Paper detail

COVID-19 Blockchain Framework: Innovative Approach

The world is currently witnessing dangerous shifts in the epidemic of emerging SARS-CoV-2, the causative agent of (COVID-19) coronavirus. The infection, and death numbers reported by World Health Organization (WHO) about this epidemic forecasts an increasing threats to the lives of people and the economics of countries. The greatest challenge that most governments are currently suffering from is the lack of a precise mechanism to detect unknown infected cases and predict the infection risk of COVID-19 virus. In response to mitigate this challenge, this study proposes a novel innovative approach for mitigating big challenges of (COVID-19) coronavirus propagation and contagion. This study propose a blockchain-based framework which investigate the possibility of utilizing peer-to peer, time stamping, and decentralized storage advantages of blockchain to build a new system for verifying and detecting the unknown infected cases of COVID-19 virus. Moreover, the proposed framework will enable the citizens to predict the infection risk of COVID-19 virus within conglomerates of people or within public places through a novel design of P2P-Mobile Application. The proposed approach is forecasted to produce an effective system able to support governments, health authorities, and citizens to take critical decision regarding the infection detection, infection prediction, and infection avoidance. The framework is currently being developed and implemented as a new system consists of four components, Infection Verifier Subsystem, Blockchain platform, P2P-Mobile Application, and Mass-Surveillance System. This four components work together for detecting the unknown infected cases and predicting and estimating the infection Risk of Corona Virus (COVID-19).

preprint2020arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.