Intelligent Environment Research Articles

Unveiling the Potential: Experts' Perspectives on Artificial Intelligence Integration in Higher Education

<p style="text-align:justify">This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.</p>

The ethical problems of ‘intelligence–AI’

Abstract Interest in artificial intelligence (AI) has grown rapidly alongside the ability to examine information in far vaster quantities and from more diverse sources, and to provide previously unattainable forms of evaluation. For the intelligence community, AI offers an important solution to their data collection bottleneck, allowing the data to be processed and analysed at speeds and in ways not previously possible. While AI has received some general criticism, when it is combined with the reach, secrecy, and coercive power of the intelligence community it creates unique ethical problems. Intelligence–AI exacerbates the biases AI creates, undermines proposed transparency solutions, and creates new ethical dilemmas and harms. This article examines intelligence–AI across its collection, processing, and analysis phases. It argues that open-source does not necessarily mean ethical, as the AI collection en masse of social media data violates citizens' privacy, consent and autonomy. The article also argues that AI-aided categorization is overly reductive and perpetuates harmful social binaries, while also revealing new private information beyond what was initially shared. Finally, it argues that the secretive intelligence environment prevents critical interrogation while promoting practices that, through the coercive power of the state, cause unequal harms across society.

Wireless programmable patterns of electro-hydraulic haptic electronic skins able to create surface morphology

Haptic feedback technology represents a frontier with revolutionary potential, particularly in virtual and augmented reality. Skin, as an underexplored sensory interface, holds tremendous potential to significantly enrich our perceptual experiences while directly impacting the fields of communication, entertainment, and medicine. This article presents a programmable, ultra-lightweight, and ultra-thin wireless wearable haptic electronic skin that achieves rapid response and large mechanical feedback force and deformation displacement output. The electronic skin comprises a series of haptic electro-hydraulic actuators, each with the weight of 0.023 g and the thickness of 199 μm. Each actuator can be independently regulated and produce a maximum normal force of 150 mN and a normal displacement of 0.58 mm, simultaneously achieving the haptic presentation of textures. Relying on a portable multi-channel control circuit system designed, each electro-hydraulic actuator of the haptic electronic skin can be precisely control to achieve various haptic patterns. Showcasing its potentials, the haptic technology aids visual-impaired individuals in reading books, provides ground navigation instructions, and enhances gaming experiences, contributing to a more immersive and authentic artificial intelligence environment.

Indoor localization algorithms based on Angle of Arrival with a benchmark comparison

Indoor localization is crucial for developing intelligent environments capable of understanding user contexts and adapting to environmental changes. Bluetooth 5.1 Direction Finding is a recent specification that leverages the angle of departure (AoD) and angle of arrival (AoA) of radio signals to locate objects or people indoors. This paper presents a set of algorithms that estimate user positions using AoA values and the concept of the Confidence Region (CR), which defines the expected position uncertainty and helps to remove outlier measurements, thereby improving performance compared to traditional triangulation algorithms. We validate the algorithms with a publicly available dataset, and analyze the impact of body orientation relative to receiving units. The experimental results highlight the limitations and potential of the proposed solutions. From our experiments, we observe that the Conditional All-in algorithm presented in this work, achieves the best performance across all configuration settings in both line-of-sight and non-line-of-sight conditions.

Precise Evaluation of Foreign Language Learning in Intelligent Environment

Precise Evaluation of Foreign Language Learning in Intelligent Environment

Usability and User Experience Evaluation in Intelligent Environments: A Review and Reappraisal

Intelligent environments are rapidly gaining ground, propelled by a rich sensor infrastructure, the Internet of Things, sophisticated reasoning capabilities, and Artificial Intelligence. In this complex technological landscape, crafting usable intelligent environments and assessing the user experience (UX) demands a thorough understanding of the concepts involved and the parameters that need to be studied. This paper carries out a review of usability and UX evaluation methods and frameworks, elaborating on fundamental concepts and presenting in detail approaches and methods reported in the literature. It additionally examines evaluation approaches in adaptive and ubiquitous computing systems, which are closely associated with intelligent environments, and presents UX challenges and evaluation frameworks in intelligent environments. Finally, the findings are synthesized and consolidated to produce a comprehensive overview of the field and the challenges that lie ahead.

