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Статті в журналах з теми "Artificial Intelligence of Thing"
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Seng, Kah Phooi, Li Minn Ang, and Ericmoore Ngharamike. "Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks." International Journal of Distributed Sensor Networks 18, no. 3 (March 2022): 155014772110628. http://dx.doi.org/10.1177/15501477211062835.
Повний текст джерелаАнотація:
The advances and convergence in sensor, information processing, and communication technologies have shaped the Internet of Things of today. The rapid increase of data and service requirements brings new challenges for Internet of Thing. Emerging technologies and intelligent techniques can play a compelling role in prompting the development of intelligent architectures and services in Internet of Things to form the artificial intelligence Internet of Things. In this article, we give an introduction and review recent developments of artificial intelligence Internet of Things, the various artificial intelligence Internet of Things computational frameworks and highlight the challenges and opportunities for effective deployment of artificial intelligence Internet of Things technology to address complex problems for various applications. This article surveys the recent developments and discusses the convergence of artificial intelligence and Internet of Things from four aspects: (1) architectures, techniques, and hardware platforms for artificial intelligence Internet of Things; (2) sensors, devices, and energy approaches for artificial intelligence Internet of Things; (3) communication and networking for artificial intelligence Internet of Things; and (4) applications for artificial intelligence Internet of Things. The article also discusses the combination of smart sensors, edge computing, and software-defined networks as enabling technologies for the artificial intelligence Internet of Things.
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Peters, Ted. "Intelligence? Not Artificial, but the Real Thing!" Theology and Science 17, no. 1 (January 2, 2019): 1–5. http://dx.doi.org/10.1080/14746700.2018.1557376.
Повний текст джерела
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LAWRENCE, DAVID R., CÉSAR PALACIOS-GONZÁLEZ, and JOHN HARRIS. "Artificial Intelligence." Cambridge Quarterly of Healthcare Ethics 25, no. 2 (March 9, 2016): 250–61. http://dx.doi.org/10.1017/s0963180115000559.
Повний текст джерелаАнотація:
Abstract:It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries—namely, with regard to artificially (super)intelligent persons—but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.
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Supriyadi, Endang Irawan, and Dianing Banyu Asih. "IMPLEMENTASI ARTIFICIAL INTELLIGENCE (AI) DI BIDANG ADMINISTRASI PUBLIK PADA ERA REVOLUSI INDUSTRI 4.0." Jurnal RASI 2, no. 2 (January 9, 2021): 12–22. http://dx.doi.org/10.52496/rasi.v2i2.62.
Повний текст джерелаАнотація:
Revolusi industri 4.0 merupakan perkembangan keempat dari revolusi industri, pada revolusi industri keempat ini banyak penemuan teknologi baru yang belum pernah ditemukan pada era revolusi sebelumnya, sepereti Internet of Thing (IOT), percetakan 3D, big data, dan artificial intelligence. Artificial intelligence merupakan salah satu produk revolusi industri 4.0 yang perkembangan dan pemanfaatannya telah banyak digunakan dalam kehidupan sehari-hari dan pada banyak sektor bidang. Artificial intellegence digunakan untuk meningkatkan pelayanan publik melalui penyediaan aplikasi berbasis teknologi di bidang administrasi publik. Tulisan ini akan mengkaji tentang sejauh mana implementasi artificial intelligence pada bidang administrasi publik, dampak yang timbul dari penerapan artificial intelligence pada bidang administrasi publik serta kesiapan sumber daya manusia(SDM) pemerintahan dalam penerapan artificial intelligence.
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Takama, Yasufumi. "Web Intelligence and Artificial Intelligence." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 1 (January 20, 2017): 25–30. http://dx.doi.org/10.20965/jaciii.2017.p0025.
Повний текст джерелаАнотація:
This paper briefly summarizes the progress of artificial intelligence (AI) and web intelligence (WI) in the last two decades. The reason why we mention AI and WI together is because those have strong relationship with each other. This paper first summarizes the history of AI, and then gives brief description of supervised learning, which I think has played a major role in AI in the last two decades. As most history of WI is in the target decades, this paper first briefly describes major WI topics, and then gives more detailed description about information recommendation, which I think one of more successful and necessary technologies in practical use.
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Park, Yeonsook. "Can Artworks by Artificial Intelligence be Artworks?" AM Journal of Art and Media Studies, no. 20 (October 15, 2019): 113. http://dx.doi.org/10.25038/am.v0i20.332.
Повний текст джерелаАнотація:
The thinking power of Homo sapiens made human beings the lord of all creation. The ability to reason is also the premise of human existence. We, however, now know that this is not confined only to human but to Artificial Intelligence. Over the history of humankind, human beings have attempted to create an immortal being that could surpass their abilities and complements their inferiorities. We are making something immortal and transcendent, which are different properties from our own. Artificial Intelligence may be able to evolve on its own like humans have been doing. As a kind of numerical being, humans are able to be omnipresent with the technology provided. This new kind of existence makes us think about and see things differently. Humans are attempting to create ‘beings’ that can generate art, take care of weak human beings, talk and discuss human issues, and even fall in love with humans. As our minds can run beyond the boundaries created by our body limitations, we would like to infuse our creativity into AI that might evolve from its original state. Similar to what Prometheus did, humans are attempting to share their legacy with another existence. Recently a research team from Rutgers University in New Jersey proposed a system named CAN: Creative Adversarial Networks for generating art with creative characteristics. The team demonstrated a realization of this system based on a novel, creative adversarial network. Their proposed system possesses the ability to produce novel artworks which make people believe human artists produced them. The data the team proposes proves that AI now attempts to do something considered as a creative activity. With this research, the definition of art should be reconsidered. Since the Fountain(1917) by Duchamp, open concepts toward artworks have been embraced by many artists and their colleagues. However, it is time to contemplate the new phase. When we regard something as artwork, should it be created, selected, and combined by human beings? Is it possible that the thing that is accepted as artwork by people can be art? This paper seeks to propose several opinions regarding these questions. Article received: June 23, 2019; Article accepted: July 6, 2019; Published online: October 15, 2019; Review articleHow to cite this article: Park, Yeonsook. "Can Artworks by Artificial Intelligence be Artworks?" AM Journal of Art and Media Studies 20 (2019): 113-121. doi: 10.25038/am.v0i20.332
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Liebowitz, J. "If there is artificial intelligence? Is there such a thing as artificial stupidity." ACM SIGART Bulletin, no. 109 (July 1989): 26–28. http://dx.doi.org/10.1145/70632.70634.
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Доценко, Серій Ілліч. "ПРО ПРИРОДНИЙ ТА ШТУЧНИЙ ІНТЕЛЕКТ КІБЕРНЕТИЧНИХ СИСТЕМ". RADIOELECTRONIC AND COMPUTER SYSTEMS, № 3 (30 вересня 2019): 4–18. http://dx.doi.org/10.32620/reks.2019.3.01.
