AHFE Open AccessHuman Interaction and Emerging Technologies (IHIET-FS 2026): Future Systems and Design Applications
Editors: Tareq Ahram, Tibor Barath
Topics: Artificial Intelligence & Computing, Human Systems Interaction
ISBN: 979-8-950676-11-6
DOI: 10.54941/ahfe1007254
Table of Contents
Enhancing Operability of Glove-Type Power-Assist Systems: Descent-Assist Mechanism based on Human Centered Design
Power assist devices can reduce the physical burden on factory workers; however, conventional control methods often induce hand pain and unstable operation during lowering tasks. Guided by human centered design (HCD), we adopted a design policy that does not require fine grip force modulation from operators during the most demanding phase. To this end, we developed and integrated a descent-assist switch (DAS) into the glove type interface of a traction type power-assist device (TPAD), enabling explicit switching of assistive behavior during lowering to improve operability and reduce physical/mental workload. We conducted comparative experiments with and without the DAS during lowering. Objective physical burden was assessed via lumbar joint torque, focusing on the peak value (maximum mechanical stress) and the time integral (sustained load). Subjective operability and perceived workload were measured using a Semantic Differential (SD) questionnaire, and factor analysis identified three latent dimensions: Sense of Security, Operability, and Fatigue. With the DAS, both the peak and time integral of lumbar joint torque during lowering were reduced relative to the no DAS condition, indicating lower physical burden. Questionnaire outcomes likewise showed higher ratings across Sense of Security, Operability, and Fatigue. Collectively, these findings demonstrate that the descent-assist switch reduces user burden and improves operability of the TPAD during lowering tasks.
Hironao Yamada
Open Access
Article
Conference Proceedings
Towards an Ergonomic Assessment Framework for Innovative Digital Interfaces: A Multimethod Approach with a Smart-Building Use Case
This study proposes a multimethod ergonomic assessment framework for innovative digital interfaces, using a smart-building software ecosystem as a representative use case. Eight participants completed two interactions with each interface (End-User App and Management Software) under controlled conditions. The assessment combined subjective questionnaires, task-performance measures, electrodermal activity, pupil diameter, and face units’ analysis. The results were more favourable for the End-User App, which showed acceptable usability, a more positive user experience, and improvement with repeated use. In contrast, the Management Software presented lower usability, more errors, greater difficulty in complex tasks, and higher cognitive and emotional demands. Overall, the study shows that combining subjective, performance, physiological, and emotional indicators provides a more comprehensive assessment of interaction demands and helps identify usability issues beyond isolated measures. The proposed framework offers a practical basis for the human-centered assessment of innovative digital interfaces.
Ana Colim, André Cardoso, Filipe Moreira, Manuel Alves, Ricardo Rodrigues, Rosana Alexandre
Open Access
Article
Conference Proceedings
Human-Centered Assessment Methods for Smart Building Systems: A Systematic Review of Ergonomics and Human Interaction
Smart Building Systems (SBS) are becoming increasingly integrated into everyday life, and their effectiveness depends not only on technological performance but also on how well they fit human needs, capabilities, and limitations. This systematic review examines Ergonomics and Human Factors (E&HF) assessment methods applied in SBS. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a literature search was conducted in Scopus, Web of Science, PubMed, and ScienceDirect for studies published between 2020 and 2025. Of the records screened, eight studies met the inclusion criteria. The included studies covered residential smart homes, inclusive housing, educational buildings, and industrial settings, and evaluated interfaces such as mobile applications, web interfaces, voice assistants, chatbots, tablet-based systems, and multimodal solutions. Most studies focused on cognitive ergonomics, while only one explicitly addressed both cognitive and physical ergonomics. The main assessment methods identified were: (i) subjective questionnaires, including usability, trust, comfort, and user experience scales; (ii) behavioural and performance-based measures, such as task completion time, effectiveness, and observational methods; and (iii) physiological measures, namely eye-tracking and heart rate. The findings highlight that usability and user acceptance are strongly influenced by interface modality, task demands, and user characteristics. However, the evidence remains methodologically fragmented, with small samples and limited ecological validity. Overall, the review underlines the need for more integrated, multimethod, and human-centered assessment frameworks to support the design of SBS that are usable, inclusive, and responsive to diverse users.
André Cardoso, Rosana Alexandre, Filipe Moreira, Ana Colim
Open Access
Article
Conference Proceedings
Empowering Nursing Mothers: A Bioinspired Wearable Breast Pump Fostering Emotional and Physiological Well-being.
Breastfeeding provides irreplaceable nutritional, immunological, and psychological benefits to both mother and child. However, sociocultural barriers, unfavorable work conditions, and lack of supportive infrastructure often force women to rely on breast pumps—devices that, despite their prevalence, remain limited in mimicking the physiological and emotional dynamics of natural lactation. Prior research has largely focused on mechanical performance and milk volume, neglecting the maternal psychological experience. This study addresses that gap through the development of Nura, a smart, wearable breast pump designed with psychophysiological principles in mind.Using the Double Diamond methodology, the design process integrated user-centered design, market analysis, anthropometric data, and expert interviews. A functional prototype was developed through 3D printing, incorporating custom flanges, adaptive heating and massage elements, a mobile application for control and tracking, and a modular PCB architecture for improved ergonomics. User testing was conducted to assess anatomical fit, usability, and emotional perception of the device.Results show that Nura improves user comfort through an anatomically adapted flange, reduces emotional distress via sensory features (heat and vibration), and offers improved discretion and usability through a custom wearable bra. The application interface successfully enhanced user engagement and enabled personalized lactation profiles. Feedback revealed reduced stress, increased feelings of control, and better alignment between technological functionality and maternal identity.These findings suggest that lactation support technologies must evolve to consider not only mechanical efficiency but also the psychological dimensions of motherhood. Nura’s design advances understanding of how product experience influences maternal well-being, bonding, and breastfeeding sustainability—especially among mothers who rely on exclusive pumping. Moreover, it underscores the importance of empathy-driven engineering in women's health technologies.This research contributes to improving maternal health (SDG 3), promoting gender equality (SDG 5), and supporting decent work and workplace inclusivity (SDG 8) by facilitating breastfeeding continuity without compromising personal or professional life. As a replicable and scalable model, Nura offers a new standard for human-centered innovation in maternal care.
