Intelligent Society Research Articles

Research on the Issues and Strategies of Constructing Intelligent Classrooms in Higher Education

Driven by the robust wave of informatization, emerging industries based on information technology continue to deepen their development, reshaping human society and leading a historic leap from traditional industrial society to information society, and further towards an intelligent society. In this transformative process, information technology serves as a key driving force, profoundly impacting the education sector, particularly accelerating the pace of educational reform and promoting continuous innovation and upgrading of educational models. This paper focuses on higher education, deeply analyzing the construction pathways and practical values of intelligent classroom teaching models. Specifically, we explore strategies for deeply integrating Internet technology with traditional classroom teaching, aiming to create a highly intelligent, personalized, and interactive teaching environment in higher education—intelligent classrooms.

Проблема ценности в цифровом обществе роевого интеллекта

Introduction. The emerging digital society demonstrates the problem of justifying the value, worth and price of digital products and services, which requires consideration of the specificity of value in this society. Theoretical analysis. Following the financial and art market, the boundary between “value” and “worth” is blurred in the digital society. Value, including the value of an individual, becomes variable and is conditioned by the presence of unique attributes and unique experiences that obtain market value. At the same time, under standard digital protocols and technologies, the true uniqueness of an individual experience can only be achieved through the creation of customized digital ecosystems in the form of robotic swarms that support human life activities. A set of digital devices that have sufficient resources to continuously self-renew and form a closed environment around the individual that provides a unique experience can be called a chrysalic swarm. The chrysalic swarm creates an opportunity for the individual to escape from the logic of mutual competition dictated by society. Conclusion. Studying the value problematization in the digital society of swarm intelligence opens a theoretical perspective on the problem of the crisis of social elites in the context of the fulfillment of this scenario of society development.

Participation of Pesantren in Society 5.0: Building Globally Competitive Skills

Society 5.0 is the age of intelligent societies that participate in training as a place of innovation with modern technology. The aim of this research is to study how trainees participate in Society 5.0 with a focus on human resource development in building traineeships competence in the global world. This research method is library research. (library research). The results of this study revealed that the gymnasium is not only a place for learning, but also a place to form an inclusive character, creating an independent individual with strong ethics and morality. The research also emphasizes important steps to preserve the original character of the trainees, such as instilling a noble morality, applying technology in the training system, ethical digital literacy, and cross-disciplinary collaboration. It helps the coach not only maintain the good tradition, but also create a better new tradition “Al-Muhafadhotu ‘Ala Qodimis Sholih Wal Akhdzu Bil Jadidil Ashlah”. With an innovative approach, the gymnasium becomes a place of education that prepares for the future by blending traditional values and technological advances.

Augmented Tactile Perception of Robotic Fingers Enabled by AI‐Enhanced Triboelectric Multimodal Sensors

AbstractRecent developments in robotics increasingly highlight the importance of sensing technology, especially tactile perception, in enabling robots to effectively engage with their environment and interpret physical interactions. Due to power efficiency and low cost, the triboelectric mechanism has been frequently studied for measuring pressure and identifying materials to enhance robot perception. Nevertheless, there has been limited exploration of using the triboelectric effect to detect curved surfaces, despite their prevalence in daily lives. Here, a triboelectric multimodal tactile sensor (TMTS) of multilayered structural design is proposed to recognize distinct materials, curvatures, and pressure simultaneously, thus decoupling different modalities to enable more accurate detection. By attaching sensors to robotic fingertips and leveraging deep learning analytics, the quantitative curvature measurement provides more precise insights into an object's detailed geometric characteristics rather than merely assessing its overall shape, hence achieving automatic recognition of 12 grasped objects with 99.2% accuracy. The sensor can be further used to accurately recognize the softness of objects under different touch gestures of a robotic hand, achieving a 94.1% accuracy, demonstrating its significant potential for wide‐ranging applications in a future robotic‐enabled intelligent society.

MedInt And The Contours Of The Definitional Question

Medical Intelligence is not a new field of medicine or intelligence, but with the advent of the pandemic, its perspective has broadened and its definition requires the consideration of multiple theoretical and methodological factors that have not been considered until now. This paper aims to show, through a different perspective, the new areas and issues on which Medical Intelligence is becoming more and more a crucial element. The consideration presented makes use of the studies and insights that have been carried out and continue to be developed as part of the National Medical Intelligence Group as part of the SOCINT – Italian Society of Intelligence established in March 2023 at the Catholic University, Milan under the direction provided by Marco Lombardi and the coordination by Barbara Lucini. Finally, this paper traces lines of work that orient in an innovative way the field of Medical Intelligence and its future developments.

