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Journal articles on the topic 'Intelligent Environment'

To see the other types of publications on this topic, follow the link: Intelligent Environment.

Author: Grafiati

Published: 4 June 2021

Last updated: 29 January 2023

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1

Liu, Zhenghao, and Xi Zeng. "Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service." Data and Information Management 5, no. 2 (January 5, 2021): 262–76. http://dx.doi.org/10.2478/dim-2020-0051.

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Abstract Based on the emerging concept of “Hybrid Intelligence,” this paper aims to explore a new model of human–computer interaction, and deeply research on its development and application of Intelligent Service in the big data environment. It systematically explores the related academic concepts of hybrid intelligence, and establishes its architecture model. The development of hybrid intelligence is faced with cognitive differences, system fragmentation, human–machine digital divide, and other issues. Strengthening the interaction between cognition and perception can be the key to break through the bottleneck. The intelligent service system based on the hybrid intelligent architecture takes knowledge fusion as the core, and “cloud intelligent brain” is making it possible for the human–computer symbiosis driven by hybrid intelligence. The proposed advanced human–computer interaction mode constructs a hybrid intelligent architecture model, enriches the concept system of human–machine hybrid intelligence, and provides a new landing scheme for intelligent services based on complex scenes in the big data environment.

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Aztiria, Asier, Juan Carlos Augusto, Rosa Basagoiti, Alberto Izaguirre, and Diane J. Cook. "Discovering frequent user--environment interactions in intelligent environments." Personal and Ubiquitous Computing 16, no. 1 (October 7, 2011): 91–103. http://dx.doi.org/10.1007/s00779-011-0471-4.

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3

Ming Rao, Tsung-Shann Jiang, and Jeffrey J. P. Tsai. "Integrated intelligent simulation environment." SIMULATION 54, no. 6 (June 1990): 291–95. http://dx.doi.org/10.1177/003754979005400607.

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4

Krishnaswamy, Ganesh M., and Ahmad K. Elshennawy. "Intelligent concurrent engineering environment." Computers & Industrial Engineering 25, no. 1-4 (September 1993): 321–24. http://dx.doi.org/10.1016/0360-8352(93)90286-7.

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5

Bryndin, Evgeny. "About Formation of International Ethical Digital Environment with Smart Artificial Intelligence." International Journal of Information Technology, Control and Automation 11, no. 1 (January 31, 2021): 1–9. http://dx.doi.org/10.5121/ijitca.2021.11101.

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Intellectual agent ensembles allow you to create digital environment by professional images with language, behavioral and active communications, when images and communications are implemented by agents with smart artificial intelligence. Through language, behavioral and active communications, intellectual agents implement collective activities. The ethical standard through intelligent agents allows you to regulate the safe use of ensembles made of robots and digital doubles with creative communication artificial intelligence in the social sphere, industry and other professional fields. The use of intelligent agents with smart artificial intelligence requires responsibility from the developer and owner for harming others. If harm to others occurred due to the mistakes of the developer, then he bears responsibility and costs. If the damage to others occurred due to the fault of the owner due to non-compliance with the terms of use, then he bears responsibility and costs. Ethical standard and legal regulation help intellectual agents with intelligent artificial intelligence become professional members of society. Ensembles of intelligent agents ith smart artificial intelligence will be able to safely work with society as professional images with skills, knowledge and competencies, implemented in the form of retrained digital twins and cognitive robots that interact through language, behavioral and active ethical communications. Cognitive robots and digital doubles through self-developing ensembles of intelligent agents with synergistic interaction and intelligent artificial intelligence can master various high-tech professions and competencies. Their use in the industry increases labor productivity and economic efficiency of production. Their application in the social sphere improves the quality of life of a person and society. Their widespread application requires compliance with an ethical standard so that their use does not cause harm. The introduction and use of an ethical standard for the use of cognitive robots and digital doubles with smart artificial intelligence increases the safety of their use. Ethical relationships between individuals and intellectual agents will also be governed by an ethical standard.

