Developing a blockchain-based digitally secured model for the educational sector in Saudi Arabia toward digital transformation

Enabling blockchain for Saudi Arabia drug supply chain using Internet of Things (IoT)

The availability of drugs across the country is a direct measure for fairer public health. Several issues have been reported drastically related to various organizations that fail to provide quality medicines on time. There has been a consistent increase in cases where the treatment, as well as exempted drugs, were supplied due to the unavailability of proper traceability of the supply chain. Several parties are involved in the supply and have similar interests that may defer the adequate shareability of the drugs. The existing system for managing the drug supply chain suffers from several backlogs. The loss of information, unavailability of resources to track the proper medicinal storage, transparency of information sharing between various stakeholders and sequential access. The applicability of the decentralized model emerging from the blockchain can apply to one of the perfect solutions in this case. The drug traceability chain can be deployed to a Ledger-based blockchain that may result in decentralized information. Continuous supply from the Internet of Things (IoT) based devices might be handy as the middleware for providing a trustworthy, safe, and proper transaction-oriented system. The data integrity, along with the provenance resulting from the IoT-connected devices, is an effective solution towards managing the supply chain and drug traceability. This study presents a model that can provide a token-based blockchain that will help provide a cost-efficient and secure system for a reliable drug supply chain.

A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain

Recently, the use of the Internet of Medical Things (IoMT) has gained popularity across various sections of the health sector. The historical security risks of IoMT devices themselves and the data flowing from them are major concerns. Deploying many devices, sensors, services, and networks that connect the IoMT systems is gaining popularity. This study focuses on identifying the use of blockchain in innovative healthcare units empowered by federated learning. A collective use of blockchain with intrusion detection management (IDM) is beneficial to detect and prevent malicious activity across the storage nodes. Data accumulated at a centralized storage node is analyzed with the help of machine learning algorithms to diagnose disease and allow appropriate medication to be prescribed by a medical healthcare professional. The model proposed in this study focuses on the effective use of such models for healthcare monitoring. The amalgamation of federated learning and the proposed model makes it possible to reach 93.89 percent accuracy for disease analysis and addiction. Further, intrusion detection ensures a success rate of 97.13 percent in this study.

COVID-19 advising application development for Apple devices (iOS)

One of humanity's most devastating health crises was COVID-19. Billions of people suffered during this pandemic. In comparison with previous global pandemics that have been faced by the world before, societies were more accurate with the technical support system during this natural disaster. The intersection of data from healthcare units and the analysis of this data into various sophisticated systems were critical factors. Different healthcare units have taken special consideration to advance technical inputs to fight against such situations. The field of natural language processing (NLP) has dramatically supported this. Despite the primitive methods for monitoring the bio-metric factors of a person, the use of cognitive science has emerged as one of the most critical features during this pandemic era. One of the essential features is the potential to understand the data based on various texts and user inputs. The deployment of various NLP systems is one of the most challenging factors in handling the bulk amount of data flowing from multiple sources. This study focused on developing a powerful application to advise patients suffering from ailments related to COVID-19. The use of NLP refers to facilitating a user to identify the present critical situation and make necessary decisions while getting infected. This article also summarises the challenges associated with NLP and its usage for future NLP-based applications focusing on healthcare units. There are a couple of applications that reside for android-based systems as well as web-based chat-bot systems. In terms of security and safety, application development for iOS is more advanced. This study also explains the block meant of an application for advising COVID-19 infection. A natural language processing powered application for an iOS operating system is indeed one of its kind, which will help people who need to advise proper guidance. The article also portrays NLP-based application development for healthcare problems associated with personal reporting systems.