Artificial Intelligence Robotics Research Articles

From Tradition to Technology: Robotic Artificial Intelligence in Dental Implantology

From Tradition to Technology: Robotic Artificial Intelligence in Dental Implantology

Neuromorphic Computing for Smart Agriculture

Neuromorphic computing has received more and more attention recently since it can process information and interact with the world like the human brain. Agriculture is a complex system that includes many processes of planting, breeding, harvesting, processing, storage, logistics, and consumption. Smart devices in association with artificial intelligence (AI) robots and Internet of Things (IoT) systems have been used and also need to be improved to accommodate the growth of computing. Neuromorphic computing has a great potential to promote the development of smart agriculture. The aim of this paper is to describe the current principles and development of the neuromorphic computing technology, explore the potential examples of neuromorphic computing applications in smart agriculture, and consider the future development route of the neuromorphic computing in smart agriculture. Neuromorphic computing includes artificial synapses, artificial neurons, and artificial neural networks (ANNs). A neuromorphic computing system is expected to improve the agricultural production efficiency and ensure the food quality and safety for human nutrition and health in smart agriculture in the future.

Can AI Robot Teaching Improve Children’s Performance in Housework? A Quasi-Experimental Study

Background: The primary objective of this study is to explore the effects of using Artificial Intelligence (AI) robot-assisted instruction in preschool activities on young children’s performance in housework. Methods: A quasi-experimental design was employed, with an experimental group and two control groups, to observe changes in children’s performance in housework before and after AI robot-assisted teaching. The study sample consisted of preschoolers from metropolitan Taipei, with 65 children in the experimental group, 53 in control group 1, and 75 in control group 2. Children participating in the research project required consent from the school, teachers, and parents. The children in the experimental group received AI robot-assisted instruction on household tasks for two days a week over three consecutive weeks, with each session lasting approximately 20–30 min. Control group 1 did not receive any experimental treatment, while control group 2 underwent the same learning schedule and content as the experimental group but was instructed by teachers instead of AI robots. The data were analyzed based on pre- and post-test surveys of parents observing their children’s performance in household tasks. Results: This study found that both AI robot-assisted teaching and teacher-led instruction enhanced children’s household skills, with the AI robot-assisted method showing slightly better results. These findings suggest that both technological tools and teacher guidance can effectively improve children’s housework performance, while artificial intelligence robots may provide young children with motivation and curiosity to learn due to their appearance and interactive design, which deserves further analysis. Conclusion: As technology rapidly advances, young children are exposed to various technological devices at an early age. Integrating technological media into future preschool teaching is inevitable, and leveraging tools like AI robots to support teaching, reduce teacher burden, and diversify instructional methods could be a direction worth considering.

Machine vision system for automatic defect detection of ultrasound probes

Industry 4.0 conceptualizes the automation of processes through the introduction of technologies such as artificial intelligence and advanced robotics, resulting in a significant production improvement. Detecting defects in the production process, predicting mechanical malfunctions in the assembly line, and identifying defects of the final product are just a few examples of applications of these technologies. In this context, this work focuses on the detection of ultrasound probes’ surface defects, with a focus on Esaote S.p.A.’s production line probes. To date, this control is performed manually and therefore biased by many factors such as surface morphology, color, size of the defect, and by lighting conditions (which can cause reflections preventing detection). To overcome these shortfalls, this work proposes a fully automatic machine vision system for surface acquisition of ultrasound probes coupled with an automated defect detection system that leverage artificial intelligence. The paper addresses two crucial steps: (i) the development of the acquisition system (i.e., selection of the acquisition device, analysis of the illumination system, and design of the camera handling system); (ii) the analysis of neural network models for defect detection and classification by comparing three possible solutions (i.e., MMSD-Net, ResNet, EfficientNet). The results suggest that the developed system has the potential to be used as a defect detection tool in the production line (full image acquisition cycle takes ~ 200 s), with the best detection accuracy obtained with the EfficientNet model being 98.63% and a classification accuracy of 81.90%.

A Biomimetic Nociceptor Based on a Vertical Multigate, Multichannel Neuromorphic Transistor.