Повний текст джерелаАнотація:
It is proposed as part of the concept of the “cybernetic system” to distinguish the following components: - cybernetic systems impervious to information, as a control system; - cybernetic systems permeable to information: intelligent functional systems based on natural intelligence; Intelligent information systems based on artificial intelligence. From an analysis of the content of the concept of “artificial intelligence,” it follows that at present there is no unambiguous definition of the content of this concept. Almost all authors agree that artificial intelligence should be similar to human intelligence. From an analysis of the content of the concept of “natural intelligence,” it follows that its basis is the central regularity of the integrative activity of the brain. It is proposed to define thinking as the possibility of representing things in measure, and intelligence as the ability to implement the process of measuring things. The measure is the presentation of a thing in the form of a dialectical unity of concepts general (qualitative definition) – single (quantitative definition). It is shown that the main problem that has not been solved so far for artificial neural networks is the problem of the formation of a capable mathematical model of a natural neuron based on the central regularity of integrative brain activity. The second problem requiring its solution is the need to teach the artificial intelligence system to "measure" things, as well as their properties. Without mastering this ability, no artificial intelligence system can implement the actions that characterize the activity of the natural neural network. The third problem is the need to train the artificial intelligence system to remember the previous experience. Manipulating knowledge is possible only by applying the laws of natural intelligence. Therefore, to form the knowledge base, experts are involved as a source of knowledge and knowledge engineers, as specialists in the extraction of knowledge from experts. Moreover, between the concepts of “data” and “information”, as well as “information” and “knowledge”, there is a dialectical connection in the form of “single” – “general”. Intelligent information technology can be the basis for the implementation of cybernetic systems permeable to information: intelligent functional systems; intelligent information systems. The fundamental task that needs to be solved is the task of establishing the composition and content of the concept of “unit of knowledge”.
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Tyagi, Dr Aarati, and Dr K. Manikyamba. "An Analysis of the Gory and Glory of Artificial Intelligence." Journal of Artificial Intelligence, Machine Learning and Neural Network, no. 25 (September 14, 2022): 1–14. http://dx.doi.org/10.55529/jaimlnn.25.1.14.
Повний текст джерелаАнотація:
In era of travel destinations planning to moon and mars Artificial Intelligence to overcome all the natural phenomena is not erratic. A time has come to thing of natural ways to sustain life. A time has come to know the benefits of Glory of Artificial Intelligence(AI) in the Gory of Life is an imperative aspect. The AI is to be protected under the Intellectual Property Rights(IPR). Laws pertaining to Anti-trust, anti-monopoly, IPR, National and International treaties to protect organic farming and varieties and so on are to brought in to effect to protect the Gory and Glory of Artificial Intelligence.
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Joseph, Joby, and Catherin Edward. "Artificial Intelligence Literaturised in Jose Saramango’s Novels: An Endorsement of Creativity, Rationality and Magic Realism." Think India 22, no. 2 (October 17, 2019): 342–47. http://dx.doi.org/10.26643/think-india.v22i2.8734.
Повний текст джерелаАнотація:
Apparently, there is no connection between artificial intelligence and literature, but at closer scrutiny, it is discernibly clear that a link-up is quite possible in a harmonious manner because both the subjects do have commonalities dotting them one end to the next. Literature is a journey through the trajectories or pathways of imagination, illusion, fantasy, and dreamlike situations. The world of artificial intelligence does have virtual realities taking place in an imaginative plain. Artificial intelligence is a repetitive, perennial and a crucial current topic in science fiction, whether unworldly, stressing the capacity advantages, or dystopian, emphasizing the possible risks and insecurities. The belief of machines with human-like intelligence dates lower back to the talented writer Samuel Butler's 1872 novel Erewhon. Buoyant or positive perceptions of the destiny of artificial intelligence are feasible in science fiction. The artificial intelligence facilitates the quick and robust operational efficiency of the world and literature fulfills this role through its crucial ingredient imagination running riot to beautify the world. The literary works of Jose Saramago do sublimate in their scope the role of artificial intelligence fair and square. John McCarthy, the founder of the idea of Artificial Intelligence, conveys the idea that ‘Artificial Intelligence is the technology and designing of making sensible and brilliant machines, particularly intelligent packages’. For me, Jose Saramago acts as an intelligent machine to check and reformulate the fundamental ethical values which are considered as universal, secular and scientific. His Scepticism goes beyond all pessimistic worldviews and his humanistic ideology surpasses all notions of illogical and unreasonable thought patterns. Through this paper, I intend to present his literary contributions packed with ecstasy, prophetic pronouncements and visionary ability. I call his intelligence as artificial intelligence that represents his ideology, prophetic activity, and reasoning power.
Дисертації з теми "Artificial Intelligence of Thing"
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Antonini, Mattia. "From Edge Computing to Edge Intelligence: exploring novel design approaches to intelligent IoT applications." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/308630.
Повний текст джерелаАнотація:
The Internet of Things (IoT) has deeply changed how we interact with our world. Today, smart homes, self-driving cars, connected industries, and wearables are just a few mainstream applications where IoT plays the role of enabling technology. When IoT became popular, Cloud Computing was already a mature technology able to deliver the computing resources necessary to execute heavy tasks (e.g., data analytic, storage, AI tasks, etc.) on data coming from IoT devices, thus practitioners started to design and implement their applications exploiting this approach. However, after a hype that lasted for a few years, cloud-centric approaches have started showing some of their main limitations when dealing with the connectivity of many devices with remote endpoints, like high latency, bandwidth usage, big data volumes, reliability, privacy, and so on. At the same time, a few new distributed computing paradigms emerged and gained attention. Among all, Edge Computing allows to shift the execution of applications at the edge of the network (a partition of the network physically close to data-sources) and provides improvement over the Cloud Computing paradigm. Its success has been fostered by new powerful embedded computing devices able to satisfy the everyday-increasing computing requirements of many IoT applications. Given this context, how can next-generation IoT applications take advantage of the opportunity offered by Edge Computing to shift the processing from the cloud toward the data sources and exploit everyday-more-powerful devices? This thesis provides the ingredients and the guidelines for practitioners to foster the migration from cloud-centric to novel distributed design approaches for IoT applications at the edge of the network, addressing the issues of the original approach. This requires the design of the processing pipeline of applications by considering the system requirements and constraints imposed by embedded devices. To make this process smoother, the transition is split into different steps starting with the off-loading of the processing (including the Artificial Intelligence algorithms) at the edge of the network, then the distribution of computation across multiple edge devices and even closer to data-sources based on system constraints, and, finally, the optimization of the processing pipeline and AI models to efficiently run on target IoT edge devices. Each step has been validated by delivering a real-world IoT application that fully exploits the novel approach. This paradigm shift leads the way toward the design of Edge Intelligence IoT applications that efficiently and reliably execute Artificial Intelligence models at the edge of the network.
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Antonini, Mattia. "From Edge Computing to Edge Intelligence: exploring novel design approaches to intelligent IoT applications." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/308630.
Повний текст джерелаАнотація:
The Internet of Things (IoT) has deeply changed how we interact with our world. Today, smart homes, self-driving cars, connected industries, and wearables are just a few mainstream applications where IoT plays the role of enabling technology. When IoT became popular, Cloud Computing was already a mature technology able to deliver the computing resources necessary to execute heavy tasks (e.g., data analytic, storage, AI tasks, etc.) on data coming from IoT devices, thus practitioners started to design and implement their applications exploiting this approach. However, after a hype that lasted for a few years, cloud-centric approaches have started showing some of their main limitations when dealing with the connectivity of many devices with remote endpoints, like high latency, bandwidth usage, big data volumes, reliability, privacy, and so on. At the same time, a few new distributed computing paradigms emerged and gained attention. Among all, Edge Computing allows to shift the execution of applications at the edge of the network (a partition of the network physically close to data-sources) and provides improvement over the Cloud Computing paradigm. Its success has been fostered by new powerful embedded computing devices able to satisfy the everyday-increasing computing requirements of many IoT applications. Given this context, how can next-generation IoT applications take advantage of the opportunity offered by Edge Computing to shift the processing from the cloud toward the data sources and exploit everyday-more-powerful devices? This thesis provides the ingredients and the guidelines for practitioners to foster the migration from cloud-centric to novel distributed design approaches for IoT applications at the edge of the network, addressing the issues of the original approach. This requires the design of the processing pipeline of applications by considering the system requirements and constraints imposed by embedded devices. To make this process smoother, the transition is split into different steps starting with the off-loading of the processing (including the Artificial Intelligence algorithms) at the edge of the network, then the distribution of computation across multiple edge devices and even closer to data-sources based on system constraints, and, finally, the optimization of the processing pipeline and AI models to efficiently run on target IoT edge devices. Each step has been validated by delivering a real-world IoT application that fully exploits the novel approach. This paradigm shift leads the way toward the design of Edge Intelligence IoT applications that efficiently and reliably execute Artificial Intelligence models at the edge of the network.