A Survey on AI Integration into Industry 5.0

Industry 5.0 (IR 5.0) is a modern production model focused on human-machine collaboration. The goal is to maintain a balance between machine and human interaction, with an emphasis on creative production and customization. Artificial intelligence (AI) will play a key role in IR 5.0, enabling intelligent manufacturing and transforming many aspects of society. Technologies such as AI, Internet of Things (IoT), Blockchain, Virtual Reality (VR)/Augmented Reality (AR), Big Data Analytics and Cyber-Physical Systems (CPS) are essential to achieve the goals of an intelligent society. This article explores the integration of AI in IR 5.0. However, there are some challenges to overcome such as data security, ethical concerns, employee training, black box AI, etc. Despite its challenges, AI integration to IR 5.0 promises to drive manufacturing automation, efficiency, and customization. To ensure inclusive and sustainable development, the social implications and impacts of IR 5.0 must be carefully considered.

Model inductive bias enhanced deep reinforcement learning for robot navigation in crowded environments

Navigating mobile robots in crowded environments poses a significant challenge and is essential for the coexistence of robots and humans in future intelligent societies. As a pragmatic data-driven approach, deep reinforcement learning (DRL) holds promise for addressing this challenge. However, current DRL-based navigation methods have possible improvements in understanding agent interactions, feedback mechanism design, and decision foresight in dynamic environments. This paper introduces the model inductive bias enhanced deep reinforcement learning (MIBE-DRL) method, drawing inspiration from a fusion of data-driven and model-driven techniques. MIBE-DRL extensively incorporates model inductive bias into the deep reinforcement learning framework, enhancing the efficiency and safety of robot navigation. The proposed approach entails a multi-interaction network featuring three modules designed to comprehensively understand potential agent interactions in dynamic environments. The pedestrian interaction module can model interactions among humans, while the temporal and spatial interaction modules consider agent interactions in both temporal and spatial dimensions. Additionally, the paper constructs a reward system that fully accounts for the robot’s direction and position factors. This system's directional and positional reward functions are built based on artificial potential fields (APF) and navigation rules, respectively, which can provide reasoned evaluations for the robot's motion direction and position during training, enabling it to receive comprehensive feedback. Furthermore, the incorporation of Monte-Carlo tree search (MCTS) facilitates the development of a foresighted action strategy, enabling robots to execute actions with long-term planning considerations. Experimental results demonstrate that integrating model inductive bias significantly enhances the navigation performance of MIBE-DRL. Compared to state-of-the-art methods, MIBE-DRL achieves the highest success rate in crowded environments and demonstrates advantages in navigation time and maintaining a safe social distance from humans.

Perspectives on AI use in medicine: views of the Italian Society of Artificial Intelligence in Medicine.

The first annual meeting of the Italian Society for Artificial Intelligence in Medicine (Società Italiana Intelligenza Artificiale in Medicina, SIIAM) on December 7, 2023, marked a significant milestone in integrating artificial intelligence (AI) into Italy's healthcare framework. This paper reports on the collaborative workshop conducted during this event, highlighting the collective efforts of 51 professionals from diverse fields including medicine, engineering, data science, and law. The interdisciplinary background of the participants played a crucial role in generating ideas for innovative AI solutions tailored to healthcare challenges. Central to the discussions were several AI applications aimed at improving patient care and streamlining healthcare processes. Notably, the use of Large Language Models (LLMs) in remote monitoring of chronic patients emerged as an area of focus. These models promise enhanced patient monitoring through detailed symptom checking and anomaly detection, thereby facilitating timely medical interventions. Another significant proposal involved employing LLMs to improve empathy in medical communication, addressing the challenges posed by cultural diversity and high-stress levels among healthcare professionals. Additionally, the development of Machine Learning algorithms for standardizing treatment in pediatric emergency departments was discussed, along with the need for educational initiatives to enhance AI adoption in rural healthcare settings. The workshop also explored using LLMs for efficient data extraction and analysis in scientific literature, interpreting healthcare norms, and streamlining hospital discharge records. This paper provides a comprehensive overview of the ideas and solutions proposed at the workshop, reflecting the participants' forward-thinking vision and the potential of AI to revolutionize healthcare.

