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• Randomised controlled trial of acceptance of C-ITS installed in participants' cars. • Both within and between groups methods and counterbalanced C-ITS activation periods. • Participants responded to four questionnaires over nine months. • High acceptance ratings but reduced slightly over time and after C-ITS activated. • Participants perceived some warnings were presented inaccurately. Connected Intelligent Transport Systems (C-ITS) may provide safety and mobility benefits for drivers and other road users by providing timely, safety focused messaging to drivers. However, the knowledge-base regarding drivers' experiences with C-ITS technology is limited given that interactions with these advanced systems are still relatively uncommon and often constrained by time and place. The current study explored participants' acceptance of, and experiences with a Human Machine Interface (HMI) that displayed C-ITS warnings, during nine months of participation. The specific warnings included speed and hazardous driving at signalised intersections, road-works zones, and on highways. Importantly, the HMI was installed in each participant's personal vehicle thereby integrating the C-ITS experience into each participant's daily routine for an extended period. Subjective data were obtained via four questionnaires focused on drivers' acceptance and general experiences with the HMI, as part of a large-scale (n = 325) longitudinal Field Operational Test of C-ITS conducted in Ipswich, Queensland, Australia. Analyses exposed several significant factors that predicted acceptance including HMI activation, age, and technology readiness. Subsequent contrasts revealed that significant, but small decreases in mean acceptance following the activation of warnings (use cases) on the HMI likely due to perceived limitations with respect to timing and accuracy. Still, participants' ratings of the warnings being displayed on the HMI were positive and remained as such throughout the FOT. [ABSTRACT FROM AUTHOR]

The effective operation of surface electromyography (sEMG) signal-based controlled active prostheses and humanmachine interaction systems in daily life is crucial to work with high accuracy in different angles and positions of the arm. In this study, sEMG recordings from three different positions and angles of the arm were combined with accelerometer and gyroscope data to classify four different hand movements. The classification data (8-channel sEMG, accelerometer, and gyroscope) were collected from the right forearm of 13 participants. To create the dataset, six features were extracted from sEMG signals and three from accelerometer and gyroscope data. As a result, the methodological investigation was carried out on how different arm positions and angles affect the classification of hand movements. Evaluations were also made regarding whether the adverse effects arising from different arm positions and angles of the movement could be mitigated using accelerometer and gyroscope data, and their effects on classifier performance were discussed. As classifiers, Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were used. SVM classifiers achieved an average success rate of 83% in the five different categories of analysis, while ANN classifiers achieved an average success rate of 82%. It was found that accelerometer and gyroscope data in various positions contributed very little to the performance of movement classification. As a result of the evaluation, it was discovered that collecting training data in all positions and angles of the forearm improved classification results for a sEMG-based systems. [ABSTRACT FROM AUTHOR]

Introduction: In robotic-assisted surgery (RAS), the input device is the primary site for the flow of information between the user and the robot. Most RAS systems remove the surgeon's console from the sterile surgical site. Beneficial for performing lengthy procedures with complex systems, this ultimately lacks the flexibility that comes with the surgeon being able to remain at the sterile site. Methods: A prototype of an input device for RAS is constructed. The focus lies on intuitive control for surgeons and a seamless integration into the surgical workflow within the sterile environment. The kinematic design is translated from the kinematics of laparoscopic surgery. The input device uses three degrees of freedom from a flexible instrument as input. The prototype's performance is compared to that of a commercially available device in an evaluation. Metrics are used to evaluate the surgeons' performance with the respective input device in a virtual environment implemented for the evaluation. Results: The evaluation of the two input devices shows statistically significant differences in the performance metrics. With the proposed prototype, the surgeons perform the tasks faster, more precisely, and with fewer errors. Conclusion: The prototype is an efficient and intuitive input device for surgeons with laparoscopic experience. The placement in the sterile working area allows for seamless integration into the surgical workflow and can potentially enable new robotic approaches. [ABSTRACT FROM AUTHOR]

