Innovative Intelligence Research Articles

Artificial Intelligence Applications Featuring Ease and Safety Factors at the Two Holy Mosques

To ensure that millions of Muslim visitors from around the world receive high-quality services, leadership, and the latest administrative practices at the Grand Mosque, the Presidency of the Two Holy Mosques is committed to providing the best services, leadership, and administrative practices. In addition, reducing physical effort and enhancing smart technology will improve visitors' daily services to keep up with Vision 2030 and the presidency's strategic plan for 2024. Artificial Intelligence (AI) represents the biggest project applied by the presidency to keep pace with vision, where the presidency provided several applications based on AI to enhance ease and safety factors for pilgrims and worshipers at the Two Holy Mosques. This research, entitled "Artificial intelligence applications featuring ease and safety factors at the Two Holy Mosques" is important in highlighting the aspects of Saudi Arabia's interest in artificial intelligence in the Two Holy Mosques to achieve safety and ease and to achieve global competition in this side. To achieve these aspects, the descriptive and analytical approach was used. I dealt with it through the following demands: presenting some literary reviews and presenting some applications that contribute to safety and ease. And I concluded the most important results: achieving artificial intelligence innovations in the Two Holy Mosques for security and ease and demonstrating aspects of diversity in these applications.

Intelligent Innovation Platform Design of Chinese Film and Television Music Based on Multi-Dimensional Information Fusion Algorithm

Experienced changes in recording techniques and musical styles. With the development of the times, digital technology is constantly developing and progressing. In the aspect of film and television music creation, the application of digital technology has been innovated accordingly. Using multi-source information fusion to build a music feature system to solve the problem of music recommendation cold start Users provide personalized music recommendations. The optimized high-concurrency Cuckoo Hashing algorithm is implemented on the DPDK platform, and the algorithm is optimized for large page memory, batch processing and preprocessing combined with DPDK features. Music information retrieval is expanded from the traditional retrieval based on keywords such as file name and artist name. At the same time, the evaluation of the example model of the system also verifies that the multi-information source fusion method proposed in this paper can optimize the precision and recall rate of the system.

Artificial intelligence in hospitality and tourism. State of the art and future research avenues

ABSTRACT The hospitality and tourism industry has recently undergone a profound transformation driven by information and communication technologies developments thanks to innovations in Artificial Intelligence and its tools. However, although the literature on AI and tourism is growing, scientific research on these themes is still fuzzy and fragmented. This article aims to explore the current state of the art and possible future developments of AI and its tools in tourism. The study develops a bibliometric analysis using the ISI database and applies social network analysis to map its intellectual structure. Then, the study develops a qualitative literature review to investigate the main research themes and propose future research avenues. The findings identify some main research strands such as: Big Data for demand forecasting and customer satisfaction; Augmented Reality and Virtual Reality for co-creation processes; the COVID-19 pandemic, social distances issues and service robots; and the smart tourism trends.

Modeling and Simulation Analysis of Digital Standardization Transformation Teaching Organization and Management System

With the comprehensive development of the "Double High Plan" construction in higher vocational colleges, teaching organization management plays an important role in promoting the high-quality development of higher vocational education. However, there are inevitably problems in higher vocational colleges that the teaching management system is not perfect and the teaching management operation mechanism is not optimized enough, which hinders the high-quality development of higher vocational colleges to a certain extent. In order to better solve the above problems, this paper proposes a new teaching organization and management system, guided by constructivism and multimedia learning cognition theory, through the digitalization and intelligent innovation of the teaching organization and management system, in order to further optimize resource allocation, Improve governance capabilities.