Nociceptors, crucial sensory receptors within biological systems, are essential for survival in diverse and potentially hazardous environments. Efforts to replicate nociceptors through advanced electronic devices, such as memristors and neuromorphic transistors, have achieved limited success, capturing basic nociceptive functions while more advanced characteristics like various forms of central sensitization and analgesic effect remain out of reach. Here, we introduce a vertical multigate, multichannel electrolyte-gated transistor (Vm-EGT), designed to mimic nociceptors. Utilizing the hybrid mechanism combining electric-double-layer (EDL) with ion intercalation/deintercalation in EGTs, our approach successfully replicates peripheral sensitization and desensitization characteristics of nociceptors. The intricate multigate and multichannel design of the Vm-EGT enables the emulation of more advanced nociceptive functionalities, including central sensitization and analgesic effect. Furthermore, we demonstrate that by exploiting the inherent current-voltage relationship, the Vm-EGT can simulate these advanced nociceptive features and seamlessly transition between them. Integrating a Vm-EGT with a thermistor and a heating plate, we have developed an artificial thermal nociceptor that closely mirrors the sensory attributes of its biological counterpart. Our approach significantly advances the emulation of nociceptors, providing a basis for the development of sophisticated artificial sensory systems and intelligent robotics.

Qualitative Analysis of Responses in Estimating Older Adults Cognitive Functioning in Spontaneous Speech: Comparison of Questions Asked by AI Agents and Humans.

Artificial Intelligence (AI) technology is gaining attention for its potential in cognitive function assessment and intervention. AI robots and agents can offer continuous dialogue with the elderly, helping to prevent social isolation and support cognitive health. Speech-based evaluation methods are promising as they reduce the burden on elderly participants. AI agents could replace human questioners, offering efficient and consistent assessments. However, existing research lacks sufficient comparisons of elderly speech content when interacting with AI versus human partners, and detailed analyses of factors like cognitive function levels and dialogue partner effects on speech elements such as proper nouns and fillers. This study investigates how elderly individuals' cognitive functions influence their communication patterns with both human and AI conversational partners. A total of 34 older people (12 men and 22 women) living in the community were selected from a silver human resource centre and day service centre in Tokyo. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and participants engaged in semi-structured daily conversations with both human and AI partners. The study examined the frequency of fillers, proper nouns, and "listen back" in conversations with AI and humans. Results showed that participants used more fillers in human conversations, especially those with lower cognitive function. In contrast, proper nouns were used more in AI conversations, particularly by those with higher cognitive function. Participants also asked for explanations more often in AI conversations, especially those with lower cognitive function. These findings highlight differences in conversation patterns based on cognitive function and the conversation partner being either AI or human. These results suggest that there are differences in conversation patterns depending on the cognitive function of the participants and whether the conversation partner is a human or an AI. This study aims to provide new insights into the effective use of AI agents in dialogue with the elderly, contributing to the improvement of elderly welfare.

Applications of Artificial Intelligence and Machine Learning in Tourism Marketing Research

Purpose of the study: This study aims to investigate the applications of artificial intelligence and machine learning in tourism marketing research. Methodology: The importance and advantages of using artificial intelligence or machine learning in tourism marketing have been investigated. A literature review has been conducted in this field. Main Findings: As a result of this research, it has been found that using artificial intelligence or machine learning in tourism marketing will be more effective in learning customers' feelings and thoughts about businesses, more useful in making predictions about the future, and ultimately productive in customer satisfaction, which is considered the dedication point of modern marketing. Future studies can address the readiness and competencies of marketing managers employed in the tourism sector in the face of this development. In addition, researching current and potential customers in terms of user acceptance can guide businesses in tourism marketing, which can be considered as important findings of this study. Applications of the study: It is known and seen that artificial intelligence, machine learning and service robots are applied in many tourism companies today. Novelty/Originality of the study: Artificial intelligence and machine learning are making rapid progress in their use in every sector today. The innovations and benefits provided by the new and constantly developing use of artificial intelligence and machine learning for tourism marketing have been investigated.

Blockchain evolution, artificial intelligence and ferrous metal trade

This study examines the impact of blockchain technology and artificial intelligence (AI) on the trade volume of iron and steel in 20 major producing countries from 2005 to 2022. Using the FMOLS method, the results show that blockchain regulations reduce trade volumes by increasing transparency and compliance costs, deterring market participation. A 1% increase in AI robotics imports leads to a 0.296% decline in trade due to improved production efficiency. Economic growth and population growth, however, boost trade. A 1% rise in internet access reduces trade by 0.336% as digitalization enhances supply chain efficiency. Overall, blockchain and AI reduce extraction and trade volumes, supporting environmental sustainability. Policy recommendations include developing blockchain regulations, promoting green cryptocurrencies, and leveraging big data for sustainable practices in the ferrous metal industry.

