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实现一种混合智能系统,以评估人机界面中交互渠道使用的有效性。

Implementation of a Hybrid Intelligence System Enabling the Effectiveness Assessment of Interaction Channels Use in HMI.

机构信息

Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland.

Weegree Sp. z o.o. S.K., 45-018 Opole, Poland.

出版信息

Sensors (Basel). 2023 Apr 8;23(8):3826. doi: 10.3390/s23083826.

DOI:10.3390/s23083826
PMID:37112173
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10140840/
Abstract

The article presents a novel idea of Interaction Quality Sensor (IQS), introduced in the complete solution of Hybrid INTelligence (HINT) architecture for intelligent control systems. The proposed system is designed to use and prioritize multiple information channels (speech, images, videos) in order to optimize the information flow efficiency of interaction in HMI systems. The proposed architecture is implemented and validated in a real-world application of training unskilled workers-new employees (with lower competencies and/or a language barrier). With the help of the HINT system, the man-machine communication information channels are deliberately chosen based on IQS readouts to enable an untrained, inexperienced, foreign employee candidate to become a good worker, while not requiring the presence of either an interpreter or an expert during training. The proposed implementation is in line with the labor market trend, which displays significant fluctuations. The HINT system is designed to activate human resources and support organizations/enterprises in the effective assimilation of employees to the tasks performed on the production assembly line. The market need of solving this noticeable problem was caused by a large migration of employees within (and between) enterprises. The research results presented in the work show significant benefits of the methods used, while supporting multilingualism and optimizing the preselection of information channels.

摘要

本文提出了一种新颖的交互质量传感器(IQS)的概念,该传感器在混合智能(HINT)架构的完整解决方案中被引入,用于智能控制系统。该系统旨在使用和优先考虑多个信息渠道(语音、图像、视频),以优化人机交互系统中的信息流效率。所提出的架构在培训非熟练工人-新员工(技能较低和/或存在语言障碍)的实际应用中得到了实现和验证。借助 HINT 系统,根据 IQS 的读数故意选择人机通信信息渠道,以使未经培训、没有经验的外国员工候选人能够成为一名优秀的工人,而在培训过程中无需口译员或专家在场。所提出的实现符合劳动力市场的趋势,该趋势显示出显著的波动。HINT 系统旨在激活人力资源,并支持组织/企业有效地将员工融入到生产装配线上执行的任务中。解决这个明显问题的市场需求是由企业内部(和企业之间)员工的大量流动引起的。工作中提出的研究结果表明所使用方法的显著优势,同时支持多语言并优化信息渠道的预选。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/379a21456b4e/sensors-23-03826-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/6302d6d37a96/sensors-23-03826-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/abf8e4ec8db4/sensors-23-03826-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/9125b7858284/sensors-23-03826-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/4842645abaa3/sensors-23-03826-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/146b06ae0d81/sensors-23-03826-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/bef104541958/sensors-23-03826-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/2ed073711d3d/sensors-23-03826-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/5c469bdee665/sensors-23-03826-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/379a21456b4e/sensors-23-03826-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/6302d6d37a96/sensors-23-03826-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/abf8e4ec8db4/sensors-23-03826-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/9125b7858284/sensors-23-03826-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/4842645abaa3/sensors-23-03826-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/146b06ae0d81/sensors-23-03826-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/bef104541958/sensors-23-03826-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/2ed073711d3d/sensors-23-03826-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/5c469bdee665/sensors-23-03826-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e87c/10140840/379a21456b4e/sensors-23-03826-g009.jpg

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