A Contact‐Separation Mode Hybrid Generator Based on Magnetic Springs

The emergence of the intelligent society presents a significant challenge with regard to distributed energy. One potential solution is to harvest energy from the environment to power micro/nano systems. Herein, an electric‐triboelectric hybrid generator (ETMHG) supported by magnetic springs is presented that operates in the contact‐separation mode. The traditional mechanical springs in the triboelectric nanogenerators are replaced by magnetic springs, and solenoid coils are added. This structure can achieve electromagnet‐triboelectric hybrid generation without significantly increasing the volume of the generator, and the use of magnetic springs offers a solution to the issues of difficult installation and mechanical wear and tear that are inherent in mechanical spring‐based triboelectric nanogenerators. The proposed hybrid generation ETMHG is shown to increase the output capacity of the generator, improve the efficiency of environmental energy harvesting, and achieve an instantaneous maximum power of 4.75 mW and instantaneous maximum power density of 95 W m−3. The ETMHG can charge a 10 μF capacitor that improves efficiency by 52.6% compared to an electromagnetic generator. The output surface power density of TENG in ETMHG can reach 1.12 W m−2.

On the Protection and Inheritance of the Evenki Ethnic Culture

In previous studies of the Evenki ethnic group, different perspectives have been presented regarding the research on Evenki language culture in various historical contexts and research periods: researchers from each era exhibit differences in research directions, angles, and awareness of issues. These differences are closely related to research objectives, external backgrounds, power relations, and the development of disciplines in different eras. This article suggests that an analysis of the Evenki language not only helps us understand the changes in ethnic language forms over different periods but also allows us to observe people's psychological states and practical needs against the backdrop of the times. In the context of today's era, this can effectively enhance our adaptability to linguistic and cultural transformation, and desktop research is a rapid method of reading literature and collecting language information categorization. The article demonstrates that the desktop learning research method proposed surpasses current typical language learning methods, helping us better adapt to the intelligent society and the era of big data.

AI literacy and its implications for prompt engineering strategies

Artificial intelligence technologies are rapidly advancing. As part of this development, large language models (LLMs) are increasingly being used when humans interact with systems based on artificial intelligence (AI), posing both new opportunities and challenges. When interacting with LLM-based AI system in a goal-directed manner, prompt engineering has evolved as a skill of formulating precise and well-structured instructions to elicit desired responses or information from the LLM, optimizing the effectiveness of the interaction. However, research on the perspectives of non-experts using LLM-based AI systems through prompt engineering and on how AI literacy affects prompting behavior is lacking. This aspect is particularly important when considering the implications of LLMs in the context of higher education. In this present study, we address this issue, introduce a skill-based approach to prompt engineering, and explicitly consider the role of non-experts' AI literacy (students) in their prompt engineering skills. We also provide qualitative insights into students’ intuitive behaviors towards LLM-based AI systems. The results show that higher-quality prompt engineering skills predict the quality of LLM output, suggesting that prompt engineering is indeed a required skill for the goal-directed use of generative AI tools. In addition, the results show that certain aspects of AI literacy can play a role in higher quality prompt engineering and targeted adaptation of LLMs within education. We, therefore, argue for the integration of AI educational content into current curricula to enable a hybrid intelligent society in which students can effectively use generative AI tools such as ChatGPT.

Low-income, yet Highly Literate? The Future Towards Developing a ‘Super Smart Society’

The low-income community is generally associated with a lower level of education, poor quality housing, unemployment, and financial debt. As digital technologies become increasingly integrated into society, this study aims to re-examine the understanding of advertising literacy within low-income communities by introducing digital literacy as a new dimension. The focus is on assessing their awareness of visual pollutants, specifically fly-poster, in Malaysia. The study involved 574 respondents from five Public Housing Programs (PHP) to represent the distribution of the low-income community. The study combined media literacy theory and the model of advertising literacy. Results indicated that individuals in the low-income community exhibit high advertising literacy influenced by digital technological factors, empowering them to make informed decisions amidst the deluge of advertisements. Despite this, the challenge of visual pollutants remains unresolved due to the insufficient efficacy of collective actions by the community, hindering efforts to mitigate their impact on the local environment. To embrace the future of a 'super smart society,' the low-income community must collectively adapt and adopt digital technologies. This study contributes to the discourse on the importance of digital literacy and collaborative efforts in shaping an intelligent society, often referred to as Society 5.0 or the 'super smart society.' Keywords: Advertising literacy, society 5.0, digital literacy, fly-poster, super smart society.