Systematic Analysis of Retrieval-Augmented Generation-Based LLMs for Medical Chatbot Applications

Artificial Intelligence (AI) has the potential to revolutionise the medical and healthcare sectors. AI and related technologies could significantly address some supply-and-demand challenges in the healthcare system, such as medical AI assistants, chatbots and robots. This paper focuses on tailoring LLMs to medical data utilising a Retrieval-Augmented Generation (RAG) database to evaluate their performance in a computationally resource-constrained environment. Existing studies primarily focus on fine-tuning LLMs on medical data, but this paper combines RAG and fine-tuned models and compares them against base models using RAG or only fine-tuning. Open-source LLMs (Flan-T5-Large, LLaMA-2-7B, and Mistral-7B) are fine-tuned using the medical datasets Meadow-MedQA and MedMCQA. Experiments are reported for response generation and multiple-choice question answering. The latter uses two distinct methodologies: Type A, as standard question answering via direct choice selection; and Type B, as language generation and probability confidence score generation of choices available. Results in the medical domain revealed that Fine-tuning and RAG are crucial for improved performance, and that methodology Type A outperforms Type B.

Fabrication of carbon nanotube neuromorphic thin film transistor arrays and their applications for flexible olfactory-visual multisensory synergy recognition

Abstract Artificial multisensory devices play a key role for the human-computer interaction in the field of artificial intelligence (AI). In this work, we have designed and constructed a novel olfactory-visual bimodal neuromorphic carbon nanotube thin film transistor (TFT) arrays for artificial olfactory-visual multisensory synergy recognition with the ultralow single-pulse power consumption of 25 aJ, employing semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials and gas sensitive materials, and poly[[4,8-bis[5-(2-ethylhexyl)-2-thienyl]benzo[1,2-b:4,5-b0]dithiophene-2,6-diyl]-2,5-thiophenediyl-[5,7-bis(2-ethylhexyl)-4,8-dioxo-4H,8H-benzo[1,2-c:4,5-c0]dithio-phene-1,3-diyl]] (PBDB-T) as the photosensitive material. It is noted that it is the first time to realize the simulation of olfactory and visual senses (from 280 nm to 650 nm) with the wide operating temperature range (0-150 °C) in a single SWCNT TFT device and successfully simulate the recovery of olfactory senses after COVID-19 by olfactory-visual synergy. Furthermore, our SWCNT neuromorphic TFT devices with high Ion/Ioff ratio (up to 106) at a low operating voltage (-2-0.5 V) can mimic not only the basic biological synaptic functions of olfaction and vision (such as paired-pulse facilitation, short-term plasticity, and long-term plasticity), but also optical wireless communication by Morse code. The proposed multisensory, broadband light-responsive, low-power synaptic devices provide great potential for developing AI robots to face complex external environments.

AI service robots in a 4-star hotel: enhancing guest and employee experiences

ABSTRACT: Artificial intelligence (AI) has recently become a vital technology affecting several sectors, including hospitality. The expanding use of AI robots in functions previously performed by humans raises important issues — which are currently unknown — regarding how AI robotics may affect personnel and guests. This study examined guests’ and staff’s experiences with service robots in a 4-star southern Dutch hotel. The report offers the hospitality industry AI robot implementation advice. In-depth staff interviews and 4-star hotel guest surveys were completed. Data from customers and staff showed a need for service robots at the front office. This demand highlights the need for service robots at the front desk to serve leisure and business clients and to aid staff. However, both quantitative and qualitative studies imply that a tangible human welcome is still necessary, especially for leisure tourists. This study found that customers and personnel at the front office want service robots, with leisure and business guests preferring something different. These demographics perceive human connections as essential for a good visitor experience, emphasising the complexities of AI in hospitality.