The emerging trend in sustainable industrial processes focuses on energy‐efficient drives to enhance performance in both intermediate and continuous operating conditions. For decades, researchers have focused on permanent magnet synchronous machines (PMSM) for industrial applications in order to retain consistency in performance and efficiency under wide speed ranges. Common bus regenerative control is an energy‐efficient method used in industrial systems to manage power flow between multiple devices on a shared DC bus. It captures and reuses excess energy generated during braking/deceleration, reducing waste and improving overall system efficiency. The experimental behavior of the drive scheme has been observed as per the standards of the laboratory. In this article, regenerative control of a PMSM drive is using the voltage vector control (VVC+) technique and the SCADA based condition monitoring for the PMSM drive system is integrated to supervise the parameters including current, voltage, power, speed, torque, and temperature under dynamic operating conditions. As a primary step of implementing the drive condition monitoring is carried out through Danfoss's motion control tool software. Further, the SCADA control system is interfaced to FC302 PMSM drive through RS485 Modbus communication to extract the necessary electrical attributes and monitor the same. [ABSTRACT FROM AUTHOR]

In the present study, we proposed two types of e-HMI that promotes safe and smooth pedestrian behavior by􀀃 measuring pedestrians' crossing and eye movement at pedestrian crossings where multiple vehicles are approaching. "Crossing icon" on the windshield encourages pedestrians to cross, and "Brake light" turns green when a car slows down. The experiment was conducted with 36 participants using a VR pedestrian simulator. It was found that the proposed e-HMI increased the sense of safety for many of the participants, and some participants were able to cross the street smoothly. [ABSTRACT FROM AUTHOR]

Human-Machine Interfaces (HMIs) must bridge human skills with machine control, notably in active prosthesis. Electromyography (EMG) is the most popular prosthesis actuation method. However, researchers need new HMIs for active prosthesis development. This research introduces Forcemyography (FMG)- based HMI using force-sensitive resistors (FSRs) to capture myoelectric data. A particularly constructed case with two integral parts—an internal and an exterior component—is FMG. This FMG enclosure adapts effortlessly to the user's limb and shape for best performance and comfort. FMG and sEMG were compared in the experimental evaluation. Stability, forecast accuracy, hair and sweat resistance, wearability, and cost-effectiveness were examined. FMG signals outperformed sEMG signals in this comprehensive examination. FMG outperformed sEMG in stability and prediction accuracy. FMG produced outstanding results right from capture without post-processing, a unique advantage. The specialised enclosure protected FSRs from outside interference and delivered precise signals. The Forcemyography (FMG)-based HMI is a breakthrough in active prosthesis technology. Its versatility, consistent signal acquisition, and user-centric design promise improved human-machine interactions. FMG leads the way to smooth, intuitive, and efficient humanmachine interface. [ABSTRACT FROM AUTHOR]

This paper presents a novel vision-based human–machine interface (HMI) incorporated into an exoskeleton glove tailored for patients with brachial plexus injuries. Addressing the challenges posed by the loss of hand muscle control in individuals affected by these injuries, a fully automated exoskeleton glove function akin to a robotic gripper is used to prevent muscle atrophy through targeted hand muscle exercises. The proposed vision-based HMI is designed for a fully automated exoskeleton glove and incorporates computer vision techniques for the automatic identification of the target object, estimating its material and size, allowing the precise application of the required force to the target object. This novel approach enables users to efficiently grasp unknown objects with a significantly reduced failure rate. The vision-based method exhibits a grasp success rate of 87.5%, surpassing the baseline slip-grasp method's 71.9%. These results underscore the effectiveness of our vision-based HMI in enhancing the grasp functionality of the exoskeleton glove. [ABSTRACT FROM AUTHOR]