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Lee, J. H., K. Morioka, N. Ando, and H. Hashimoto. "Cooperation of Distributed Intelligent Sensors in Intelligent Environment." IEEE/ASME Transactions on Mechatronics 9, no. 3 (September 2004): 535–43. http://dx.doi.org/10.1109/tmech.2004.834655.

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7

Liu, Heng Li, and Tao Cheng. "Research on Multi-Physical Domain Information Fusion Method of Intelligent Processing Machine Based on GMM-HMM." Applied Mechanics and Materials 864 (April 2017): 184–91. http://dx.doi.org/10.4028/www.scientific.net/amm.864.184.

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As a typical unit of intelligent manufacturing system, intelligent processing machine is also a microcosm of Intelligent Manufacturing System (IMS), and the realization of intelligent manufacturing system will be firstly embodied in the intelligent processing machine as the core of intelligence. Therefore, it is inevitable to do a comprehensive and systematic study of intelligent processing machines and will get more and more attentions. In the study of intelligent machines, perceptual technology is an important part. Without effective perceptual technology, intelligent machines cannot interact with the environment, and thus the intelligence level cannot be improved. At present, the quite popular approach is to study the connection between perception and behavior from various simple behaviors and realize the higher intelligence through the combination of these behaviors on the basis of simple behaviors. The basis of autonomy perception of intelligent machines is to make it have the capability of multi-physical domain information fusion of manufacturing process and environment. An improved data processing and information fusion method based on GMM-HMM is proposed, which provides a self-perception of intelligent processing machines and a multi-physical domain information fusion method [1]. The simulation results show that the method proposed in this paper can realize the self - identification of intelligent processing machines in the intelligent manufacturing environment, such as the state of manufacturing, health and fault.

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Lee, Joo-Ho, Noriaki Ando, and Hideki Hashimoto. "Mobile Robot Architecture in Intelligent Space." Journal of Robotics and Mechatronics 11, no. 2 (April 20, 1999): 165–70. http://dx.doi.org/10.20965/jrm.1999.p0165.

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We propose a concept for constructing an intelligent mobile system, stating why a new mobile architecture is needed in intelligent space. Intelligent space is expected to be an authentic future environment. Intelligent space is a room or area with sensors, a network, and computers. If the environment gets intelligence, it is no long a distinct part of an intelligent mobile system and the mobile system becomes a physical agent of intelligent space. Our experiments show what is possible for a mobile robot in intelligent space.

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9

Bin Rodzman, Shaiful Bakhtiar, Nordin Abu Bakar, Yun-Huoy Choo, Syed Ahmad Aljunid, Normaly Kamal Ismail, Nurazzah Abd Rahman, and Marshima Mohd Rosli. "I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 2 (February 1, 2020): 1021. http://dx.doi.org/10.11591/ijeecs.v17.i2.pp1021-1028.

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Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the students should study or do next in order to fully understand the subjects. Hence, the researchers propose an online learning environment called Intelligent Online Assessment and Revision (I-OnAR). It facilitates the learning process at multiple learning phases such as test creation, materials revision, feedback for improvement and performance analysis. These components are incorporated into the tutoring system to assist self-pace learning at anytime and anywhere. The intelligent agent uses a Rule-based Machine Learning method for the adaptive capabilities such as automated test creation and feedbacks for improvement. The system has been tested on a group of students and found to be useful to support learning process. The results have shown that 60% of the subjects’ performance have improved with the help of the system. The students were given feedbacks on the topic they did poorly as well as how to improve their performance. This proves that the Intelligent Online Assessment and revision (I-OnAR) can be a useful tool to help online students intelligently, systematically and efficiently. For the future works, the researchers would like to apply the usage of other techniques such as Fuzzy Logic to strengthen the analysis and decision of the current system.

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10

Alexander, Samuel Allen. "Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents." Journal of Artificial General Intelligence 10, no. 1 (January 1, 2019): 24–45. http://dx.doi.org/10.2478/jagi-2019-0003.