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Bäckström, Amanda, and Hannah Larsson. "Is There Such A Thing As Too Much Intelligence? : A qualitative study exploring how Born Global e-commerce companies are working towards adopting Artificial Intelligence into their Customer Relationship Management Systems." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-74865.
Повний текст джерелаАнотація:
The purpose of this thesis is to explore the drivers and barriers of adoption of technology such as AI and how it could facilitate an internationalization. The thesis also hopes to explore how Born Global e-commerce companies are working towards an adoption of AI into the companies CRM-system. The model of multiple case study was chosen together with a qualitative method and an abductive approach. This was done by collecting primary data from three different Born Global firms within the e-commerce sector, as well as one CRM expert company, all located in Sweden and active on the international market. Furthermore, the theoretical framework presented Born Global, Technology Adoption, Customer Relationship Management and Artificial Intelligence. With the theoretical framework in mind, the conceptual framework was developed to show how the theories are connected to each other. Thereafter, the empirical findings were first presented and analysed together with theory and the voice of the authors of the thesis. The analysis visualize both similarities and dissimilarities between the empirical findings and the theory presented in the thesis. The final chapter concludes the barriers and drivers that Born Global e-commerce companies faces when adopting AI into their CRM-system. It also explains how AI within CRM could be beneficial as a tool on the Global market, rather than in the actual process of internationalization. To conclude the authors present the fact that companies are not working towards an adoption of AI into their CRM-systems. However, further development within the field is presented as well as theoretical and practical implications.
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Ma, Xin. "Optical characterization of ferromagnetic and multiferroic thin-film heterostructures." W&M ScholarWorks, 2015. https://scholarworks.wm.edu/etd/1539623372.
Повний текст джерелаАнотація:
This thesis presents optical characterization of the static and dynamic magnetic interactions in ferromagnetic and multiferroic heterostructures with time-resolved and interface-specific optical techniques. The focus of the thesis is on elucidating the underlying physics of key physical parameters and novel approaches, crucial to the performance of magnetic recording and spintronic devices.;First, time-resolved magneto-optical Kerr effect (TRMOKE) is applied to investigate the spin dynamics in L10 ordered FePt thin films, where perpendicular magnetic anisotropy Ku and intrinsic Gilbert damping alpha0 are determined. Furthermore, the quadratic dependence of Ku and alpha0 on spin-orbit coupling strength xi is demonstrated, where xi is continuously controlled through chemical substitution of Pt with Pd element. In addition, a linear correlation between alpha0 and electron scattering rate 1/T e is experimentally observed through modulating the anti-site disorder c in the L10 ordered structure. The results elucidate the basic physics of magnetic anisotropy and Gilbert damping, and facilitate the design and fabrication of new magnetic alloys with large perpendicular magnetic anisotropy and tailored damping properties.;Second, ultrafast excitation of coherent spin precession is demonstrated in Fe/CoO heterostructures and La0.67Ca0.33MnO 3 thin films using TRMOKE technique. In the Fe/CoO thin films, Instant non-thermal ferromagnet (FM) -- antiferromagnet (AFM) exchange torque on Fe magnetization through ultrafast photo-excited charge transfer possesses in the CoO layer is experimentally demonstrated at room temperature. The efficiency of spin precession excitation is significantly higher and the recovery is notably faster than the demagnetization procedure. In the La0.67Ca 0.33MnO3 thin films, pronounced spin precessions are observed in a geometry with negligible canting of the magnetization, indicating that the transient exchange field is generated by the emergent AFM interactions due to charge transfer and modification of the kinetic energy of eg electrons under optical excitation. The results will help promoting the development of novel device concepts for ultrafast spin manipulation.;Last, the interfacial spin state of the multiferroic heterostructure PbZr0.52Ti0.4803/La0.67Sr0.33MnO 3 and its dependence on ferroelectric polarization is investigated with interface specific magnetization induced second harmonic generation (MSHG). The spin alignment of Mn ions in the first unit cell layer at the heterointerface can be tuned from FM to AFM exchange coupled, while the bulk magnetization remains unchanged as probed with MOKE. The discovery provides new insights into the basic physics of interfacial magneto-electric (ME) coupling.
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Negrea, Andrei Liviu. "Optimization of energy efficiency for residential buildings by using artificial intelligence." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEI090.
Повний текст джерелаАнотація:
La consommation, en général, représente le processus d’utilisation d’un type de ressource où des économies doivent être réalisées. La consommation d’énergie est devenue l’un des principaux problèmes d’urbanisation et de crise énergétique, car l’épuisement des combustibles fossiles et le réchauffement climatique mettent en péril l’utilisation de l’énergie des plantes. Cette thèse présent une méthode d’économie d’énergie a été adoptée pour la réduction de consommation d’énergie prévu le secteur résidentiel et les maisons passives. Un modèle mathématique basé sur des mesures expérimentales a été développé pour simuler le comportement d’un laboratoire d’essai de l’UPB. Le protocole expérimental a été réalisé à la suite d’actions telles que : la construction de bases de données sur les paramètres, la collecte de données météorologiques, l’apport de flux auxiliaires tout en considérant le comportement humain. L’algorithme de contrôle-commande du système est capable de maintenir une température constante à l’intérieur du bâtiment avec une consommation minimale d’énergie. Les mesures et l’acquisition de données ont été configurées à deux niveaux différents: les données météorologiques et les données sur les bâtiments. La collection de données est faite sur un serveur qui a été mis en œuvre dans l’installation de test en cours d’exécution d’un algorithme complexe qui peut fournir le contrôle de consommation d’énergie. La thèse rapporte plusieurs méthodes numériques pour envisage la consommation d’énergie, utilisée avec l’algorithme de contrôle. Un cas expérimental basé sur des méthodes de calcul dynamiques pour les évaluations de performance énergétique de construction a été faite à Grenade, en Espagne, l’information qui a été plus tard utilisée dans cette thèse. L’estimation des paramètres R-C avec la prévision du flux de chaleur a été faite en utilisant la méthode nodal, basée sur des éléments physiques, des données d’entrée et des informations météorologiques. La prévision d’énergie de consommation présent des résultats améliorés tandis que la collecte de données IoT a été téléchargée sur une carte à base de système de tarte aux framboises. Tous ces résultats ont été stables montrant des progrès impressionnants dans la prévision de la consommation d’énergie et leur application en énergieConsumption, in general, represents the process of using a type of resource where savings needs to be done. Energy consumption has become one the main issue of urbanization and energy crisis as the fossil depletion and global warming put under threat the planet energy utilization. In this thesis, an automatic control of energy was developed to reduce energy consumption in residential area and passive house buildings. A mathematical model founded on empirical measurements was developed to emphasize the behavior of a testing laboratory from Universitatea Politehnica din București - Université Politechnica de Bucarest - Roumanie. The experimental protocol was carried out following actions such as: building parameters database, collecting weather data, intake of auxiliary flows while considering the controlling factors. The control algorithm is controlling the system which can maintain a comfortable temperature within the building with minimum energy consumption. Measurements and data acquisition have been setup on two different levels: weather and buildings data. The data collection is gathered on a server which was implemented into the testing facility running a complex algorithm which can control energy consumption. The thesis reports several numerical methods for estimating the energy consumption that is further used with the control algorithm. An experimental showcase based on dynamic calculation methods for building energy performance assessments was made in Granada, Spain, information which was later used in this thesis. Estimation of model parameters (resistances and capacities) with prediction of heat flow was made using nodal method, based on physical elements, input data and weather information. Prediction of energy consumption using state-space modeling show improved results while IoT data collection was uploaded on a Raspberry Pi system. All these results were stable showing impressive progress in the prediction of energy consumption and their application in energy field
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Bahers, Quentin. "AI Planning-Based Service Modeling for the Internet of Things." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-246212.
