Innovative Intelligence Research Articles

Promoting Intelligent Finance, the Exploration and Innovation of Enterprise Financial Management System

With the current changes in the trend of digital information technology, the development needs of the macroeconomic market within the new economic development stage and the international diversified economic wave, it is obvious that the financial management system of Chinese enterprises is no longer applicable.Then enterprise to promote intelligent finance, explore innovative enterprise financial management system for the urgent need. In view of the fact that, this article analyzes and discusses the problems belonging to the financial management system of Chinese enterprises at the existing stage, and creates a practicable path for the financial management system in a multi-dimensional and multi-level manner. The management of business operations and financial management is accompanied by a synchronised and optimized system for the management of communities, providing timely integration and dynamic quality enhancement.

An Investigation into the relationship between AI enabled Chabot Interface and Online buying behavior of Consumers in Delhi NCR Region

The rapid advancement in the field of artificial intelligence (AI) has offered tremendous opportunities to different organizations engaged in serving customers. AI provides a platter of add-ons that promise to enhance relationships with the stakeholders, to seamlessly upgrade and update marketing initiatives and to positively impact the consumer buying behaviour process. COVID-19 pandemic emerged as an immitigable disaster for many businesses; however, at the same time, online platforms gave way for a new edition of digital marketing. Thanks to the e-commerce websites consumers are now purchasing anything and everything online be it groceries or vegetables or clothes or washing machines. The need to physically visit a store to shop appeared to have weakened against the compulsion to shop from home during pandemic. However, studies have shown that given a chance, consumers will not trade-off traditional mode of shopping for online shopping, at least not completely. There still exists a desire to connect- physically, socially and emotionally- to buying process. In order impart personal touch to online shopping experience of the consumers a new AI enabled application, ‘Chatbot’, was developed. Chatbot assumes a human persona to enhance consumers’ online shopping experience, modify (amplify) their expectations related to product and assist them in making an informed purchase decision. Chatbots are a novel and trending artificial intelligence (AI) innovation. Through this study we attempt to investigate the impact of AI enabled Chatbots on pre-purchase, purchase and post-purchase behaviours of consumers in Delhi NCR region. The study proposes to investigate the relationship between consumers’ interface with AI enable chatbots and the impact thereof on pre-purchase, purchase and post-purchase behaviours. The implications of the study to marketers have also been suggested. The research employs correlation and regression techniques to test the research hypothesis on the Page primary data collected using a structured and undisguised questionnaire. The sample size is projected to be 200 respondents.

Innovations in Internet of Medical Things, Artificial Intelligence, and Readiness of the Healthcare Sector Towards Health 4.0 Adoption

Recent years witnessed lots of advancements in Internet of Medical Things, Innovations in Artificial Intelligence and Big Data Analytics based health care practices. Further, recent pandemic has compelled health care institutions to adopt remote patient care practices throughout the world and India is not an exception. Growth in mobile infrastructure and cheap mobile data packages also encouraged adoption of telemedicine and m-health care practices in India which eventually supports attempts of health care policy makers for transition of traditional health care systems to Health 4.0 in the lines of industry4.0. However, success of Health 4.0 depends upon the coordinated efforts from all the stakeholders. In this regard this research has been conducted to investigate the current status of Health 4.0 implementation in India and readiness of Indian health care sector towards its adoption. This paper further employs the SWOT-AHP analysis to identify the current areas that need immediate improvement to facilitate Health 4.0 adoption.

Sourcing product innovation intelligence from online reviews

In recent years, online reviews have offered a rich new medium for consumers to express their opinions and feedback. Product designers frequently aim to consider consumer preferences in their work, but many firms are unsure of how best to harness this online feedback given that textual data is both unstructured and voluminous. In this study, we use text mining tools to propose a method for rapid prioritization of online reviews, differentiating the reviews pertaining to innovation opportunities that are most useful for firms. We draw from the innovation and entrepreneurship literature and provide an empirical basis for the widely accepted attribute mapping framework, which delineates between desirable product attributes that firms may want to capitalize upon and undesirable attributes that they may need to remedy. Based on a large sample of reviews in the countertop appliances industry, we demonstrate the performance of our technique, which offers statistically significant improvements relative to existing methods. We validate the usefulness of our technique by asking senior managers at a large manufacturing firm to rate a selection of online reviews, and we show that the selected attribute types are more useful than alternative reviews. Our results offer insight in how firms may use online reviews to harness vital consumer feedback.

