Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3
Design of Deep Learning Algorithm for IoT Application by Image based Recognition
Volume-3 | Issue-3
Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3
Health Record Management System – A Web-based Application
Volume-3 | Issue-4
A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3
IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2
Secure Data Sharing Platform for Portable Social Networks with Power Saving Operation
Volume-3 | Issue-3
Review of Internet of Wearable Things and Healthcare based Computational Devices
Volume-3 | Issue-3
Stock Index Prediction with Financial News Sentiments and Technical Indicators
Volume-4 | Issue-3
Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs
Volume-3 | Issue-3
Suspicious Human Activity Detection System
Volume-2 | Issue-4
ROBOT ASSISTED SENSING, CONTROL AND MANUFACTURE IN AUTOMOBILE INDUSTRY
Volume-1 | Issue-3
EFFICIENT RESOURCE ALLOCATION AND QOS ENHANCEMENTS OF IOT WITH FOG NETWORK
Volume-1 | Issue-2
Live Streaming Architectures for Video Data - A Review
Volume-2 | Issue-4
IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2
Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3
A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3
IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS
Volume-2 | Issue-1
Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3
Hybrid Intrusion Detection System for Internet of Things (IoT)
Volume-2 | Issue-4
Volume - 4 | Issue - 2 | june 2022
Published
15 July, 2022
Sensory data is used in industrial processes for making decisions, evaluating performance, and measuring risks. To extract useful insights from the data acquired, as well as a system that can guarantee the transmission of reliable data, are needed. To be reliable, physical data must be model-free using numerous overlapping field-of-view sensor origin. Events that occur during the product lifetime supplied for the motive of process monitoring, recognition, and optimum control when dependable data is put down on the blockchain. Given this, The use of digital twins (DTs) to derive intuitive inferences based on the data by spotting flaws with advising preventative solutions before key events occur. We give complete evaluation results of cutting-edge research for blockchain-based DTs Throughout this study, while stressing its important benefits of employing DTs built on blockchain. We propose trustworthy DTs built on blockchain architecture according to recent studies. In DTs built on blockchain, awe emphasise its importance relating to artificial intelligence (AI). We also go about existing and future blockchain-based DT research and implementation difficulties that need to be looked into further.
KeywordsInternet of things blockchain digital twins artificial intelligence
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