Multimodal Technologies and Interaction

20 pages, 3083 KiB

Open AccessArticle

Exploring an Emoji-Based Evaluation and Intervention Method for Psychological Safety in Ongoing Co-Creations

by Qiner Lyu, Gaku Kutsuzawa, Hiroyuki Umemura, Kenta Kimura, Masaaki Mochimaru and Akihiko Murai

Multimodal Technol. Interact. 2025, 9(5), 40; https://doi.org/10.3390/mti9050040 - 24 Apr 2025

Abstract

Psychological safety is pivotal for co-creation to build an open environment where innovative ideas can flourish. Traditionally, psychological safety has been evaluated from a stable and long-term perspective by implementing psychological scales. Consequently, existing interventions often focus on steadily enhancing psychological safety, which is less suitable for dynamic short-term co-creation settings. The purpose of this study is to introduce the use of emojis as a novel and intuitive interaction during co-creations and assess their effectiveness in evaluating and influencing psychological safety. We performed two experiments with 140 participants in total to test emojis as evaluations and interventions, respectively. The participants watched videos and annotated them with emojis based on their perceptions of emotions. This process allowed us to explore the relationship between perceived emotions and psychological safety. In the next phase, we embedded emojis directly into the videos to observe whether the participants’ emotional perceptions—and, consequently, their psychological safety—could be influenced by visual cues. Our findings demonstrate that positive emojis are positively correlated with psychological safety and negative emojis are negatively correlated with psychological safety. We also revealed that negative emojis significantly decreased psychological safety scores, whereas positive emojis did not lead to a corresponding increase. Full article

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22 pages, 4770 KiB

Open AccessArticle

Internet of Things and Artificial Intelligence for Secure and Sustainable Green Mobility: A Multimodal Data Fusion Approach to Enhance Efficiency and Security

by Manuel J. C. S. Reis

Multimodal Technol. Interact. 2025, 9(5), 39; https://doi.org/10.3390/mti9050039 - 24 Apr 2025

Abstract

The increasing complexity of urban mobility systems demands innovative solutions to address challenges such as traffic congestion, energy inefficiency, and environmental sustainability. This paper proposes an IoT and AI-driven framework for secure and sustainable green mobility, leveraging multimodal data fusion to enhance traffic management, energy efficiency, and emissions reduction. Using publicly available datasets, including METR-LA for traffic flow and OpenWeatherMap for environmental context, the framework integrates machine learning models for congestion prediction and reinforcement learning for dynamic route optimization. Simulation results demonstrate a 20% reduction in travel time, 15% energy savings per kilometer, and a 10% decrease in CO₂ emissions compared to baseline methods. The modular architecture of the framework allows for scalability and adaptability across various smart city applications, including traffic management, energy grid optimization, and public transit coordination. These findings underscore the potential of IoT and AI technologies to revolutionize urban transportation, contributing to more efficient, secure, and sustainable mobility systems. Full article

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36 pages, 12483 KiB

Open AccessArticle

Environments That Boost Creativity: AI-Generated Living Geometry

by Nikos A. Salingaros

Multimodal Technol. Interact. 2025, 9(5), 38; https://doi.org/10.3390/mti9050038 - 23 Apr 2025

Abstract

Generative AI leads to designs that prioritize cognition, emotional resonance, and health, thus offering a tested alternative to current trends. In a first AI experiment, the large language model ChatGPT-4o generated six visual environments that are expected to boost creative thinking for their occupants. The six test cases are evaluated using Christopher Alexander’s 15 fundamental properties of living geometry as criteria, as well as ChatGPT-4o, to reveal a strong positive correlation. Living geometry is a specific type of geometry that shows coherence across scales, fractal structure, and nested symmetries to harmonize with human neurophysiology. The human need for living geometry is supported by interdisciplinary evidence from biology, environmental psychology, and neuroscience. Then, in a second AI experiment, ChatGPT-4o was asked to generate visual environments that suppress creativity for comparison with the cases that boost creative thinking. Checking these negative examples using Alexander’s 15 fundamental properties, they are almost entirely deficient in living geometry, thus confirming the diagnostic model. Used together with generative AI, living geometry therefore offers a useful method for both creating and evaluating designs based on objective criteria. Adopting a hybrid epistemological framework of AI plus living geometry as a basis for design uncovers a flaw within contemporary architectural practice. Dominant design styles, rooted in untested aesthetic preferences, lack the empirical validation required to address fundamental questions of spatial quality responsible for human creativity. Full article

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36 pages, 18792 KiB

Open AccessArticle

VICTORIOUS: A Visual Analytics System for Scoping Review of Document Sets

by Amir Haghighati, Amir Reza Haghverdi and Kamran Sedig

Multimodal Technol. Interact. 2025, 9(5), 37; https://doi.org/10.3390/mti9050037 - 22 Apr 2025

Abstract

Scoping review is an iterative knowledge synthesis methodology concerned with broad questions about the nature of a research subject. The increasingly large number of published documents in scholarly domains poses challenges in conducting scoping reviews. Despite attempts to address these challenges, the specific step of sensemaking in the context of scoping reviews is seldom addressed. We address sensemaking of a curated document collection by developing a VIsual analytiCs sysTem for scOping RevIew of dOcUment Sets (VICTORIOUS). Using known methods within the machine learning community, we propose and develop six modules within VICTORIOUS: Map, Summary, Skim, SemJump, BiblioNetwork, and Compare. To demonstrate the utility of VICTORIOUS, we describe three usage scenarios. We conclude by a qualitative comparison of VICTORIOUS and other available systems. While existing systems leave their users with singular information items regarding a document set and gaining an aggregated assessment in a scoping review is often a challenge, VICTORIOUS shows promise for making sense of documents in a scoping review process. Full article

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Multimodal Technol. Interact., Volume 9, Issue 5 (May 2025) – 4 articles

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