Fuzzy logic for situation awareness: a systematic review

D’Aniello, Giuseppe

doi:10.1007/s12652-023-04560-6

Cited by 12 publications

(5 citation statements)

References 161 publications

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“…In addressing the challenge of attention recognition, facial emotion detection has been employed to forecast human attention allocation within visual saliency prediction scenarios, yielding favorable outcomes [59,60]. The current attention recognition systems, which are crucial for ensuring the reliability of emotional data, incorporate fuzzy logic to capture the nuances of a user's attention level [61].…”

Section: Technologies For Valence and Engagement Evaluationmentioning

confidence: 99%

Facial Expression Recognition for Measuring Jurors’ Attention in Acoustic Jury Tests

Jamali,

Generosi,

Villafan

et al. 2024

Sensors

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The perception of sound greatly impacts users’ emotional states, expectations, affective relationships with products, and purchase decisions. Consequently, assessing the perceived quality of sounds through jury testing is crucial in product design. However, the subjective nature of jurors’ responses may limit the accuracy and reliability of jury test outcomes. This research explores the utility of facial expression analysis in jury testing to enhance response reliability and mitigate subjectivity. Some quantitative indicators allow the research hypothesis to be validated, such as the correlation between jurors’ emotional responses and valence values, the accuracy of jury tests, and the disparities between jurors’ questionnaire responses and the emotions measured by FER (facial expression recognition). Specifically, analysis of attention levels during different statuses reveals a discernible decrease in attention levels, with 70 percent of jurors exhibiting reduced attention levels in the ‘distracted’ state and 62 percent in the ‘heavy-eyed’ state. On the other hand, regression analysis shows that the correlation between jurors’ valence and their choices in the jury test increases when considering the data where the jurors are attentive. The correlation highlights the potential of facial expression analysis as a reliable tool for assessing juror engagement. The findings suggest that integrating facial expression recognition can enhance the accuracy of jury testing in product design by providing a more dependable assessment of user responses and deeper insights into participants’ reactions to auditory stimuli.

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Section: Technologies For Valence and Engagement Evaluationmentioning

confidence: 99%

Facial Expression Recognition for Measuring Jurors’ Attention in Acoustic Jury Tests

Jamali,

Generosi,

Villafan

et al. 2024

Sensors

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“…Alamri et al, 2022;Edwita et al, 2017;ZareRavasan and Krčál, 2021) separately. Reviews that analyse combinations of these concepts, such as fuzzy ontologies (Qasim et al, 2020;Zhang et al, 2016), fuzzy logic for different types of systems (Yu et al, 2023;D'Aniello, 2023), are rarely found (see Table 1).…”

Section: Related Work and Reviewsmentioning

confidence: 99%

Ontology and Fuzzy Theory Application in Information Systems: A Bibliometric Analysis

Kalibatienė,

Miliauskaitė,

Slotkienė

2024

Informatica

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Ontologies are used to semantically enrich different types of information systems (IS), ensure a reasoning on their content and integrate heterogeneous IS at the semantical level. On the other hand, fuzzy theory is employed in IS for handling the uncertainty and fuzziness of their attributes, resulting in a fully fuzzy IS. As such, ontology- and fuzzy-based IS (i.e. ontology and fuzzy IS) are being developed. So, in this paper, we present a bibliometric analysis of the ontology and fuzzy IS concept to grasp its main ideas, and to increase its body of knowledge by providing a concept map for ontology and fuzzy IS. The main results obtained show that by adding ontologies and fuzzy theory to traditional ISs, they evolve into intelligent ISs capable of managing fuzzy and semantically rich (ontological) information and ensuring knowledge recognition in various fields of application. This bibliometric analysis would enable practitioners and researchers gain a comprehensive understanding of the ontology and fuzzy IS concept that they can eventually adopt for development of intelligent IS in their work.

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“…In an effort to effectively enhance the regulation of room temperature and humidity, Fuzzy Inference Systems (FIS) have emerged as efficient solutions (13)(14)(15). FIS is a regulatory method rooted in fuzzy logic, enabling machines to make decisions based on multiple influencing variables (16). In the context of regulating room temperature and humidity, FIS empowers IoT devices to intelligently manage indoor temperature and humidity based on specified parameters.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency with Internet of Things Based Fuzzy Inference System for Room Temperature and Humidity Regulation

Furizal,

Sunardi,

Yudhana

et al. 2024

IJE

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Energy consumption is a crucial aspect in the effort to optimize the utilization of resources and reduce energy wastage. Focusing on energy efficiency can result in operational cost savings, a reduction in greenhouse gas emissions, and support for environmental sustainability for future generations. Therefore, it is important to consider energy efficiency in daily life, especially in the use of electricity for electronic devices. This research aims to compare the energy efficiency of two different approaches to Air Conditioner (AC) usage: the manual method and the fuzzy logic method. The manual method involves eight tests with direct power measurements over a 30-minute period at various AC temperature settings, namely 18°C, 20°C, 23°C, 24°C, 25°C, 26°C, 27°C, and 30°C. On the other hand, the fuzzy logic method involves six tests allowing for dynamic temperature adjustments based on room conditions. The research findings indicate that the fuzzy logic method achieves lower average power consumption, except at 30°C, where the manual method is slightly more efficient (a difference of 140,745 watts). This difference is primarily attributed to the "cooling and fan" mode used at lower temperatures in the manual method, resulting in higher power consumption. Furthermore, this research reveals the potential of the fuzzy logic in optimizing AC power usage based on real-time conditions, achieving approximately a 41.96% energy savings. The primary contribution of this study is to provide practical insights into how the fuzzy logic method can significantly reduce AC energy consumption, support energy efficiency efforts, and contribute to environmental sustainability.

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Fuzzy logic for situation awareness: a systematic review

Cited by 12 publications

References 161 publications

Facial Expression Recognition for Measuring Jurors’ Attention in Acoustic Jury Tests

Facial Expression Recognition for Measuring Jurors’ Attention in Acoustic Jury Tests

Ontology and Fuzzy Theory Application in Information Systems: A Bibliometric Analysis

Energy Efficiency with Internet of Things Based Fuzzy Inference System for Room Temperature and Humidity Regulation

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