Pyroelectricity enables autonomous perception and remote detection in the field of infrared sensor, human machine interfacing and virtual reality. However, the low pyroelectric coefficient and inferior thermal conductivity hinders the energy conversion and signal transduction of pyroelectric sensors. Herein, we designed and prepared PZT-CNT/PVDF ternary composite (PTC) capable of infrared sensing and noncontact human machine interfacing (HMI). The incorporation of CNT not only facilitates the photo-thermal energy conversion and the heat transfer toward embedded PZT fillers, but also boost the all-trans conformation of fluoropolymer matrix and thus pyroelectric activity. The influence of CNT doping mass fractions on the pyroelectric noncontacted HMI and infrared detection properties was investigated. It is found that a doping content of 3 wt% gives rise to an optimal proximity sensitivity of 55.78 % and infrared detection optimum value of Fd 6.42 μPa−1/2, which is 13.97 % higher than that of the undoped version. This work provides insight into the interfacial coupling mechanism of pyroelectrics, and offers the new possibility for design of high-performance self-powered sensing devices.

Abstract The concept of an innovative human–machine interface and interaction modes based on virtual and augmented reality technologies for airport control towers has been developed with the aim of increasing the human performances and situational awareness of air traffic control operators. By presenting digital information through see-through head-mounted displays superimposed over the out-of-the-tower view, the proposed interface should stimulate controllers to operate in a head-up position and, therefore, reduce the number of switches between a head-up and a head-down position even in low visibility conditions. This paper introduces the developed interface and describes the exercises conducted to validate the technical solutions developed, focusing on the simulation platform and exploited technologies, to demonstrate how virtual and augmented reality, along with additional features such as adaptive human–machine interface, multimodal interaction and attention guidance, enable a more natural and effective interaction in the control tower. The results of the human-in-the-loop real-time validation exercises show that the prototype concept is feasible from both an operational and technical perspective, the solution proves to support the air traffic controllers in working in a head-up position more than head-down even with low-visibility operational scenarios, and to lower the time to react in critical or alerting situations with a positive impact on the human performances of the user. While showcasing promising results, this study also identifies certain limitations and opportunities for refinement, aimed at further optimising the efficacy and usability of the proposed interface.

This article presents the method Wave Top-k Random-d Lineage Search (WaveLSea) which guides an expert through data mining results according to her interest. The method exploits expert feedback, combined with the relation between patterns to spread the expert's interest. It avoids the typical feature definition step commonly used in interactive data mining which limits the flexibility of the discovery process. We empirically demonstrate that WaveLSea returns the most relevant results for the user's subjective interest. Even with imperfect feedback, WaveLSea behavior remains robust as it primarily still delivers most interesting results during experiments on graph-structured data. In order to assess the robustness of the method we design novel oracles called soothsayers giving imperfect feedback. Finally, we complete our quantitative study with a qualitative study using a user interface to evaluate WaveLSea. [ABSTRACT FROM AUTHOR]

Copyright of e & i Elektrotechnik und Informationstechnik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Extensive efforts in providing upper limb amputees with sensory feedback have primarily focused on the restoration of tactile capabilities, while challenges in evoking proprioceptive sensations have been poorly addressed. Previously, an human–machine interface (HMI) was proposed based on permanent magnets implanted in residual muscles of an amputee, namely the myokinetic interface, to control robotic limb prostheses. Besides control, implanted magnets offer an unprecedent opportunity to trigger musculotendon proprioceptors via untethered selective vibrations. Herein, the challenge of tracking multiple moving magnets is addressed (e.g., following muscle contractions) while being vibrated by controlled magnetic fields produced by external coils. Results demonstrate the viability of a real‐time (RT) system capable of simultaneously tracking and vibrating multiple moving magnets within a three‐dimensional workspace. Highly selective torsional vibrations in the frequency span eliciting movement illusions (70, 80, and 90 Hz) are achieved on two moving magnets, with efficiencies above 0.82 (over 80% of spectral power at the desired frequency). Tracking accuracy and precision remain robust to the coil magnetic field, with position median errors below 1.2 mm and median displacement errors below 0.95 mm. This study represents a crucial step towards the development of a bench system to study proprioception in humans. [ABSTRACT FROM AUTHOR]