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Abstract Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg-Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant answer based on the following insight: we can view Legg-Hutter agents as candidates in an election, whose voters are environments, letting each environment vote (via its rewards) which agent (if either) is more intelligent. This leads to an abstract family of comparators simple enough that we can prove some structural theorems about them. It is an open question whether these structural theorems apply to more practical intelligence measures.

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11

Pan, Tiande. "Intelligent Monitoring System for Prison Perimeter Based on Cloud Intelligence Technology." Wireless Communications and Mobile Computing 2022 (March 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/2517446.

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In order to realize the security of prison perimeter, a prison perimeter intelligent monitoring system based on cloud intelligence technology is designed. Based on the multisupply chain collaboration framework, the prison network interface submodule and sniffer monitoring structure are connected on demand to complete the hardware execution environment of the prison perimeter intelligent monitoring system. Analyze the specific service mode of the cloud smart technology host, set the necessary cloud smart technology service monitoring protocol, judge the processing information parameters, select the prison perimeter remote communication port number, set the prison perimeter network IP address and password program, complete the construction of the software execution environment of the monitoring system, and intelligently monitor and track the abnormal conditions around the prison; combined with the relevant hardware and software structure, the design of prison perimeter intelligent monitoring system based on cloud intelligence technology is realized. The experimental results show that the DPI index of the designed system has an obvious upward trend, and the processing results are close to the original image results to avoid the impact caused by the change of monitoring scene.

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12

Nishida, Toyoaki. "Augmenting Conversational Environment." International Journal of Cognitive Informatics and Natural Intelligence 6, no. 4 (October 2012): 103–24. http://dx.doi.org/10.4018/jcini.2012100105.

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People are proficient in collaboratively forming and maintaining gatherings thereby shaping and cultivating collective thoughts through fluent conversational interactions. A big challenge is to develop a technology for augmenting the conversational environment so that people can conduct even better conversational interactions for collective intelligence and creation. Conversational informatics is a field of research that focuses on investigating conversational interactions and designing intelligent artifacts that can augment conversational interactions. The field draws on a foundation provided by artificial intelligence, natural language processing, speech and image processing, cognitive science, and conversation analysis. In this article, the author overviews a methodology for developing augmented conversational environment and major achievements. The author also discusses issues for making agents empathic so that they can induce sustained and constructive engagement with people.

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13

Khan, Manzoor Ahmed. "Intelligent Environment Enabling Autonomous Driving." IEEE Access 9 (2021): 32997–3017. http://dx.doi.org/10.1109/access.2021.3059652.

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14

Jerinic, Ljubomir, and Vladan Devedzic. "The friendly intelligent tutoring environment." ACM SIGCHI Bulletin 32, no. 1 (January 2000): 83–94. http://dx.doi.org/10.1145/333329.333353.

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15

Colton, Jonathan S., and John L. Dascanio. "An integrated, intelligent design environment." Engineering with Computers 7, no. 1 (December 1991): 11–22. http://dx.doi.org/10.1007/bf01208342.

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16

Pitkow, James E., and R. K. Jones. "Towards an intelligent publishing environment." Computer Networks and ISDN Systems 27, no. 6 (April 1995): 729–37. http://dx.doi.org/10.1016/0169-7552(95)00030-b.

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17

Masood, S. H., and B. S. Lim. "Concurrent intelligent rapid prototyping environment." Journal of Intelligent Manufacturing 6, no. 5 (October 1995): 291–310. http://dx.doi.org/10.1007/bf00124674.

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18

BENJAMIN, D. PAUL. "ON THE EMERGENCE OF INTELLIGENT GLOBAL BEHAVIORS FROM SIMPLE LOCAL ACTIONS." International Journal on Artificial Intelligence Tools 08, no. 03 (September 1999): 291–312. http://dx.doi.org/10.1142/s0218213099000208.