Gabriela Duran-Aguilar, Alberto Rossa-Sierra, Mariel Garcia-Hernandez, Fabiola Cortes-Chavez, Alejandro Emmanuel Perez Lopez, Fernando Dávalos Hernández
Open Access
Article
Conference Proceedings
Designing a Wearable Mental Health Tracker: A Seven-Week Collaboration with a Health-Tech Startup
The potential of digital technologies enables us to shape and develop new approaches to healthcare practices. This paper illustrates the outcomes of a seven-week product design project carried out with senior year students in collaboration with a health tech start-up firm, UMAXLIFE. The company has developed a wearable device that tracks patients’ physiological data to create evidence for psychotherapy sessions, which is helpful for both adopting an evidence-based approach to patient monitoring and creating an objective documentation of patient records. The studio project aimed to develop the next generation of the physical wearable device and to redesign the software component of the system. The objective of the project was to explore how industrial design approaches can transform a technologically driven prototype into a clinically appropriate and user-centered design concepts suitable for needs of therapeutic processes.The seven-week project started with desk research, including a literature review with benchmarking of existing wearable health technologies. The research stage is followed by concept generation based on identified user needs, technical requirements, and workflows. The concepts are refined through design iterations and low-fidelity prototypes during the design detailing phase of the project, following the concept selection stage. In the final stage, project teams developed detailed product designs, including ergonomic considerations, technological capabilities, and product software user interface for tracking and documentation. This paper documents the studio process and discusses the resulting design outcomes in terms of ideation themes, design qualities, challenges, and the integration of technological and human-centered considerations. The project shows how collaborations with health technology companies can generate innovative product concepts while providing the learning outcomes for design students. It also highlights the contribution of industrial design approaches in development of emerging health technologies toward usable, acceptable, and meaningful tools.
Mehmet Erçin Okursoy
Open Access
Article
Conference Proceedings
Advanced Digitization and CAD Simulation: Technological Convergence, Skills, and Innovation for a Circular Fashion Industry
The digital transformation in the textile and apparel industry has reinforced the role of advanced CAD systems to supporting more sustainable and circular practices. Technologies such as CAD/CAM, 3D garment simulation, material digitization, and digital twins are increasingly integrated into product development, enabling waste reduction, improved efficiency, more sustainable use of materials and less reliance on physical prototyping. This study is based on a systematic literature review with focusing on CAD systems, digital representation of fabrics, and textile circularity. The obtained results highlight that the reliability of simulation is strongly dependent on the accuracy of digital models of the materials and their parameterization. The literature analysis identifies two main approaches in simulation systems. While fashion-oriented platforms prioritize the visual realism and rapid design iteration, the technically oriented systems are focus on the accurate representation of the structure the materials and their physical properties. The integration of these two approaches is a key challenge and opportunity for improving simulation reliability. The findings also show that the integration of CAD systems with artificial intelligence and digital twin technologies is emerging as a key driver of innovation, enabling for more efficient digital workflows and the reducing reliance of physical prototyping. The adoption of these technologies can support sustainability through the reduction of materials and improved decision-making, although challenges remain in modelling recycled materials, ensuring data consistency, and integrating digital workflows.
Teresa Raquel Barata, Marta Bicho, Sandra Ferreira, Nuno Monteiro, Nuno Belino, Rui Miguel, Madalena Pereira
Open Access
Article
Conference Proceedings
Bridging Traditional Islamic Scholarship and Modern AI: A Human-Centered Voice Recognition System for Quran Reciter Identification
Identifying Quran reciters from short audio excerpts can support reciter discovery, religious learning, and user engagement, yet practical deployment is challenging because recordings are often captured in noisy everyday environments. This paper presents a human-centered voice recognition system for Quran reciter identification that combines audio preprocessing, feature engineering, neural classification, and mobile deployment into a single user-facing service. The workflow begins with Quran-recitation metadata linked to online audio sources, followed by download, cleaning, duplicate filtering, normalization, fixed-length segmentation, and extraction of Mel-Frequency Cepstral Coefficients (MFCCs) and embedded utterance features. The learning task was formulated as reciter classification from short clips, with experiments comparing 10-, 15-, and 20-second durations as well as artificial neural network (ANN) and recurrent neural network (RNN) models. The results showed that a 15-second clip provided the best balance between usability and recognition capability. The ANN outperformed the RNN and was selected as the final deployed model, achieving 97.8% accuracy on the test set and 99.0% on the training set under controlled conditions. A mobile application and server-side inference service were then implemented to deliver the system to users. Although deployment remained constrained by the mismatch between clean training audio and noisy real-world recordings, the study demonstrates the feasibility of a practical, human-centered AI system for Quran reciter identification.
Omar Alsaleh
Open Access
Article
Conference Proceedings
Balancing Automation with Designerly Autonomy: A UX-Driven Design Intervention
This paper focuses on the unique, domain-specific requirements of industrial design tasks and workflows, and the tension between automation and creative autonomy from a user-centred perspective. The presented case is a design project carried out in a UX design course in an industrial design department. The project targeted effective designer-AI collaboration scenarios for specialised tasks, supported by interface designs balancing the benefits of AI automation with designers’ creative control. A mixed-method user study was conducted consisting of a questionnaire (n=105), workflow analysis (n=34) and generative interviews (n=18) to identify the perceived benefits of automation, interaction flaws as barriers to creative control in currently available generative AI tools, and designers’ expectations to enhance AI-supported industrial design workflows. The findings are enriched with novel design interventions from conceptual student projects carried out in the course. These interventions focus on familiar UI design features, enhanced designer-AI communication strategies, personalisation opportunities, transparent and reliable AI contribution, domain-specific automation support, and continuous design workflows. This study contributes to the field of human-AI interaction by proposing grounded, domain-specific interface design requirements and examples to inform future collaborative platform designs that optimise both AI automation and human creative control.
Sedef Süner-Pla-Cerdà
Open Access
Article
Conference Proceedings
Designing for Emotional Memory: Affective User Interfaces for Learning
The majority of studies related to the area of ‘emotional design’ for learning interfaces are focused on the impact of an interface's emotional aspects on retaining student information. The consensus is generally that there should be an element of engagement with the learning experience; however, relatively few studies have investigated the effect of emotional tone on students' ability to remember (recall) information from those experiences. This study attempts to fill this void in research by developing various interfaces according to a design-and-emotion approach that vary in terms of their emotional tone and are tested through controlled experiments. The researchers conducted a mixed-methods experimental study, comparing an emotionally-tuned interface with a baseline affect-neutral interface among 40 randomly assigned users. Participants completed a learning task and subsequently underwent recall and recognition tests to measure their memory retention. Quantitative results demonstrated that the emotionally-tuned interface significantly improved users' recall and recognition abilities and yielded a more positive user experience. Additionally, qualitative feedback from short post-task interviews revealed insights into users' perceptions of the emotional tone of each interface, further underscoring the effectiveness of emotionally-tuned interfaces in enhancing learning outcomes.