Heritage and Innovation of Art Creation in the Context of Big Data and Public Health Events

In the context of big data of public health events, the inheritance and innovation of fine art creation becomes a new opportunity and challenge. In this paper, based on the art image data collection, we establish a convolutional neural network model with migration learning and inverse algorithm for the recognition of art creation under the big data of public health events. The experimental results show that the visual image analysis algorithm can classify paintings with an accuracy of more than 99%, which has good painting recognition effect and classification ability. The migration learning model achieves a training accuracy of over 97% at 50 training rounds and also performs well on the test set with an accuracy of 96. 97%. Using the neural network model of art creation established in this paper for intelligent innovation of art images, with the increase of model settings, it can guarantee the recognition of art creation images between 60% and 80%, and with the increase of iterations, the effective linearity keeps stabilizing and the innovation rate keeps increasing, up to 79.0%. In this paper, the established methods are introduced into Lenet-s model, GoogleNet model and ResNet model for experiments, and it can be seen that the training sets1 of the three models have greater than or equal to 99.8%, 99.6% and 99.4%, respectively, and the training sets2 of the three models have 99.4%, 99.2% and 99.4%, respectively, which proves the neural network model of this paper validity.

The Role of Patent (In)Eligibility in Promoting Artificial Intelligence Innovation (Work-In-Progress)

The Role of Patent (In)Eligibility in Promoting Artificial Intelligence Innovation (Work-In-Progress)

Analyzing the Role of Governmental Organizations in Artificial Intelligence Innovation: A Patent-Based Perspective

Analyzing the Role of Governmental Organizations in Artificial Intelligence Innovation: A Patent-Based Perspective

Exploring and Practicing Smart Teaching Mode by Integrating Innovation and Empowering Data for College English

In view of the new requirements of education and teaching reform under the background of information technology, this paper, based on the characteristics of talent cultivation of Anhui University of Science and Technology, carries out practical exploration and makes intelligent innovation keep pace with the times as well as fosters students’ virtue through education. This paper aims to build a student-centered, innovative and intelligent teaching model of integrated innovation and data empowerment under the guidance of the value of Three All-around Education .Based on the textbook of New Horizon College English, advantages of the school’s information technology and application of the Learning Platform have been given full play. Practice has proved that we should promote the construction of college English ideological and political digital wisdom curriculum, so as to form a good ecological teaching chain, and achieve remarkable talent training results.

Local Practice of Intelligent Innovation and Sustainable Development of Environmental in NCUT of Taiwan

The purpose of this project is to assist local fruit farmers to increase output value through innovative development, build a distribution network for agricultural products, and increase farmers' income. In the technology of increasing agricultural output value, NCUT's professional team applies smart agricultural technology to monitor fruit trees to prevent pests and diseases, maintain the healthy growth and yield of fruit trees, and solve the problem of lack of labor in farmland. The NCUT team practices strategic marketing and business models to guide fruit farmers to promote local creation and enhance local cultural characteristics. This project assists in the implementation of new quality-guaranteed and value-added technologies, promotes high-quality agricultural products across the country and improves local tourism marketing, and activates agricultural product promotion activities to achieve mutual support between industry and academia. In addition, in response to the 50th anniversary of the World Earth Day, NCUT held a tree planting to save the earth to implement the concept of sustainable environmental development. President Chen, faculty and students planted 500 Cinnamomum camphor seedlings on the NCUT campus in response to the UN Climate Change Framework Convention.Keyword: Environmental Protection, Local Practice, Intelligent Innovation, Intelligent Agricultural Technology, Sustainable Development

How Do Consumer Innovation Characteristics and Consumption Value Shape Users’ Willingness to Buy Innovative Car Safety Seats?

The intelligent innovation of child safety seats has brought new impacts and challenges to the Chinese market. Researchers in the car seat industry have been focusing on industry regulations and the abuse of car seats, but there is a lack of consumer-centered research. This study is the first to combine two theories of consumer subject-specific innovation (DSI) and the theory of consumption value (TCV). This study explores how consumer innovations influence consumers’ purchase of innovative child safety seats through perceived value. The proposed research model was evaluated using a partial least squares structural equation model, and data analysis revealed that the model had good model fit, reliability, and validity. Consumer product innovation has a significantly better impact on willingness to buy than consumer information innovation. In this study, in the relationship between consumers of information innovation and purchase intention in the automobile seat industry, a new kind of parallel multi-mediating relationship between the social value, hedonic value, and novelty value of perceived products was proposed. The study’s results address the need for more consumer research in the intelligent seating industry, as well as how to give researchers and marketing firms solutions and suggestions based on facts.

