Internet of Things-enabled technologies help to collect data and make it understandable, especially in supply chain processes, thus minimizing the problems that may arise in supply chains. It is extremely important to support this process with Internet of Things-enabled technologies, especially in supply chains that are vulnerable to disruptions such as the dairy supply chain. Moreover, dairy supply chains are the type of supply chains where the most waste is generated; evaluating this waste is very beneficial to the circular economy. Therefore, monitoring data in dairy supply chains and using Internet of Things-enabled technologies prevent losses; it is critical to have Internet of Things-enabled circular dairy supply chains in operation. The aim of this study is to determine the success factors of Internet of Things-enabled circular dairy supply chains based on the various stages of these chains; we hope to match each dairy supply chain stage with a success factor of Internet of Things-enabled technology and determine a ranking for these factors. Hence, six success factors of Internet of Things-enabled circular supply chains are weighted for each stage of the chain; Internet of Things-enabled digital technologies are then matched with each stage of the chain, and the success factor is determined. The ranking of factors can then be drawn up through the integration of Step Wise Weight Assessment Ratio Analysis (SWARA) and Technique for Order Preference Similar to Ideal Solution (TOPSIS). The outcome of this study will provide managers and policy makers with insights into Internet of Things-enabled circular dairy supply chains.
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http://dx.doi.org/10.1007/s11356-021-17697-8 | DOI Listing |
Digit Health
September 2024
UCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia.
Objective: Health self-monitoring technologies are gaining popularity worldwide, but they face low adoption rates in emerging countries. There is a deficiency in studies that have applied the value-belief-norm (VBN) model to understand the adoption of IoT-enabled wearable healthcare devices (WHDs). This study investigates the adoption of IoT-enabled WHDs among older adults in China, using the VBN model as a theoretical framework.
View Article and Find Full Text PDFSensors (Basel)
August 2024
College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates.
Machine learning (ML) represents one of the main pillars of the current digital era, specifically in modern real-world applications. The Internet of Things (IoT) technology is foundational in developing advanced intelligent systems. The convergence of ML and IoT drives significant advancements across various domains, such as making IoT-based security systems smarter and more efficient.
View Article and Find Full Text PDFSensors (Basel)
July 2024
School of Info Technology, Deakin University, Burwood, VIC 3125, Australia.
Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diagnosis is a difficult one since it often calls for specialist testing, such as blood tests, bone marrow aspiration, and biopsy, all of which are highly time-consuming and expensive. It is essential to obtain an early diagnosis of ALL in order to start therapy in a timely and suitable manner.
View Article and Find Full Text PDFTransl Vis Sci Technol
May 2024
Department of Ophthalmology, Kangwon National University Hospital, Chuncheon, South Korea.
Purpose: We aimed to design, develop, and evaluate an internet of things-enabled patch (IoT patch) for real-time remote monitoring of adherence (or patch wear time) during patch treatment in child participants in clinical trials. This study provides healthcare providers with a tool for objective, real-time, and remote assessment of adherence and for making required adjustments to treatment plans.
Methods: The IoT patch had two temperature microsensors and a wireless chip.
Heliyon
May 2024
UCSI Graduate Business School, UCSI University, Malaysia. No. 1, Jalan Menara Gading, UCSI Heights (Taman Connaught), Cheras, 56000, Kuala Lumpur, Malaysia.
Self-health monitoring technologies have become increasingly popular in averting unanticipated health complications. However, the adoption rate of such technologies in developing countries is surprisingly low. Furthermore, empirical studies on the application of the value-belief-norm (VBN) model to elucidate intention to use IoT-enabled wearable fitness devices (IoT-enabled WFDs) are scarce.
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