Проблема приватности в цифровом обществе роевого интеллекта

Introduction. The development of digital technologies requires the specification of the type of the emerging digital society. One of the development scenarios is the formation of a digital society of swarm intelligence. Theoretical analysis. The concept of swarm intelligence means an optimization algorithm that imitates the behavior of swarms or colonies of insects and bird flocks. Human society is characterized by the manifestation of swarm intelligence as a condition of joint organized activity, but the development of digital technologies brings swarm intelligence to a higher level. Creation of private swarms causes risks in the form of “Byzantine robot” – a hacked particle of the swarm, transmitting false information and jeopardizing the whole swarm. The solution is to incorporate elements of the economic game that support the values of honesty, cooperation and solidarity into the particle interactions. This leads to making privacy a “process” and changing its value status. Protecting privacy in swarm intelligence society has the potential to cause labor to lose its public status and acquire a private, hidden status and anonymize employment. Conclusion. The possible scenario of human society development towards the digital society of swarm intelligence can become a source of profound social changes and, above all, a rethinking of the social stratification based on the division of labor and social hierarchy in general.

Research on Government Data Sharing Mechanism Based on Smart Contracts

Exploring mechanisms for internal data sharing within government departments is important in advancing digital and intelligent society. This paper is based on the establishment of decentralized nodes on the external network of government departments, constructing a decentralized node, and establishing a government internal data sharing model based on blockchain. Subsequently, integrating attribute fields from government data into the shared model, accompanied by the formulation of data-sharing rules through smart contracts, serves to streamline the implementation of efficient and secure cross-validation mechanisms across diverse departments. Finally, this article concludes by conducting a model performance testing experiment, evaluating the model from three perspectives: storage cost, blockchain performance, and security analysis. The test results show that our model enhances the efficiency of querying and retrieving data within the government's internal data-sharing system, effectively addressing challenges such as low efficiency, high costs, and issues related to the security and real-time aspects of data sharing within the government. Overall, our article provides a new way of thinking about government data sharing.

Digital Diplomacy in Africa: Opportunities and Challenges

Globally, digital diplomacy is taking over as the dominating format. As long as Africa is a part of the globalization era, it must adapt to new technologies. However, there are several obstacles that African digital diplomacy must overcome, such as a lack of infrastructure, a lack of proficiency with new technologies, limiting regulations, the anonymity issue and others. So, with the proliferation of digital technologies, Africa is facing growing cyber security threats. These include hacker attacks, online fraud and disinformation campaigns. Weak cyber security measures and limited capacity to address these challenges make African countries vulnerable to cyber-attacks. Africa should follow the present realities and dynamics in digital diplomacy as the world constantly changes and transitions. In fact, in the diplomatic sphere of Africa, digital diplomacy is being practiced without the concept and practice promoted. However, Africa has many opportunities to embrace digital diplomatic initiatives. The primary ones include; the penetration of the internet, the rise in the public interest, the engagement of the African diaspora, the African Union’s digital strategy, the desire to create an intelligent society, and the revolution of smartphones. Africa also offers much potential for improving the natural and human resources used in digital platform infrastructure. Thus, Africa should assist in developing the information and communication technology (ICT) infrastructure and encouraging training for these electronic platforms. Therefore, the paper aims to analyze the opportunities, challenges, and potentials of digital diplomacy in the African context. To do so, a qualitative research approach was used collected from secondary sources and document analysis. Finally, the collected data is thematically analyzed.

Investigating The Smart Community Empowerment in the Utilization of Micro Hydro Power Plants (PLTMH): Enhancing The Welfare of Rural Community