Amic Ho
Open Access
Article
Conference Proceedings
Human-Centered Design: A Playful Tool for Teaching HCD in the Design Process
Human-Centered Design (HCD) has become a key paradigm in contemporary product development, emphasizing empathy with users, contextual understanding, and evidence-based decision-making. Despite its relevance in professional design practice, integrating HCD principles effectively into design and engineering education remains challenging. Students frequently rely on intuition, aesthetic preferences, or assumptions rather than research-based reasoning when defining product characteristics.This paper presents a pedagogical methodology designed to strengthen the integration of Human-Centered Design principles within product design education through a gamified learning strategy. The proposed method introduces a coin-based questioning system implemented during the conceptual development phase of the design process, when students present prototypes derived from their design research.The methodology organizes structured critique sessions in which design teams present their proposals and justify design decisions using research evidence. Peer teams challenge these proposals through a structured questioning process consisting of contextual verification questions and a critical “coin question” designed to evaluate the coherence between research insights and design decisions.Inspired by Socratic questioning, the dynamic encourages students to identify inconsistencies in their reasoning and refine their design proposals iteratively. The methodology has been implemented for more than fifteen years in undergraduate courses in industrial design and product design engineering. Qualitative observations from classroom implementation indicate that the approach enhances students’ ability to justify design decisions, strengthens the connection between research insights and product characteristics, and promotes a deeper understanding of Human-Centered Design processes.
Fabiola Cortes-Chavez, Mariel Garcia-Hernandez, Elvia Luz Gonzalez Muñoz, Gabriela Duran-Aguilar, Alberto Rossa-Sierra
Open Access
Article
Conference Proceedings
Multimedia Web Content Generation Using Large Language Models with Chain-of-Thought Reasoning Strategy
Recent advances in Large Language Models (LLMs) and Chain-of-Thought (CoT) reasoning have improved the quality of AI-generated multimedia content and code. However, the reliability and stability of generated outputs still depend heavily on prompt design, model capability, and application context. This study examines a human–AI collaborative framework for multimedia web content generation and programming education. By integrating CoT-guided prompting with full-stack web development processes, the framework supports frontend interface construction, backend logic implementation, and database connectivity within a unified workflow. Two prompting approaches are compared: conventional zero-shot generation and CoT reasoning. The generated outputs are evaluated using quantitative indicators, including memory usage, execution time, and test coverage, together with user-based assessments of visual aesthetics and creative expression. The results show that CoT prompting improves the logical consistency and structural completeness of AI-generated code when compared with conventional zero-shot generation. Comparative benchmarking also indicates that ChatGPT and Gemini produce more stable results than Grok in tasks involving complex algorithmic reasoning. From an educational perspective, the framework further demonstrates the potential of generative AI to support learners without strong programming backgrounds through structured prompting, intermediate feedback, and iterative refinement. These findings suggest that CoT-guided human–AI collaboration can provide practical support for multimedia web development and programming education, while also revealing the current limitations of generative AI in resource-constrained and logic-intensive tasks.
Cheng Chao-Hsi, Shyi-Chyi Cheng, Hsun Yu Lan
Open Access
Article
Conference Proceedings
BEHOLD: An Extensible Eye-Tracking Infrastructure Supporting Multimodal, Multi-Device Interaction Evaluation
Interactive systems increasingly span multiple devices, modalities, and physical spaces, which makes interaction evaluation harder than in single-device settings. Traditional post-task methods (e.g., questionnaires and logs) often miss when and why problems occur. Eye tracking can complement these approaches by continuously capturing visual attention, helping reveal what users notice or overlook and how effort is distributed across interfaces. However, deploying eye tracking in such ecosystems raises challenges: different contexts require different trackers (wearables, environmental cameras, or display-mounted sensors); existing tools are often tied to specific hardware and may lack evaluation-oriented analysis; and synchronising gaze with other contextual and system-level data typically requires multiple disconnected components. This work presents the first stage of BEHOLD (Biometric Eye-tracking Hub for Observation, Logging, and Data), a plugin-based proof of concept that separates device-specific logic from a unified processing and analysis pipeline. Each eye tracker is supported via an individual plugin for parsing and validation, while the framework treats gaze streams consistently regardless of source. For storage, BEHOLD combines TimescaleDB for high-frequency gaze samples, PostgreSQL for session metadata, and MinIO for recordings and exports. We demonstrate the approach by integrating data from Tobii Pro Glasses, showing how the plugin architecture accommodates device-specific requirements while enabling a coherent workflow from acquisition to analysis.
Hugo Correia, Bernardo Marques, Liliana Vale Costa, Samuel Silva
Open Access
Article
Conference Proceedings
Human-AI Collaborative Learning: AI-Enhanced Project-Based Learning for Future Technology Prototyping in Higher Education
Higher education has debated the thin line between AI literacy development and cognitive disengagement in AI-supported learning environment. This paper presents a detailed AI-Enhanced Conceptual Prototyping (A-ECP) framework that integrates human-AI interaction into project-based learning through interactive design, structured monitoring, and AI-assisted visualization of abstract Management Information Systems (MIS) concepts. The study was conducted at the undergraduate level at the College of Business at Prince Mohammad bin Fahd University in Saudi Arabia. Using ChatGPT as a human-centred generative AI tool, students transformed theoretical MIS concepts into future technology prototypes through iterative prompting, visualization, and reflective refinement. ChatGPT was selected due to its familiarity and accessibility among students, reducing technological barriers and supporting collaborative human-AI learning experiences. The framework was evaluated through a post-intervention survey, which indicated a mean score of x̄ = 4.64 and 92.9% confidence in AI integration within academic settings. Themes identified from qualitative thematic analysis include AI-Augmented Creativity and Visual Clarity in Learning, highlighting the role of human-AI collaboration in supporting conceptual understanding and engagement. Academic performance improved by 6.05 percentage points from the previous semester, rising from 77.34% to 71.29%, with a moderate effect size (Cohen's d = 0.60). The findings show that integrating human-centred AI in a structured way can improve conceptual understanding, student engagement, and AI literacy while still maintaining critical thinking. Additionally, the study confirms the pedagogical significance of the A-ECP framework, aligning it with the SAMR model, AI-TPACK, Cognitive Load Theory, and Saudi Vision 2030’s goals for a digital workforce.