The object of this study is modern Human-Machine Interfaces (HMI) and SCADA systems in the industry. The subject of research is techniques for optimizing the number of tags (variables) in the SCADA/HMI environment to enhance resource utilization efficiency. One of the challenges in creating SCADA/HMI-based solutions can be the number of tags (variables) in the runtime environment. A large number of tags can lead to a problem of limited available resources. The technique presented here allow for the optimization of the number of tags used in HumanMachine Interface systems built with SCADA software and operator panels in combination with Programmable Logic Controllers (PLCs). An evaluation of the efficiency of techniques for reducing the number of HMI tags was conducted on an experimental configuration consisting of objects such as discrete input/output, analog input/output, actuators such as valves with discrete/analog control, and drives with frequency converters. The optimization coefficient, defined as the ratio of the number of input/output tags used directly to the number of tags after applying the optimization principle, was used as the efficiency criterion. Depending on the techniques and their combinations, the criterion values reached orders of 4, 10, and in one case even more than 100. These values are explained by the application of multiplexing approaches and various packing techniques. The advantages and disadvantages of the reported techniques, as well as their application limitations, have been identified. Some techniques are suitable only for specific tasks. These techniques could be applied in practical implementation when designing modern high-efficiency Human-Machine Interfaces under conditions of limited resources. [ABSTRACT FROM AUTHOR]

To solve the problems of empiricism, subjectivity and randomness in the manual layout of human machine interface in wheelhouse, an optimization layout design method of human machine interface that combines virtual simulation and optimization algorithm is proposed. First, the optimal operating point and the operating comfort of each area of the human machine interface are obtained through virtual simulation. Then, the layout criteria and ergonomics criteria of human machine interface are quantified as objective functions and constraints, a layout optimization mathematical model of human machine interface is established, and a large number of initial positions of the particles in the particle swarm optimization (PSO) algorithm are obtained through the differential evolution algorithm. Finally, the optimal layout scheme is obtained, and virtual simulation evaluation is conducted. Taking a control panel as an example for layout optimization and virtual simulation, the optimal layout scheme obtained is proved to satisfy ergonomic criteria, and the performance of the human machine interface has been improved. This paper can provide references for the layout design of the high performance human machine interface in wheelhouse.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Controlling a remotely operated underwater vehicle (ROV) is an extremely challenging task that requires precise maneuvering and navigation in complex as well as often unpredictable environments. The operator faces numerous difficulties, including limited visibility and communication constraints, in addition to the need to interpret data from various sensors. This paper describes a method for calibration of a wearable system equipped with inertial measurement unit (IMU) sensors that control the underwater manipulators. To implement a solution that allows the robot to be controlled by the operator's hand movements, it is necessary to measure the movement of the arm. This task is carried out using the IMU sensors, which are mounted in appropriate places on the ROV operator's suit to allow mapping the movement of his/her upper limbs. These movements are transferred to the manipulator's arms on the ROV, making it possible to interact with the environment by -- manipulating objects under-water. [ABSTRACT FROM AUTHOR]

In order to handle free speech while driving, we constructed spoken dialogue system combining a question-and-answer database and a large-scale language model. We analyzed user behavior and the usefulness of the system by collecting utterances using an actual vehicle. Among the utterances that could not be answered by the conventional system, the large-scale language model was able to respond to more than half of them. This indicated the effectiveness of the introduction of the large-scale language model. [ABSTRACT FROM AUTHOR]