Adoption model of healthcare wearable devices

• Data Privacy, economy Burden, and perceived ease of use were identified as the factors to affect perceived usefulness. • Data Privacy, perceived ease of Use, and perceived usefulness were identified as the factors to affect the intention of adoption of wearable medical devices. • Economy burden has a negative insignificant impact on the intention of adoption. The progressive advances in the fifth-generation standard for cellular networks have led to innovations in the artificial intelligence of things, which have changed the layout of the medical industry. The applications of wearable medical devices and services are under continual expansion. Key factors influencing intention to use (e.g., economic burden, data privacy, perceived ease of use, and perceived usefulness) require further investigation. In the present study, the participants were surveyed by questionnaire, and path analysis was used to examine causality. The results revealed that intention to adopt was likely to be higher for wearable medical devices that offered high data privacy, had high perceived ease of use, and provided reliable data (with regard to accurate references for physical health). Conversely, the economic burden imposed by wearable medical devices and services was likely to reduce intention to adopt. Therefore, the payment mechanism warrants cautious evaluation.

The best use of technology in the health emergency operation centers during COVID-19 pandemic

Since the outbreak of the coronavirus in the Kingdom of Saudi Arabia in 2020, National Health Emergency Center aligned itself to the Saudi Arabia's Vision 2030 and has played a key role to link the different health sectors in the country with Ministry of Health, through the use of state-of-the-art infrastructure, innovative digital technologies, location intelligence, data analysis, and real time data. Thereby, General Directorate of Emergency, Disasters and Medical Transportation - Deputyship of Curative Services, launched the National Health Emergency Operation Center, which integrates digital technologies to deliver substantial improvements to emergency healthcare management. Through real-time maps, apps, and dashboards, the innovative integration of different technologies has revolutionized the Center's operations by providing location intelligence and evidence-based analysis that shapes sound policy and saves lives. Disaster health management has become a key goal for every nation in order to reduce the impact of disasters on human health and wellbeing. It is an important aspect of any resilient healthcare system.

Design, implementation, and evaluation of an innovative intelligence information management system for premature infants.

IntroductionLow birth weight is the most important condition of neonatal community health and the main cause of neonates' mortality. Identifying the indexes associated with this condition, and factors to prevent, and managing related data can help reduce the birth of premature infants to reduce the mortality rate due to this condition. The goal of present study was to design, implement and evaluate an innovative intelligence information management system for premature infants.Material and methodThe present study was a multidisciplinary research that was done in 2019 to 2021 in four integrated phases in Iran. The first phase aimed to compare the current status of registration systems of premature infants through a systematic review and semi-structured interviews by using the Delphi model Then the minimum data set was determined and was designed a proposed model based on it. In the second phase, the structure and how the user interacts with the system were determined, and, using Microsoft Visio software, Unified Modeling Language diagrams were drawn to define the logical relationship of data. In the third phase, the system was developed, and finally in the last phase, in three methods, users' views on the usability of the system were evaluated.ResultsThe findings of this study included 233 essential data elements that were placed in two main groups of essential data, and the system was approved by end users for 87.73% consent and 67.19% satisfaction for SUMI (Software Usability Measurement Inventory) and 7.97 of 9 in QUIS questionnaire.ConclusionThis research's results can be beneficial and functional such as a complete sample for design and development of other systems concerned to health systems.

Extension knowledge representation of evolutionary law of technological systems in TRIZ

Due to lack of formal and quantitative evolutionary laws, current technology systems in TRIZ can hardly be used in intelligent innovation design. To this end, an Extenics-based method is proposed in this work, which formally expresses the extension knowledge implied in the evolutionary law of technology systems. Based on domain knowledge, extension model, extension rules, extension transformation, and transformation rules, etc., the general steps of extension knowledge representation of evolutionary law of technology systems are studied. Taking evolution law to super system as an example, the corresponding extension knowledge is established. Research results suggest that the proposed method is able to clearly express the connotation and extension of the evolutionary laws of technology systems, thus paving a way applying these laws to extension intelligent design. Application outcomes on the dust removal and spraying system in coal preparation plant validates the effectiveness of the proposed method.

Media Coverage of Labor Issues and Artificial Intelligence Innovation

Media Coverage of Labor Issues and Artificial Intelligence Innovation

CI-Block: A Blockchain System for Information Management of Collaborative Innovation

Blockchain technology ensures the security of cross-organizational data sharing in the process of collaborative innovation. It drives the development of collaborative innovation in discrete manufacturing to intelligent innovation. However, collaborative innovation is a multi-role, networked, and open resource-sharing process. Therefore, it is easy to form information barriers and increase the risk of cooperation between organizations. In this paper, we firstly analyze the blockchain-based information management models in the traditional discrete manufacturing collaborative innovation process. Then, we found that in the process of industry-university-research (IUR) collaborative innovation, consensus servers maintain too many connections due to the high latency between them, which leads to lower consensus performance and efficiency. To solve this problem, we proposed the ependency nalysis (DA) model, which separates and assembles transactional data and non-transactional data into different blocks by analyzing read_set and write_set of transactions. Besides, we propose the ut-of-rder (OORaft) model to allow non-transactional blocks to be copied in parallel, which can also prioritize transactional blocks. Finally, we implement the blockchain model in the discrete manufacturing scenario based on Hyperledger Fabric. The experimental results show that our model improves the transactions per second (TPS) performance of 1.9X-3.7X and reduces transactional data committing latency by more than 40% in the target scenario.

