Back to Search Start Over

Evolution of Industry and Blockchain Era: Monitoring Price Hike and Corruption Using BIoT for Smart Government and Industry 4.0.

Authors :
Hasan, Mohammad Kamrul
Akhtaruzzaman, Md.
Kabir, S. Rayhan
Gadekallu, Thippa Reddy
Islam, Shayla
Magalingam, Pritheega
Hassan, Rosilah
Alazab, Mamoun
Alazab, Moutaz A.
Source :
IEEE Transactions on Industrial Informatics; Dec2022, Vol. 18 Issue 12, p9153-9161, 9p
Publication Year :
2022

Abstract

The price gouging or price hike is a worldwide issue, and it is related to inflation. Because of rising prices, people in various countries cannot afford nutritious food or proper treatment. Sometimes shops, restaurants, and transportation service providers charge more than the prescribed product price from buyers. In addition, unauthorized VAT or Tax is taken on products that the government exempts. Another reason for price hikes is bribery, and it occurs in transporting and delivering goods. This article introduces a blockchain-based Internet of Things model to monitor product price hikes and corruption from the Industry 4.0 and blockchain 5.0 point of view. Industries produce and package different products. Wholesalers and retailers purchase products from industrial companies. The primary goal of this article is to propose a blockchain mechanism for monitoring price hikes and corruption where the government can monitor buying and selling between buyers and industrial companies. Here, we have established blockchain-integrated remote database model where blockchain relates to a relational database management system that uses remote database access protocol and Cloud server. This article presents the brief evolution of blockchain and industry generations. Finally, this article provides a next generation blockchain model. An intelligent government connected with Industry 4.0 monitors price hikes and corruption. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15513203
Volume :
18
Issue :
12
Database :
Complementary Index
Journal :
IEEE Transactions on Industrial Informatics
Publication Type :
Academic Journal
Accession number :
160688389
Full Text :
https://doi.org/10.1109/TII.2022.3164066