Повний текст джерелаАнотація:
It is estimated that by 2020, more than 50 billion devices will be interconnected, to form what is called the Internet of Things. Those devices range from consumer electronics to utility meters, including vehicles. Provided with sensory capabilities, those objects will be able to transmit valuable information about their environment, not only to humans, but even more importantly to other machines, which should ultimately be able to interpret and take decisions based on the information received. This “smartness” implies gifting those devices with a certain degree of automation. This Master’s Thesis investigates how recent advances in artificial intelligence planning can be helpful in building such systems. In particular, an artificial intelligence planner able to generate workflows for most of IoT-related use cases has been connected to an IoT platform. A performance study of a state-of-the planner, Fast Downward, on one of the most challenging IoT application, Smart Garbage Collection (which is similar to the Traveling Salesman Problem) has also been carried out. Eventually, different pre-processing and clustering techniques are suggested to tackle the latest AI planners’ inefficiency on quickly finding plans for the most difficult tasks.
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An, Yinan. "Building Smart Cities and Intelligent Societies in Australia with the Aid of Internet of Things, Big Data and Artificial Intelligence." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23029.
Повний текст джерелаАнотація:
Countries around the world are facing urban planning challenges in fast-growing areas. As a developed country, Australia has a sound social system, with laws, rules and regulations. Rapid growth has brought new development opportunities, but also accompanied by serious social planning and decision-making issues. In some fast-growing areas, investments for infrastructure cannot keep up with the rapid population growth due to inaccurate data and other factors. As a result, sometimes it’s becoming very hard and challenging for the government to make the best decision for investments in order to achieve the maximum potential. Embracing emerging technologies, to build smart cities in Australia, to improve governance and decision making has become critical. This thesis explores challenges we are facing in fast-growing areas in Australia and how emerging technology-aided strategy making, community consultation and smart governance can help building a smart city. We demonstrate in-depth in how emerging technologies like Internet of Things and Big Data can improve a city’s operation efficiency and assisting decision-makers to solve challenging leadership, planning and decision-making issues. This thesis demonstrates by using these technologies how a planning decision or a community consultation which currently take months to process could be reduced to days, or how an operational decision which currently takes a week could be reduced to a day.
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SABBATINI, LUISIANA. "Artificial Intelligence and Internet of Things for Industry 4.0 and Society 5.0: Exploration of Theories and Practices to Implement the Future." Doctoral thesis, Università Politecnica delle Marche, 2022. http://hdl.handle.net/11566/295522.
Повний текст джерелаАнотація:
Il contesto sociale di oggi è modellato da due tendenze coesistenti: spinta tecnologica e richiesta di applicazioni. Con il primo termine si intende l'emergere, la rapida evoluzione e l'applicazione di tecnologie innovative, del regno dell'ICT (come IoT) e dell'analisi dei dati (come Intelligenza Artificiale, Machine e Deep Learning). La seconda tendenza è invece una peculiarità del mercato odierno, costruito su requisiti come il basso costo, l’alto tasso tecnologico, la personalizzazione e la facile accessibilità tra gli altri. Grazie a queste due tendenze coesistenti e sinergiche, l'intera società sta rapidamente passando al livello successivo (da cui i paradigmi Industria 4.0 e Società 5.0). Il ragionamento che ha permesso questa rapida evoluzione, è stato la comprensione del fatto che prendere decisioni basate su informazioni reali estratte dalla complessa realtà in cui viviamo, consente miglioramenti in termini di costi, tempi e qualità. In quasi tutti i contesti, disporre di buoni sistemi che consentano il passaggio da dati grezzi effettivamente raccolti sul campo, a conoscenze significative, è la chiave del successo. Da un punto di vista architetturale, ci sono tre livelli principali che consentono la creazione di conoscenza e saggezza partendo dalla realtà: acquisizione, comunicazione ed analitica. L'innovazione a uno o più livelli è essenziale per lo sviluppo della comunità mondiale. Questa tesi presenta numerosi contributi innovativi ed esplorazioni tecnologiche, appartenenti a uno o più livelli dell’architettura semplificata a tre livelli, per lo più focalizzati nell'ambito delle pratiche dell'Industria 4.0, come la manutenzione basata sulle condizioni e i sistemi di visione artificiale, e nelle pratiche della società 5.0, come i dispositivi indomabili per la sanità intelligente e i Sistemi Visual-IoT per la gestione delle inondazioni nelle smart cities del futuro. I paradigmi tecnologici IoT e IA sono stati profondamente analizzati sia da un punto di vista teorico che pratico. Attraverso la loro applicazione in diverse attività di ricerca, ciascuna focalizzata su aspetti specifici, è stato raggiunto l'obiettivo finale di sviluppare una comprensione ampia e completa. L'IoT è un paradigma rivoluzionario, che abbraccia i tre livelli tra i dati grezzi e la conoscenza significativa, essendo quindi un argomento complesso da affrontare in modo completo. L'IA è un fattore essenziale per rendere tangibile l'impatto dell'IoT ed al contempo le metodologie e le tecniche dell'IA sono diversificate e complesse. Per questo motivo è stato adottato un approccio dal basso verso l’alto, partendo da una varietà di casi d’uso reali focalizzati su un livello specifico, ognuno dei quali affrontato applicando rigorosamente il metodo scientifico di ricerca, sono state estratte conoscenze globali e adattabili sull’IoT e sull’IA. Le fonti di casi d'uso sono state aziende private, progetti di ricerca nazionali ed internazionali, focalizzati sui paradigmi Industria 4.0 e Società 5.0, come verrà presentato più in dettaglio. Nello specifico verranno presentate le seguenti attività di ricerca: un sistema di e-Health basato su sensori indossabili, un sistema IoT per il monitoraggio in tempo reale degli edifici, un proxy cross-protocollo per reti di sensori IoT, un algoritmo di Machine Vision per il conteggio dei pezzi assemblati manualmente, un Modello basato su ML per valutare lo stato di salute della cinghia di trasmissione di un robot cartesiano, un modello basato su ML in grado di valutare lo stato di salute di una macchina per lo stampaggio ad iniezione sulla base dei parametri di processo raccolti da sensori diffusi, un sistema basato su OCR in grado di suggerire interventi di manutenzione per le targhe utilizzate nella gestione degli ordini di un sistema di robot per la verniciatura, una soluzione di visione artificiale per il monitoraggio del livello dell'acqua dei fiumi attraverso una telecamera che inquadra l’asta idrometrica ed infine un modello dinamico di razionamento del consumo di energia per gli impianti di raffinazione del petrolio. Affrontando casi reali più o meno specifici incentrati su IoT e AI, è stato possibile comprendere le possibilità e le peculiarità architetturali e software dei due paradigmi. Questa ampia varietà di possibilità dovrebbe essere ottimizzata per soddisfare il più possibile il contesto e i requisiti specifici del compito. In conclusione, IoT ed IA possono avvantaggiarsi a vicenda grazie alla stretta interconnessione nel paradigma edge-AI, che insieme all'in-network e al cloud computing, sono stati ritenuti essenziali per il futuro successo di una società più intelligente.The societal context of today is shaped by two coexisting tendencies: technology-push and application-pull. The former is the emergence and rapid evolution and application of innovative technologies, in the realm of ICT (like IoT) and Data Analysis (like Artificial Intelligence, Machine and Deep Learning). The latter tendency is the trend of the market of today, built on requirements like low-cost, high-tech, customized, easily accessible, and so on so forth. Thanks to these coexisting and synergistic tendencies, the entire society is rapidly passing to the next level (hence Industry 4.0 and Society 