Human-machine Interaction Model Research Articles

Human-machine interaction with intelligent machine learning algorithms for smart classrooms

ABSTRACT The modern technology of learning and teaching in education has moved on to smart classes. The introduction of artificial intelligence (AI) in the education sector has essentially taken over traditional classrooms and transformed how education leads to admiration. Various data types, such as videos, images, sound, text, and biometric data like eye-tracking potentially captured through smart classrooms, pose new issues and challenges for artificial intelligence algorithms. Hence, this paper suggests the Machine Learning Assisted Intelligent Human-Machine Interaction (MLIHMI) model for the smart classroom monitoring system. The real-time interactive dimension signifies the capability to support the Smart classroom’s teaching and human-computer interactions, including smooth interaction, convenient operation, and interactive monitoring. This paper used ML and HMI models to introduce a new effective database for online learning and smart classroom environments utilising the learners’ body postures, facial expressions, and hand gestures. The numerical findings show that the suggested system achieves less error rate of 10.1% and enhances the accuracy rate of 96.5%, with the highest classification ratio of 95.6%, prediction rate of 93.6%, the detection rate of 97.3%, and engagement rate of 81.3% in student gesture and postures recognition and the identification of facial expressions with the high performance of 93.3% when compared to other existing models.

Modeling Interaction in Human–Machine Systems: A Trust and Trustworthiness Approach

Trust has been clearly identified as a key concept for human–machine interaction (HMI): on the one hand, users should trust artificial systems; on the other hand, devices must be able to estimate both how much other agents trust them and how trustworthy the other agents are. Indeed, the applications of trust in these scenarios are so complex that often, the interaction models consider only a part of the possible interactions and not the system in its entirety. On the contrary, in this work, we made the effort to consider the different types of interaction together, showing the advantages of this approach and the problems it allows to face. After the theoretical formalization, we introduce an agent simulation to show the functioning of the proposed model. The results of this work provide interesting insights for the evolution of HMI models.

Hip-Knee Coupling Exoskeleton With Offset Theory for Walking Assistance.

To alleviate the influence of aging on the elderly, a hip–knee coupling exoskeleton with offset theory is designed in this article to improve people’s athletic ability. With the novel design, the unique application strategy of the offset principle for hip and knee joints is developed, and a hip–knee coupling mechanism is proposed to solve the discrete power assistance problem for the knee joint. To acquire the success of the design, the mathematical model of the coupling mechanism is established to optimize the load environment of the exoskeleton system, and furthermore, an algorithm adapted to human movement is proposed to determine the monotonicity of the cam profiles. For the selection of the elastic parameters in the coupling mechanism, the sensitivity condition is proposed, and the human–machine interaction model of the KESM is further established. A man–machine coupling model was used to verify the scientificity of the exoskeleton design, and the comparison between the joint powers with or without exoskeleton indicated that the exoskeleton theoretically saved at least 20% of the human body’s energy.

Intelligent interaction model for battleship control based on the fusion of target intention and operator emotion

Due to the complexity of situation information and the diversity of display modes, the traditional battleship information system cannot provide the operator with important information effectively, which leads to its low ability to express the details of target intentions. Therefore, taking air targets as the main research object, this paper proposes a battleship human-machine intelligent interaction model based on the fusion of target intention and operator emotion. The model mainly includes four modules: the intention recognition of the target, the emotion cognition of the operator, the fusion of the intention and the emotion, and the interactive visualization. The goal is to provide a personalized human-machine interaction scheme that can realize auxiliary decision-making and man-machine integration intelligence according to the target intention and the operator's emotion. Finally, the evaluation results have demonstrated the feasibility and reliability of the proposed model.

Human–Machine Collaboration for Automated Driving Using an Intelligent Two‐Phase Haptic Interface

Prior to realizing fully autonomous driving, human intervention is periodically required to guarantee vehicle safety. This poses a new challenge in human–machine interaction, particularly during the control authority transition from automated functionality to a human driver. Herein, this challenge is addressed by proposing an intelligent haptic interface based on a newly developed two‐phase human–machine interaction model. The intelligent haptic torque is applied to the steering wheel and switches its functionality between predictive guidance and haptic assistance according to the varying state and control ability of human drivers. This helps drivers gradually resume manual control during takeover. The developed approach is validated by conducting vehicle experiments with 26 participants. The results suggest that the proposed method effectively enhances the driving state recovery and control performance of human drivers during takeover compared with an existing approach. Thus, this new method further improves the safety and smoothness of human–machine interaction in automated vehicles.