The evolution of military operations: artificial intelligence to detect hand gestures in defence

Artificial intelligence innovations hold promise for improving military operations while gestures have been the simplest and most powerful medium for communications. This idea proposes a system identifying hand movements and translating them to spoken words, where soldiers on battlegrounds may readily converse with one another. We utilise computational vision, Haar cascade classifiers, CNN, MediaPipe and other approaches for thought patterns through results. There are three techniques in this process: firstly, hand identification system that provides borders around the hand placed to another screen fixing image magnification using OpenCV and Matplot; following with a hand-held skeleton-projected connection model using MediaPipe's mapping system libraries in real-time capturing at 30 fps; lastly, sound element being introduced in each class improving recognition of the gestures. Dataset of around 10,000 images across five different classes are built with CNN architecture used to classify. This research shows results to discover AI options for military applications.

Embracing artificial intelligence: how can we make it inclusive and relevant for real-world dermatological practice?

Artificial intelligence (AI) developments are rapidly advancing with algorithms capable of out-performing dermatologists in specific contrived challenges, but where prospective evaluation in real-world settings remain limited. Professional bodies have a role to encourage AI approaches to address clinical unmet needs, improve quality of care, and enhance patient experience without compromising safety. In 2019, the American Academy of Dermatology advocated principles of human-centred design for augmented intelligence innovations (1) emphasising the importance of synergy between dermatologist and the computer. More recently, the British Association of Dermatologists highlighted the weak current evidence-base supporting effectiveness of AI interventions in routine clinical practice and encouraged clinicians to independently evaluate the evidence prior to adoption (2).

The Transformation and Upgrading of English Teaching Modernization under the Background of Information Technology

With the development of Information Technology, English teaching system has realized intelligent innovation and all-round development, especially by paying attention to students' learning demands and integrating all kinds of teaching resources, it realizes the essential optimization of English teaching ecology. Therefore, based on the mature application of information technology, it is of great practical significance to focus on the transformation and upgrading of English teaching modernization. Based on the trend of modernization and transformation of English teaching under the background of information technology, this paper puts forward some corresponding upgrading strategies and suggestions.

The Effect of Individual Innovation and Emotional Intelligence on Positive Organizational Behavior

The purpose of this research is to examine the effects of individual innovation and emotional intelligence levels on organizational behavior of the participants working in the Provincial Directorate of Youth and Sports. The study group of the research consists of 77 female (38.7%) and 122 male (61.3%) participants working in the Provincial Directorate of Youth and Sports. As a data collection tool in the research; Individual Innovation, Emotional Intelligence and Positive Organizational Behavior Scales were used. The participants drew a high level of innovative profile; It can be stated that he has an above-average level of emotional intelligence and organizational behavior. According to the results of the research; A significant, positive and moderate relationship was found between individual innovation, emotional intelligence and organizational behavior. In addition; It can be said that 53% of organizational behavior is explained by individual innovation and emotional intelligence characteristics.

Warehouse robot market boosted by Covid pandemic and technological innovations

PurposeThis paper aims to provide details of recent commercial and technological developments that are driving robotic warehouse automation.Design/methodology/approachFollowing a short introduction, this first provides a commercial background and identifies the factors driving the market growth. It then gives examples of robotics companies, products and applications that exploit innovations in artificial intelligence (AI). It then considers future prospects, and finally, brief conclusions are drawn.FindingsAmazon’s acquisition of Kiva led to a community of new robot manufacturers and the realisation by major e-commerce companies that robotic automation would be required to maintain competitiveness. The Covid pandemic caused a surge in e-commerce and a critical shortage of labour, which further highlighted the need for automation and boosted robotic deployments. Recent advances in AI have resulted in a rapidly growing community of companies producing AI-powered robots which offer advanced capabilities such as mixed product picking, sorting and kitting. These are being deployed by a growing number of e-commerce and logistics companies and are paving the way towards ever-higher levels of warehouse automation. Full automation will soon become a reality.Originality/valueThis paper identifies the factors driving the rapidly developing warehouse robot business by considering the companies, products, technology and applications.