An investigation of public trust in autonomous humanoid AI robot doctors: a preparation for our future healthcare system

As a preparation for our future healthcare system with artificial intelligence (AI)-based autonomous robots, this study investigated the level of public trust in autonomous humanoid robot (AHR) doctors that would be enabled by AI technology and introduced to the public for the sake of better healthcare accessibility and services in the future. Employing the most frequently adopted scales in measuring patients’ trust in their primary care physicians (PCPs), this study analyzed 413 survey responses collected from the general public in the United States and found trust in AHR nearly matched the level of trust in human doctors, although it was slightly lower. Based on the results of data analysis, this study provided explanations about the benefits of using AHR doctors and some proactive recommendations in terms of how to develop AHR doctors, how to implement them in actual medical practices, more frequent exposure of humanoid robots to the public, and the need of interdisciplinary collaboration to enhance public trust in AHR doctors. This line of study is urgently demanded because the placement of such advanced robot technology in the healthcare system is unavoidable as the public has experienced it more these days. The limitations arising from the non-experimental design, a voluntary response sampling through social media, and few theories on communication with humanoid robots remain tasks for future studies.

인공지능 로봇의 도덕감정 함양 가능성에 대한 검토 -초등 도덕과를 중심으로-

This study examined the possibility of cultivating moral emotions of artificial intelligence robots that are developing recently. The 2022 revised elementary moral curriculum provides an opportunity for thought by asking questions about the relationship between artificial intelligence robots and humans. For the study, we first investigated the nature and expression process of emotions from ancient Western philosophy to modern brain science and neuroscience. Based on this, we explored what kind of emotional view the currently developed artificial intelligence robots express emotions based on. As a result, current artificial intelligence robots showed responses to humans using information accumulated through facial movements and facial expressions, focusing on basic emotions, according to Ekman's theory. This may be seen as a passive form based on human physical characteristics. However, moral emotion has a complex and active character that combines understanding of moral problem situations, empathy for others, and appropriate responses to situations. Accordingly, it was recommended to clearly teach the status and limitations of artificial intelligence robots in the field of current moral emotions in elementary moral education and educate students to form desirable relationships with artificial intelligence robots.

Application of AI integrated semi-autonomous robotics in spine surgery: A review

Spine surgery is a high-risk surgery associated with high precision and accuracy. Artificial intelligence (AI) and semi-autonomous robotics can benefit the surgery. This paper explores the impact of AI and robotics on improving surgical precision, accuracy, and safety with details on preoperative planning, optimal screw placement, and intraoperative real-time monitoring. In addition, the potential of AI-driven simulation spaces for training and skill assessment was evaluated. Various AI models and robotic systems have improved surgical outcomes by providing precise guidance and reducing human error. This review aims to summarize the recent developments and highlight the challenges of AI and semi-autonomous robotics in spine surgery.

Research on the application of new technologies in Vietnam's construction industry: Assessment of current status and prospects of industry 4.0 technologies

The Fourth Industrial Revolution is profoundly transforming the global construction industry. This study surveys and analyzes the application level, predicted impact, and investment trends of 8 core technologies of Industry 4.0 in the Vietnamese construction sector. Through a survey of 141 industry experts and managers, the results reveal a significant gap between current application levels and future impact expectations of these technologies. Cybersecurity, Internet of Things, and Big Data are rated highest in terms of application and investment. The study also highlights challenges in adopting new technologies such as Artificial Intelligence, Blockchain, and Advanced Robotics. The research findings provide an overview of digital transformation trends in Vietnam's construction industry, contributing to guiding businesses and policymakers in implementing Industry 4.0 technologies.

Can an AI-carebot be filial? Reflections from Confucian ethics.

This article discusses the application of artificially intelligent robots within eldercare and explores a series of ethical considerations, including the challenges that AI (Artificial Intelligence) technology poses to traditional Chinese Confucian filial piety. From the perspective of Confucian ethics, the paper argues that robots cannot adequately fulfill duties of care. Due to their detachment from personal relationships and interactions, the "emotions" of AI robots are merely performative reactions in different situations, rather than actual emotional abilities. No matter how "humanized" robots become, it is difficult to establish genuine empathy and a meaningful relationship with them for this reason. Even so, we acknowledge that AI robots are a significant tool in managing the demands of elder care and the growth of care poverty, and as such, we attempt to outline some parameters within which care robotics could be acceptable within a Confucian ethical system. Finally, the paper discusses the social impact and ethical considerations brought on by the interaction between humans and machines. It is observed that the relationship between humans and technology has always had both utopian and dystopian aspects, and robotic elder care is no exception. AI caregiver robots will likely become a part of elder care, and the transformation of these robots from "service providers" to "companions" seems inevitable. In light of this, the application of AI-augmented robotic elder care will also eventually change our understanding of interpersonal relationships and traditional requirements of filial piety.