Exploring Stakeholder Requirements to Enable the Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Protocol for a Multistep Mixed Methods Study

In recent years, research and developments in advancing artificial intelligence (AI) in health care and medicine have increased. High expectations surround the use of AI technologies, such as improvements for diagnosis and increases in the quality of care with reductions in health care costs. The successful development and testing of new AI algorithms require large amounts of high-quality data. Academic hospitals could provide the data needed for AI development, but granting legal, controlled, and regulated access to these data for developers and researchers is difficult. Therefore, the German Federal Ministry of Health supports the Protected Artificial Intelligence Innovation Environment for Patient-Oriented Digital Health Solutions for Developing, Testing, and Evidence-Based Evaluation of Clinical Value (pAItient) project, aiming to install the AI Innovation Environment at the Heidelberg University Hospital in Germany. The AI Innovation Environment was designed as a proof-of-concept extension of the already existing Medical Data Integration Center. It will establish a process to support every step of developing and testing AI-based technologies. The first part of the pAItient project, as presented in this research protocol, aims to explore stakeholders' requirements for developing AI in partnership with an academic hospital and granting AI experts access to anonymized personal health data. We planned a multistep mixed methods approach. In the first step, researchers and employees from stakeholder organizations were invited to participate in semistructured interviews. In the following step, questionnaires were developed based on the participants' answers and distributed among the stakeholders' organizations to quantify qualitative findings and discover important aspects that were not mentioned by the interviewees. The questionnaires will be analyzed descriptively. In addition, patients and physicians were interviewed as well. No survey questionnaires were developed for this second group of participants. The study was approved by the Ethics Committee of the Heidelberg University Hospital (approval number: S-241/2021). Data collection concluded in summer 2022. Data analysis is planned to start in fall 2022. We plan to publish the results in winter 2022 to 2023. The results of our study will help in shaping the AI Innovation Environment at our academic hospital according to stakeholder requirements. With this approach, in turn, we aim to shape an AI environment that is effective and is deemed acceptable by all parties. DERR1-10.2196/42208.

A Cloud-Based Computing Framework for Artificial Intelligence Innovation in Support of Multidomain Operations

The DoD’s artificial intelligence (AI) strategy requires the delivery of transformative and disruptive capabilities that impact the “character of the future battlefield and the pace of threats” that US forces must be prepared to handle. Candidate frameworks must also address key mission areas while enabling partnerships with the private sector, academia, and global allies. To meet these challenges, a flexible, cost-effective, and scalable computing infrastructure that incorporates cutting edge technologies and complies with stringent information assurance requirements is necessary. The DoD AI strategy mandates the agile employment of innovative AI capabilities that “rapidly and iteratively” execute experimentation with new operating concepts, and leverage lessons learned in subsequent experiments. Using cloud computing, we present a flexible approach to solve complex systems problems. Promoting “rapid experimentation” and collaboration on problems such as recursive algorithm implementation, deep learning, and inference in neural networks has enabled inherent advantages over existing computing frameworks. Leveraging the cloud to implement shared responsibility security models, serverless architectures, and high-performance virtual machines, aspects of the AI lifecycle including build, deploy, and monitor have resulted in an adaptable and scalable computing framework that is not only disruptive to the current computing paradigm but also promotes enhanced and productive collaboration.

Concept of Military Asset Management System in Indonesian Armed Forces

The Internet of Things (IoT) is a very fast-growing technology and has a huge impact on our daily life, including military performance. In the military, IoT known as the Internet of Military Things (IoMT) or Internet of Battlefield Things (IoBT) has the function create network communication to increase readiness in the military and can apply to all aspects of military asset management and uses the interconnection, real-time, and intelligent innovation of the IoT technology to build a military asset management system. The research purpose is to analyze the Military Asset Management System (MAMs) in Indonesian National Armed Forces. The research applies a qualitative research methodology. The literature review method and the interviews were used to obtain data and analyze to describe or explain the phenomenon of problems with the Maintenance, Repair, and Overhaul (MRO) and Military Asset Management system (MAMs) in supporting the operation of the Alutsista Indonesian National Armed Forces. The research result shows that the integration of asset management in the Indonesian National Armed Forces is still not centralized, which it means needs more time to collect material asset data and of course, will impact the readiness of the military. In this case, Complex Aerial Mission Simulation (CAMS) can be a reference for Indonesian National Armed Forces to develop a Military Asset Management System (MAMs).