Natural Language Processing (NLP) has many applications such as Speech recognition, Speech understanding, and Speech synthesis. Several approaches have been proposed in the literature in dealing with NLP. This paper describes an ongoing research project that tackles Speech Arabic Synthesis using multi-agent system techniques. The system consists of five modules (agents): the User Interface Agent (UIA), the Facilitator Agent (FA), the Preprocessing Agent (PPA), the Orthographic and Phonetic Transcription Agent, and the Speech Generation Agent. These agents are communicating with each other to construct agent sub societies representing the user input. All the agents are cognitive, work together, and communicate with the Knowledge-Base and the Sound Segments Database to generate Arabic speech signals. We used 800 Arabic sentences and asked 10 listeners with different levels of knowledge of the Arab language to accomplish the evaluation perception process. The system presents in general a Success Rate of 86% for the set of 800 tested sentences. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Extensive efforts in providing upper limb amputees with sensory feedback have primarily focused on the restoration of tactile capabilities, while challenges in evoking proprioceptive sensations have been poorly addressed. Previously, an human–machine interface (HMI) was proposed based on permanent magnets implanted in residual muscles of an amputee, namely the myokinetic interface, to control robotic limb prostheses. Besides control, implanted magnets offer an unprecedent opportunity to trigger musculotendon proprioceptors via untethered selective vibrations. Herein, the challenge of tracking multiple moving magnets is addressed (e.g., following muscle contractions) while being vibrated by controlled magnetic fields produced by external coils. Results demonstrate the viability of a real‐time (RT) system capable of simultaneously tracking and vibrating multiple moving magnets within a three‐dimensional workspace. Highly selective torsional vibrations in the frequency span eliciting movement illusions (70, 80, and 90 Hz) are achieved on two moving magnets, with efficiencies above 0.82 (over 80% of spectral power at the desired frequency). Tracking accuracy and precision remain robust to the coil magnetic field, with position median errors below 1.2 mm and median displacement errors below 0.95 mm. This study represents a crucial step towards the development of a bench system to study proprioception in humans.

As the issues of social sustainability and the aging of population becomes increasingly severe, Autonomous Driving technology is increasingly being seen as an important issue for future travel. At present, the Human Machine Interface (HMI) of Autonomous Driving system has certain difficulties for middle-aged and elderly users, which further affects their perception of cars status and operation experience. Therefore, in order to design an elderly-oriented HMI design of Autonomous Driving cars that meets the Kansei needs of middle-aged and elderly users, a design flow based on Kansei Engineering/ Rough Set Theory/ Backpropagation Neural Network is proposed. The HMI of Autonomous Driving cars is taken as an example in this paper. Under the framework of Kansei Engineering research, Kansei intention analysis is carried out. Factor Analysis is used to reduce dimension and cluster the collected Kansei words. By using the morphological analysis method, the HMI samples are deconstructed into 14 different design features. The attribute reduction algorithm in Rough Set Theory is used to identify the key design features of HMI that have important influence on the elderly-oriented level. Backpropagation Neural Network is used to establish the mapping model between the Kansei intention of middle-aged and elderly users and the key design features of HMI. The mapping model demonstrates good fit as the errors between the predicted and actual values in the 4 types of kansei semantic evaluation tests are all less than 5%. So that it could meet the needs of middle-aged and elderly users and obtain the design combination with the highest Kansei average value. Based on the experimental results, it is found that the optimal emotion of middle-aged and elderly users could be obtained by overall color type three, mode of speed display type three, font display of rotate speed type three, reminding color of turning type four and mode of fuel indicator display one in the morphological deconstruction table. The research results show that the elderly-oriented HMI design constructed by Kansei Engineering/ Rough Set Theory/ Backpropagation Neural Network can meet the sentimental needs of middle-aged and elderly users and can provide a reference example for relevant elderly-oriented design.