5.0 paradigms). The reasoning that allowed this rapid evolution, has been the comprehension of the fact that making decisions based on real information extracted from the complex reality we live in, allows improvements in terms of costs, time, and quality. In almost every context, having good systems that allow the passage from raw actual data collected to meaningful knowledge is the key for success. From an architectural point of view, there are three main levels that allow the creation of knowledge and wisdom from the reality: acquisition, communication, and analytic. Innovation in either one or multiple levels is essential for the development of the worldwide community. This thesis presents several innovative contributions and technological explorations, belonging to either one or multiple levels, mostly focused in the realm of Industry 4.0 practices, like Condition-Based Maintenance, and Machine Vision Systems, and Society 5.0 practices, like e-Health devices and Visual-IoT systems for flood management in smart cities. IoT and AI technological paradigms have been deeply analysed from both a theoretical and practical point of view. Through their application in several research activities, each focused on specific aspects, the final aim of developing a broad and comprehensive understanding has been achieved. IoT is a revolutionary paradigm, which spans the three levels between raw data and meaningful knowledge, thus being a complex topic to deal with comprehensively. AI is an essential enabler for making IoT's impact tangible, and AI methodologies and techniques are diversified and complex too. For this reason, a bottom-up approach has been adopted, starting from a variety of real cases focused on a specific level, and each addressed rigorously applying the scientific method of research, global and adaptable knowledge about IoT and AI has been extracted. The sources of use cases have been private companies, National and International research projects, committed to Industry 4.0 and Society 5.0 paradigms, as will be presented. Specifically, the following research activities will be presented: an e-Health system based on wearable sensors, an IoT system for real-time building monitoring, a cross-protocol proxy for sensors networks, a Machine Vision algorithm for counting manually assembled pieces, a ML-based model for assessing the health status of a cartesian robot's drive belt, a ML-based model able to assess the health of an injection moulding machine based on process parameters collected by widespread sensors, an OCR-based system able to suggest maintenance intervention for painting robot's number plates, a Computer Vision solution for monitoring the water level of rivers through a camera framing the gauge, and a dynamic energy consumption rationing model for oil refining plants. By addressing more or less specific real cases centered on IoT and AI, it has been possible to understand architectural and software possibilities and peculiarities of the two paradigms. These wide variety of possibilities should be tuned in order to satisfy as better as possible context and task-specific requisites. Concluding, IoT and AI can benefit each other by the strict interconnection into the edge-AI paradigm, which together with in-network and cloud computing, have been found essential for the future successful achievement of smarter society.
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Tundrea, Darius. "Artificial Intelligence is Getting Personal : A study on the Usage Motivations and Privacy Concerns of Intelligent Personal Assistants’ Users." Thesis, Uppsala universitet, Medier och kommunikation, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-334967.
Повний текст джерелаАнотація:
The present study is aiming to evaluate the Intelligent Personal Assistants usage motivations, addressing at the same time various privacy issues and concerns related to this emergent technology. To fulfil the purpose of the study I have applied two different research methods. Initially, a web survey conducted gathered 18 respondents answering 24 questions related to the presented topic. Subsequently, was organised a focus group by gathering seven respondents who shared their opinions on the subject of research. Two research questions were developed based on two hypotheses. First research question: “To what extent IPA users agree to personal data collection in order to gratify their sought needs?”; exploring the participants’ opinions when it comes to the degree of acceptance of personal information disclosure to gratify their needs. Moreover, second research question: “What are the motivating criteria that determine the usage of IPA?”. This question develops opinions and experiences on the usage of Intelligent Personal Assistants, as well as the way people perceive this new technology. The finding of this studies reveals that users of new media are concerned and aware of their personal data collection. However, as a result, they feel trapped in the network society by the peer pressure towards the usage of favourite mediums. Therefore, the denial of technology would bring unfavourable consequences from a social perspective. Further researches can be conducted on this topic, addressing in depth the Artificial Intelligence and its societal implications, possible utilities of the Intelligent Personal Assistants as a companion for children, elders and people with disabilities, Artificial Intelligence used in public administration. Consequently, many different aspects can be explored having the topic of this thesis as a starting point.
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Timothy, Edward Bant Breen. "I think therefore I am…? An exploration of artificial intelligence (AI) marketing practitioner perceptions and practices." Doctoral thesis, Universitat Ramon Llull, 2020. http://hdl.handle.net/10803/668994.
Повний текст джерелаАнотація:
Aquesta tesi explora les percepcions de la IA per part de la indústria de la publicitat i el màrqueting i les contrasta amb l’estat actual de desenvolupament de la IA. La indústria de la publicitat és un punt focal interessant per discussions amb relació a la IA, ja que és una indústria emblemàtica i creativa, sovint vista com una àrea en què les màquines únicament poden copiar o donar suport però no pas idear i crear.
La intel·ligència artificial (IA) és una intel·ligència exposada per màquines. En la ciència de la computació, una màquina “intel·ligent” ideal és un agent flexible i racional que percep el seu entorn i pren accions per minimitzar les seves possibilitats de succés envers un objectiu arbitrari (Russell i Norvig, 2013).
Els desenvolupaments de la IA estan canviant la societat. Algunes millores són petites, com per exemple la IA de Google amb relació a les millores del Gmail per contestar els correus de manera més fàcil i ràpida. Altres canvis estan en procés. Aquest és el cas de la versió d’iteració de Tesla en el cas dels programes de vehicles autònoms. També estan havent-hi altres canvis com succeeix amb Echo, l’assistent personal d’Amazon per la teva llau que s’activa amb la veu. Tots aquests exemples i molts més estan fent possible que la IA formi part del nostre dia a dia. En el camp dels mitjans, Mark Zuckerberg, el fundador i CEO de Facebook, ofereix chat-bots en la seva plataforma de missatges instantanis per empreses que vulguin comunicar-se amb els seus consumidors.
En el món de la publicitat i el màrqueting, la IA està començant a ser més que un tema de ciència-ficció o una estratègia a imitar per inèrcia. Creatius, executius en els mitjans de comunicació i emprenedors AdTech estan activament explorant la IA. En el 2016, l’empresa de publicitat McCann va anunciar que la seva divisió japonesa dirigida al públic jove, anomenada McCann Millennials, havia construït i estava utilitzant un director creatiu d’IA (Doland, 2016).
En contrast amb el moviment cap a la IA, diversos creadors d’anuncis mítics es mantenen fermament compromesos amb la idea que la creativitat humana individual es mantingui en el centre del procés creatiu dels mitjans de comunicació i del màrqueting. En els últims anys, el llegendari executiu publicitari John Hegarty va defensar el paper crític que els humans juguen per raonar i curar i, finalment, crear bon màrqueting (Arthur, 2016).
La recerca principal de la tesi es basa en una enquesta a grups d’interès clau de la publicitat i el món del màrqueting sobre el tema de la IA. Després d’emplenar el qüestionari, un grup més reduït d’enquestats va participar en entrevistes de seguiment per ampliar les seves opinions sobre diverses àrees de l’enquesta.
