4,956 research outputs found

    Healthcare 4.0: Trends, Challenges and Benefits

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    The Fourth Industry Revolution, known as Industry 4.0, refers to the forces that are transforming industry, including the healthcare industry, where it has been termed Healthcare 4.0. Though lagging other industries in the adoption of new innovative technologies, the healthcare industry is embracing the potential benefits that arise from new innovative technologies. New trends revealed both in the academic literature and by industry practice show that researchers and practitioners are becoming more aware of the benefits technology can bring to an industry as complex as the healthcare industry. The object of the study is to identify the challenges, trends and gaps in the existing body of research with regard to Healthcare 4.0. In this study, a systematic literature review on Healthcare 4.0 research papers was conducted to identify trends, challenges and the perceived benefits that may arise from it. This paper found that there is a need to conduct more empirical studies in this area. It, further, identified the need to implement practical procedures in the industry to get feedback from patients and healthcare participants in order to promote the adoption of new Healthcare 4.0 technologie

    Digital technologies in architecture, engineering, and construction

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    Digitalization in the architecture, engineering, and construction (AEC) sector is slow due to significant challenges in technology adoption. The study aims to promote technology adoption by advancing the understanding of digital technologies in the AEC sector. This article presents the findings from a quantitative scoping review, encompassing 3950 technology-related abstracts retrieved from the Scopus database, providing a preliminary assessment of literature size, geographic innovation hotspots, research gaps, and key concepts in the AEC field. The results show that Building Information Modelling (1852 studies) dominates the literature, while topics like 3D Printing (311) and Internet of Things (227) are gaining traction. China (687 publications) and the United States (566) produce most research articles. Despite the increasing interest in emerging technologies, their implementation often necessitates acquiring specific skill sets. Academia needs to put a stronger focus on these technologies in education and tighter collaboration with the industry is needed.publishedVersio

    Health 4.0: How Digitisation Drives Innovation in the Healthcare Sector

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    Driven by networked Electronic Health Record systems, Artificial Intelligence, real-time data from wearable devices with an overlay of invisible user interfaces and improved analytics, a revolution is afoot in the healthcare industry. Over the next few years, it is likely to fundamentally change how healthcare is delivered and how the outcomes are measured. The focus on collaboration, coherence, and convergence will make healthcare more predictive and personalised. This revolution is called Health 4.0. Data portability allows patients and their physicians to access it anytime anywhere and enhanced analytics allows for differential diagnosis and medical responses that can be predictive, timely, and innovative. Health 4.0 allows the value of data more consistently and effectively. It can pinpoint areas of improvement and enable decisions that are more informed. What it also does is help move the entire healthcare industry from a system that is reactive and focused on fee-for-service to a system that is value-based, which measures outcomes and ensures proactive prevention (Thuemmler, Bai, 2017). In this paper, the authors discuss how digitisation is paving the way for data-driven innovation in the healthcare systems. They elaborate on the opportunities and challenges for all stakeholders involved and discuss how emerging technologies can help overcome the inherent rigidity of today’s healthcare ecosystem. Following on from this, the authors explain the importance of research on the actual design of smart healthcare products and product service systems of the future and the challenges faced from the viewpoint of design practice

    Usability analysis of contending electronic health record systems

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    In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe

    Modelling of Internet of Things (IoT) for Healthcare

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    Purpose: Information technology benefits the world, and it’s required for health care system, such as electronic medical records (EMR). We have proposed systematic model to study hoe IoT with 5g network has potential to benefit various healthcare services. For example, telemedicine may have some usage restrictions in rural areas and physicians may find it difficult to provide continuous monitoring to patients from such area. There are higher chances that the calls or video conferences getting significantly affected by poor networks and signals as well as non-compatible devices and patient may not get the treatment on time. 5G networking with IoT devices are believed to be the game changer for communication technology. The IoT model assists in attaining information by measuring its benefits through criteria which include 5G and IoT features along with a healthcare service requirement. Purpose of this paper is to present a model using Internet of Things (IoT) and 5G technology which will help to understand improved efficiency and efficacy of healthcare services. Our main research methodologies are literature review and modeling. The obtained results can be used for information technology applications in healthcare for various healthcare services and assist in increasing health quality in the healthcare industry.Method: Created a model to set the standard for incorporating 5G IoT devices health related technology and services. Reviewed through several models that serve as potential model to involve key factors that are unique certain healthcare services. We picked one model that can be easily incorporated in the system and can be revised to fit within the requirements using 5G IoT devices. Gathering of related literature served as a foundation in understanding the benefits of 5G IoT in the healthcare systems and parameters were pooled from it to revise the IoT model. Results: Incorporating 5G IoT features into a chosen model gave an overview of various determinants that can help understanding how IoT can influence any healthcare service and improve the quality of health. There are no rules and restrictions for use and utilization of this technology for health management yet in developing stage however, healthcare systems can rely on the 5G IoT devices for quality betterment. Conclusion: IoT with 5G has potential to improve healthcare management. The 5G world with an IoT will allow us to enter an era where real-time health services will become the part of the daily routine rather than the exception. However, further research needs to be done about its usage within any kind of specific health technology. Future research directions can utilize our model for other lesser known healthcare services

    Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

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    In this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.WOS:000604482500002Science Citation Index ExpandedQ2Article; Early AccessUluslararası işbirliği ile yapılmayan - HAYIROcak2021YÖK - 2020-2

    IoMT Supported COVID Care – Technologies and Challenges

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    The Internet of Things (IoT) has sparked substantial progress in the recent days of pandemic and achieved several milestones especially in healthcare. Wearable technologies have gained in popularity as a means of ensuring the health and safety of users in medical and disaster relief activities, facilitating the evolution of the Internet of Medical Things (IoMT). The IoMT is a phenomenon in which computer networks and medical equipment are linked over the Internet to allow physicians and patients to interact in real time. This coronavirus pandemic has demonstrated how unprepared our systems are for a disaster of this magnitude, as well as the necessity for robust, computationally intelligent, and profound meddling. This study piece looks at the many IoT-enabled smart solutions that could be used to respond to various aspects of this rising epidemic, from diagnosis to treatment to prevention. The paper provides a retrospective survey and identifies several obstacles and obstructions to IoT integration as an attempt to deal with coronavirus pandemic. The work concludes with a discussion of challenges and future scope to the difficulties mentioned in the bench marked works

    Harnessing IoT Data and Knowledge in Smart Manufacturing

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    In the modern digitalized era, the use of electronic devices is a necessity in daily life, with most end users requiring high product quality of these devices. During the electronics manufacturing process, environmental control, for monitoring ambient temperature and relative humidity, is one of the critical elements affecting product quality. However, the manufacturing process is complicated and involves numerous sections, such as processing workshops and storage facilities. Each section has its own specific requirements for environmental conditions, which are checked regularly and manually, such that the whole environmental control process becomes time-consuming and inefficient. In addition, the reporting mechanism when conditions are out of specification is done manually at regular intervals, resulting in a certain likelihood of serious quality deviation. There is a substantial need for improving knowledge management under smart manufacturing for full integration of Internet of Things (IoT) data and manufacturing knowledge. In this chapter, an Internet-of-Things Quality Prediction System (IQPS), which is a mission critical system in electronics manufacturing, is proposed in adopting the advanced IoT technologies to develop a real-time environmental monitoring scheme in electronics manufacturing. By deploying IQPS, the total intelligent environmental monitoring is achieved, while product quality is predicted in a systematic manner

    A comparison of processing techniques for producing prototype injection moulding inserts.

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    This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed
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