Engineering human-in-the-loop interactions in cyber-physical systems

Gil, Míriam; Albert, Manoli; Fons, Joan; Pelechano, Vicente

doi:10.1016/j.infsof.2020.106349

Cited by 37 publications

(24 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A key approach to system intelligence augmentation by SAS is via symbiotic knowledge learning for autonomous problem solving. Knowledge learning helps to extend the state space of mind as the foundation for creativity and wisdom generation, while autonomous problem solving enables an SAS to generate intelligent behaviours at run-time as a counterpart of humans in the loop [16,23,33,34]. Definition 4.1.…”

Section: Symbiotic Autonomous Systemsmentioning

confidence: 99%

On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems

Wang

Karray

Plataniotis

et al. 2021

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human–machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, cognitive computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via autonomous knowledge learning systems that symbiotically work between humans and cognitive robots. This article is part of the theme issue ‘Towards symbiotic autonomous systems'.

show abstract

Section: Symbiotic Autonomous Systemsmentioning

confidence: 99%

On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems

Wang

Karray

Plataniotis

et al. 2021

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

show abstract

“…13 HiL prototype with a MAPE-K control loop adaptation plan (7). Finally, the effectors perform the changes within the running system (8) to obtain the next system configuration at t n + 1 , which is a configuration that is less obtrusive than the previous one.…”

Section: Adaptation Example: Decreasing the Obtrusiveness Level Of Thmentioning

confidence: 99%

“…Definitively, I would use this design method to design HiL interactions ITU2 I intend to use this design method in the case I would have to design HiL interactions in the future It contained the description of the Takeover task. 8 In order to shorten the evaluation process, we provided the subjects with an example of the Handover task (in this task, the driver gives the order to the system for it takes over control of the car) designed with our method to guide the design of the Takeover task.…”

Section: Experimental Contextmentioning

confidence: 99%

“…This technique is built under the premise of managing human attention in a way that achieves human-in-the-loop interactions that get the human's attention and avoid obtrusiveness. In [7,8], the authors introduced a conceptual framework to model human-in-the-loop interactions, which is consolidated in this paper. Based on this conceptual framework, the proposal is extended with a software infrastructure that helps designers to easily and automatically obtain a "smart" prototype from the human-system collaboration design.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling and “smart” prototyping human-in-the-loop interactions for AmI environments

Gil

Albert

Fons

et al. 2021

Pers Ubiquit Comput

Self Cite

View full text Add to dashboard Cite

Autonomous capabilities are required in AmI environments in order to adapt systems to new environmental conditions and situations. However, keeping the human in the loop and in control of such systems is still necessary because of the diversity of systems, domains, environments, context situations, and social and legal constraints, which makes full autonomy a utopia within the short or medium term. Human-system integration introduces an important number of challenges and problems that have to be solved. On the one hand, humans should interact with systems even in those situations where their attentional, cognitive, and physical resources are limited in order to perform the interaction. On the other hand, systems must avoid overwhelming the user with unnecessary actions. Therefore, appropriate user-centered methods for AmI development should be used to help designers analyze and design human-in-the-loop interactions in AmI environments. This paper presents a user-centered design method that defines a process with a set of tools and techniques that supports the process steps in order to systematically design, prototype, and validate human-in-the-loop (HiL) solutions. The process starts with the definition of the HiL design, which defines how the system cooperates with the human. This HiL design is built using a conceptual framework that focuses on achieving human-system interactions that get human attention and avoid obtrusiveness. Then, we provide a software infrastructure to generate a prototype based on the HiL design and validate it by having end-users use a web simulator. The feedback data generated during the prototype user validation is gathered and used by a machine learning tool that infers the user’s needs and preferences. Finally, these inferences are used to automatically enhance the human-in-the-loop designs and prototypes. We have validated the proposed method through a twofold perspective: an experiment to analyze the perception of interaction designers regarding their acceptance of the design method and another experiment to evaluate the usefulness of the “smart” prototyping technique. The results obtained point out the acceptability of the proposed method by designers and the useful adaptations provided by the “smart” prototyping technique to achieve a HiL design that adapts well to users’ preferences and needs.

show abstract

“…It is, especially, important in the manufacturing to consider the human-in-the-loop challenge to provide a good user experience for the purpose of achieving the task's goal successfully and efficiently. A rule of thumb for designing interactions is to ensure user participation, provide a natural and understandable collaboration, and avoid disturbing users [16]. e basis of the graphical user interface (GUI) is the fact that recognition is easier than recall [17].…”

Section: Related Workmentioning

confidence: 99%

A Lightweight Application for Reading Digital Measurement and Inputting Condition Assessment in Manufacturing Industry

Jwo

Lin

Lee

et al. 2021

Mobile Information Systems

View full text Add to dashboard Cite

There is a vast need for the use of digital display instruments in the manufacturing industry due to the simple operation and high precision. In addition to the numerical data acquisition, it is usually necessary to input additional text for the condition assessment as well. However, since most of these measure instruments do not provide any interfaces for users to access the values and it often lacks proper devices to input the text during the working process, these two tasks are highly human intensive under current conditions. In order to facilitate the smooth running of the work for operators, we propose a lightweight application which can be installed on smartphones or wearable devices using multidigit recognition and speech recognition techniques without changing too much of their workflow. The experimental results demonstrate that our approach can achieve high accuracy. Thus, the proposed solution can effectively resolve data input issues in the manufacturing sites, thereby reducing human labor, increasing productivity, and automating part of the process. Taking operators’ existing workflow into consideration for design can provide an application with an easy learning curve. Moreover, with the rapid and economical approach, companies can financially benefit from the development of this low-cost application, especially for small- and medium-sized enterprises.

show abstract

Engineering human-in-the-loop interactions in cyber-physical systems

Cited by 37 publications

References 71 publications

On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems

On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems

Modeling and “smart” prototyping human-in-the-loop interactions for AmI environments

A Lightweight Application for Reading Digital Measurement and Inputting Condition Assessment in Manufacturing Industry

Contact Info

Product

Resources

About