Rabaa Alabdulrahman
Open Access
Article
Conference Proceedings
Emotional Interfaces and Sensorimotor Skill Learning in Interactive Training Systems
Emotions affect the performance of sensorimotor functions; however, few existing training programs address the emotional side of the learning process. Training systems traditionally focus on the task itself and whether the user receives accurate information about it. Yet, research has shown that users' perceptions of how well they are doing (the ‘emotional’ aspect) have an impact on how well they perform the task. Therefore, researchers in this study used a different type of training system, which included either a virtual environment or a physical environment (a desk), to examine how the way users received emotional feedback impacted how well they performed tasks in the sensorimotor skills area. By examining the differences between the groups that received each type of emotional feedback, researchers were able to evaluate the effect of emotional feedback on both motor performance and sensorimotor skill acquisition. A major hypothesis was that participants who received supportive emotional feedback would demonstrate improved motor performance, less variability in motor performance, and higher self-efficacy expectations compared to other participants. The purpose of this research was to provide evidence-based findings concerning how emotional feedback influences sensorimotor learning within interactive environments. As such, these findings can be applied toward enhancing user confidence and reducing anxiety when using interactive training technology.
Amic Ho, P. W. Chau
Open Access
Article
Conference Proceedings
Challenges of Moving Beyond Digital Twins to Digital Patients
The past decade has seen a rapidly expanding body of literature on the development and use of digital twins in medicine. Since 2020 around 3000 articles have been published that broadly address various topics related to digital twins, including their use in medicine. This paper focuses on the major challenges that come into play when considering the development of digital twins that seek to replicate an individual human and changes in health over time. Integrating the numerous medical digital twins that are currently being developed into a functional Digital Patient involves creating a detailed digital representation of a person that can simulate their behavior, health status and ranking on a variety of social determinants of health. The major challenges in the development of a multi-scale, interoperable, verifiable Digital Patient are highlighted in this paper. The overall challenge is to integrate the thousands of digital twins developed in the past few years into a usable Digital Patient. Issues that must be addressed include data collection, data integration and analysis, modeling and simulation, artificial intelligence (AI), visualization, clinical applications, security, and tools that facilitate development of usable simulated digital twins.
C Donald Combs
Open Access
Article
Conference Proceedings
Structural Risk Recalibration and Stochastic Stationarity in Localized Large-Scale Health Data: An Intelligent Difference-in-Differences Framework
This study proposes a framework for analyzing the reliability of spatial health data through structural system integrity. We define a health system state through a tuple S = <L, C, D, E, NE, OBS, RF>, where local observations (L) must be calibrated against a national contextual baseline (C) to ensure inferential integrity. In this architecture, a portion of the experimental population (E) is exposed to a specific determinant (D), compared to a non-exposed (NE) group. By applying four mathematical operators, a total system gap (Delta), a relative weighting gap (G_w), a structural difference-in-differences function (DiD), and a recentered influence function (RIF), we executed our context-aware framework on a large-scale health-disease incidence local dataset relative to its broader spatial context. Our framework demonstrated its efficacy by extrapolating, in the example of interest, a critical 32.5% G_w, indicating an under-representation of the older population within the local space compared to the national context. Significantly, the application of DiD uncovered a 18.2% asymmetric divergence of the observed disease incidence in the NE (non-exposed) group compared to E, relative to national benchmarks. The subsequent RIF recalibration failed to reach a contextual leverage, proving that the initially calculated risk factor (RF) was an outcome of internal fractures rather than a signal emitted by the health system. The use of our framework proved that an unbalanced choice of the experimental population (marked by a -45.1% deficit in the older NE arm) had rendered the initial calculation of risk structurally unstable. We demonstrate that without contextual calibration, geospatial large scale health data can produce phantom signals indistinguishable from systemic errors.
Marco Roccetti
Open Access
Article
Conference Proceedings
Design and development of an electronic oral medication dispenser for older adults
This study presents the design and development of an electronic oral medication dispenser aimed at improving therapeutic adherence and reducing risks associated with polypharmacy in older adults. Polypharmacy, commonly defined as the concurrent use of three or more medications, increases the likelihood of adverse drug reactions, medication errors, and preventable hospitalizations, particularly among aging populations with chronic conditions.A user-centered design methodology was implemented, integrating ergonomic, cognitive, and functional considerations specific to older adults. The development process included contextual inquiry, requirement definition, system architecture design, iterative prototyping, and preliminary usability validation. Design priorities focused on minimizing operational complexity, enhancing perceptual feedback, and reducing the probability of dosing errors.The resulting prototype is capable of storing and dispensing up to three daily doses over 30 days. The system incorporates a programmable electronic controller for scheduled dispensing, a visual notification interface, and an adjustable auditory alarm to reinforce medication reminders. The modular architecture allows future integration of wireless connectivity for remote adherence monitoring by caregivers or healthcare professionals, as well as optional accessory expansion.This work demonstrates the feasibility of integrating user-centered product design with embedded electronic systems to support medication management in older adults. The proposed solution contributes to safer medication administration and represents a scalable platform for future telehealth-enabled applications in geriatric care.
Alberto Rossa-Sierra, Mariel Garcia-Hernandez, Gabriela Duran-Aguilar, Fabiola Cortes-Chavez, David Vidaña-Zavala
Open Access
Article
Conference Proceedings
Deep-Learning Assisted Digital Twin of Stereo Camera for non-Invasive Underwater Fish Biomass Estimation
Digital twins have become increasingly important in aquaculture, a sector traditionally dependent on manual, subjective, invasive, and labor-intensive practices. This trend is driven by the convergence of precision aquaculture and AIoT technologies, enabling a shift from experience-based practices to intelligent, data-driven systems. Existing AIoT architectures are highly specialized, addressing function-specific requirements. This work proposes a digital twin–enabled smart stereo camera system for monitoring fish growth through non-invasive biomass estimation of freely swimming fish. The digital twin framework includes a processing pipeline consisting of RGB-D video acquisition, 6D (RGB-XYZ) representation generation, 3D point cloud Transformer-based segmentation, and fish biomass regression. First, the stereo camera captures RGB-D video in the aquaculture environment, which is automatically transmitted to a cloud system for further processing. The RGB-D frames are then transformed into 6D (RGB-XYZ) representations for subsequent analysis. A 3D point cloud Transformer is then used to detect and segment fish objects from the 6D representations. Finally, the reconstructed 3D fish objects are used for k-nearest neighbors (KNN) regression to estimate fish biomass. The contributions of this work are as follows. First, the digital twin approach enables the transformation of aquaculture toward intelligent farm management. Second, the 3D computer-vision-based fish biomass estimation scheme is a non-invasive model for understanding the status of fish growth without disturbing fish schools. Third, the proposed 3D point cloud Transformer has low computational complexity and can be deployed on edge-computing platforms with limited GPU resources. Finally, the digital twin model synthesizes fish growth data based on the existing fish growth model to improve the estimation accuracy of fish biomass. To the best of our knowledge, this work presents one of the first digital twin–enabled smart camera systems deployed in real aquaculture environments for real-time fish growth monitoring.