Aquesta tesi explora el tema de la IA en el màrqueting i la percepció de la IA per part dels venedors. Els resultats mostren una indústria interessada amb prudència en la IA i el seu potencial, però desconeguda i poc preparada per aquells reptes que aquest salt tecnològic presenta. La majoria dels participants en l’estudi van destacar la seva comprensió limitada de la IA. Dels 440 enquestats, la gran majoria de les dades van caure en el quartil més baix, situant-se en el rang 3 / 3.5 sobre 10. Quan se'ls va preguntar sobre la capacitat creativa de la IA, els participants van respondre de forma negativa, amb una mitjana de 3,0 en una escala de l’1 al 10. Quan se’ls va preguntar quines feines podrien ser substituïdes per la IA, l’opció favorita va ser “no pot ser substituïda per la IA” quan les feines estaven relacionades amb la creativitat, l’estratègia i el lideratge. Un 82% dels enquestats va dir que les seves empreses no oferien formació en IA.Esta tesi explora las percepciones de la IA por parte de la industria de la publicidad y el marketing y las contrasta con el estado actual de desarrollo de la IA. La indústria de la publicidad es un punto focal interesante para discusiones relacionadas con la IA, ya que es una industria emblemática y creativa, a menudo vista como una área en que las máquinas únicamente puede copiar o dar soporte y no idear y crear. La IA es una inteligencia expuesta para máquinas. En la ciencia de la computación, una máquina “inteligente” ideal es un agente flexible y racional que percibe su entorno y toma acciones para minimizar sus posibilidades de éxito hacia un objetivo arbitrario (Russell y Norvig, 2013). Los desarrollos de la IA están cambiando la sociedad. Algunas mejoras son pequeñas, como por ejemplo la IA de Google en relación a las mejoras del Gmail para contestar los correos de modo más fácil y rápido. Otros cambios están en proceso. Este es el caso de las versiones de Tesla al software de vehículos autónomos. También están habiendo otros cambios como sucede con Echo, el asistente personal de Amazon para tu casa que se activa con la voz. Todos estos ejemplos y muchos más están haciendo posible que la IA forme parte de nuestro día a día. En el campo de los medios, Mark Zuckerberg, el fundador y CEO de Facebook, ofrece chat-bots en su plataforma de mensajería instantánea para empresas que quieran comunicarse con sus consumidores. En el mundo de la publicidad y el marketing, la IA está empezando a ser más que un tema de ciencia ficción o una estrategia a imitar por inercia. Creativos, ejecutivos en los medios de comunicación y emprendedores AdTech están activamente explorando la IA. En el 2016, la empresa de publicidad McCann anunció que su división joven japonesa para jóvenes llamada McCann Millennial había construido y estaba utilizando un director creativo basado en IA (Doland, 2016). En contraste con el movimiento hacia la IA, distintos creadores de anuncios míticos se mantienen firmemente comprometidos con la idea que la creatividad humana individual se mantenga en el centro del proceso creativo de los medios de comunicación y del marketing. En los últimos años, el legendario ejecutivo publicitario John Hegarty defendió el papel crítico que los humanos juegan para razonar y curar y, finalmente, crear un buen marketing (Arthur, 2016). Los resultados de la tesis se basan en una encuesta a grupos de interés clave de la publicidad y el mundo del marketing sobre el tema de la IA. Después de rellenar el cuestionario, un grupo más reducido de encuestados participó en entrevistas de seguimiento para ampliar sus opiniones sobre diversas áreas de la encuesta. Esta tesi explora el tema de la IA en el marketing y la percepción de la IA por parte de sus vendedores. Los resultados muestran una industria interesada con prudencia en la IA y en su potencial, pero que es todavía desconocida, y poco preparada para aquellos retos que este salto tecnológico presenta. La mayoría de los participantes en el estudio destacaron su comprensión limitada de la IA. De los 440 encuestados, la gran mayoría de los datos cayeron en el cuartil más bajo, situándose en el rango 3/3.5 sobre 10. Cuando se les preguntó cómo de creativa puede ser la IA, los participantes respondieron de forma negativa, con una media de 3.0 en una escala de 1 al 10. Cuando se les preguntó qué trabajos podrían ser sustituidos por la IA, la opción más popular cuando se referían a labores relacionadas con la creatividad, la estrategia y el liderazgo fue “no puede ser substituida por la IA”. Un 82% de los encuestados dijeron que sus empresas no ofrecían formación en IA.
This thesis explores perceptions of artificial intelligence (AI) by the advertising industry and contrasts those perceptions with the state of AI marketing development today. The advertising industry is an interesting focal point for a discussion regarding AI because it is one of the emblematic creatively focused industries, and creative is often viewed as an area where machines can only copy or support and not ideate. Artificial intelligence (AI) is the intelligence exhibited by machines. In computer science, an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at an arbitrary goal (Russell and Norvig, 2003). AI technology developments are changing society. Some are small improvements like Google's AI enhancements in its’ Gmail product that makes it easier and faster to respond to messages. Others are on-going shifts like Tesla's version iterations to autonomous vehicle software. And even others such as Echo, Amazon's voice-activated personal assistant for your home, begin to make AI-enabled machines part of daily life. In the media space, Facebook's Founder and CEO Mark Zuckerberg offers chat-bots in their instant messaging platform that speak to consumers for brands. In the advertising and marketing world, artificial intelligence is starting to be more than a science fiction topic or a nifty copy strategy. Creatives, media executives, and AdTech entrepreneurs are actively exploring AI. In 2016, the advertising firm McCann announced that their Japanese youth division titled McCann Millennials had built and was using an AI creative director (Doland, 2016). In contrast to the movement towards AI, several legendary ad creators remain firmly committed to the idea of the individual creative human being staying solely at the center of the media and marketing creative process. In recent years, legendary ad executive Sir John Hegarty, defended the critical role humans play to reason and curate and ultimately create great marketing (Arthur, 2016). The primary research for the thesis is a survey of key stakeholders in the advertising and marketing world on the topic of artificial intelligence. After fielding the questionnaire, a smaller set of respondents participated in follow-up interviews to expand their opinions on various areas of the survey. This thesis explores the topic of artificial intelligence in marketing and the perception of AI by marketers. The results show an industry cautiously interested in AI and its potential, but woefully unaware and unprepared for the challenges this technological leap-forward presents. The majority of participants in the study highlighted their limited understanding of AI. Out of the 440 respondents, the vast majority of the data fell in the lowest quartile, being in the 3/3.5 range out of 10. When asked how creative AI can be, participants consistently responded negatively, with an average of 3.0 on a scale of 1 to 10 in terms of how creative AI can become. When asked what jobs AI can replace, roles that received the highest number of mentions for "cannot be replaced by AI" were mostly creative, strategic or leadership. An astounding 82% of respondents said their companies did not offer training in AI. This thesis wrestles with the luddite and progressive perspectives of AI in marketing and the machine-learning breakthroughs that challenge the role of the marketing department and advertising industry.
Книги з теми "Artificial Intelligence of Thing"
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Peat, F. David. Artificial intelligence: How machines think. New York: Baen Books, 1988.
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Artificial intelligence: How machines think. New York, N.Y: Baen Books, 1985.
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Goyal, Lalit Mohan, Tanzila Saba, Amjad Rehman, and Souad Larabi-Marie-Sainte. Artificial Intelligence and Internet of Things. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003097204.
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Thillaiarasu, N., Suman Lata Tripathi, and V. Dhinakaran. Artificial Intelligence for Internet of Things. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003335801.
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Russell, Stuart J. Do the right thing: Studies in limited rationality. Cambridge, Mass: MIT Press, 1991.