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Artificial Intelligence focuses on the question of how to design system to exhibit intelligent behaviour in complex environments. Complex global behaviours can emerge from simple systems acting in a complex environment; however, this emergence requires that the systems' internal structure reflect essential structures in the environment. This paper examines the algebraic structure of a system's actions. We find that these actions often possess a self-similar local neighborhood structure that permits analysis and synthesis to be performed locally yet produce global, intelligent behaviours. A procedure for finding this local structure is presented, and illustrated with examples.

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19

Zhang, Mingmin, Nan Xiang, Kangkan Wang, Zhigeng Pan, Haibo Yuan, and Houquan Liu. "Avatar-based Intelligent Navigation for Online Shanghai Expo." International Journal of Virtual Reality 9, no. 3 (January 1, 2010): 39–45. http://dx.doi.org/10.20870/ijvr.2010.9.3.2777.

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Shanghai Expo 2010 is an international event which will demonstrate the scientific, economic and cultural advance of the exhibiting countries. The local government launches a project named on-line Shanghai Expo in order to make the event accessible to people through Internet. Virtual reality technologies, especial intelligent virtual environment (IVE), are exploited to support the Expo. IVE, based on semantic, is the integration of Virtual Environment and Artificial Intelligence. It can improve the interaction between avatar and the virtual world by giving the objects in the environment semantic information. In this paper we employ intelligent virtual environment to build a virtual environment of realistic behavior and intelligent navigation.

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20

Wang, Zhengxin, Minghuan Shou, Shuai Wang, Ruinan Dai, and Keqian Wang. "An Empirical Study on the Key Factors of Intelligent Upgrade of Small and Medium-sized Enterprises in China." Sustainability 11, no. 3 (January 24, 2019): 619. http://dx.doi.org/10.3390/su11030619.

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Promoting the intelligent upgrades of small and medium-sized enterprises is one of the important tasks of implementing “Made in China 2025” in China. As a front runner of nation-level reform, Zhejiang Province has provided much room for innovation and development, along with the emergence of a new type of ecology, accelerated formation of two ecosystems and international cooperation, and a supportive policy environment. Therefore, this paper uses 173 Small and Medium-sized Enterprises (SMEs) from Zhejiang Province as the research objects, builds a binary selection model, and analyzes the dynamic and constraining mechanism of intelligent upgrades of SMEs with regard to employee qualification, technology, capital, policy environment, and so on. The study finds that: First, among three main industries, manufacturing is the major industry for the intelligent upgrades of SMEs and there are significant demonstration effects and industry heterogeneity. Secondly, the willingness to upgrade intelligently for SMEs is relatively strong. More than half of SMEs that have not intelligently upgraded show willingness to implement intelligent upgrades. Thirdly, factors such as corporate profitability, human capital quality, and industry intelligence level have significantly promoted the intelligent upgrades of SMEs, while the impact of labor cost, capital structure, government subsidies, and other variables are not significant. This conclusion still works after a number of robustness tests. Last but not least, based on the above conclusions, this paper proposes corresponding policy recommendations which are practically beneficial to the development of SMEs in China.

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21

Shi, Zhixing, and Shiyue Liu. "Intelligent Learning Environment and Future Development Tendency." Scientific and Social Research 3, no. 5 (November 3, 2021): 57–66. http://dx.doi.org/10.36922/ssr.v3i5.1196.

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In the recent years, intelligent learning environment replace the traditional learning environment gradually. Compare with the traditional learning environment, intelligent learning environment consider more about the learning experience of students, improve the communication between students and intelligent learning environment. One of the most paramount factors is intelligent tools in intelligent learning environment. These intelligent tools contain 5G communication technology, Mobile library, artificial intelligent and virtual reality. In this paper, we will mention the impact of these tools on intelligent learning environment, and how these tools influent students learning methods as well as teaching approach during the class. Besides, we still analyze the merits and disadvantages about intelligent tools. What is more, what kind of development will the intelligent tools going to happen in the future? We should deliberate it.

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Zhou, Xi, Mengnan Wang, Dexiang Deng, and Xi Li. "Design and Construction of Urban Waste Intelligent Treatment System." E3S Web of Conferences 199 (2020): 00011. http://dx.doi.org/10.1051/e3sconf/202019900011.