Identifying the job competencies of Generation Z hotel employee in an intelligent environment in China

This study aims to identify and enhance the job competencies of Generation Z hotel employees in China, focusing specifically on how intelligent environments influence their job roles. Employing a mixed-methods approach, the research integrates focus group interviews with five groups to explore how job roles evolve in response to intelligent environments and uses questionnaires with 167 participants to develop a competency framework. The investigation addresses various dimensions of the intelligent hotel environment, including work support, internal communications, customer experience, and staff-customer interactions. Results show that the sense of responsibility towards customer interactions escalates to another level after hotels adopt an intelligent environment. Furthermore, this study establishes a job competency framework with 3 dimensions and 33 evaluation factors for Generation Z hotel employees, validated through Exploratory Factor Analysis and Confirmatory Factor Analysis. The framework of job competencies assists hotels in refining job competency assessment standards, developing robust performance appraisal systems, planning effective career development pathways, and designing targeted training programs. We expect these enhancements to significantly enhance the operational excellence and competitive advantage of hotels in China.

Preface to the 10th Anniversary Issue: Journal of Reliable Intelligent Environments

Preface to the 10th Anniversary Issue: Journal of Reliable Intelligent Environments

Towards intelligent environments: human sensing through 3D point cloud

To realize the concept of “Society 5.0”, which seeks to enhance well-being by integrating the Internet of Things to connect people, objects, and environments, intelligent environments are essential. These environments focus on creating sensor-enhanced spaces capable of recognizing and interpreting human behaviors and needs. This paper explores how we achieve intelligent environment by highlighting current technologies and applications of human sensing and tracking that enables such intelligent environments. Specifically, it introduces the development and application of LiDAR-based human sensing and tracking technologies, including the Hitonavi and Hitonavi-μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu $$\\end{document} systems, designed for multi-person tracking in extensive areas and for enabling person detection and activity recognition on edge devices, respectively. Moreover, the paper explains the services and applications of these methodologies to smart buildings, shopping malls, and elderly care, showcasing their potential to enhance safety, convenience, and understanding of human behavior within intelligent environments. Throughout this paper, we present our vision for creating reliable intelligent environments, which are fundamentally supported by sophisticated human sensing technologies.

Multiple Self-Powered Sensor-Integrated Mobile Manipulator for Intelligent Environment Detection.

A multiple self-powered sensor-integrated mobile manipulator (MSIMM) system was proposed to address challenges in existing exploration devices, such as the need for a constant energy supply, limited variety of sensed information, and difficult human-computer interfaces. The MSIMM system integrates triboelectric nanogenerator (TENG)-based self-powered sensors, a bionic manipulator, and wireless gesture control, enhancing sensor data usability through machine learning. Specifically, the system includes a tracked vehicle platform carrying the manipulator and electronics, including a storage battery and a microcontroller unit (MCU). An integrated sensor glove and terminal application (APP) enable intuitive manipulator control, improving human-computer interaction. The system responds to and analyzes various environmental stimuli, including the droplet and fall height, temperature, pressure, material type, angles, angular velocity direction, and acceleration amplitude and direction. The manipulator, fabricated using 3D printing technology, integrates multiple sensors that generate electrical signals through the triboelectric effect of mechanical motion. These signals are classified using convolutional neural networks for accurate environmental monitoring. Our database shows signal recognition and classification accuracy exceeding 94%, with specific accuracies of 100% for pressure sensors, 99.55% for angle sensors, and 98.66, 95.91, 96.27, and 94.13% for material, droplet, temperature, and acceleration sensors, respectively.

Fuzzy cognitive network process for software reliability and quality measurement: comparisons with fuzzy analytic hierarchy process

Software reliability and quality measurement has a long-lasting impact on the final products and user experiences. The analytic hierarchy process (AHP) and its various hybrid models, including fuzzy AHP, have been applied to software reliability and quality measurement in various aspects. Related studies indicate that limitations in the paired ratio scales of AHP may lead to misapplications, which most AHP users might not be aware of. To address this issue, the fuzzy cognitive network process (FCNP) is proposed as a promising alternative applied for software reliability and quality measurement. One application based Fuzzy AHP is revisited to demonstrate the feasibility and usability of the FCNP. The paper discusses conversion from the FAHP to the FCNP, examining their reproducibility, comparability, merits, and limitations. The proposed fuzzy CNP method can a valuable tool for software customers, designers, developers, testers, and purchasers, to evaluate the level of software reliability and quality in general applications within intelligent environment.

