Intelligent Environment Research Articles

Study on dexterous structure and control of bio-inspired musculoskeletal robots in artificial intelligence environment

Study on dexterous structure and control of bio-inspired musculoskeletal robots in artificial intelligence environment

Multimodal Interaction, Interfaces, and Communication: A Survey

Multimodal interaction is a transformative human-computer interaction (HCI) approach that allows users to interact with systems through various communication channels such as speech, gesture, touch, and gaze. With advancements in sensor technology and machine learning (ML), multimodal systems are becoming increasingly important in various applications, including virtual assistants, intelligent environments, healthcare, and accessibility technologies. This survey concisely overviews recent advancements in multimodal interaction, interfaces, and communication. It delves into integrating different input and output modalities, focusing on critical technologies and essential considerations in multimodal fusion, including temporal synchronization and decision-level integration. Furthermore, the survey explores the challenges of developing context-aware, adaptive systems that provide seamless and intuitive user experiences. Lastly, by examining current methodologies and trends, this study underscores the potential of multimodal systems and sheds light on future research directions.

The impact of digital intelligence on energy-intensive firms’ green transformation

Abstract The green transformation of energy-intensive firms is expected to make an outstanding contribution to global carbon neutrality. Digital intelligence, the new phase of digitalization, has injected fresh momentum into corporate green development. Most previous studies focused on the green effect of digitalization using statistical data from listed firms, and failed to make detailed exploration on the impact of digital intelligence on energy-intensive firms' green transformation based on survey data. Based on empowerment theory and technology-organization-environment theory, this study proposed a three-dimensional concept of digital intelligence, including digital intelligence technology, digital intelligence organization and digital intelligence environment. Using survey data from 348 energy-intensive firms in China, this paper employed the structural equation modeling and bootstrap test to investigate the influence of digital intelligence on energy efficiency transformation and green emission transformation, and the mediating effect of energy management. The results indicate that digital intelligence technology, digital intelligence organization and digital intelligence environment promote energy efficiency and green emission of energy-intensive firms. Energy management is the key to the green transformation of energy-intensive firms in the context of digital intelligence. Specifically, energy saving literacy, energy audit, and energy use structure optimization play the positive mediating effects between digital intelligence and energy-intensive firms’ green transformation. It is worth noting that the mediating effect of energy saving literacy between digital intelligence environment and energy-intensive firms' green transformation is insignificant. These findings provide policy and practice references for the government and practitioners in energy-intensive industries to leverage digital intelligence to promote green sustainability.

A Future Perspective for Digitalization of Egyptian Ports (Opportunities and Challenges) Case Study: Alexandria Port Authority

Abstract The adoption of digital technologies at ports has emerged as a key trend in maritime industry, as nations endeavor to achieve economic prosperity through the process of digital transformation. This trend is consistent with worldwide movement towards digitization in various domains. Digitization is an essential element in process of converting surroundings into an intelligent environment. Automated procedures in port operations and trading enables development of advanced and automated terminals, as well as independent port control operations. The aim of paper is to present a proposal to transform port of Alexandria into a smart port and execute necessary measures. The analysis began by classifying Digital revolution into three separate epochs, covering period from 1980 to 2022. An abridged chronicle of crucial occurrences in every generation and their importance. The challenges faced, scientific progress made, and data processing techniques employed in each era. A clarification of the purpose of information technology. In order to improve port operations and maximize efficiency, the analysis also considered the impact and scope of each generation, as well as conducting a comprehensive examination of the concept of smart ports. The BOX-JENKINS methodology, ARIMA models and EVIEW software were used to analyze the time series for the years 2012–2021 through the statistical center of Alexandria Port Authority. The steps of this package were then applied to the study's sample data in the following stages: Identification Phase Model Estimation Phase Forecasting Phase and Prediction of Performance Levels from 2022–2026. In order to establish the requirements for Alexandria Port's transformation into a smart port, a comparison was done between the smart port application already in place at Damietta Port and what was implemented at Singapore, Tangier Med Port and Rotterdam.

A proposal for an IoT operating system for plug-n-play wireless sensors

The proposal is focused on the development of an operating system that reduces the gap in the needed technological knowledge for the installation of an intelligent environment. The aim is to develop an operating system that is sufficiently advanced to autonomously manage the inclusion of new devices, and that at hardware level becomes largely versatile to integrate new devices and components into the environment. The proposal is based on modular hardware composed on three main elements: a brain, a module (a transductor) and a power supply. Consequently, the software must be able to recognize the installed hardware and subsequently manage communication with other devices with minimal human intervention, being helped by algorithms and fuzzy logic. Therefore, the contribution focuses on the creation of ubiquitous and pervasive systems, where the system manages itself and benefit.

