Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Singh, Rajani; Dwivedi, Ashutosh Dhar; Srivastava, Gautam

doi:10.3390/s20143951

Cited by 138 publications

(69 citation statements)

References 36 publications

(35 reference statements)

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“…On the other hand, blockchain technology is applied in the drug supply chain management, supply chain involves a certain degree of stakeholders, and one of the biggest challenges associated with the supply chain is temperature monitoring and preventing fake drugs. Singh et al [ 23 ] proposed a blockchain framework based on IoT sensors to track the movement of drugs in the supply chain. The safety of the pharmaceutical supply chain has become a major public health concern, and this is a collective process [ 24 ].…”

Section: Theme Clustering Analysismentioning

confidence: 99%

Literature Review on the Applications of Machine Learning and Blockchain Technology in Smart Healthcare Industry: A Bibliometric Analysis

Shan

Beiwei

et al. 2021

Journal of Healthcare Engineering

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The emergence of machine learning (ML) and blockchain (BC) technology has greatly enriched the functions and services of healthcare, giving birth to the new field of “smart healthcare.” This study aims to review the application of ML and BC technology in the smart medical industry by Web of Science (WOS) using bibliometric visualization. Through our research, we identify the countries with the greatest output, the major research subjects, funding funds, and the research hotspots in this field. We also find out the key themes and future research areas in application of ML and BC technology in healthcare area. We reveal the different aspects of research under the two technologies and how they relate to each other around five themes.

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Section: Theme Clustering Analysismentioning

confidence: 99%

Literature Review on the Applications of Machine Learning and Blockchain Technology in Smart Healthcare Industry: A Bibliometric Analysis

Shan

Beiwei

et al. 2021

Journal of Healthcare Engineering

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“…We assume that, at any stage, the number of states of the system is finite and that these states are perfectly described by the corresponding variables (often multidimensional) [ 17 ]. However, in general, supply forecasting in hospital pharmacies [ 18 ] is done for a short period, so it is better to consider SP models in two stages rather than multiple.…”

Section: Symbology Introduction Bibliographical Review and Objectivesmentioning

confidence: 99%

Lot-Size Models with Uncertain Demand Considering Its Skewness/Kurtosis and Stochastic Programming Applied to Hospital Pharmacy with Sensor-Related COVID-19 Data

Rojas

Leiva

Huerta

et al. 2021

Sensors

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Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. Under this pandemic, the demand for pharmaceutical products has changed significantly. Some of these products are in high demand, while, for others, their demand falls sharply. These changes in the random demand patterns are connected with changes in the skewness (asymmetry) and kurtosis of their data distribution. Such changes are critical to determining optimal lots and inventory costs. The lot-size model helps to make decisions based on probabilistic demand when calculating the optimal costs of supply using two-stage stochastic programming. The objective of this study is to evaluate how the skewness and kurtosis of the distribution of demand data, collected through sensors, affect the modeling of inventories of hospital pharmacy products helpful to treat COVID-19. The use of stochastic programming allows us to obtain results under demand uncertainty that are closer to reality. We carry out a simulation study to evaluate the performance of our methodology under different demand scenarios with diverse degrees of skewness and kurtosis. A case study in the field of hospital pharmacy with sensor-related COVID-19 data is also provided. An algorithm that permits us to use sensors when submitting requests for supplying pharmaceutical products in the hospital treatment of COVID-19 is designed. We show that the coefficients of skewness and kurtosis impact the total costs of inventory that involve order, purchase, holding, and shortage. We conclude that the asymmetry and kurtosis of the demand statistical distribution do not seem to affect the first-stage lot-size decisions. However, demand patterns with high positive skewness are related to significant increases in expected inventories on hand and shortage, increasing the costs of second-stage decisions. Thus, demand distributions that are highly asymmetrical to the right and leptokurtic favor high total costs in probabilistic lot-size systems.

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“…Singh et al/2020 [43] IoT Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention. Sekaran et al/2020 [44] 6G/IoT Automation.…”

Section: Iovt Archetypementioning

confidence: 99%

“…The impact of IoT will affect how mRNA vaccine supply chain leaders access information needed to improve the service. The IoT revolution can improve supply chain management by smart connectivity [43].…”

mentioning

confidence: 99%

Quantum Biotech and Internet of Virus Things: Towards a Theoretical Framework

Padhi

Charrua-Santos

2021

ASI

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Quantumization, the process of converting information into quantum (qubit) format, is a key enabler for propelling a new and distinct infrastructure in the pharmaceutical space. Quantum messenger RNA (QmRNA) technology, an indispensable constituent of quantum biotech (QB), is a compelling alternative to conventional vaccine methods because of its capacity for rapid development, high efficacy, and low-cost manufacturing to combat infectious diseases. Internet of Virus Things (IoVT), a biological version of Internet of Things (IoT), comprises applications to fight against pandemics and provides effective vaccine administration. The integration of QB and IoVT constitutes the QBIoVT system to advance the prospect of QmRNA vaccine discovery within a few days. This research disseminates the QBIoVT system paradigm, including architectural aspects, priority areas, challenges, applications, and QmRNA research engine design to accelerate QmRNA vaccines discovery. A comprehensive review of the literature was accomplished, and a context-centered methodology was applied to the QBIoVT paradigm forensic investigations to impel QmRNA vaccine discovery. Based on the above rumination, the principal motive for this study was to develop a novel QBIoVT theoretical framework which has not been produced through earlier theories. The proposed framework shall inspire future QBIoVT system research activities to improve pandemics detection and protection.

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Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Cited by 138 publications

References 36 publications

Literature Review on the Applications of Machine Learning and Blockchain Technology in Smart Healthcare Industry: A Bibliometric Analysis

Literature Review on the Applications of Machine Learning and Blockchain Technology in Smart Healthcare Industry: A Bibliometric Analysis

Lot-Size Models with Uncertain Demand Considering Its Skewness/Kurtosis and Stochastic Programming Applied to Hospital Pharmacy with Sensor-Related COVID-19 Data

Quantum Biotech and Internet of Virus Things: Towards a Theoretical Framework

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