In the present study, we proposed the information provision systems using icons shown on the meter cluster and guide lights shown on the road surface as a speed adjustment support to encourage smooth merging behavior by drivers traveling on the main road using ACC. To verify the effectiveness of two types of information provision systems, an experiment was conducted with 26 participants using Virtual Reality headset-based Driving Simulator (VRDS). It was found that the icons and the guide lights assisted judgment of acceleration and deceleration behavior, and enabled smooth merging. [ABSTRACT FROM AUTHOR]

Hand gesture recognition plays an important role in developing effective human–machine interfaces (HMIs) that enable direct communication between humans and machines. But in real-time scenarios, it is difficult to identify the correct hand gesture to control an application while moving the hands. To address this issue, in this work, a low-cost hand gesture recognition system based human-computer interface (HCI) is presented in real-time scenarios. The system consists of six stages: (1) hand detection, (2) gesture segmentation, (3) feature extraction and gesture classification using five pre-trained convolutional neural network models (CNN) and vision transformer (ViT), (4) building an interactive human–machine interface (HMI), (5) development of a gesture-controlled virtual mouse, (6) smoothing of virtual mouse pointer using of Kalman filter. In our work, five pre-trained CNN models (VGG16, VGG19, ResNet50, ResNet101, and Inception-V1) and ViT have been employed to classify hand gesture images. Two multi-class datasets (one public and one custom) have been used to validate the models. Considering the model's performances, it is observed that Inception-V1 has significantly shown a better classification performance compared to the other four CNN models and ViT in terms of accuracy, precision, recall, and F-score values. We have also expanded this system to control some multimedia applications (such as VLC player, audio player, playing 2D Super-Mario-Bros game, etc.) with different customized gesture commands in real-time scenarios. The average speed of this system has reached 25 fps (frames per second), which meets the requirements for the real-time scenario. Performance of the proposed gesture control system obtained the average response time in milisecond for each control which makes it suitable for real-time. This model (prototype) will benefit physically disabled people interacting with desktops. [ABSTRACT FROM AUTHOR]

Human locomotion is an important activity of daily life. Every individual human walk with a specific gait pattern, and there underlay a neural command mechanism that works in synergy with that particular walking pattern. The presented study explored the neural command mechanism for walking at different speeds using muscle synergies and proposed a walking speed prediction algorithm. The difference in the neural control mechanism has been examined by comparing muscle synergies extracted for different walking speeds. The linear factorization technique was implemented to extract synergies from four lower limb muscle's electromyogram signals, recorded at different walking speeds (3–11 km/hr). A 2- synergy model was found most suitable for all walking conditions; each synergy served a particular purpose during a complete gait cycle. The activation pattern of muscle synergy has shown a significant difference in terms of duration, timing, and magnitude (p-value < 0.05). Further, the same synergy model has been utilized for walking speed prediction, and an average accuracy of 97.28 ± 0.43% has been achieved. The performance of the developed prediction module has also been estimated over the lower range of walking speed (0.5–2.5 km/hr). The time complexity of the proposed algorithm has been found within the boundaries of its real-time implementation. The outcomes of the research work will be helpful for lower limb assistive/rehabilitative device control and the development of an effective human-machine interface. [ABSTRACT FROM AUTHOR]

Pembangkit listrik tenaga angin adalah salah satu jenis energi terbarukan yang mulai berkembang di Indonesia. Pembangkit listrik tenaga angin ini menggunakan turbin angin untuk mengkonversikan daya angin menjadi daya mekanik yang akan menggerakan generator listrik. Generator yang digunakan pada pembangkit listrik tenaga angin ini memiliki batas maksimum. Turbin angin yang beroperasi harus dibawah batas maksimum generator agar tidak terjadi kerusakan pada generator tersebut. Agar tidak terjadi operasi melampaui batas maksimum generator, maka perlu dilakukan monitoring dan proteksi terhadap komponen-komponen yang ada pada pembangkit listrik tenaga angin tersebut. Dengan hal itu paper ini mengusulkan monitoring pembangkit listrik tenaga angin menggunakan Human Machine Interface (HMI) yang dilengkapi dengan Programable Logic Controller (PLC). Alat yang dibuat dalam penelitian ini diujicobakan pada pembangkit listrik tenaga angin yang menggunakan turbin angin sumbu horizontal dan generator sinkron jenis magnet permanent. Monitoring pembangkit listrik tenaga angin ini dirancang dengan menggunakan Programable Logic Controller (PLC) S7 1200 1215C DC/DC/Relay dan Human Machine Interface (HMI) Simatic KTP 700 Basic PN untuk display dari parameter yang dimonitor yaitu arus, tegangan, kecepatan angin, kecepatan putaran dan daya. Monitoring ini dilengkapi dengan sensor tegangan, sensor arus, sensor kecepatan angin, sensor kecepatan putaran dan kontaktor sebagai pemutus arus ketika telah melebihi batas arus yang telat diatur sebelumnya. HMI sudah berhasil menampilkan data tegangan, arus kecepatan angin, kecepatan putaran dan daya. Hasil eksperimen menunjukan bahwa monitoring pembangkit listrik tenaga angin yang diusulkan telah bekerja dengan baik sesuai dengan tujuan.