Hsun Yu Lan, Bo-Cheng Huang, Shyi-Chyi Cheng
Open Access
Article
Conference Proceedings
Environmental Digital Twins: a review of challenges and opportunities
Digital Twin (DT) technology has emerged as a transformative paradigm for environmental monitoring, modelling, and sustainability governance, yet its development across ecological and territorial domains remains fragmented and unevenly documented in the literature. This review provides a systematic mapping of Ecological Digital Twin (EcoDT) and Environmental Digital Twin applications published between 2020 and 2025, analysing a corpus of 121 peer-reviewed studies spanning urban environments, agriculture, marine and coastal systems, river and lake networks, forestry, ecology, glaciers, Earth system science, and building sustainability. Drawing on a structured analytical matrix , the review focuses on Technology Readiness Level (TRL), remote sensing integration, data-related challenges, and future development priorities, interrogating Dts technological maturity, sustainability framing, and data readiness in practice. Results reveal a field in active but early-stage development: the TRL distribution is concentrated between levels 2 and 6, with no study in the corpus reaching deployment-ready status, and sustainability framing remains predominantly environmental in orientation, with social and economic co-benefits systematically underrepresented across nearly all application themes. Integration, interoperability, and calibration emerge as the most pervasive and structurally recurring technical constraints. Scaling and deployment, alongside governance and institutional alignment, dominate the stated future priorities of reviewed studies. The review concludes by advocating for the adoption of F.A.I.R., C.A.R.E., and T.R.U.S.T. data governance principles as a foundational framework for advancing EcoDTs and Environmental DTs towards integrated, equitable, and policy-relevant implementation at territorial and ecosystem scales.
Letizia Artioli, Giovanni Borga, Pietro Costa
Open Access
Article
Conference Proceedings
Methodical Approach for the Development of Multi Domain Testing Environments for Stable Operation Under Impulse Excitation
Repeated impulsive loads are critical for both structural integrity and human vibration exposure in power tools such as rotary hammers. Therefore, they need to be evaluated in a precise manner in order to consider them in design of these power tools. However, existing testing environments used to gain insights often fail to reproduce highly transient impact behaviour in a controllable and adjustable way, particularly when different physical domains, like mechanic and hydraulic, and workpiece properties must be represented. This paper proposes a five step, multi domain capable methodical development approach that operationalises Ewins’ structural dynamics toolkit into an approach for developing testing environments under impulse excitation, covering virtual modelling, real system characterisation, model parametrization, derivation of design parameters, and testing. For evaluation this method, is then applied to a hydraulically based substitute workpiece for rotary hammers to achieve adjustable damping behaviour and equivalence in effect to different real concrete workpieces within defined operating limits. The results demonstrate that the proposed approach enables the systematic development of testing environments and substitute workpieces that realistically reproduce impact behaviour while remaining reproducible, adjustable and suitable for integrated modelling, identification and validation.
Sascha Hasenoehrl, Johannes Klotz, Patric Grauberger, Sebastian Zimprich, Niklas Bargen-Herzog, Jiahang Li, Marcus Geimer, Sven Matthiesen
Open Access
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Conference Proceedings
E-learning Design for Visually Impaired Students
Some of the most common problems faced by students with serious vision impairment bring in inaccessibility of web sites. The guidelines for web accessibility for the visually impaired are not specific enough for the effective design of learning materials for the vision impaired. Additional teaching aids created specifically for vision impaired students are necessary to ensure the students understand the concepts being taught. This paper describes the development of an available e-learning environment to bring advanced IT network curriculum to visually impaired students. The program involves a virtual classroom, accessible learning materials, a remote computer laboratory, and delivery of the learning materials by trained instructors. Cisco Program course in advanced IT was improved, and the accessible on-line learning environment was developed to supply the courses. Trained instructors were used to assist with the design of accessible methods and provided the materials to the visually impaired students. The project has been operational for two years with an experimental project being conducted over two-year period in the School of Design of IADE, followed by the delivery of the courses both local and remote visually impaired students across Portugal using this available e-learning environment. Estimate results shows that vision impaired students situated both locally and remotely got equivalent grades to their sighted students, because of additional time to comprehend and experiment via the virtual classroom and remote computer laboratory. In addition, the use of trained instructors has resulted in more innovative approaches to available teaching methods and the successful of the program.
Theresa Lobo
Open Access
Article
Conference Proceedings
Formulating Cybersecurity Strategies in Corporate Management: Business Strategy and Cybersecurity
In recent years, the landscape surrounding cyberattacks has been steadily becoming more sophisticated and cunning. Amidst this situation, companies, particularly operating companies, need to advance countermeasures against cyberattacks, yet it is difficult to say that cybersecurity measures are necessarily robust. On the other hand, a survey on the actual state of information security measures among small and medium-sized enterprises (SMEs), published by the Information-technology Promotion Agency (IPA), an external organization of the Ministry of Economy, Trade and Industry (METI) which oversees Japan's information security sector, also reports that implementing countermeasures has reduced the damage from cyberattacks. Under this situation, cybersecurity must be recognized as a “management issue.” This paper focuses on the fact that while cybersecurity has become a critical risk issue in corporate management, there are few frameworks to advance countermeasures. It employs the concept of the Balanced Scorecard, a management evaluation method used in corporate management. The Balanced Scorecard holds that financial management alone cannot accurately evaluate business performance; it incorporates non-financial elements to appropriately assess corporate management. Similarly, in cybersecurity, promoting countermeasures based solely on the financial perspective of countermeasure costs is difficult. Therefore, this paper proposes a methodology using the concept of a “Balanced Scorecard.” Furthermore, to bridge the gap between management and security personnel in the cybersecurity field, it proposes solutions through two distinct approaches.
Hiroyuki Hasegawa, Kenji Watanabe, Ichiro Koshijima, Masahiro Arakawa
Open Access
Article
Conference Proceedings
Design of an Intelligent Agent for Offshore Cage Aquaculture Based on a Cold-Damage Early-Warning Model
Climate-change-driven anomalies in seawater temperature frequently trigger cold-damage events, leading to significant fish mortality and economic losses in marine cage aquaculture. Although Internet of Things (IoT) systems and marine meteorological observation (MMO) data have been widely used for environmental monitoring, challenges remain in addressing microclimate data scarcity, domain shift, and the prediction of rare extreme events, limiting their effectiveness for actionable farm management. In this study, long-term (2000–2025) MMO datasets from 14 stations of the Taiwan Central Weather Administration, including seawater temperature, air pressure, and wave dynamics, were integrated with real-time offshore sensor data. Based on these inputs, a time-series deep-learning-based intelligent agent, TPP-CASTformer, is proposed. To address data scarcity and domain shift, Test-Time Training (TTT) enables model adaptation during inference using unlabeled target-site data. In addition, a classification mechanism combining Temporal Point Processes and Prototypical Networks is designed to improve interpretability and handle extreme-event imbalance through few-shot learning. The proposed framework integrates heterogeneous MMO and local sensing data, incorporates domain knowledge to define temperature thresholds and exposure durations, and provides interpretable early-warning signals with corresponding management actions. Experimental results based on documented cold-damage events in Penghu, Taiwan indicate that the proposed approach can reduce potential losses by at least 30%, demonstrating improved accuracy and timeliness in cold-damage risk assessment.
