A Decentralized Digital Voting System Based on Block chain Architecture

Voting is the backbone of democracy and the fundamental right of every citizen. BlockChain based Election is like a boon for every nation through which the election can be conducted digitally, Unlike those old (paper based) and traditional (EVM) voting systems it makes the whole process of election safe, smooth and easy. In this era of Covid-19 this Block chain enabled election is the need of the hour, People can cast votes from their own space just with the help of a mobile phone or a computer, Security would get enhanced and threats like EVM hacking, Chaos at election booth would reduce drastically just by the implementation of this advanced voting system. Personal ID's and unique keys would be provided to each and every eligible voter which can't be tampered at any cost. It has two modules to make the entire project look consolidated and unified. First module is the Election Commission who could be liable for undertaking it, appending concerned everyone competing for the voting attached under blockchain. User end will be the resident's component where every eligible voter can choose a leader according to their separate Constituent sitting and the votes would get registered on the blockchain to make it tamper protected. © 2022 IEEE.

Blockchain and machine learning for e-healthcare systems

Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient’s entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results. This book examines the application of blockchain technology and machine learning algorithms in various healthcare settings, covering the basics of the technologies and exploring how they can be used to improve clinical outcomes and improving the patient’s experience. These topics are illustrated with reference to issues around the supply chain, drug verification, reimbursement, control access and clinical trials. Case studies are given for applications in the analysis of breast cancer, hepatitis C, and COVID-19. © The Institution of Engineering and Technology 2021.

Data visualization using machine learning for efficient tracking of pandemic - COVID-19

From the first case in December 2019 to more than 2.92 million cases in just 3 months, COVID-19 became a pandemic. COVID-19 is spreading all around the world, and due to this pandemic situation, humans’ life is at risk. On one side, healthcare and sanitization workers are stretching themselves to deal with this situation at the frontline, and on the other, data scientists and machine learning (ML) experts are researching to provide data in an understandable form to the world. This chapter provides the details of different ways of processing and visualizing the huge amount data generated on this pandemic. This includes the clusters on the basis of symptoms in different age groups, effects of COVID-19 on different countries, etc. © The Institution of Engineering and Technology 2021.