Kebutuhan terhadap energi listrik saat ini semakin meningkat seiring dengan pesatnya perkembangan peralatan-peralatan yang menggunakan daya listrik dipakai oleh manusia dalam kehidupan sehari-hari. Mulai dari peralatan rumah tangga, peralatan perkantoran sampai pada peralatan produksi di industri. Umumnya daya listrik untuk peralatan-peralatan ini diperoleh dari jaringan listrik yang disediakan oleh pemerintah. Hal ini menjadi masalah bagi daerah yang belum terjangkau oleh jaringan listrik. Untuk mengatasi hal ini, maka dapat digunakan pembangkit listrik tenaga surya (PLTS) stand alone dengan memanfaatkan energi cahaya matahari sebagai sumber energi primernya. Agar PLTS stand alone dapat bekerja dengan baik, maka PLTS tersebut perlu dikendalikan dan dimonitor. Paper ini mengusulkan system kendali dan monitoring PLTS stand alone dengan menggunakan Human Machine Interface (HMI) yang dilengkapi dengan Programable Logic Controller (PLC). PLTS stand alone yang diusulkan terdiri dari delapan panel surya 50 WP, solar charger, inverter, baterai dan beban. Untuk mendapatkan data yang akan dimonitor, maka digunakan sensor yang outputnya akan diolah oleh PLC dan ditampilkan pada HMI. Hasil eksperimen di laboratorium menunjukan bahwa system kendali dan monitoring PLTS stand alone yang diusulkan telah bekerja dengan baik sesuai dengan yang diharapkan.

Industrial systems require efficient techniques to observe the stable operation of various industrial processes and to achieve optimal control. Considering the importance of industrial processes, Proportional Integral and Derivative (PID), Adaptive PID, and fuzzy logic are the most utilized control systems. Programmable Logic Controller (PLC) is a low-cost solution for the industrial processes requiring control and having the flexibility of graphical user interface. In this paper, an experimental study on flow rate control system for water flowing in a vessel is realized and implemented using Proportional (P), Proportional Derivative (PD), Proportional Integral (PI), and PID controllers with Programming Logic Controller (PLC). For optimal control, the constants for the PID controller are calculated based on Zeigler-Nichols (ZN) rules. ZN tuning rules can be used to find controller constants where the plant dynamics are not available. The experimental analysis is performed to validate the theoretical concepts. The achieved results and analysis demonstrate that the process variable, which is water inflow rate 4.92L/minute, is equal to the set point without any overshoot and remains controllable at every set point change. [ABSTRACT FROM AUTHOR]