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Pal, Souvik, Debashis De, and Rajkumar Buyya, eds. Artificial Intelligence-based Internet of Things Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87059-1.
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1917-, Hyde Margaret O., ed. Artificial intelligence: A revision of Computers that think? Hillside, N.J: Enslow Publishers, 1986.
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Kumar, R. Lakshmana, Yichuan Wang, T. Poongodi, and Agbotiname Lucky Imoize, eds. Internet of Things, Artificial Intelligence and Blockchain Technology. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74150-1.
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Raj, Pethuru, Ashutosh Kumar Dubey, Abhishek Kumar, and Pramod Singh Rathore, eds. Blockchain, Artificial Intelligence, and the Internet of Things. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-77637-4.
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Soufiene, Ben Othman, Chinmay Chakraborty, and Faris A. Almalki. Practical Artificial Intelligence for Internet of Medical Things. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003315476.
Повний текст джерелаЧастини книг з теми "Artificial Intelligence of Thing"
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Singh, Ishita, Joy Gupta, and K. P. Arjun. "Artificial Intelligence." In Blockchain, Internet of Things, and Artificial Intelligence, 41–64. First edition. | Boca Raton : C&H/CRC Press, 2021.: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429352898-4.
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Singh, Ranbir, Amiya Kumar Dash, Ravinder Kumar, Anand Bewoor, and Ashwini Kumar. "Internet of Things." In Artificial Intelligence, 171–85. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003095910-12.
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Bowman, Charles F. "What Is Artificial Intelligence?" In How Things Work, 175–214. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003143437-9.
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Stolze, M. "Visual Critiquing in Domain Oriented Design Environments: Showing the Right Thing at the Right Place." In Artificial Intelligence in Design ’94, 467–82. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0928-4_27.
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Jokanović, Vukoman. "Synthetic Biology and Artificial Intelligence." In Computer Vision and Internet of Things, 141–75. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003244165-13.
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Stahl, Bernd Carsten, Doris Schroeder, and Rowena Rodrigues. "The Ethics of Artificial Intelligence: A Conclusion." In Ethics of Artificial Intelligence, 107–11. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17040-9_9.
Повний текст джерелаАнотація:
AbstractThe concluding chapter highlights broader lessons that can be learned from the artificial intelligence (AI) cases discussed in the book. It underlines the fact that, in many cases, it is not so much the technology itself that is the root cause of ethical concerns but the way it is applied in practice and its reliability. In addition, many of the cases do not differ radically from ethics cases related to other novel technologies, even though the use of AI can exacerbate existing concerns. Ethical issues can rarely be resolved to everybody’s full satisfaction, not least because they often involve the balancing of competing goods. What is essential is space for human reflection and decision-making within the use of AI. Questions about what we can and should do, why we should act in particular ways and how we evaluate the ethical quality of our actions and their outcomes are part of what it means to be human. Even though Immanuel Kant believed that a good will is the only thing in the world that is ethical per se, a good will alone does not suffice where complex consequences may not be obvious. The complex nature of AI systems and their interaction with their human, social and natural environment require constant vigilance and human input.
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Murthy, Ch V. N. U. Bharathi, and M. Lawanya Shri. "Artificial Intelligence for Blockchain II." In Blockchain, Internet of Things, and Artificial Intelligence, 141–54. First edition. | Boca Raton : C&H/CRC Press, 2021.: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429352898-8.
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Gupta, Joy, Ishita Singh, and K. P. Arjun. "Artificial Intelligence for Blockchain I." In Blockchain, Internet of Things, and Artificial Intelligence, 109–40. First edition. | Boca Raton : C&H/CRC Press, 2021.: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429352898-7.
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Redozubov, Alexey, and Dmitry Klepikov. "The Meaning of Things as a Concept in a Strong AI Architecture." In Artificial General Intelligence, 290–300. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52152-3_30.
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Gupta, Shailja, and Mayank Khattar. "Internet of Things and Artificial Intelligence." In Towards Smart World, 99–118. First edition. | Boca Raton : C&H/CRC Press, 2021.: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781003056751-7.
Повний текст джерелаТези доповідей конференцій з теми "Artificial Intelligence of Thing"
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Tzavaras, Aimilios, Nikolaos Mainas, Fotios Bouraimis, and Euripides G. M. Petrakis. "OpenAPI Thing Descriptions for the Web of Things." In 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai52525.2021.00220.
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Ben Ali Kaddour, Asmaa, and Nidhal Abdulaziz. "Artificial Intelligence Pathologist: The use of Artificial Intelligence in Digital Healthcare." In 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT). IEEE, 2021. http://dx.doi.org/10.1109/gcaiot53516.2021.9693090.
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Motah, Mahendrenath. "The Ontogeny of Memory and Learning: Natural Intelligence versus Artificial Intelligence in Information Technology Education." In InSITE 2006: Informing Science + IT Education Conference. Informing Science Institute, 2006. http://dx.doi.org/10.28945/3028.
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Over the past decades Information Technology has made a tremendous impact on the lives of humans, so much so, that one can safely state that humans eat, breathe and live IT. Each and every aspect of the life of those living in the “modern” world is under the spell of IT. The talk of the day is E-economy, E-education, E-commerce, E-finance, E-government, E-entertainment, E-communication, E-mail; E-learning.. ..the world we are living in has become an E-world. In this whirlpool, many are still groping in the dark while a lot more have kept the pace in both developed and developing countries. The impact of the E thing and IT has attained such dimensions that concepts like cognition, cognitive development, fluid intelligence, crystallized intelligence, emotional intelligence, memory, learning, sensation and perception, and other related terms used to qualify, quantify and explain human experiences have become almost empty concepts in the face of what is nowadays known as artificial intelligence. This paper aims to analyse the biological, physiological and psychological aspects of memory and learning and to critically look at the impact of Information Technology Education and Information Technology in the every day dealings of humans. It also aims to be a thought provoking piece of work, to the scientific minds working on Artificial Intelligence, Robotics, Computers and derivatives, and all the perspectives that Artificial Intelligence offers to humanity, not forgetting that “the human mind and natural intelligence is behind it all”.
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Bendík, Dávid, and Andrej Novák. "Artificial intelligence and its use in air transport." In Práce a štúdie. University of Žilina, 2022. http://dx.doi.org/10.26552/pas.z.2022.1.18.
Повний текст джерелаАнотація:
In recent years, modern technologies have found large applications in sectors such as engineering, healthcare, information technology, robotics, and so forth. One important field in the use of such modern technologies is the field of air transport, where the main objective of using these technologies is to facilitate work for people, make individual tasks more efficient and faster, or reduce the risks associated with human error. In this paper, we will look at artificial intelligence and its use in aviation. Despite the rapid pace of improvement, artificial intelligence is still finding its way to reach its full potential. The history of artificial intelligence dates back to ancient times when many philosophers wondered whether a machine could think. The answer is found in the second half of the 20th century, when, besides theoretical knowledge, we can also observe the first intelligent machines. There is no clear and single correct definition for artificial intelligence, so the subject of the next section is to define artificial intelligence from different sources. The following section details the difference between deep learning and machine learning, comparing their main differences and applications in aviation. The analysis of the current state of application of artificial intelligence in aviation represents the core part of this paper. The emphasis in the analysis is put mainly on applications in the field of airports, air traffic management and safety. In each of these areas, the benefits of using AI are evaluated based on already established AI-enabled technologies. Finally, by analysing the sources available and those applied in our work with the use of a mathematical model, we assess how important the role artificial intelligence currently plays in air transport.
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Kavitha, P., B. Krishna Moorthy, P. S. Sudharshan, and T. Aarthi. "Mapping Artificial Intelligence and Education." In 2018 International Conference on Communication, Computing and Internet of Things (IC3IoT). IEEE, 2018. http://dx.doi.org/10.1109/ic3iot.2018.8668123.