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With the rapid expansion of urban scale, urban waste disposal has become an important issue for ecological environment construction. In order to seek the coordinated development of economy and environment, we systematically intervene in urban waste intelligent treatment plans and management through design thinking and methods, and build urban waste intelligent treatment systems to achieve waste volume control, waste monitoring, classified collection, stacking and transportation, processing and Reprocessing production forms a controllable intelligent operation chain, which realizes the collaboration of human brain intelligence and artificial intelligence to improve the level of urban waste treatment and management capabilities.

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23

LEE, RAYMOND S. T. "iJADE AUTHENTICATOR — AN INTELLIGENT MULTIAGENT BASED FACIAL AUTHENTICATION SYSTEM." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 04 (June 2002): 481–500. http://dx.doi.org/10.1142/s0218001402001794.

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In modern consumer e-shopping environments, customer authentication is a critical process for confirming the identity of the customer. Traditional authentication techniques that rely on the customers to proactively identify themselves (using various schemes) can affect the user-friendliness of the e-shopping experience, and therefore reduce the customers' preference for such facilities. In this paper, we propose an innovative intelligent multiagent-based environment, called iJADE (intelligent Java Agent Development Environment) to provide an intelligent agent-based platform in the e-commerce environment. Contemporary agent development platforms are focused on the autonomy and mobility of the agents, whereas iJADE provides an intelligent layer (known as the "conscious layer") to implement various AI (artificial intelligence) functionalities in order to produce "smart" agents. From an implementation perspective, we introduce an innovative e-shopping authentication scheme called the "iJADE Authenticator", which is an invariant face recognition system that uses intelligent mobile agents. This system can provide fully automatic, mobile and reliable user authentication. More importantly, the authentication process can be carried out without the users necessarily being aware of it. Experimental results are presented for a database of 1020 tested face images obtained under conditions of widely varying facial expressions, viewing perspectives and image sizes. An overall average correct recognition rate of over 90% is attained.

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Lester, James C., Eun Y. Ha, Seung Y. Lee, Bradford W. Mott, Jonathan P. Rowe, and Jennifer L. Sabourin. "Serious Games Get Smart: Intelligent Game-Based Learning Environments." AI Magazine 34, no. 4 (December 15, 2013): 31–45. http://dx.doi.org/10.1609/aimag.v34i4.2488.

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Intelligent game-based learning environments integrate commercial game technologies with AI methods from intelligent tutoring systems and intelligent narrative technologies. This article introduces the CRYSTAL ISLAND intelligent game-based learning environment, which has been under development in the authors’ laboratory for the past seven years. After presenting CRYSTAL ISLAND, the principal technical problems of intelligent game-based learning environments are discussed: narrative-centered tutorial planning, student affect recognition, student knowledge modeling, and student goal recognition. Solutions to these problems are illustrated with research conducted with the CRYSTAL ISLAND learning environment.

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25

Ma, Yao. "Feasibility Analysis of Intelligent Piano in Piano Teaching." Scientific Programming 2022 (October 10, 2022): 1–8. http://dx.doi.org/10.1155/2022/5010428.

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With the rapid development of artificial intelligence, big data, blockchain, and other technologies, the impact of intelligent environment on the development of education has become more and more profound. Other developed countries have realized that education reform is urgent in the intelligent environment. So as to seize the major strategic opportunity of artificial intelligence development, my country has optimized the teaching content, teaching methods, and teaching methods of traditional piano teaching on the basis of respecting the traditional piano teaching concept. Upgrade to achieve the innovation of the relationship between teaching and learning in piano education in normal schools, and create a new situation for piano teaching in normal schools. Based on the current situation of piano education for musicology majors in normal schools, this paper takes the intelligent piano as the research object, compares the advantages and disadvantages of the application of smart pianos and traditional pianos in the environment of normal schools, combines the intelligent technology provided by smart pianos, and explores the application of technology to pianos in normal normal schools. The path of teaching reflects the value and use value of intelligent piano in piano teaching in normal schools and explores the value of intelligent piano teaching.