Improving adherence to medication in an intelligent environment using reinforcement learning

Improving adherence to medication in an intelligent environment using reinforcement learning

A Smart Crowd Monitoring and Management Model for Humanity in Intelligent Environments: A Real-Time Application Scenario

A Smart Crowd Monitoring and Management Model for Humanity in Intelligent Environments: A Real-Time Application Scenario

Automotive Safety‐Assisted Driving Technology Based on Computer Artificial Intelligence Environment

Automotive Safety‐Assisted Driving Technology Based on Computer Artificial Intelligence Environment

The Critical Role of Tangible User Interfaces in Human Computer Interaction

Human-Computer Interaction has evolved from command-line, then to graphical, up to a tangible user interface (TUI). TUIs represent a new paradigm in incorporating physical objects within the digital environment in order to offer users richer, more natural, and intuitive interaction means. This paper reviews the applications of TUIs within cognitive ergonomics, education, and industry, with special emphasis on the potential effects that TUI might have in reducing cognitive load and improving retention and enhancing problem-solving behavior. It covers various case studies on cognitive benefits at TUI, frameworks of distributed and embodied cognition, scalability and accessibility issues, ways to reduce technical obstacles along with users' reluctance, and how TUI is being merged with IoT. The authors also discuss how TUI will see huge improvements in terms of networking and control in intelligent environments. From the above, though TUIs promise great benefits related to the conventional GUIs, full utilization in different applications calls for addressing cost, adaptability, and inclusivity for wide usage.

Limits of speech in connected homes: Experimental comparison of self-reporting tools for human activity recognition

Data annotation for human activity recognition is a well-known challenge for researchers. In particular, annotation in daily life settings relies on self-reporting tools with unknown accuracy. Speech is a promising interface for activity labeling. In this work, we compare the accuracy of two commercially available tools for annotation: voice diaries and connected buttons. We retrofit the water meters of thirty homes in the USA for infrastructure-mediated sensing. Participants are split into equal groups and receive one of the self-reporting tools. The balanced accuracy metric is transferred from the field of machine learning to the evaluation of the annotation performance. Our results show that connected buttons perform significantly better than the voice diary, with 92% median accuracy and 65% median reporting rate. Using questionnaire answers, we highlight that annotation performance is impacted by habit formation and sentiments toward the annotation tool. The use case for data annotation is to disaggregate water meter data into human activities beyond the point of use. We show that it is feasible with a machine-learning model and the corrected annotations. Finally, we formulate recommendations for the design of studies and intelligent environments around the key ideas of proportionality and immediacy.

RLL-SWE: A Robust Linked List Steganography Without Embedding for intelligence networks in smart environments

With the rapid development of technology, smart environments utilizing the Internet of Things, artificial intelligence, and big data are improving the quality of life and work efficiency through connected devices. However, these advances present significant security challenges. The data generated by these smart devices contains many private and sensitive information. In data transmission, crime and terrorism may intercept this sensitive information and use it for secret communications and illegal activities. Steganography hides information in media files and prevents information leakage and interception by criminal and terrorist networks in an intelligent environment. It is an important technology to protect data integrity and security. Traditional steganography techniques often cause detectable distortions, whereas Steganography Without Embedding (SWE) avoids direct modification of cover media, thereby minimizing detection risks. This paper introduces an innovative and robust technique called Robust Linked List (RLL)-SWE, which improves resistance to attacks compared to traditional methods. Using multiple median downsampling and gradient calculations, this method extracts stable features. It restructures them into a multi-head unidirectional linked list, ensuring accurate message retrieval and high resistance to adversarial attacks. Comprehensive analysis and simulation experiments confirm the technique’s exceptional effectiveness and steganographic capacity.

DADNet: text detection of arbitrary shapes from drone perspective based on boundary adaptation

The rapid development of drone technology has made drones one of the essential tools for acquiring aerial information. The detection and localization of text information through drones greatly enhance their understanding of the environment, enabling tasks of significant importance such as community commercial planning and autonomous navigation in intelligent environments. However, the unique perspective and complex environment during drone photography lead to various challenges in text detection, including diverse text shapes, large-scale variations, and background interference, making traditional methods inadequate. To address this issue, we propose a drone-based text detection method based on boundary adaptation. We first conduct an in-depth analysis of text characteristics from a drone’s perspective. Using ResNet50 as the backbone network, we introduce the proposed Hybrid Text Attention Mechanism into the backbone network to enhance the perception of text regions in the feature extraction module. Additionally, we propose a Spatial Feature Fusion Module to adaptively fuse text features of different scales, thereby enhancing the model’s adaptability. Furthermore, we introduce a text detail transformer by incorporating a local feature extractor into the transformer of the text detail boundary iteration optimization module. This enables the precise optimization and localization of text boundaries by reducing the interference of complex backgrounds, eliminating the need for complex post-processing. Extensive experiments on challenging text detection datasets and drone-based text detection datasets validate the high robustness and state-of-the-art performance of our proposed method, laying a solid foundation for practical applications.

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.

The Changing Role of the Architect from Craftsmanship to Artificial Intelligence Environment in Historical Context

Architects differentiated themselves from master builders, craftsmen, and engineers, acquiring a distinct identity, social status, and position with modernity. The observation of this study indicates the presence of signs that a similar radical change is beginning to emerge. The knowledge and skills that contemporary architects need to possess are diverging with the incorporation of systems such as artificial intelligence, metaverse, blockchain, machine learning, and digital twins into the process, thereby transforming the ways architects design and represent. In this context, the study attempts to identify changes in the architect's identity through the evolving role of the architect in the historical process. It concludes that the role of the architect throughout the historical process is not stable but subject to continuous and dynamic change.

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.

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>

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.

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.