A Cognitive Assistant for Operators: AI-Powered Knowledge Sharing on Complex Systems

IF 1.6 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Pervasive Computing Pub Date : 2023-01-01 DOI:10.1109/MPRV.2022.3218600

Samuel Kernan Freire, Sara Panicker, Santiago Ruiz-Arenas, Z. Rusák, E. Niforatos

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引用次数: 7

Abstract

Operating a complex and dynamic system, such as an agile manufacturing line, is a knowledge-intensive task. It imposes a steep learning curve on novice operators and prompts experienced operators to continuously discover new knowledge, share it, and retain it. In practice, training novices is resource-intensive, and the knowledge discovered by experts is not shared effectively. To tackle these challenges, we developed an AI-powered pervasive system that provides cognitive augmentation to users of complex systems. We present an AI cognitive assistant that provides on-the-job training to novices while acquiring and sharing (tacit) knowledge from experts. Cognitive support is provided as dialectic recommendations for standard work instructions, decision-making, training material, and knowledge acquisition. These recommendations are adjusted to the user and context to minimize interruption and maximize relevance. In this article, we describe how we implemented the cognitive assistant, how it interacts with users, its usage scenarios, and the challenges and opportunities.

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操作员的认知助手:复杂系统上的人工智能知识共享

操作一个复杂的动态系统，如敏捷生产线，是一项知识密集型任务。它对新手操作人员施加了陡峭的学习曲线，并促使有经验的操作人员不断发现新知识，分享并保留它。在实践中，培训新手是资源密集型的，专家发现的知识没有得到有效的共享。为了应对这些挑战，我们开发了一个人工智能驱动的普适系统，为复杂系统的用户提供认知增强。我们介绍了一种人工智能认知助手，它可以为新手提供在职培训，同时从专家那里获取和分享(隐性)知识。认知支持作为对标准工作指导、决策、培训材料和知识获取的辩证建议提供。这些建议根据用户和上下文进行调整，以最大限度地减少干扰并最大化相关性。在本文中，我们将描述如何实现认知助手，它如何与用户交互，它的使用场景，以及挑战和机遇。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Pervasive Computing 工程技术-电信学

CiteScore

4.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： IEEE Pervasive Computing explores the role of computing in the physical world–as characterized by visions such as the Internet of Things and Ubiquitous Computing. Designed for researchers, practitioners, and educators, this publication acts as a catalyst for realizing the ideas described by Mark Weiser in 1988. The essence of this vision is the creation of environments saturated with sensing, computing, and wireless communication that gracefully support the needs of individuals and society. Many key building blocks for this vision are now viable commercial technologies: wearable and handheld computers, wireless networking, location sensing, Internet of Things platforms, and so on. However, the vision continues to present deep challenges for experts in areas such as hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, data science, and societal issues including privacy and ethics. Through special issues, the magazine explores applications in areas such as assisted living, automotive systems, cognitive assistance, hardware innovations, ICT4D, manufacturing, retail, smart cities, and sustainability. In addition, the magazine accepts peer-reviewed papers of wide interest under a general call, and also features regular columns on hot topics and interviews with luminaries in the field.