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Chun Wang. "Information Security in Intelligent Traffic Environment." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 10 (May 31, 2013): 1190–97. http://dx.doi.org/10.4156/aiss.vol5.issue10.139.

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Li, Shu Jiang, Chen Wang, Xiang Yu Ke, and Xiang Dong Wang. "The Intelligent Control of Greenhouse Environment." Applied Mechanics and Materials 427-429 (September 2013): 533–36. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.533.

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The greenhouse is an important part of facilities agriculture,also is one of the focus of the development of modern agriculture. Including temperature and humidity are the two most important environmental factors in greenhouse, nonlinear, strong coupling relationship between them, increasing the difficulty of greenhouse control. According to this complicated problem, this paper establishes a model of greenhouse temperature and humidity, studies a kind of model based fuzzy PID intelligent greenhouse control algorithm,and used MATLAB/simulink simulation platform, set up a simulation system. Results show that the control algorithm which solve the problem of strong coupling of temperature and humidity, and stable control of the greenhouse temperature and humidity. With a small amount of overshoot and fast convergence rate, etc. Satisfy the greenhouse nonlinear, big lag, multiple input, multiple output complex system control requirements.

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NOGUCHI, Noboru. "Intelligent Bioproduction System towards Environment Protection." Environment Control in Biology 47, no. 2 (2009): 111–20. http://dx.doi.org/10.2525/ecb.47.111.

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Khayut, Ben, Lina Fabri, and Maya Abukhana. "Intelligent User Interface in Fuzzy Environment." International Journal of Artificial Intelligence & Applications 5, no. 1 (January 31, 2014): 63–78. http://dx.doi.org/10.5121/ijaia.2014.5105.

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Wang, Jianyu, Xing Sheng, and Yingnan Dong. "Intelligent Environment System Based on CIM." Journal of Physics: Conference Series 1881, no. 4 (April 1, 2021): 042033. http://dx.doi.org/10.1088/1742-6596/1881/4/042033.

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Li, Guo Liang, Jian Li, and Zhen Jia. "New Intelligent-Environment Wood-Based Materials." Advanced Materials Research 113-116 (June 2010): 2296–98. http://dx.doi.org/10.4028/www.scientific.net/amr.113-116.2296.

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The objective of this paper is to apply the wood-based composite materials into the field of intelligent decorative materials or wooden crafts materials, and then improve people's life quality in the micro-environment. We introduce photochromic materials and the micro-capsule technology, and bring them into the processing field of wood-based composite materials, which make us find a new thinking direction for high value-added wood-based products. So that wood will be efficient and rational use of meeting demands of domestic and international market for intelligent and environment-friendly high-grade raw materials.

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Le Gal, C., J. Martin, A. Lux, and J. L. Crowley. "SmartOffice: design of an intelligent environment." IEEE Intelligent Systems 16, no. 4 (July 2001): 60–66. http://dx.doi.org/10.1109/5254.941359.

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Iassinovski, S. I., C. Raczy, and A. Artiba. "Intelligent simulation based decision support environment." Computers & Industrial Engineering 37, no. 1-2 (October 1999): 227–30. http://dx.doi.org/10.1016/s0360-8352(99)00061-3.

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Benkrid, K., S. Belkacemi, and A. Benkrid. "HIDE: A hardware intelligent description environment." Microprocessors and Microsystems 30, no. 6 (September 2006): 283–300. http://dx.doi.org/10.1016/j.micpro.2006.02.005.

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Foo, Schubert, Siu Cheung Hui, and Peng Chor Leong. "Web-based intelligent helpdesk-support environment." International Journal of Systems Science 33, no. 6 (January 2002): 389–402. http://dx.doi.org/10.1080/00207720210133642.

