peut également améliorer le suivi des exploitations, faciliter l'accès au financement et à l'information sur les marchés, augmentant ainsi la résilience des agriculteurs face aux chocs climatiques. Au Bénin, il existe 50 solutions numériques agricoles, notamment des conseils, formation et information pour les producteurs, commercialisation des produits agricoles, facilitation de la mise en relation entre les acteurs de la chaîne de valeur agricole, et services de suivi des activités culturales et de cartographie des exploitations. Out of these, 24 ont le potentiel d'aborder les problèmes liés à l'adaptation aux changements climatiques. Les défis pour la transformation numérique de l'agriculture et de l'adaptation aux changements climatiques sont nombreux, telles que un accès limité à Internet dans les régions rurales, une infrastructure technologique insuffisante, un taux élevé d'analphabétisme numérique, une inadéquation des solutions numériques aux conditions et besoins locaux, une viabilité économique dépendante de subventions, un manque de solutions abordant les changements climatiques, une fiabilité incertaine des services numériques climatiques, et une collaboration insuffisante entre les acteurs du numérique dans le secteur agricole.
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Cao, Larry. IV. Chatbot, Knowledge Graphs, and AI Infrastructure. CFA Institute Research Foundation, April 2023. http://dx.doi.org/10.56227/23.1.10.

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Expert contributors discuss AI and big data applications that are being developed for financial services, such as AI-powered intelligent customer service systems; “factories” for data processing, AI, simulation, and visualization; and symbolic AI.
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Ehlschlaeger, Charles, Jeffrey Burkhalter, Imes Chiu, Igor Linkov, Jeffrey Cegan, Olaf David, Yanfeng Ouyang, et al. Resilience modeling for civil military operations with the framework incorporating complex uncertainty systems. Engineer Research and Development Center (U.S.), September 2023. http://dx.doi.org/10.21079/11681/47562.

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Framework Incorporating Complex Uncertain Systems (FICUS) provides geographic risk analysis capabilities that will dramatically improve military intelligence in locations with the Engineer Research and Development’s (ERDC) demographic and infrastructure models built and calibrated. When completed, FICUS would improve intelligence products by incorporating existing tools from the National Geospatial Intelligence Agency, ERDC, and FICUS prototype models, even in places without demographic or infrastructure capabilities. FICUS would support higher-fidelity intelligence analysis of population, environmental, and infrastructure interaction in areas with Human Infrastructure System Assessment (HISA) and urban security models built and calibrated. This technical report will demonstrate FICUS prototype tools that allow Civil Affairs Soldiers to provide situational awareness information via a browser interface.
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Rinuado, Christina, William Leonard, Christopher Morey, Theresa Coumbe, Jaylen Hopson, and Robert Hilborn. Artificial intelligence (AI)–enabled wargaming agent training. Engineer Research and Development Center (U.S.), April 2024. http://dx.doi.org/10.21079/11681/48419.

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Fiscal Year 2021 (FY21) work from the Engineer Research and Development Center Institute for Systems Engineering Research lever-aged deep reinforcement learning to develop intelligent systems (red team agents) capable of exhibiting credible behavior within a military course of action wargaming maritime framework infrastructure. Building from the FY21 research, this research effort sought to explore options to improve upon the wargaming framework infrastructure and to investigate opportunities to improve artificial intelligence (AI) agent behavior. Wargaming framework infrastructure enhancements included updates related to supporting agent training, leveraging high-performance computing resources, and developing infrastructure to support AI versus AI agent training and gameplay. After evaluating agent training across different algorithm options, Deep Q-Network–trained agents performed better compared to those trained with Advantage Actor Critic or Proximal Policy Optimization algorithms. Experimentation in varying scenarios revealed acceptable performance from agents trained in the original baseline scenario. By training a blue agent against a previously trained red agent, researchers successfully demonstrated the AI versus AI training and gameplay capability. Observing results from agent gameplay revealed the emergence of behavior indicative of two principles of war, which were economy of force and mass.
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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, March 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats, such as adversarial machine learning, model poisoning, and API exploitation, while analyzing AI-powered cybersecurity techniques for threat detection, anomaly prediction, and zero-trust security. The study also examines the role of cryptographic solutions, including homomorphic encryption, federated learning security, and post-quantum cryptography, in safeguarding AI models and data integrity. By integrating AI with cutting-edge cybersecurity strategies, this research aims to enhance resilience, compliance, and trust in AI-driven infrastructures. Future advancements in AI security, blockchain-based authentication, and quantum-enhanced cryptographic solutions will be critical in securing next-generation AI applications in cloud and edge environments. Keywords: AI security, adversarial machine learning, cloud computing security, edge computing security, zero-trust AI, homomorphic encryption, federated learning security, post-quantum cryptography, blockchain for AI security, AI-driven threat detection, model poisoning attacks, anomaly prediction, cyber resilience, decentralized AI security, secure multi-party computation (SMPC).
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Schulze, Max, Radika Kumar, and Michael Oghia. Taxonomy Guide: Infrastructure in the Digital Economy. Commonwealth Secretariat, April 2022. https://doi.org/10.14217/comsec.952.