Innovation intelligence in managing co-creation process between tech-enabled corporations and startups

This paper focuses on the issue of digital tech-enabled corporations that co-create an innovative digital-output with startups; in this process, they require knowledge for decision-making known as innovation intelligence to build a co-creation space by implementing and fortifying a collective intelligence. In this regard, this research introduces co-creation realization, co-creation pivoting, and co-creator relationship management as three key innovation intelligence topics (KITs). Then, it addresses the dynamic capabilities to create indispensable knowledge for decision-making in these three topics through empirical insight from a multi-case study in four tech-enabled corporations in the Iranian entrepreneurial e-commerce ecosystem. The results indicate two plannable and unplannable categories as organizational and group level capabilities for each recognized KITs, respectively. The proposed innovation intelligence framework represents how these capabilities are interrelated and the effect of strengthening and weakening them on the co-creation process by affecting collective intelligence. The results can provide insight to tech-enabled corporations in employing innovation intelligence to overcome a dipole between corporations and startups, which results in managing the co-creation process effectively. Also, it contributes to constantly filling the dynamic innovation gap between the expectations of innovation co-creation and actual achievements among managers during the co-creation process.

Intelligent Technologies for Excellency in Sustainable Operational Performance in the Healthcare Sector

Recent years witnessed lots of advancements in internet of medical things (IoMT), innovations in artificial intelligence (AI), big data analytics, and fog computing-based healthcare practices. Adoption of these intelligent technology-based solutions could help healthcare establishments to improve their sustainable operational performance. However, success of implementation of smart technology-enabled Health 4.0 practices depends upon the coordinated efforts from all the stakeholders including patients, physicians, healthcare workers, healthcare administrators, policy makers, and technology service providers towards its adoption. In this regard, this research has been conducted to investigate the current status of Health 4.0 implementation in India and readiness of the Indian healthcare sector towards its adoption. This paper further employs the SWOT analysis to identify the current areas that need immediate improvement to facilitate Health 4.0 adoption.

Hydrological Drought Forecasting Using a Deep Transformer Model

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were collected from these two stations. The two deep learning models were used to predict stage data for five different time steps: 30, 60, 90, 120, and 180 days. A drought series was created from the forecasted values using a monthly fixed threshold of the 75th percentile (75Q). The transformer model outperformed the LSTM model for all of the timescales at both locations when considering the following averages: MSE=0.11, MAE=0.21, RSME=0.31, and R2=0.92 for the Chattahoochee station, and MSE=0.06, MAE=0.19, RSME=0.23, and R2=0.93 for the Blountstown station. The transformer model exhibited greater accuracy in generating the same drought series as the observed data after applying the 75Q threshold, with few exceptions. Considering the evaluation criteria, the transformer deep learning model accurately forecasts hydrological drought in the Apalachicola River, which could be helpful for drought planning and mitigation in this area of contested water resources, and likely has broad applicability elsewhere.

Extended Arm of Precision in Prosthodontics: Artificial Intelligence.

Dentistry based onartificial intelligence (AI) is not a myth but turning into a reality. AI has revolutionized medicine and dentistry in various ways. AI is a technology that uses machines to imitate intelligent human behavior. AI is gaining popularity worldwide because ofits significant impact and breakthrough in the field of intelligence innovation. It is a lifesaver in dentistry, particularly in the field of prosthodontics, because it aids in the design of prostheses and the fabrication of functional maxillofacial appliances. It also helps in the processes of patient documentation, diagnosis, treatment planning, and patient management, allowing oral healthcare professionals to work smarter rather than harder. While it cannot replace the work of a dentist because dentistry is not about disease diagnosis, it does involve correlation with other clinical findings and provides treatment to the patient. The integration of AI and digitization has brought a new paradigm in dentistry, with extremely promising prospects. The availability of insufficient and inaccurate data is now the only barrier to the deployment of AI. Therefore, dentists and clinicians must focus on collecting and entering authentic data into their database, which will be completely utilized for AI in dentistry shortly. This study focuses on various applications of AI in prosthodontics along with its limitations and future scope.