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Yanagida, Hiroaki. "Intelligent materials for environment and people." Materials & Design 21, no. 6 (December 2000): 507–9. http://dx.doi.org/10.1016/s0261-3069(00)00011-x.

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Kabanza, Froduald, Dominic Bourdua, and Goze Bénié. "Intelligent image analysis for environment monitoring." Advances in Environmental Research 5, no. 4 (November 2001): 327–35. http://dx.doi.org/10.1016/s1093-0191(01)00083-1.

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Mozer, M. C. "An Intelligent Environment Must Be Adaptive." IEEE Intelligent Systems and their Applications 14, no. 2 (March 1999): 11–13. http://dx.doi.org/10.1109/mis.1999.757623.

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Mahlawat, Shweta, O. P. Rishi, and Praveen Dhyani. "Intelligent Agents in Learning Environment ABDITS." International Journal of Computer Applications 127, no. 12 (October 15, 2015): 17–22. http://dx.doi.org/10.5120/ijca2015906550.

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Du, Jinsong, Wei Wang, Jie Gao, and Rigang Cong. "Distributed intelligent urban environment monitoring system." IOP Conference Series: Earth and Environmental Science 113 (February 2018): 012222. http://dx.doi.org/10.1088/1755-1315/113/1/012222.

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Wasfy, Ayman, Tamer Wasfy, and Ahmed Noor. "Intelligent virtual environment for process training." Advances in Engineering Software 35, no. 6 (June 2004): 337–55. http://dx.doi.org/10.1016/j.advengsoft.2004.04.005.

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Ehlers, Elizabeth M., Eugene van Rensburg, and Riaan L. van der Merwe. "Intelligent scheduling in the manufacturing environment." Computers & Industrial Engineering 27, no. 1-4 (September 1994): 31–34. http://dx.doi.org/10.1016/0360-8352(94)90230-5.

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Cowell, Laura, and John Williams. "Intelligent materials for the clinical environment." Infection, Disease & Health 21, no. 3 (November 2016): 132. http://dx.doi.org/10.1016/j.idh.2016.09.072.

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Ander, Veronika, Petr Cihelka, Jan Tyrychtr, and David Novák. "Towards Compromise User Experience Design in Ambient Intelligent Environment." Agris on-line Papers in Economics and Informatics 14, no. 2 (June 30, 2022): 3–13. http://dx.doi.org/10.7160/aol.2022.140201.

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Building, testing and evaluating UX for applications for Agricultural Ambient Intelligence Environments can be a difficult and time-consuming job. It can be an even longer and more challenging process due to their complexity and area of scope for complex intelligent systems. Many studies address the issue of UX design and evaluation of website user interface, mobiles, tangible equipment, wearable equipment and other, but it is necessary to look for UX deficiencies in all possible functions, every possible task. Depending on the structure of expert teams, experts’ opinions can vary broadly vary or may even contradict. This paper presents possibilities of use the Best-Compromise-Mean (BeCoMe) method for evaluation UX design. BeCoMe was not used for UX evaluation yet. Verification of whether the BeCoMe method is suitable for UX evaluation is carried out on a tablet using two prototypes of control panels of an intelligent environment.

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Santofimia, María J., Francisco Moya, Félix J. Villanueva, David Villa, and Juan C. López. "How Intelligent Are Ambient Intelligence Systems?" International Journal of Ambient Computing and Intelligence 2, no. 1 (January 2010): 66–72. http://dx.doi.org/10.4018/jaci.2010010106.

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Since the appearance of the Ambient Intelligence paradigm, as an evolution of the Ubiquitous Computing, a great deal of the research efforts in this ?eld have been mainly aimed at anticipating user actions and needs, out of a pre?xed set. However, Ambient Intelligence is not just constrained to user behaviour pattern matching, but to wisely supervise the whole environment, satisfying those unforeseen requirements or needs, by means of rational decisions. This work points at the lack of commonsense reasoning, as the main reason underlying the existance of these idiots savant systems, capable of accomplishing very speci?c and complex tasks, but incapable of making decisions out of the pre?xed behavioral patterns. This work advocates for the integration of the commonsense reasoning and understanding capabilities as the key elements in bridging the gap between idiot savant systems and real Ambient Intelligence systems.