The Impact of Artificial Intelligence Virtual Oral Tutoring APPs on Chinese Youth’s Anxiety in Oral English learning——Interview Research Based on Users of Artificial Intelligence Speaking Tutoring APPs

Foreign language learning anxiety is a long-standing topic that people use to guide foreign language teaching and the setting of foreign language education scenarios by studying the anxiety emotions that exist in foreign language learning. However, in today’s era of artificial intelligence (AI), with the release of ChatGPT, large language model AI technology is widely used. In such a new context, various AI virtual foreign language oral coaches have emerged. Due to the short development time of the large language model technology, the foreign language training model built on this technology is still in the initial stage of development, and the research on this field is very limited. The research on the improvement of foreign language learning emotions brought by GAI is even rarer. The foreign language learning method provided by the AI coach. What help does it have for foreign language learning? Does it alleviate foreign language learning anxiety? It has become a blank in foreign language learning emotion research. This study used semi-structured interviews with 10 Chinese young people between the ages of 20 and 40. Using the method of thematic analysis, the data of this interview were recorded and analyzed, and the conclusions reached were explained from the control value theory, and it was found that AI robots can alleviate many aspects of anxiety in foreign language oral learning, such as: communicative anxiety, situational anxiety, oral anxiety, hearing anxiety, and cognitive anxiety. It is very friendly to socially phobic people, providing emotional companionship and cognitive support for students who are lonely and helpless in foreign language oral communication, although the effect of foreign language improvement is different for different students, but it has an obvious effect on alleviating anxiety when learning foreign languages, and it is unexpectedly found that the AI robot foreign language coach also has the role of emotional companionship for learners, in addition to helping to alleviate anxiety, it can also provide positive emotional value through care, companionship, communication, etc. The findings of this paper are helpful to understand the help of AI technology on foreign language learning emotions, and to provide support for subsequent research on AI accompanying foreign language learning.

Effectiveness of artificial intelligence robot interventions on psychological health in community-dwelling older adults: A systematic review

Effectiveness of artificial intelligence robot interventions on psychological health in community-dwelling older adults: A systematic review

Anthropomorphism-based artificial intelligence (AI) robots typology in hospitality and tourism

Purpose Anthropomorphism plays a crucial role in the deployment of human-like robots in hospitality and tourism. This study aims to propose an anthropomorphism-based typology of artificial intelligence (AI) robots, based on robot attributes, usage, function and application across different operational levels. Design/methodology/approach Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist, the research was conducted in two stages. A search strategy was implemented to explore anthropomorphism-based AI robots and to develop a robot typology. Findings This study provides a comprehensive typology of anthropomorphism-based AI robots used in tourism and hospitality and classifies them into four types, namely, chatbots, mechanoids, humanoids and android robots. Each type features distinct functions and applications. Practical implications The findings can assist companies in using anthropomorphic robots to improve service and strengthen competitiveness. This study offers valuable insights to managers for deploying AI robots across diverse service sectors. Originality/value This research provides a novel typology of hospitality and tourism AI robots and extends the understanding of anthropomorphism in human–robot interaction. This typology encompasses both virtual and physical robots, providing clarity on their attributes, usage, functions and applications across diverse areas of hospitality operations.

Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT®, Bard®, Gemini®, Copilot®, and Perplexity® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care. Responses from each 5 AI chatbots were analyzed separately. This study did not involve any human participants. Study results revealed significant differences between the readability assessments of responses from all 5 AI chatbots (P < .05). According to the results of our study, when different readability indexes were evaluated holistically, the readability of AI chatbot responses was evaluated as Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, from easy to difficult (P < .05). In our study, the median readability indexes of each of the 5 AI chatbots Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini® responses were compared to the "recommended" 6th grade reading level. According to the results of our study answers of all 5 AI chatbots were compared with the 6th grade reading level, statistically significant differences were observed in the all formulas (P < .001). The answers of all 5 artificial intelligence robots were determined to be at an educational level well above the 6th grade level. The modified DISCERN and Journal of American Medical Association scores was found to be the highest in Perplexity® (P < .001). Gemini® responses were found to have the highest Global Quality Scale score (P < .001). It is emphasized that patient education materials should have a readability level of 6th grade level. Of the 5 AI chatbots whose answers about palliative care were evaluated, Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, their current answers were found to be well above the recommended levels in terms of readability of text content. Text content quality assessment scores are also low. Both the quality and readability of texts should be brought to appropriate recommended limits.