Analysis of Home Furnishing Marketing Based on Internet of Things in the Intelligent Environment

How to improve marketing efficiency and how to formulate scientific, effective and practical marketing strategies according to changes in the market environment are important issues facing current smart home companies. This paper adopts the analysis methods such as PEST macro model analysis method, Porter's five forces model, SWOT analysis model and STP analysis, taking Suzhou as the research object, conducts an in-depth analysis of the development environment of smart home, and clarifies the suitable smart home market. From the aspects of 6P marketing mix (product, price, channel, promotion, public relations and political rights), it proposes a Suzhou smart home marketing mix strategy based on mid-to-high-end smart home products. The research results of this paper will promote the development of the city's smart home market and have important reference value for other cities to carry out smart home marketing and can also be used as a reference for relevant government departments to formulate policies.

Working with AI: the impact of organizational intelligent service strategy on employees’ perception of career achievement

In the artificial intelligence (AI) environment, there is limited research on employees’ perception of career achievement. Previous literature has presented two different viewpoints: AI either reduces or increases employees’ perception of career achievement. We introduce the concept of the intelligent service strategy to resolve this contradiction and explore its underlying reasons. Through three experiments involving 736 front-line employees (with valid responses of 223, 232, and 281 for each study, respectively), this research reveals the influence of organizational intelligent service strategy (substitution vs. collaboration) on employees’ perception of career achievement. To elucidate, compared with the intelligence collaboration service strategy, the intelligence substitution service strategy decreases human–human interactivity and enhances human–machine interactivity, thus reducing employees’ perception of career achievement. Intriguingly, the organizational innovation climate significantly moderates the relationship between (human–human and human–machine) interactivity and employees’ perception of career achievement. Specifically, the organizational innovation climate might mitigate the positive effect of human-human interactivity and the negative effect of human-machine interactivity on the perception of career achievement. This research provides a finer-grained understanding of how employees perceive career achievement when working with AI, thus explaining conflicting conclusions drawn in previous studies. These insights contribute innovatively to the theoretical framework concerning employees’ intrinsic motivations within the intelligent service environment.

Innovations in Tactile Sensing: Microstructural Designs for Superior Flexible Sensor Performance

AbstractTactile sensors have garnered considerable interest for their capacity to detect and quantify tactile information. The incorporation of microstructural designs into flexible tactile sensors has emerged as a potent strategy to augment their sensitivity to pressure variations, thereby enhancing their linearity, response spectrum, and mechanical robustness. This review underscores the imperative for progress in microstructured flexible tactile sensors. Subsequently, the discourse transitions to the prevalent materials employed in the fabrication of sensor electrodes, encapsulation layers, and active sensing mediums, elucidating their merits and limitations. In‐depth discussions are devoted to tactile sensors adorned with microstructures, including but not limited to, micropyramids, microhemispheres, micropillars, microporous configurations, microcracks, topological interconnections, multilevel constructs, random roughness, biomimetic microstructures inspired by flora and fauna, accompanied by exemplar studies from each category. Moreover, the utility of flexible tactile sensors within the realm of intelligent environments is explicated, highlighting their application in the monitoring of physiological signals, the detection of sliding motions, and the discernment of surface textures. The review culminates in a critical examination of the paramount challenges and predicaments that must be surmounted to further the development and enhance the functional performance of tactile sensors, paving the way for their integration into advanced sensory systems.

Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms

Human Activity Recognition (HAR) plays an important role in the automation of various tasks related to activity tracking in such areas as healthcare and eldercare (telerehabilitation, telemonitoring), security, ergonomics, entertainment (fitness, sports promotion, human–computer interaction, video games), and intelligent environments. This paper tackles the problem of real-time recognition and repetition counting of 12 types of exercises performed during athletic workouts. Our approach is based on the deep neural network model fed by the signal from a 9-axis motion sensor (IMU) placed on the chest. The model can be run on mobile platforms (iOS, Android). We discuss design requirements for the system and their impact on data collection protocols. We present architecture based on an encoder pretrained with contrastive learning. Compared to end-to-end training, the presented approach significantly improves the developed model’s quality in terms of accuracy (F1 score, MAPE) and robustness (false-positive rate) during background activity. We make the AIDLAB-HAR dataset publicly available to encourage further research.

