Automation Potential and Artificial Intelligence

This Fact Sheet highlights the automation potential in the Mountain West states (Nevada, Utah, Arizona, New Mexico, and Colorado) and its metropolitan statistical areas using the findings of Automation and Artificial Intelligence: How machines are affecting people and places, a report by the Brookings Institution

Application of artificial intelligence technology in electrical automation

with the vigorous development of artificial intelligence technology, it has quietly entered all fields of human life and production, especially the application of artificial intelligence technology in the field of electrical automation has greatly improved the quality and effi ciency of electrical automation, which shows that artifi cial intelligence technology has a bright future. Therefore, this paper focuses on the advantages, strategies and specific applications of artificial intelligence technology in electrical automation, in order to provide eff ective reference and reference for maximizing the level of electrical automation intelligence, so as to contribute to the vigorous development of artifi cial intelligence technology in the future

Automation and Artificial Intelligence in Software Engineering: Experiences, Challenges, and Opportunities

Automation and Artificial Intelligence have a transformative influence on many sectors, and software engineers are the actors who engineer this transformation. On the other hand, there is little knowledge of how automation and Artificial Intelligence impact software engineering practice. To answer this question, we conducted semi-structured interviews with experienced software practitioners across frontend and backend development, DevOps, R&D, integration, and leadership positions. Our findings reveal 1) automation to appear as micro-automation in the sense of automation of tiny and specific tasks, 2) automation as a side product of work, and bottom-up driven in software engineering, and 3) automation as a possible cause for cognitive overhead due to automatically generated notifications. Furthermore, we notice that our interview participants do not expect automation and artificial intelligence tools to substantially change software engineering\u27s essence in the foreseeable future

Artificial intelligence and space power systems automation

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development

An overview of the program to place advanced automation and robotics on the Space Station

The preliminary design phase of the Space Station has uncovered a large number of potential uses of automation and robotics, most of which deal with the assembly and operation of the Station. If NASA were to vigorously push automation and robotics concepts in the design, the Station crew would probably be free to spend a substantial portion of time on payload activities. However, at this point NASA has taken a conservative attitude toward automation and robotics. For example, the belief is that robotics should evolve through telerobotics and that uses of artificial intelligence should be initially used in an advisory capacity. This conservativeness is in part due to the new and untested nature of automation and robotics; but, it is also due to emphases plased on designing the Station to the so-called upfront cost without thoroughly understanding the life cycle cost. Presumably automation and robotics has a tendency to increase the initial cost of the Space Station but could substantially reduce the life cycle cost. To insure that NASA will include some form of robotic capability, Congress directed to set aside funding. While this stimulates the development of robotics, it does not necessarily stimulate uses of artificial intelligence. However, since the initial development costs of some forms of artificial intelligence, such as expert systems, are in general lower than they are for robotics one is likely to see several expert systems being used on the Station

Evolution towards Smart Optical Networking: Where Artificial Intelligence (AI) meets the World of Photonics

Smart optical networks are the next evolution of programmable networking and programmable automation of optical networks, with human-in-the-loop network control and management. The paper discusses this evolution and the role of Artificial Intelligence (AI)

PALANG PINTU OTOMATIS BERBASIS WEBCAM DENGAN PROGRAM RASPBERRY PI 3

Artificial intelligence is highly demand in this modern world, human cannot be separated with the technology in now days, and the evolution of the technology, especially for artificial intelligence, are unstoppable. The artificial intelligence application is more wider, business transportation sector is one of the many sector are involve to using this technology. One of the example is the automation and detection license plate of the vehicle. Like in this research, the detection of license plate are using raspberry pi 3b connected with Arduino uno using serial communication, and for the image catcher, using 720p webcamera. In this research, we are using deep neural network method to do image processing, it refer to 300 images of data training, the training data using google collab, with yolov4-tinyy metho

Application of algorithms in newsrooms

Professional project report submitted in partial fulfillment of the requirements for the degree of Masters of Arts in Journalism from the School of Journalism, University of Missouri--Columbia.This research examines how early journalistic adopters of algorithms gained skills necessary to work with automation and artificial intelligence in newsrooms. The researcher conducted semi-structured interviews with eight journalists from medium to large news organizations. The research identified three key findings: Not every journalist needs to learn skills related to automation and artificial intelligence but having a basic understanding of what they are and their capabilities would be beneficial. It is more about learning those skills at conceptual levels without having to learn highly technical mathematics and statistics behind automation and artificial intelligence. Knowledge about common failures of automation and artificial intelligence or being able to see where things can go wrong is as equally important as technical and professional skills

Human in the AI loop via xAI and Active Learning for Visual Inspection

Industrial revolutions have historically disrupted manufacturing by introducing automation into production. Increasing automation reshapes the role of the human worker. Advances in robotics and artificial intelligence open new frontiers of human-machine collaboration. Such collaboration can be realized considering two sub-fields of artificial intelligence: active learning and explainable artificial intelligence. Active learning aims to devise strategies that help obtain data that allows machine learning algorithms to learn better. On the other hand, explainable artificial intelligence aims to make the machine learning models intelligible to the human person. The present work first describes Industry 5.0, human-machine collaboration, and state-of-the-art regarding quality inspection, emphasizing visual inspection. Then it outlines how human-machine collaboration could be realized and enhanced in visual inspection. Finally, some of the results obtained in the EU H2020 STAR project regarding visual inspection are shared, considering artificial intelligence, human digital twins, and cybersecurity