Hsun Yu Lan, Chi-Lin Tsai, Shyi-Chyi Cheng
Open Access
Article
Conference Proceedings
Acceptance of Social Robots in Institutional Reception Services: Findings from a Focus Group Study Using Temi
The integration of social robots into service environments is gaining increasing attention, especially in contexts that combine efficiency demands with interpersonal interaction. This study explores the potential use of the social robot Temi in the reception area of a Swiss institutional service setting and examines how reception staff assess suitable applications, acceptance conditions, and implementation-related concerns. Guided by the Service Robot Acceptance Model (sRAM), the study draws on an exploratory qualitative focus group with five reception staff members, complemented by reflection tasks, a live robot demonstration, and a final ranking exercise. Data was analyzed using qualitative content analysis.The findings show that reception work is valued primarily for its social and relational qualities, whereas repetitive information requests, routine technical questions, and frequent interruptions are seen as burdensome. Temi was therefore seen mainly as a complementary support tool for standardized, repetitive, and high-frequency tasks, especially wayfinding, room information, Wi-Fi access, and simple first-level IT support. Acceptance depended on reliability, ease of use, and clear, context-appropriate communication. Participants also emphasized the importance of voice, appearance, and first impression, as Temi needed to appear both approachable and appropriate to the institutional setting. Concerns about job loss were minimal; instead, participants highlighted data protection, maintenance responsibilities, and effort-benefit considerations. Overall, Temi was seen as most acceptable when relieving staff of routine tasks while preserving meaningful human interaction
Selin Sengül, Brigitte Meier, Chantal Meier, Pascal Meier, Marc Zeugin, Oliver Christ
Open Access
Article
Conference Proceedings
Interpretable Analysis of Rainfall-Runoff Forecasting Using MLP and Perturbation-based Approach in the Sisaony River, Madagascar
This study examines the performance of a rainfall-runoff model based on a Multi-Layer Perceptron (MLP), supplemented by an Explainable Artificial Intelligence (XAI) analysis using a perturbation-based approach. The MLP model predicts the hourly instantaneous discharge of the Sisaony River in Madagascar based on precipitation, two estimates of potential evapotranspiration (PET), and past discharge data, for forecast horizons of 24 hours, 18 hours, 12 hours, 9 hours, 6 hours, or 3 hours. The results are compared to forecasts obtained from a conventional GRP (Génie Rural pour la Prévision de crue)-type rainfall-runoff model and show that the MLP performs well, particularly for longer horizons. To address the issue of interpretability, a perturbation-based explainability approach was applied by replacing input variables with zero or their mean. The analysis reveals that discharge is the most influential variable, confirming the strong autoregressive behavior of the system. Finally, the study demonstrates that combining deep learning models with explainability techniques provides both strong predictive performance and improved understanding of model behavior, offering a promising approach for flood forecasting and risk management in data-limited regions.
Hanitriniaina Marielle Rakotozanany, Pierre NICOLLE, Josué RATOVONDRAHONA, Bob SAINT-FLEUR, Andry RAZAKAMANANTSOA, Samuel RAZANAKA, MAHATODY Thomas, Olivier PAYRASTRE
Open Access
Article
Conference Proceedings
Virtual Reality Simulation as a Tool for Salutogenic and Multisensory Interior Design: A Human-Centric Well-Being Approach
Contemporary interior architecture increasingly shifts from function-oriented design toward approaches that prioritise users’ wellbeing and spatial experience. However, despite growing recognition of the role of multisensory spatial atmosphere in shaping emotional responses and environmental comfort, designers still lack methodological tools enabling systematic evaluation of these factors at early design stages. This paper proposes a conceptual framework integrating immersive virtual reality (VR) simulation with multisensory perception theory and the salutogenic model of sense of coherence (SOC) as a methodological basis for analysing atmospheric spatial parameters in interior environments. The framework organises relationships between spatial design variables, perceptual mechanisms, and simulation-based evaluation procedures within a three-level structure enabling controlled investigation of users’ responses to colour, lighting conditions, material tactility, spatial proportions, and environmental legibility. By positioning immersive virtual environments as perceptual laboratories rather than visualisation tools, the proposed model supports evidence-based assessment of spatial atmosphere prior to implementation and contributes to the development of wellbeing-oriented interior design strategies grounded in measurable environmental parameters.
Agnieszka Rek-Lipczyńska
Open Access
Article
Conference Proceedings
Virtual Reality for Safe Integration of Collaborative Robots
Industry 4.0, the ongoing transformation of production systems and work organization through the integration of digital technologies, creates new health and safety challenges in the workplace. In particular, collaborative robotics offers increased flexibility in workstation design, permitting a robot and an operator to share a task or a workspace. However, this proximity with the robot exposes the operator to physical risks in a way that requires new means of prevention. In this context, digital technologies of Industry 4.0, such as simulation and Virtual Reality (VR) offers promising opportunities for early-stage, human-centered, rapid, iterative workstation design by involving operators in the design process of their future workstation when adaptations are still easy to implement. However, we have identified limitations of current robotic simulation tools with respect to integrating safety concerns or human-robot interaction, and of VR that has limited validity, i.e., ability to accurately reflect the activity of the operator in the real workstation. To further assess and address these limitations, a VR application was developed using ROS 2 and Unity. It enables the execution of the robot program within a virtual environment and in interaction with the workpieces and human operator, so that it can later be seamlessly deployed on the real robot. In this article, we present a proof of concept of how VR can be used in the collaborative robot integration process. A preliminary validation step and user feedback suggests differences between the real and virtual task with respect to execution time and mental load, but with good validity with regard to postures. An experimental protocol for more robust validation is proposed.
Gabin Personeni, Daniil Danilovskii, Adriana Savescu
Open Access
Article
Conference Proceedings
Presenting ADS-B Labels in a Conventional and in a Remote Virtual Tower Environment: Beneficial or Disruptive?