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Lenka, Dr Reena Mahapatra. "The impact of Emotional intelligence in the Digital Age." Psychology and Education Journal 58, no. 1 (January 1, 2021): 1844–52. http://dx.doi.org/10.17762/pae.v58i1.1039.

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In today’s digital and automation obsessed world emotional intelligence is one important aspect which can differentiate a man from a machine. In this superbly technologically oriented world where most of us are crippled without a machine to help us it is a necessity for all of us to maintain our uniqueness in respect to machine. The uniqueness which differentiates us from a machine is our emotions towards different situations and people around us and how intelligently we handle these situations in a more human way. Simply put emotional intelligence is an aspect of human nature which helps all human being to understand themselves and others and try to overcome any problems or situations in a better way. Previously companies used to give more importance to IQ (Intelligent quotient) but now most of the companies are hiring those employees who are high on Emotional intelligence. The difference between intelligent quotient and emotional intelligence is that in intelligent quotient, people make smartdecisions irrespective of people’s feelings but in case of emotional intelligence, people make smart decisions by keeping people’s feelings in mind. The decision made by keeping in mind people’s feelings makes people happy and creates a happy and motivatedenvironment within the organization. Intelligent quotient is from birth but emotional intelligence depends on the environment we are born in and our surroundings and this can be changed according to the situation. In this digital age where the environment is constantly changing and full of challenges where people have stopped thinking about others feeling, emotional intelligence is the only way where people would start feeling a sense of belonginess, start being happy, relieved, motivated and start enjoying life to the fullest. This case study sheds light on the fact that emotional intelligence is very important in today’s automated world and also can also be a secret weapon which will help us survive and maintain our uniqueness before machine takes over human being in workplace.

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Singh, Amarjit, and Malcolm Carr. "Learning theories and environments: A student-initiated intelligent computer-assisted environment." Research in Science Education 22, no. 1 (December 1992): 367–76. http://dx.doi.org/10.1007/bf02356917.

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Ji, Wen, Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, and Yiqiang Chen. "Quality-time-complexity universal intelligence measurement." International Journal of Crowd Science 2, no. 1 (March 5, 2018): 18–26. http://dx.doi.org/10.1108/ijcs-01-2018-0003.

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Purpose With development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more and more autonomous and smart. Therefore, there is a growing demand to develop a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method. Design/methodology/approach This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents. Findings By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment. Practical implications In a crowd network, a number of intelligent agents are able to collaborate with each other to finish a certain kind of sophisticated tasks. The proposed approach can be used to allocate the tasks to the agents within a crowd network in an optimized manner. Originality/value This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

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SAVORY, PAUL A., and GERALD T. MACKULAK. "THE IMPACT OF INTELLIGENT TOOLS ON SIMULATION METHODOLOGY." International Journal of Software Engineering and Knowledge Engineering 06, no. 01 (March 1996): 135–58. http://dx.doi.org/10.1142/s0218194096000077.

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Simulation is one of the most effective techniques for analyzing stochastic systems. Recent computer software and hardware advances have had an important impact on the traditional discrete-event simulation methodology. Intelligent simulation environments consisting of integrated sets of “intelligent” tools for performing simulation studies have emerged. These tools significantly impact the methodology of a simulation analysis. This paper defines these intelligent tools and discusses how they alter the simulation paradigm by illustrating the development of a simulation model using an intelligent simulation environment. Special emphasis is on how an intelligent simulation environment provides a responsive analysis technique for studying manufacturing systems.

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Poza-Lujan, Jose-Luis, Juan-Luis Posadas-Yagüe, José-Enrique Simó-Ten, and Francisco Blanes. "Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities." Sensors 20, no. 1 (December 23, 2019): 112. http://dx.doi.org/10.3390/s20010112.

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Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. Smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). Smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2–4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices.

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