Advancing competitive advantage in manufacturing firms through competitive intelligence

This study investigated the relationship between Competitive Intelligence Practices and Competitive Advantage in Manufacturing Industry: A study of selected Aluminum Firms in Nigeria. The specific objectives of the study are to ascertain the effect of the selected measures of Competitive Intelligence, namely; Strategic Intelligence (SI) and Innovative Intelligence (II) on Competitive Advantage (CA). The responses from the respondents were collected with the aid of five (5) Likert scale questionnaires and descriptive survey research. A total of one hundred and sixty-nine (169) questionnaires were administered, out of the one hundred and sixty-nine (169) questionnaires administered to staff of selected registered Aluminium Firms. One hundred and forty-six (146) were retrieved and properly filled. These one hundred and forty-six (146) respondents represent 86.39 per cent of the total questionnaire administered, which shows that one hundred and forty-six (146) respondents are sufficient for the study. Thus, the sample used for the study was the one hundred and forty-six (146) respondents from the staff of Aluminium Industries used. The questionnaire was coded with the aid of an excel spread sheet, the respondent's profile was analyzed with manual simple percentage, and the research questions were analyzed with the aid of descriptive statistics, correlation matrix and multiple regression statistical tools with the aid of SPSS version 23 as the basis of testing hypotheses. The findings revealed that Strategic Intelligence (SI) and Innovative Intelligence (II) have a significant relationship with Competitive Advantage (CA). From the findings of the study, it can be concluded that overall the competitive intelligence practices had a positive significant effect on the competitive advantage in selected Aluminum Firms. Thereby the study recommends that there should be adequate investment in the competitive intelligence process, facilities, and activities by the manufacturing firms to be innovative in their product, services and competitive dispositions.

Inovasi Penanaman Nilai-Nilai Karakter Pendidikan Agama Islam pada Anak Usia Dini melalui Metode Permainan di Taman Kanak-Kanak

This study aims to describe the innovation of planting character valuesof Islamic religious education through the game method. This study uses the type of action research (action research) while the data collection methods used are interviews, observation and documentation.The development of religious and moral intelligence innovations can be used to instill character values in the learning process of Islamic Religious Education, including: hijaiyah lettering games, arranging pictures of ablution sequences, prayer sequences puzzles. From the game, it is hoped that it can bring out the character values of good Islamic religious education in early childhood.

Overview Of Artificial Intelligence In Agriculture For Enhancement Of Irrigation , Application Of Pesticides And Insecticide

Agriculture plays a crucial role within the economic sector. The automation in agriculture is the fundamental concern and the arising subject across the world. The population is increasing massively and with this increment the interest of food and work is in addition increasing. The traditional methods used by the farmers, were insufficient to fulfill these requirements. These new methods consummated the food wants and what is more gave work open doors to billions of people. Automation in agriculture has brought an excellent revolution. This technology has protected the yield from numerous factors just like the climate changes, food security downside, increment and also the employment problems. Artificial intelligence frameworks are assisting with further developing the general gather quality and exactness - known as accuracy agribusiness. Computer based intelligence innovation helps in distinguishing illness in plants, vermin and unfortunate sustenance of homesteads. Simulated intelligence sensors can identify and target weeds and afterward choose which herbicide to apply within the region. An immediate utilization of AI (Artificial Intelligence) or machine knowledge across the cultivating area could act to be an exemplification of shift in how cultivating is drilled today. Cultivating arrangements which are AI controlled empowers a rancher to accomplish more with less, improving the quality, likewise guaranteeing a fast GTM (go-to-showcase procedure) methodology for crops. The ongoing paper tosses a dream of how the different areas of farming can be fuelled utilizing AI. It likewise examines the AI controlled thoughts in for future and the difficulties expected in future