This study evaluates whether Automatic Dependent Surveillance - Broadcast (ADS-B) information presented as aircraft label tags can enhance air traffic controllers’ situational awareness at conventional aerodrome towers and in remote virtual tower environments, despite the well-known limitations of ADS-B information. The concept leverages augmented reality to superimpose traffic labels onto the conventional out-of-the-window view using a HoloLens 2 headset, and secondly, a fully virtual aerodrome tower environment where the out-of-the-window view is generated by video streams or rendered in a Virtual Reality headset. By relying on an affordable ADS-B receiver, the solution aims to provide a cost-effective way to enhance traffic awareness, particularly at airports with very limited or even without any surveillance infrastructure. Three main research questions are addressed: (1) whether the concept is perceived as beneficial by operators despite the known limitations, (2) the level of user acceptance with respect to content, design, and presentation of the ADS-B label, and (3) operator preferences for head-up and head-down ADS-B label presentation in different equipage and visibility environments. A user-centred passive shadow-mode experiment was conducted with 10 subject-matter experts. Each expert tested the DLR prototype Virtual Tower application in good and low visibility, each experimental run twice with and without the augmented ADS-B label activated using recorded traffic scenarios at Braunschweig-Wolfsburg airport. Results show strong acceptance of the concept, with one expert recommending, and 9 out of 10 strongly recommending it. Very high usability ratings were achieved (average System Usability Scale score of 89), and qualitative feedback confirmed a general appreciation of the interface and the overall concept, further supporting this. Leveraging ADS-B data, especially at airports lacking surveillance, offers a cost-effective means to enhance controllers’ SA and could be implemented in the short term.
Jörn Jakobi, Julia Schön, Sara Bagassi, Tommaso Fadda
Open Access
Article
Conference Proceedings
An Adaptive XR Platform for Multimodal Public Speaking Training and Performance Assessment
Public speaking is a fundamental competence across academic, professional, and social contexts, yet an estimated 77% of the population experiences public speaking anxiety (PSA), manifesting through psychological symptoms – such as fear of judgment and avoidance behaviours – and physiological responses including increased heart rate and electrodermal activity. Traditional training approaches face limitations in scalability, reproducibility, and objective performance assessment, often relying on subjective rubrics and offering limited opportunities for repeated practice in realistic settings. Extended Reality (XR) technologies have emerged as a promising alternative, as immersive virtual environments can reliably elicit anxiety responses comparable to real audiences while providing safe, controllable, and repeatable practice scenarios. However, most existing XR platforms focus primarily on exposure, without systematically capturing or leveraging the multimodal signals that reflect a speaker's internal state and communicative behaviour. Incorporating behavioural data such as gaze patterns, gesture dynamics, and spatial movement, alongside psychophysiological signals and speech acoustics, is essential to move beyond subjective evaluation toward objective characterization of user states, enabling personalized feedback and real-time training adaptation. This paper presents the design, implementation, and preliminary assessment of an adaptive XR platform for public speaking training that integrates these multimodal data streams within a five-layer architecture (Environment Generation, Data Gathering, Analysis, Feedback, and Visualization), instantiated through a modular microservices approach. A preliminary usability assessment with ten participants demonstrates the platform's learnability and task completion effectiveness, advancing beyond exposure-only systems toward intelligent, data-driven, and personalized skill development.
Lia Cardoso, Hugo Correia, Bernardo Marques, Paulo Dias, Samuel Silva, Beatriz Sousa Santos
Open Access
Article
Conference Proceedings
Designing Together at a Distance: Mediating Industrial Remote Co-Design Through eXtended Reality Technologies
Remote collaboration is increasingly central to today’s globalized economy, yet distributed teams still face challenges related to limited shared context, reduced expressiveness, and lower engagement. These issues are especially critical in industrial co-design, where complex physical artifacts, spatial reasoning, and multidisciplinary coordination play a key role. Conventional remote tools often fail to adequately convey geometry, scale, and functional relationships, resulting in misunderstandings and extended iteration cycles. To address these challenges, we explore eXtended Reality (XR) to support remote co-design in industrial settings. XR enables collaborators to establish common ground through spatially anchored digital content, such as three-dimensional models, annotations, measurements, and multimodal communication, bridging gaps between physical and remote collaboration. We propose a pervasive Augmented Reality (AR) tool for distributed co-design that allows users to manipulate digital models, generate exploded views, inspect components, perform precise measurements to assess tool applicability, and create three-dimensional annotations. Collaboration can occur synchronously or asynchronously, enabling iterative contributions and refinement of design decisions until consensus is achieved. We evaluated the approach through a user study with 30 participants in a real-world industrial scenario involving the central mold of a heavy hydraulic press. Results show that the tool establishes a shared discussion space, promotes attentional engagement, enhances understanding of complex design information, and supports articulation of ideas, while maintaining low mental and physical workload. Overall, the findings highlight the potential of immersive technologies to enhance industrial co-design beyond physical boundaries and reinforce the value of a human-centered design approach aligned with existing work practices.
Fábio Barros, Pedro Reisinho, Bernardo Marques, João Alves, Mariana Leite, Tiago Coelho, Jorge Neves, Jorge Figueiredo, Duarte Almeida, Carlos Ferreira, Paulo Dias, Beatriz Sousa Santos
Open Access
Article
Conference Proceedings
The contribution of artificial intelligence for optimization pattern cutting plan to reducing textile industry waste in fashion design solutions
By increasing knowledge about the problem and calling for sustainable and circular solutions, governments, institutions, and organizations encourage companies, fashion brands, and industries to address the main sources of pollution in the textile sector by reducing waste. Scaling sustainable solutions is quite challenging because these solutions require a lot of study to develop eco-friendly production methods. This study explores how artificial intelligence (AI) using digital solutions for pattern cutting plan reduced waste from cutting the manufacturing of garments. The digital solutions for development pattern cutting plan, such as optimization plan software, is a program that enables the creation of pattern plans for cutting and production of clothing pieces. On the other hand, the software of making plans, supports the use of artificial intelligence to optimize an expansion strategy by conducting nesting simulations to achieve the most efficient and least wasteful plan. These studies, which used these digital solutions, were conducted in the CAD laboratories of the textile department at the University of Beira Interior and aim to develop a study for different fashion design pieces, different sizes, and combinations of sizes in the marker plan. With the study conducted on the various marker-making, it is concluded that the use of AI in digital tools given more efficiency and productivity, and there is a limit of number of combinations of sizes to reduce waste. It was cut and a prototype was produced to demonstrate the potential of the threads made with visual textile yarn orientation material. For this, a twill fabric produced within the scope of be@t was used, with a yarn in the weft 50% recycled produced in the DCTT laboratories at University of Beira Interior. It was concluded that these digital tools allow companies in the textile industry to save time, resources and improve their ability to make quick decisions and study different options with less time for reduce waste, compared with solutions without artificial intelligence.