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Tomić, Ivana, Ivan Pinćjer, Nada Miketić, and Savka Adamović. "Artificial intelligence in printing." In 11th International Symposium on Graphic Engineering and Design. University of Novi Sad, Faculty of technical sciences, Department of graphic engineering and design, 2022. http://dx.doi.org/10.24867/grid-2022-p49.
Повний текст джерелаАнотація:
Artificial intelligence has entered into many aspects of our lives – from virtual assistants and Netflix's recommendations, to fraud prevention and autonomous vehicles. In this paper we present an overview of the current use of artificial intelligence in printing industry. We discuss what does it imply for printers and clients, and how it might be used in the future. Since the main idea behind creating artificial intelligence is to mimic the capabilities of human mind, it does not surprise the fact that in printing it is mostly use for monitoring and decision making. Smart algorithms for choosing different layouts in order to minimize print waste, automated process control, creating targeted catalogues, are just a few examples. Even though the printing industry is one of the few not so disrupted by AI, it seems that the things are changing, and we might expect to see more of AI in printing in the near future.
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Abou-Zahra, Shadi, Judy Brewer, and Michael Cooper. "Artificial Intelligence (AI) for Web Accessibility." In W4A '18: The Internet of Accessible Things. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3192714.3192834.
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Facchini, Sante Dino. "Decentralized Autonomous Organizations and Multi-agent Systems for Artificial Intelligence Applications and Data Analysis." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/828.
Повний текст джерелаАнотація:
The Ph.D research project aims to explore the potential of the Decentralized Autonomous Organization paradigm in conjunction with classic software architectures for Artificial Intelligence applications. The intended goal is to investigate and formalize a possible integration path between Multi-agent System architectures and Decentralized Autonomous Organizations. Starting from the Foundation for Intelligent Physical Agents standards, we will extend basic primitives to integrate Multi-agent Systems on Distributed Ledger Technology networks. Possible deployment of services and applications in the Internet-of-Things, Artificial Intelligence and Distributed Machine Learning areas will be tested. Application of Data Analysis techniques on datasets built on such a framework will be also addressed.
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Zhang, Chao. "Intelligent Internet of things service based on artificial intelligence technology." In 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). IEEE, 2021. http://dx.doi.org/10.1109/icbaie52039.2021.9390061.
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Morel, Philip. "Towards an Artificial Architecture: About Superintelligent Space." In International Conference on the 4th Game Set and Match (GSM4Q-2019). Qatar University Press, 2019. http://dx.doi.org/10.29117/gsm4q.2019.0026.
Повний текст джерелаАнотація:
Just as there are odors that dogs can smell and we cannot, as well as sounds that dogs can hear and we cannot, so too there are wavelengths of light we cannot see and flavors we cannot taste. Why then, given our brains wired the way they are, does the remark, “Perhaps there are thoughts we cannot think,” surprise you? Evolution, so far, may possibly have blocked us from being able to think in some directions; there could be unthinkable thoughts.’ (Hamming, 1980). ‘We have preconceptions about how an intelligent robot should look and act, and these can blind us to what is already happening around us. To demand that artificial intelligence be humanlike is the same flawed logic as demanding that artificial flying be birdlike, with flapping wings. Robots will think different. To see how far artificial intelligence has penetrated our lives, we need to shed the idea that they will be humanlike.’ (Kelly, 2012). In the essay The Doctors of Tomorrow Will Be Supercomputers, published online at futurism.com, Leary (2017) says doctors will be replaced by artificial intelligence-fed supercomputers. This is in line with many theorists and futurists including Kelly (2012) who, on a more "material" level, declared in Wired: Even those areas of medicine not defined by paperwork, such as surgery, are becoming increasingly robotic. The rote tasks of any information-intensive job can be automated. It doesn't matter if you are a doctor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic. And it has already begun.'[Kelly,2013] For this last author, with whom I can only agree, if we are now at a 'point of inflection' in the use of robots, it is because they have become intelligent machines . Indeed, intelligence is the whole question...
Звіти організацій з теми "Artificial Intelligence of Thing"
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Cathles, Alison, Claudia Suaznabar, and Fernando Vargas. The 360 on Digital Transformation in Firms in Latin America and the Caribbean. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004635.
Повний текст джерелаАнотація:
Are firms in Latin America and the Caribbean lagging in terms of their adoption of digital technologies? Using the most updated and, in many cases, new data, this publication provides a 360-degree assessment on the adoption of technologies ranging from artificial intelligence, big data, and the internet of things, to “backbone” tools such as cloud computing and basic digital technologies (e.g., the percent of firms with websites). On certain dimensions, some firms in the region compare favorably with firms in OECD countries. However, in general, as with artificial intelligence and big data, the data point to considerable gaps in uptake. With a comprehensive outlook, this work also assesses enabling conditions for digital technology adoption and current trends in the digital economy.
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Acharya, Ashwin, Max Langenkamp, and James Dunham. Trends in AI Research for the Visual Surveillance of Populations. Center for Security and Emerging Technology, January 2022. http://dx.doi.org/10.51593/20200097.
Повний текст джерелаАнотація:
Progress in artificial intelligence has led to growing concern about the capabilities of AI-powered surveillance systems. This data brief uses bibliometric analysis to chart recent trends in visual surveillance research — what share of overall computer vision research it comprises, which countries are leading the way, and how things have varied over time.
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Solovyanenko, Nina I. ЮРИДИЧЕСКИЕ СТРАТЕГИИ ЦИФРОВОЙ ТРАНСФОРМАЦИИ АГРАРНОГО БИЗНЕСА. DOI CODE, 2021. http://dx.doi.org/10.18411/0131-5226-2021-70004.
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t.The development of global agricultural production and food trade in recent decades implies a digital transformation and the transition to a new technological order, which is an essential factor for sustainable development. Digitalization of agriculture and the food sector is carried out on the basis of IT 2 platforms, the Internet of Things, cloud computing, big data, artificial intelligence, and blockchain technology. Fragmented and unclear legal mechanisms, slow updating of legal regulation hinder the introduction of digital solutions. A modern regulatory framework based on digital strategies should strengthen the confidence of farmers in "smart agriculture". In Russia, the legal mechanism of strategic planning covers the development of the national platform "Digital Agriculture". Digital strategies also include updating basic legislation.
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Novak, Jr, Simmons Gordon S., Porter Robert F., Kumar Bruce W., Causey Vipin, and Robert L. Artificial Intelligence Project. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada230793.
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Cwik, Cynthia, Paul Grimm, Maura Grossman, and Toby Walsh. Artificial Intelligence and the Courts: Artificial Intelligence Trustworthiness, and Litigation. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0786.
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Karanicolas, Michael, and Mallory Knodel. Artificial Intelligence and the Courts: Artificial Intelligence and Bias - An Evaluation. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0788.
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Firth-Butterfield, Kay, and Karen Silverman. Artificial Intelligence and the Courts: Artificial Intelligence - Foundational Issues and Glossary. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0782.
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Lesser, Victor R., Paul Cohen, and Wendy Lehnert. Center for Artificial Intelligence. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada282272.
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Boros, E., P. L. Hammer, and F. S. Roberts. Optimization and Artificial Intelligence. Fort Belvoir, VA: Defense Technical Information Center, July 1996. http://dx.doi.org/10.21236/ada311365.
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Gowens, J. W. Applied Artificial Intelligence Seminar. Fort Belvoir, VA: Defense Technical Information Center, July 1989. http://dx.doi.org/10.21236/ada268571.
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