Self-configuration in humanized Cyber-Physical Systems

Bordel, Borja; Alcarria, Ramón; Martín, Diego; Robles, Tomás; Rivera, Diego

doi:10.1007/s12652-016-0410-3

Cited by 26 publications

(5 citation statements)

References 19 publications

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“…For example, there are articles about how to humanize process models and definitions [10]. Moreover, self-configuration technologies for humanized systems [27] may also be found.…”

Section: State Of the Artmentioning

confidence: 99%

People-as-a-Service Dilemma: Humanizing Computing Solutions in High-Efficiency Applications

Bordel¹,

Hernández²

2019

13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

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Next-generation computing solutions, such as cyber-physical systems or Industry 4.0, are focused on increasing efficiency in process execution as much as possible. Removing unproductive delays or keeping infrastructures operating at their total capacity are typical objectives in these future systems. Decoupling infrastructure providers and service providers using Anything-as-a-Service (XaaS) paradigms is one of the most common approaches to address this challenge. However, many real scenarios not only include machines or controllers but also people and workers. In this case, deploying process execution algorithms and XaaS solutions degenerates in a People-as-a-Service scenario, which poses a critical dilemma: Can highly efficient production scenarios guarantee people’s wellbeing? In this paper, we address this problem and propose a new process execution algorithm based on a novel understanding of efficiency. In this case, a humanized efficiency definition combining traditional efficiency ratios and wellbeing indicators is used to allocate tasks and assign them to different existing workers. In order to evaluate the proposed solution, a simulation scenario including social and physical elements was built. Using this scenario, a first experimental validation was carried out.

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“…For example, there are articles about how to humanize process models and definitions [10]. Moreover, self-configuration technologies for humanized systems [27] may also be found.…”

Section: State Of the Artmentioning

confidence: 99%

People-as-a-Service Dilemma: Humanizing Computing Solutions in High-Efficiency Applications

Bordel¹,

Hernández²

2019

13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

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“…Thus, for these craft industrial scenarios, heterogenous pervasive sensing platforms are investigated as a possible valid alternative [9,11]. In these platforms, although cameras may be included, we typically find low-cost sensors such as accelerometers and RFID tags and readers integrated into wearables, Bluetooth beacon devices for indoor positioning, or passive infrared sensors to control the workers movement [12,13].…”

Section: Introductionmentioning

confidence: 99%

Recognizing human activities in Industry 4.0 scenarios through an analysis-modeling- recognition algorithm and context labels

Bordel

2021

ICA

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Activity recognition technologies only present a good performance in controlled conditions, where a limited number of actions are allowed. On the contrary, industrial applications are scenarios with real and uncontrolled conditions where thousands of different activities (such as transporting or manufacturing craft products), with an incredible variability, may be developed. In this context, new and enhanced human activity recognition technologies are needed. Therefore, in this paper, a new activity recognition technology, focused on Industry 4.0 scenarios, is proposed. The proposed mechanism consists of different steps, including a first analysis phase where physical signals are processed using moving averages, filters and signal processing techniques, and an atomic recognition step where Dynamic Time Warping technologies and k-nearest neighbors solutions are integrated; a second phase where activities are modeled using generalized Markov models and context labels are recognized using a multi-layer perceptron; and a third step where activities are recognized using the previously created Markov models and context information, formatted as labels. The proposed solution achieves the best recognition rate of 87% which demonstrates the efficacy of the described method. Compared to the state-of-the-art solutions, an improvement up to 10% is reported.

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“…Dense environments where thousands of agents with heterogeneous capabilities are deployed and working together are the most common application scenarios for Industry 4.0. This context, furthermore, can get more complex if humans are considered (Bordel et al, 2017c). In fact, Industry 4.0 is inclusive, and many manufacturing companies produce handmade products where human labour is essential.…”

Section: Introductionmentioning

confidence: 99%

“…Production systems including humans are even more heterogenous, as people's behaviour is very variable and dynamic. And, obviously, human agents are not externally controllable (Bordel et al, 2017c). Thus, in Industry 4.0, complex tasks and services are provided through the choreographed coordination of heterogenous agents acting in an autonomous way (Bordel et al, 2018a).…”

Section: Introductionmentioning

confidence: 99%

Controlling Supervised Industry 4.0 Processes through Logic Rules and Tensor Deformation Functions

Bordel¹,

Alcarria²,

Robles³

2021

Informatica

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Self-configuration in humanized Cyber-Physical Systems

Cited by 26 publications

References 19 publications

People-as-a-Service Dilemma: Humanizing Computing Solutions in High-Efficiency Applications

People-as-a-Service Dilemma: Humanizing Computing Solutions in High-Efficiency Applications

Recognizing human activities in Industry 4.0 scenarios through an analysis-modeling- recognition algorithm and context labels

Controlling Supervised Industry 4.0 Processes through Logic Rules and Tensor Deformation Functions

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