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Technological innovation has become a key driver of economic development. Technological progress results in countries’ ability to produce beyond their typical production possibilities, while also altering how they consume.4 Over recent decades, however, the expansion of technology and innovation has evolved with new and more efficient ways of delivering goods and services. For example, new technology such as nanotechnology, artificial intelligence (AI) and photonics5 are upgrading old technologies, contributing to the expansion of new trade in the service sector. The COVID-19 pandemic has also added to the acceleration of deeper digitalisation among countries and across industries and businesses.
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Biswas, Sukalpa, and Alex Wright. The Digital Evolution of Highway Infrastructure Asset Management. TRL, July 2022. http://dx.doi.org/10.58446/cwlm6036.

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The last decade has seen a very gradual change at a local network level in the methods used to collect data from Highways Infrastructure Assets, how to manage and operate Assets, a change in the way those Assets are used, and the way they are maintained and constructed. This change is largely driven by digital technology improvements. This evolution has also created uncertainty around Highways Asset Management processes. The sector is now at a point where there is an imminent requirement for transition from “Traditional” to “Intelligent” styles of Asset Management. While the strategic network operators have been invested in this transformation for some time, Local Road operators are being left behind. In this paper TRL identifies some of the key actions required for local highways managers to successfully achieve this transition to digital, and in so doing realise the benefits of the digital evolution of highways Asset Management. Dr Sukalpa Biswas and Dr Alex Wright touch on the factors influencing the changes, identify the novel technologies having the greatest impact, and set out five essential steps for Asset owners to consider on their journey to Intelligent Asset Management. This is accompanied by specific practical actions required of each type of stakeholder (Asset Owners, Technology & Software Providers, Standards & Legislative Authorities).
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Mazari, Mehran, Yahaira Nava-Gonzalez, Ly Jacky Nhiayi, and Mohamad Saleh. Smart Highway Construction Site Monitoring Using Artificial Intelligence. Mineta Transportation Institute, March 2025. https://doi.org/10.31979/mti.2025.2336.

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Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. Due to the lack of a comprehensive image database specifically developed for transportation infrastructure construction projects, the first portion of this study focused on preparing a comprehensive database of annotated images for various classes of equipment and machinery that are commonly used in roadway construction and rehabilitation projects. The second part of the project focused on training the deep learning models and improving the accuracy of the classification and detection algorithms. The outcomes of the trained and improved deep learning classification model were promising in terms of the precision and accuracy of the model in detecting specific objects at a highway construction site. It should be noted that the scope of this project was limited to the image and video data recorded from the ground-level and cannot be extended to Uncrewed Aerial System (UAS) data. This study provides valuable insights on the potentials of AI and deep learning to improve the monitoring and thus safety and efficiency of transportation infrastructure construction.
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Tayeb, Shahab. Intelligent Blind Crossings for Suburban and Rural Intersections. Mineta Transportation Institute, February 2025. https://doi.org/10.31979/mti.2024.2351.

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Blind intersections in suburban and rural areas pose significant safety challenges due to limited visibility and inadequate infrastructure. This project proposes an innovative solution leveraging the Internet of Vehicles (IoV) paradigm, utilizing connected and autonomous vehicles (CAVs) for seamless communication to enhance safety at these intersections. The research focuses on developing a specialized Road-Side Unit (RSU) system equipped with a Virtual Traffic Light Algorithm implemented on a Field-Programmable Gate Array (FPGA). Key stakeholders, including transportation authorities, vehicle manufacturers, and local communities, stand to benefit from this initiative. The RSU system acts as a critical infrastructure component, facilitating efficient intersection management and mitigating visibility challenges. Methodologies involve adapting the Virtual Traffic Light Algorithm, integrating it into the FPGA-based RSU system, and demonstrating RSU communication operability through software-defined radios. Additionally, a novel solar-powered system is designed for lightweight RSUs to enhance sustainability and energy efficiency. The project's findings indicate the feasibility and practicality of the proposed RSU solution in enhancing safety at blind intersections. Successful implementation of the Virtual Traffic Light Algorithm on the FPGA demonstrates its potential for real-world deployment. The operability demonstration of RSU communication validates the effectiveness of the proposed communication system. Overall, this research contributes to advancing safety measures in transportation infrastructure, with potential implications for future urban planning and policy development.
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