The economy of an intelligent society is a concept that describes an economic system in which people have a high understanding of financial management and monetary resources. In the last decade, the idea of community empowerment by utilizing Micro hydropower plants has grown. Factors such as ecological sustainability, preservation of natural resources, and mitigation of negative impacts should be analyzed to assess the success of the project and its long-term effects. A maintained environment will help the well-being of the community, building synergies between environmental sustainability and economic development. It needs to be recognized that challenges may arise in the process of empowering intelligent communities. This study used a mixed-methods approach. The results indicate that the t-statistic is 3.527, beyond 1.96, and the p-value is 0.000, below 0.05; thus, the group’s support for beneficiary empowerment exerts an indirect influence. The influence of group support on participation was indirect, indicated by a t-statistic of 8.082, surpassing 1.96, and a p-value of 0.000, which is below 0.05. The group’s endorsement of rural community development exerts an indirect effect, producing a t-statistic of 5.217, surpassing 1.96, and a p-value of 0.000, which is below 0.05. Moreover, the social capital variable exerts an indirect effect on the advancement of rural communities, demonstrated by a p-value of 0.001, which is less than 0.05, and a t-statistic of 3.360, which is greater than 1.96. This finding suggests that the empowerment of intelligent communities through MHP not only improves economic welfare but also maintains balance with the surrounding environment, resulting in sustainable growth.

Социально-философские аспекты развития генеративного искусственного интеллекта

Introduction. The article offers a socio-philosophical reflection on the development of generative artificial intelligence (GAIN) and its interaction with human society, through the lens of the dialectical method. Theoretical analysis. The characteristic feature of the GAIN is its complexity, which makes it incomprehensible to human consciousness, making it similar to social institutions created by society but not controlled by it. The GAIN, which creates content without understanding it, reflects the characteristic of the human spirit, which creates phenomena without ever understanding the principles and consequences of their work. The possibilities and unpredictability of the GAIN’s work, which exceeds the capabilities of the human mind, lead to the emergence of an attitude towards it not as a tool, but as a helper. But the universal nature of the GAIN prevents the generation of a personal history of interaction between a person and the GAIN, which leads to the need for individualization and concretization of the GAIN in a material medium. The connection of GAIN with a certain material medium gives GAIN the experience of independent existence, which triggers the cycle of infinite self-perfection and self-generation, as well as the transformation of matter, including society. The result of such transformation can be a digital-material society of swarm intelligence, where the openness of people’s consciousnesses to each other is conditioned by their connection with GAIN. Conclusion. The development of the GAIN is a dialectical movement from universality towards its concreteness and material embodiment, and then back to universality through the inclusion and transformation of the material world within the GAIN.

Emotional health and well-being in the artificial intelligence society

Emotional health and well-being in the artificial intelligence society

LFSR state sequence image encryption method based on VHDL language

In the modern society of digitalization, integration, intelligence, and networking, while people enjoy the convenience of information technology to their production and lives, information security in the network, as the cornerstone of information communication, becomes more and more important. The research is to establish a new image encryption (IE) method based on LFSR state sequence (SS)s in VHDL language, and the stream cipher of LFSR is studied in detail to induce the idea of LFSR SSs based on VHDL language. The correlation coefficient (CC) of the original image (OI) and encrypted image (EI) pixel points (PP) are analyzed from horizontal direction, vertical direction and diagonal direction, and the results show that the CC of adjacent PP of the OI is large, which approaches 1. However, using the encryption algorithm proposed in this paper, the correlation coefficient of the PP of the EI is -0.0282 in the diagonal direction, and the highest correlation coefficient in the horizontal direction is only 0.0122, which indicates that the adjacent PP of the EI are almost uncorrelated with each other. Therefore, the encryption method can well resist statistical attacks, which illustrates the effectiveness, security, and reliability of this new IE method.

Design and Implementation of Intelligent Traffic-Management System for Smart Cities using Roaming Agent and Deep Neural Network (RAD2N)

In metropolitan areas, the exponential growth in quantity of vehicles has instigated gridlock, pollution, and delays in the transportation of freight. IoT is the modern revolution which pushes the world towards intelligent management systems and automated procedures. This makes a significant contribution to automation and intelligent societies. Traffic regulation and effective congestion management assist conserve many priceless resources. In order to recognize, collect and send data, autonomous vehicles are furnished with IoT powered Intelligent Traffic Management System (ITMS) having a set of sensors. Moreover, machine learning (ML) algorithms can also be employed to enhance the transportation system. Traffic jams, delays, and a high death rate are the results of the problems that the current transport management systems face. In this paper, an active traffic control for VANET is proposed which merges Roaming Agents (RA) with deep neural networks (DNN). The effectiveness of the DNN with RA (RAD2N) routing method in VANETs is evaluated experimentally and compared with the traditional ML and other DL routing algorithms. Several traffic congestion indicators, including delay, packet delivery ratio (PDR) and throughput are used to validate RAD2N. The outcomes demonstrate that the proposed approach delivers lower latency and energy consumption.