Human-Machine Interaction and Cognitronics

Rueckert, Ulrich

doi:10.1007/978-3-030-18338-7_28

The Frontiers Collection

2020

DOI: 10.1007/978-3-030-18338-7_28

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Human-Machine Interaction and Cognitronics

Ulrich Rueckert

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2022

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“…Companies are moving toward Internetconnected machines (Industrial Internet of Things, namely IIoT [3]) enabling mutual communication even when located in different production plants. Machines are equipped with a set of sensors monitoring different parameters such as vibration, noise, temperature, energy consumption, useful to predict machine failures thanks to Machine Learning algorithms [4,5] Another challenging issue leading the transition from Industry 4.0 to 5.0 is the paradigm of personalized human-machine interaction (HMI) [6], that implies exploiting user's biometric data to customize machine operation and improve on-board safety. Biometric recognition can be based either on face, iris, voice, finger or palm recognition.…”

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confidence: 99%

Smart retrofitting for human factors: a face recognition-based system proposal

Generosi

Agostinelli

Mengoni

2022

Int J Interact Des Manuf

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Industry nowadays must deal with the so called “fourth industrial revolution”, i.e. Industry 4.0. This revolution is based on the introduction of new paradigms in the manufacturing industry such as flexibility, efficiency, safety, digitization, big data analysis and interconnection. However, human factors’ integration is usually not considered, although included as one of the paradigms. Some of these human factors’ most overlooked aspects are the customization of the worker’s user experience and on-board safety. Moreover, the issue of integrating state of the art technologies on legacy machines is also of utmost importance, as it can make a considerable difference on the economic and environmental aspects of their management, by extending the machine’s life cycle. In response to this issue, the Retrofitting paradigm, the addition of new technologies to legacy machines, has been considered. In this paper we propose a novel modular system architecture for secure authentication and worker’s log-in/log-out traceability based on face recognition and on state-of-the-art Deep Learning and Computer Vision techniques, as Convolutional Neural Networks. Starting from the proposed architecture, we developed and tested a device designed to retrofit legacy machines with such capabilities, keeping particular attention to the interface usability in the design phase, little considered in retrofitting applications along with other Human Factors, despite being one of the pillars of Industry 4.0. This research work’s results showed a dramatic improvement regarding machines on-board access safety.

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mentioning

confidence: 99%

Smart retrofitting for human factors: a face recognition-based system proposal

Generosi

Agostinelli

Mengoni

2022

Int J Interact Des Manuf

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Human-Machine Interaction and Cognitronics

Cited by 1 publication

References 15 publications

Smart retrofitting for human factors: a face recognition-based system proposal

Smart retrofitting for human factors: a face recognition-based system proposal

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