Sandra Ferreira, Rui Miguel, Teresa Raquel Barata, Marta Bicho, Joaquim Trindade, Madalena Pereira
Open Access
Article
Conference Proceedings
Mixed Reality–Driven Rehabilitation Using a Robotic Exoskeleton and an Immersive Game-Based Interface
Stroke is a major cause of long-term disability worldwide and frequently leads to lasting motor deficits that severely compromise upper-limb function and diminish patients’ independence. The World Health Organization reports that every year millions of people live through a stroke but are left with permanent impairments that demand ongoing rehabilitation. However, access to intensive, individualized treatment is often constrained by social, economic, and technological factors, as well as poor adherence to repetitive training routines. To address these issues, this work introduces an interactive Mixed Reality (MR) rehabilitation system aimed at supporting upper-limb motor recovery while enhancing patient motivation. The system targets right-hand bidigital pinch training and offers two complementary operating modes: (i) an assisted therapy mode using a Bluetooth-controlled robotic exoskeleton, which guides users through prescribed therapeutic movements and exercise sequences; and (ii) an immersive, game-like mode that situates rehabilitation tasks within Activities of Daily Living (ADL) contexts. The platform was implemented in Unity and deployed on the Meta Quest 3S headset, delivering real-time visual feedback via an interactive human–computer interface. The system was evaluated through rehabilitation sessions with healthy volunteers, who subsequently assessed their experience using standardized tools, including the System Usability Scale (SUS), the Virtual Reality Sick-ness Questionnaire (VRSQ), and the NASA Task Load Index (NASA-TLX). The findings revealed good usability and manageable workload levels, indicating that the proposed MR-based system is a promising and engaging complement to conventional upper-limb rehabilitation approaches.
David González, Guillermo Aguilera, Jeronimo Rueda Giraldo, Iván Mondragón, Wilson Hernandez, Catalina Alvarado, Diego Mendez, Julian Colorado
Open Access
Article
Conference Proceedings
Design of a Hydraulic Substitute Base for Demolition Hammers
Substitute bases for demolition hammers should emulate mineral materials. Their advantage over mineral materials is that they are not destroyed by the energy of high-frequency impacts, enabling repeatable tests for the development of demolition hammers. To date, no substitute bases are known that can represent a wide range of different materials in an equivalently effective manner. This paper presents a hydraulic substitute base whose stiffness and damping can be adjusted by varying oil volume, orifice cross-section, and preload pressure.
Johannes Klotz, Sascha Hasenoehrl, Sven Matthiesen, Marcus Geimer
Open Access
Article
Conference Proceedings
Mapping Knowledge Creation in Digital and Workplace Environments: A Data-Driven Scoping Review of Trialogical Learning
This study presents a data-driven scoping review of trialogical learning within the knowledge creation and collaborative learning literature, with particular attention to workplace and digitally mediated contexts. Although collaborative knowledge creation has been widely studied, the relationship between its theoretical foundations and its application in organisational and digital environments remains insufficiently integrated. The study examines the evolution, structure, and applications of the literature using a dataset of 6,525 publications that cite key foundational works. Bibliometric analysis and text mining were used to identify publication trends, thematic clusters, and the distribution of workplace and digital dimensions. The results show sustained growth in the literature and a diverse thematic structure dominated by educational and theory-driven research. Digital mediation is highly prevalent (approximately 89% of studies), while workplace-related research is also widely represented (approximately 65%) but remains secondary in the thematic structure. Approximately 59% of studies include both workplace and digital elements. The findings indicate that research is distributed across multiple domains but lacks systematic integration. The study highlights the need for approaches that connect theoretical frameworks with workplace practices and digital environments.
Abiodun Afolayan Ogunyemi
Open Access
Article
Conference Proceedings
User Acceptance and Perceptions of IoT-Based Smart Trash Bin Systems for Smart Waste Management
Waste management remains a growing challenge in universities and office settings due to increased waste production, a shortage of cleaning staff, hygiene issues, and ineffective monitoring of traditional trash bins. This research explores users’ perceptions, acceptance, and expectations of IoT-based smart trash bins designed at improve waste management efficiency in business environments. It focuses on user opinions about features like automated lid opening, dual notification alerts, automatic locking, and hand sanitizer integration, which aim to enhance hygiene, prevent overflow, and boost operational efficiency. The study employed a mixed-method design, using questionnaires and interviews to assess user perceptions and acceptance of smart waste management solutions.The results show strong user support for smart waste management systems, especially for features that enhance hygiene, automate monitoring, and decrease reliance on manual inspections by cleaning staff. Participants stressed the significance of automatic lid-opening, notification alerts, and smart monitoring for improving waste management efficiency. Feedback also raised concerns about costs, network reliance, and user adaptability. Overall, the findings reveal positive attitudes toward IoT-enabled waste systems and highlight the potential of smart trash bins to advance smart campus initiatives and sustainable operations. This study adds to the expanding research on smart technologies by exploring user-focused viewpoints on IoT-driven waste management systems and highlighting practical factors for future deployment in business and office settings.
Rabaa Alabdulrahman, Shubashini Velu
Open Access
Article
Conference Proceedings
Traffic Flow Analysis in Mixed Environments with Autonomous and Human-Driven Vehicles
Autonomous vehicles (AVs) have the potential to improve traffic efficiency, safety, and environmental sustainability; however, their impacts under mixed traffic conditions remain unclear. This study investigates the effects of cautious autonomous vehicles on traffic performance at different MPRs(market penetration rates) in a mixed environment with human-driven vehicles. A microscopic traffic simulation was developed using VISSIM and applied and applied to the Harbour Toll Road in Jakarta, Indonesia with driving behavior parameters calibrated to reflect realistic human-driven and autonomous vehicle characteristics. Several scenarios were analyzed, ranging from fully human-driven traffic to fully autonomous traffic, with AV MPR in 10% increments. Traffic performance was evaluated using level of service (LOS), average speed, traffic volume, vehicle delay, queue length, fuel consumption, and emissions. The results show that at low AV penetration levels, mixed traffic conditions can initially worsen performance due to conservative autonomous driving behavior and interaction conflicts with human drivers. In these scenarios, delays, congestion, and emissions increase compared to conventional traffic. As the AV MPR increases, traffic performance improves significantly. At penetration levels above 90%, cautious autonomous vehicles substantially enhance level of service, increase average speed and traffic throughput, and reduce vehicle delays and queue lengths. Environmental benefits are also observed at high penetration levels, with notable reductions in emissions and fuel consumption. These findings indicate that the positive impacts of autonomous vehicles strongly depend on high adoption rates and highlight the importance of supportive infrastructure and traffic management strategies during the transition to autonomous mobility.
Maftuh AHNAN, Dukgeun Yun
Open Access
Article
Conference Proceedings