Artificial intelligence in wine-making

OENO One ◽  
2000 ◽  
Vol 34 (2) ◽  
pp. 61
Author(s):  
Pierre Grenier ◽  
Inmaculada Álvarez ◽  
Jean-Marie Roger ◽  
Vincent Steinmetz ◽  
Pierre Barre ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Food Industry ◽  
Recent Progress ◽  
Statistical Processing ◽  
Wine Making ◽  
Process Diagnosis ◽  
Measurement Systems ◽  
Knowledge Based ◽  
Potential Applications ◽  
Areas Of Concern

<p style="text-align: justify;">In this paper, some terms of Artificial Intelligence are defined. Some present and potential applications of knowledge based systems are presented in the field of wine-making. Areas of concern were: multi sensor fusion, prediction by model cooperation, and diagnosis. Artificial intelligence techniques can indeed be applied for aiding the wine-maker in his choices. They facilitate the combination between experience and recent progress in technology. When associated with statistical processing, they allow knowledge sources to be used more effectively. Beyond wine-making, the prospects of artificial intelligence are promising for research and food industry, especially for improving the robustness of measurement systems (multi-sensors, sensors interpreted or validated by models), and for process diagnosis (risk prediction, action proposal).</p>

Decision Support Systems and their Application in Construction

2011 ◽  
pp. 276-298
Author(s):  
Alaa Abdou ◽  
Moh’d Radaideh ◽  
John Lewis
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support Systems ◽  
Construction Industry ◽  
Support Systems ◽  
Integrated Systems ◽  
The Internet ◽  
Research Projects ◽  
Knowledge Based ◽  
Potential Applications

Decisions are activities that we face and deal with every day. Decision support systems are used to support and improve decision making. They help people make better and faster decisions than they could make themselves. The construction industry witnessed a growth in the application of knowledge-based expert systems in the eighties and early nineties, followed by the application of fuzzy, artificial neural networks and hybrid (integrated) systems. Potential applications of the Internet in the construction industry have generated many research projects recently. The purpose of this chapter is to understand decision support systems and their basic technologies, and to review their application in the construction industry. The construction industry is rapidly realising the need to integrate information technology and artificial intelligence into its processes in order to remain competitive.

Decision Support Systems and their Application in Construction

2010 ◽  
pp. 1024-1042 ◽  
Author(s):  
Alaa Abdou ◽  
Moh’d Radaideh ◽  
John Lewis
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support Systems ◽  
Construction Industry ◽  
Support Systems ◽  
Integrated Systems ◽  
The Internet ◽  
Research Projects ◽  
Knowledge Based ◽  
Potential Applications

Decisions are activities that we face and deal with every day. Decision support systems are used to support and improve decision making. They help people make better and faster decisions than they could make themselves. The construction industry witnessed a growth in the application of knowledge-based expert systems in the eighties and early nineties, followed by the application of fuzzy, artificial neural networks and hybrid (integrated) systems. Potential applications of the Internet in the construction industry have generated many research projects recently. The purpose of this chapter is to understand decision support systems and their basic technologies, and to review their application in the construction industry. The construction industry is rapidly realising the need to integrate information technology and artificial intelligence into its processes in order to remain competitive.

Decision Support Systems and their Application in Construction

2011 ◽  
pp. 1285-1303
Author(s):  
Alaa Abdou ◽  
Moh’d Radaideh ◽  
John Lewis
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support Systems ◽  
Construction Industry ◽  
Support Systems ◽  
Integrated Systems ◽  
The Internet ◽  
Research Projects ◽  
Knowledge Based ◽  
Potential Applications

Decisions are activities that we face and deal with every day. Decision support systems are used to support and improve decision making. They help people make better and faster decisions than they could make themselves. The construction industry witnessed a growth in the application of knowledge-based expert systems in the eighties and early nineties, followed by the application of fuzzy, artificial neural networks and hybrid (integrated) systems. Potential applications of the Internet in the construction industry have generated many research projects recently. The purpose of this chapter is to understand decision support systems and their basic technologies, and to review their application in the construction industry. The construction industry is rapidly realising the need to integrate information technology and artificial intelligence into its processes in order to remain competitive.

scholarly journals Toward autonomous design and synthesis of novel inorganic materials

2021 ◽  
Author(s):  
Nathan Szymanski ◽  
Yan Zeng ◽  
Haoyan Huo ◽  
Chris Bartel ◽  
Haegyum Kim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Recent Progress ◽  
Inorganic Materials ◽  
Design And Synthesis ◽  
Exciting Opportunity

Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including...

scholarly journals Application of Artificial Intelligence in Food Industry—a Guideline

2021 ◽  
Author(s):  
Nidhi Rajesh Mavani ◽  
Jarinah Mohd Ali ◽  
Suhaili Othman ◽  
M. A. Hussain ◽  
Haslaniza Hashim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Food Industry ◽  
Near Infrared ◽  
Vision System ◽  
Electronic Tongue ◽  
World Population ◽  
Computer Vision System ◽  
The Past

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.

scholarly journals Deep learning-enabled medical computer vision

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andre Esteva ◽  
Katherine Chou ◽  
Serena Yeung ◽  
Nikhil Naik ◽  
Ali Madani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Medical Imaging ◽  
Real World ◽  
Recent Progress ◽  
Medical Applications ◽  
Modern Computer ◽  
Medical Computer

AbstractA decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

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