Towards engineering higher quality intelligent environments: a multi case study approach

This study addresses the need to enhance the quality of Intelligent Environments, recognizing their unique characteristics and the absence of adequate guidance on quality management during development. It pursues three primary objectives: proposing a novel quality-in-use model, presenting an enhanced version of the User-Centered Intelligent Environment Development Process, and reporting on the application of these approaches through a multiple case study. To embed quality into systems, we advocate for the integration of quality characteristics from ISO/IEC 25000 standards with functional requirements. Stakeholders collaboratively define targets using measures from quality standards, and metrics enable early problem detection and resolution during development. The proposed quality-in-use model provides an insightful and objective perspective on system capabilities, guiding development and ensuring stakeholder involvement. However, challenges such as shortening development cycles for early and regular stakeholder feedback and managing an increased number of system tests were noted. Our study makes a significant contribution to the field of Intelligent Environments by providing a structured approach to embedding and managing quality throughout the development lifecycle. The multiple case study offers empirical evidence of the effectiveness of the proposed approaches, with ongoing considerations for challenges in the development process.

Optimizing residential light environments in simulated youth olympic village for improving young athletes’ sleep quality and reducing next-morning drowsiness

The concept of High-tech Olympics is pivotal in the modern Olympic Games. Athletes reside in the Olympic Village during the games. Therefore, ensuring a healthy and intelligent environment in the Olympic Village is crucial. A significant factor in this respect is the light environment. Previous studies indicated that adolescents are particularly sensitive to the residential light environment, adolescents experience improved sleep quality in a low correlated color temperature (CCT) light environment in the evening. However, little is known about the effects of low CCT light with varying illuminance on adolescents in the evening and the next morning. Hence, this study conducted a 17-day randomized, controlled trial (7-day baseline and 10-day light intervention) in a simulated Youth Olympic Village. Sixteen young professional athletes (12.3 ± 2.1 years of age) participated in this study. They were randomly assigned (1:1) to either a 160 lx (dim light group) or 200 lx (bright light group) environment 1 h before bedtime. Both groups had the same spectrum (CCT: 2000 K). The results of blood tests (melatonin and cortisol) and self-reported questionnaires consistently showed that young athletes in the dim light group significantly enhanced sleep quality and reduced next-morning drowsiness compared to those in the bright light group (p < 0.05). These findings demonstrate that illuminance, along with wavelength, crucially impacts young athletes' sleep quality and next-morning drowsiness in residential light environments, which provide valuable guidance for young athletes participating in the upcoming Youth Olympic Games.

Intelligent Environment Design for Indoor Spaces Based on Perception and Behavior Correlation

Intelligent Environment Design for Indoor Spaces Based on Perception and Behavior Correlation

Design and Implementation of an IOT-based Smart Home Automation System in Real World Scenario

INTRODUCTION: Automation developments have significantly increased general convenience in modern technology. Our study focuses on developing and deploying an Internet of Things (IoT)–enabled smart home automation system that maximizes energy efficiency and improves convenience in residential settings. Our technology provides homes with an intelligent environment by smoothly combining several sensors, actuators, and communication protocols. We explore the challenges of creating a reliable and useful smart home systemthat works well in everyday situations. We investigate the difficulties, architectural issues, communication protocols, and security features specific to these systems.OBJECTIVES: This project aims to use a database server and Wi-Fi module to develop an effective and reasonably priced smart home automation system. It improves accessibility and convenience by enabling smartphone voice control of household appliances.METHODS: This project was developed using various implementation techniques, including wireless home automation via GSM technology, speech recognition-based systems, Blynk, and the Internet of Things. These techniques added up to a reliable and effective smart home system.RESULTS: Although it improved user routines, the IoT-based smart home system had latency problems. Interoperability issues are still present. Improvements were guided by user input. Using Blynk, our software manages loads remotely. CONCLUSION: A home automation system that is inexpensive and locally supplied can effectively operate household appliances. It is adaptable, scalable, and a component of future smart homes. IoT applications in real life revolutionize convenience and efficiency in living environments.

A method for Designing a Guidance Law Utilizing Linear Quadratic Forms based on Differential Games in 3-Dimensional Space

Consider a T-A-D game scenario in space: the target strives to evade the attacker, the defender intercepts the target, and the attacker must both avoid the target's counterattack and attempt to hit the target. It is assumed that all entities are intelligent, anticipating the next state of their adversaries and making the most suitable maneuvering strategy based on this prediction. This paper presents a 3-dimensional linear-quadratic differential game guidance law for target-attacker-defender scenarios, which is more intelligent than traditional guidance laws and is suitable for future intelligent environments.