With the rapid advancement of autonomous vehicles, a transformative transportation paradigm is emerging in the automotive industry, necessitating a re-evaluation of how users engage with and utilize these evolving settings. This research paper introduces an innovative interaction system tailored for shared autonomous vehicles, focusing on its development and comprehensive evaluation. The proposed system uses the car's windshield as an interactive display surface, enabling infotainment and real-time information about the surrounding environment. The integration of two gesture-based interfaces forms a central component of the system. Through a study involving twenty subjects, we analyzed and compared the user experience facilitated by these interfaces. The study outcomes demonstrated that the subjects exhibited similar behaviors and responses across both interfaces, thus validating the potential of these interaction systems for future autonomous vehicles. These findings collectively emphasize the transformative nature of the proposed system and its ability to enhance user engagement and interaction within the context of autonomous transportation. [ABSTRACT FROM AUTHOR]

Cooperative recognition has been proposed as a method for human-automation cooperation in autonomous driving. In cooperative recognition, when assigning tasks to operators (i.e., request intervention), it is necessary to consider not only driving safety and efficiency but also human capabilities. In this study, we optimize the intervention request planning by formulating the problem with a Partially Observable Markov Decision Process. We evaluated the proposed method with a simple simulation to discuss the validity of the method and obtained the implications for future development. [ABSTRACT FROM AUTHOR]

Most of the old machines installed in different industries are managed manually by system operators. This action makes their productivity low and not suitable to cover the needs in other sectors. In addition, these machines are not without risks due to the proximity of the operators to them. The installing a new full system instead of the old one on the same site requires very high costs. So, modernizing the same old system by making its operation automatic has become necessary to reduce the economic cost significantly. In this paper, an automatic control system based on programmable logic controller (PLC) for the cutting steel plate machine that had been managed manually in a factory is designed. The system includes an Encoder that is used to specify the length of the steel plate to be cut by sending a signal to the PLC. The system operation is completed by using human machine interface (HMI) unit to monitor and control the system performance by the system operator. A practical test for the developed system offered more productivity (more than 30%), more safety, reduces human efforts and the total daily production cost (less than one third). [ABSTRACT FROM AUTHOR]

Connected thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.

Connected thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.

Intersection crashes can be potentially mitigated through vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) safety management systems. It is important, however, to consider some of the human factors related aspects of such systems to maximise potential safety benefits. In this study, Intersection Manoeuvre Assistance Systems were conceptualised and evaluated in a driving simulator. The systems were designed to assist drivers with intersection manoeuvres by making use of connected infrastructure and providing real-time feedback, guidance, and active vehicle controls. The study compared drivers' confidence, workload, glances at the instrument panel, and hazard anticipation when driving using three systems—System A (no alert or assist); System B (alert only); and System C (alert and assist). Study results show differences in drivers' confidence in such systems and potentially degraded visual gaze behaviours. Practitioner summary: Connected infrastructure-based intersection management assistance systems can potentially reduce crashes. This experimental driving simulation study evaluated drivers' perceptions and reactions to intersection management systems. Results indicate reduced confidence in automated systems, reduced visual scanning for external hazards at intersections, and increased off-road glances towards the instrument panel. [ABSTRACT FROM AUTHOR]

BACKGROUND: Mental workload is one of the important variables in understanding human performance in drone operation. OBJECTIVE: To test the effects of gender, age group, flight route, and altitude on the flight performance and mental workload of the novice drone operators. METHODS: Ten male and ten female participants without prior drone operating experience joined. They were split into two age groups. After attending a training, the participants operated a drone to perform photo taking missions under flight route and altitude conditions. The weighted NASA Task Load Index (TLX), Modified Cooper-Harper (MCH) scale, heart rate, and interbeat interval were measured to assess the mental workload of the participants. Flight time to complete the mission was adopted to indicate flight performance. RESULTS: The effect of age group was significant (p < 0.05) on flight time, weighted TLX score, and MCH score. Flight route and altitude were not significant on the two subjective ratings and two cardiac measures. CONCLUSION: The flight performance of younger participants was significantly better than that of their older counterpart. The effects of both the flight route and altitude on the perceived mental workload of the drone operators were insignificant. Both the weighted NASA TLX and MCH scales were appropriate in measuring the mental workload of the novice drone operators. [ABSTRACT FROM AUTHOR]