A Hybrid IIoT-based System for Real-time Monitoring and Control of Industrial Processes

The IIoT is a rapidly developing field that is changing the way factories operate by enabling real-time monitoring, control, and optimization of processes. In order to collect and analyse massive amounts of data in real time, IIoT-based systems use sensors, networking, and data analytics. This allows for more effective and reliable operations and crucial insights into the system's inner workings. The industrial, logistics, energy, and utility sectors are just a few examples of the many potential applications for systems built on the Industrial Internet of Things. Concerns over data privacy and security, interoperability between different systems and devices, and the need for skilled people to develop and operate successful IIoT-based systems are among the challenges that have followed the expansion of systems that are based on the IIoT. The goal of this paper is to provide a literature analysis that investigates the potential uses, limitations, suggested methodology, challenges, recent developments, and potential future expansion of systems based on the Industrial Internet of Things (IIoT). This study demonstrates how IIoT-based systems may improve operational effectiveness, reliability, and environmental friendliness in manufacturing. The report also highlights the need of thoroughly assessing the needs and requirements of organizations in order to construct and implement effective IIoT-based solutions. Interoperability, cyber security, sustainability, human-machine interaction, predictive maintenance, autonomous systems, and new business models are all highlighted in the evaluation as potential areas of expansion and development for IIoT-based systems. The next paragraphs go into further depth on these themes. Systems based on the IIoT have the potential to transform manufacturing in many different industries. If they take the right strategy, businesses and organizations may use these advantages to boost operational efficiency and competitiveness.

Design of Intelligent Medicine Box for Elderly People Based on Context Awareness and FAST Theory

Based on context awareness and FAST (Function Analysis System Technique) theory, this paper explored the needs of elderly users and designed an intelligent medicine box for them to provide more comprehensive health services. It defined context through context analysis method, combined four context factors to obtain human-machine interaction model, and built a functional tree through the FAST theory to analyze product design factors and functional transformation forms. Finally, this paper established a product shape matrix upon functional combination and human-machine relationship, and selected the best design scheme. Through a practical application to a case, the validity of context awareness and FAST theory hybrid approach and their technical feasibility and effectiveness was demonstrated, and an accurate mapping relationship between objective product performance and user needs was formed.

Effective approach for facial expression recognition using hybrid square-based diagonal pattern geometric model

Facial expressions convey human emotions in an expressive way. The development of an automated system to recognize the facial expressions is the difficult task. Automatic Facial Expression Recognition (FER) is an imperative process that leads to next-generation Human-Machine Interaction (HMI) for clinical practice and behavioral description. Segment detection and the extraction of relevant information from the images are the major issues to design an effective FER system. The creation of the suitable system that addresses these issues is the basic stage to achieve the accurate HMI models. The in-depth information analysis and maximization of labeled database are the real problems in the domain of FER approaches. A novel framework based on Square-Based Diagonal Pattern (SBDP) method on Geometric model called Geometric Appearance Models (GAM) has been presented through this paper that extracts the in-depth detailed of the features. The framework adopts the co-training by using detailed information from RGB-D images. The performance analysis of proposed SBDP-GAM regarding identification rate, sensitivity, accuracy and error rates with the RGB-D images shows the effectiveness diagonal patterns in facial expression identification. The comparative analysis of proposed SBDP-GAM model with the traditional methods regarding the recognition rate, error rate and F-score and on RGB-D images from EURECOMM database states the effectiveness of the proposed method. Moreover, the comparison of proposed SBDP-GAM with existing Support Vector Machine (SVM) regarding the acceptance rate (FAR, FRR, GAR) measures for biographer RGB-D image database proves the effectiveness of SBDP-GAM in FER applications.

A Human‐Oriented Simulation Approach for Labor Assignment Flexibility in Changeover Processes of Manufacturing Cells

AbstractSkilled operators are the most decisive key factors in manufacturing cells. An optimal assignment of operators is crucial for flexibility and productivity. Although there are many publications dealing with labor assignment problems, different forms of human cooperation on the shop floor and decentralized decision making, which are the main factors for system flexibility, are seldom concerned in existing models. In this article, a human‐oriented methodology to analyze, simulate, and evaluate labor assignment flexibility in changeover processes in manufacturing cells is introduced, which is characterized by an agent‐based approach. First, the problem architecture is presented along with the concepts of labor flexibility. Then, different types of human behavior in the changeover process are modeled. Furthermore, a human–machine interaction model is developed to integrate the human agent models into a generalized discrete event dynamic system (DEDS) process model. In this way, work process dynamics and cooperative behavior can be explicitly modeled and simulated. Third, the model is verified on the basis of a motorcycle engine manufacturing cell, and simulation experiments with different labor assignment schemes are designed and conducted. The simulation results show that assignment strategies incorporating different skill levels and cooperation styles have a significant impact on system performance. The agent‐based approach in conjunction with the human–machine interaction model can be used to analyze and solve a large class of assignment problems in flexible manufacturing systems, especially when human cooperation and collaboration are key factors shaping overall system performance.

Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton

Exoskeleton robots and their control methods have been extensively developed to aid post-stroke rehabilitation. Most of the existing methods using linear controllers are designed for position control and are not suitable for human-machine interaction (HMI) force control, as the interaction system between the human body and exoskeleton is uncertain and nonlinear. We present an approach for HMI force control via model reference adaptive impedance control (MRAIC) to solve this problem in case of index finger exoskeleton control. First, a dynamic HMI model, which is based on a position control inner loop, is formulated. Second, the theoretical MRAC framework is implemented in the control system. Then, the adaptive controllers are designed according to the Lyapunov stability theory. To verify the performance of the proposed method, we compare it with a proportional-integral-derivative (PID) method in the time domain with real experiments and in the frequency domain with simulations. The results illustrate the effectiveness and robustness of the proposed method in solving the nonlinear HMI force control problem in hand exoskeleton.

Study of a New Stair-Climbing and Obstacle-Traversing Robot

The author introduced a new stair-climbing and obstacle-traversing robot system. According to its working environment, the parameters of driving wheels were determined with the optimization target of rotation axis’s undulation amplitude; The gear ratios of the driving planetary gear train were determined by running resistance, which can realize the automatic switching between rotation and revolution; According to its applicable situation, the robot’s control system was designed as a human-machine interaction model.

Conception and Experimentation of a Communication Device with Adaptive Scanning

For some people with motor disabilities and speech disorders, the only way to communicate and to have some control over their environment is through the use of a controlled scanning system operated by a single switch. The main problem with these systems is that the communication process tends to be exceedingly slow, since the system must scan through the available choices one at a time until the desired message is reached. One way of raising the speed of message selection is to optimize the elementary scanning delay in real time so that it allows the user to make selections as quickly as possible without making too many errors. With this objective in mind, this article presents a method for optimizing the scanning delay, which is based on an analysis of the data recorded in “log files” while applying the EDiTH system [Digital Teleaction Environment for People with Disabilities]. This analysis makes it possible to develop a human-machine interaction model specific to the study, and then to establish an adaptive algorithm for the calculation of the scanning delay. The results obtained with imposed scenarios and then in ecological situations provides a confirmation that our algorithms are effective in dynamically adapting a scan speed. The main advantage offered by the procedure proposed is that it works on timing information alone and thus does not require any knowledge of the scanning device itself. This allows it to work with any scanning device.

Gmat. A software tool for the computation of the rovibrational G matrix

Gmat is a C++ program able to compute the rovibrational G matrix in molecules of arbitrary size. This allows the building of arbitrary rovibrational Hamiltonians. In particular, the program is designed to work with the structural results of potential energy hypersurface mappings computed in computer clusters or computational Grid environments. In the present version, 1.0, the program uses internal coordinates as vibrational coordinates, with the principal axes of inertia as body-fixed system. The main design implements a complete separation of the interface and functional parts of the program. The interface part permits the automatic reading of the molecular structures from the output files of different electronic structure codes. At present, Gamess and Gaussian output files are allowed. To such an end, use is made of the object orientation polymorphism characteristic. The functional part computes numerically the derivatives of the nuclear positions respect to the vibrational coordinates. Very accurate derivatives are obtained by using central differences embedded in a nine levels Richardson extrapolation procedure. Program summary Program title: Gmat Catalogue identifier: AECZ_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AECZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 17 023 No. of bytes in distributed program, including test data, etc.: 274 714 Distribution format: tar.gz Programming language: Standard C++ Computer: All running Linux/Windows Operating system: Linux, Windows Classification: 16.2 Nature of problem: Computation of the rovibrational G matrix in molecules of any size. This allows the building of arbitrary rovibrational Hamiltonians. It must be possible to obtain the input data from the output files of standard electronic structure codes. In addition, the program should handle the large number of files generated in massive explorations of molecular potential energy hypersurfaces. In these cases, Gmat will provide the G matrix as a function of the molecular structure. Solution method: To reach its objectives, Gmat has been organized in two components: an interface and a functional part. This organization allows for separating the input/output tasks, which are dependent on the human–machine interaction model selected, from the functional requirements, which are not. An object-oriented approach has been used in both parts. In the interface, polymorphism is used to allow the data acquisition from output files of different electronic structure codes. In the functional part, Gmat computes numerically the derivatives of the Cartesian coordinates respect to the vibrational coordinates needed to build the G matrix. Extremely accurate numerical derivatives are obtained in a double procedure. First, the truncation plus roundoff errors are minimized in the central differences expression. Second, the result is embedding in a nine levels Richardson extrapolation process. In the present version, the program allows the use of internal coordinates as vibrational coordinates, with the principal axes of inertia as body-fixed system. Running time: Sample test runs provided with the distribution take a few seconds to execute.