Creating new tech entrepreneurs with digital platforms: Meta-organizations for shared value in data-driven retail ecosystems

Creating technologically focused entrepreneurs is a crucial endeavor worldwide, especially with the exponential growth of artificial intelligence (AI) innovation. This research explores meta-organizations that enable new business models in the retail domain by acting as a powerful mechanism to support entrepreneurs in extracting value from data. This study investigates how meta-organizations engage users and empower tech entrepreneurs to create shared value by developing social innovation. This research involves an in-depth and longitudinal unique case study of a meta-organization operating in Italy, Germany, and Finland. Results indicate that the flexible structure of meta-organizations can effectively guide stakeholders of different mindsets to offer support to high-tech startups. AI-based platforms are a reliable alternative to tackle critical social issues in order to improve economic growth and increase people's performance in a stressful, competitive environment, such as the retail sector. The findings affirm that AI-based innovation orchestrated by meta-organizations can enable new business models by creating shared value for society. Seven critical success factors with implications for theory and practice are discussed, and a new model for AI-driven entrepreneurship is proposed.

CNS: Application of Dynamic Resource Allocation Based on 5G Communication in Technology Innovation of Complex High-Tech Industries

In order to improve the technological innovation effect of compound high-tech industry, this paper studies its dynamic resource allocation technology with the support of 5G communication technology, and analyzes the application of 5G communication technology in technological innovation of compound high-tech industry. In the uplink and downlink of wireless energy-carrying communication system, this paper studies the joint optimization of subcarrier allocation and power allocation of uplink and downlink to maximize the uplink and downlink weighted sum rate of the system. Moreover, this paper adopts the joint optimization algorithm of power and sub-carrier based on Lagrangian dual method and ellipsoid method to obtain the maximum information transmission rate of uplink and downlink. In addition, this paper constructs an intelligent innovation management system. The research results show that the dynamic resource allocation method based on 5G communication proposed in this paper has a very good effect in the application of technological innovation in complex high-tech industries.

Earth Observations and Statistics: Unlocking Sociodemographic Knowledge through the Power of Satellite Images

The continuous urbanisation in most Low-to-Middle-Income-Country (LMIC) cities is accompanied by rapid socio-economic changes in urban and peri-urban areas. Urban transformation processes, such as gentrification as well as the increase in poor urban neighbourhoods (e.g., slums) produce new urban patterns. The intersection of very rapid socio-economic and demographic dynamics are often insufficiently understood, and relevant data for understanding them are commonly unavailable, dated, or too coarse (resolution). Traditional survey-based methods (e.g., census) are carried out at low temporal granularity and do not allow for frequent updates of large urban areas. Researchers and policymakers typically work with very dated data, which do not reflect on-the-ground realities and data aggregation hide socio-economic disparities. Therefore, the potential of Earth Observations (EO) needs to be unlocked. EO data have the ability to provide information at detailed spatial and temporal scales so as to support monitoring transformations. In this paper, we showcase how recent innovations in EO and Artificial Intelligence (AI) can provide relevant, rapid information about socio-economic conditions, and in particular on poor urban neighbourhoods, when large scale and/or multi-temporal data are required, e.g., to support Sustainable Development Goals (SDG) monitoring. We provide solutions to key challenges, including the provision of multi-scale data, the reduction in data costs, and the mapping of socio-economic conditions. These innovations fill data gaps for the production of statistical information, addressing the problems of access to field-based data under COVID-19.

The Innovative Intelligence System—A Tool for Discovering Innovative Opportunities and for Ensuring the Sustainability and Business Prosperity

At present, in the field of building an innovative intelligence system in the company, considerable attention is paid especially to the technological side of this system and the description of its basic elements. The aim of the research is to provide a comprehensive view of building an innovative intelligence system in the company from managerial, information and organizational support. The research consists of questionnaire research and interviews conducted in Slovak companies with the intention to find out the current status of innovative intelligence systems in Slovakia by the content, organization, personnel and information aspects. The authors offer a summary of theoretical knowledge in the field of management—innovative intelligence systems. Summarizing these findings enriches the theoretical basis of management, especially in the field of innovation management. A detailed description of the individual processes, activities and actors of the innovative intelligence system model can serve for a better knowledge of the issue and its successful management. The proposed model of the innovative intelligence system includes the identification of individual actors, their tasks and the decomposition of its main process. The formulated recommendations are a valuable tool for company managers. Adherence to them will ensure the successful implementation and operation of an innovative intelligence system in the company.

Radiologists' Increasing Role in Population Health Management: AJR Expert Panel Narrative Review.

Population health management (PHM) is the holistic process of improving health outcomes of groups of individuals through the support of appropriate financial and care models. Radiologists' presence at the intersection of many aspects of health care, including screening, diagnostic imaging, and image-guided therapies, provides the opportunity for increased radiologist engagement in PHM. Furthermore, innovations in artificial intelligence and imaging informatics will serve as critical tools to improve value in health care through evidence-based and equitable approaches. Given radiologists' limited engagement in PHM to date, it is imperative to define the PHM priorities of the specialty so that radiologists' full value in improving population health is realized. The purpose of this expert review is to explore programs and future directions for radiologists in PHM.