Ideas & Insights

Digital Twin: Big Data’s brainy child

Big Data and Digital Twin Technology are transforming industries through the convergence of real and virtual worlds, predictive analytics, and the limitless possibilities of Industry 4.0.

Data has emerged  as a key element in every technological innovation, powering the rapid advancement of technologies such as the Internet of Things (IoT), Web 2.0 and artificial intelligence (AI). Gathered from various sources, including social, machine, and transactional. This vast spectrum of data is known as Big Data. 

Enter Digital Twin 

One of the innovative offshoots of Big Data is the concept of Digital Twin. Simply put, it is a virtual replica of a physical asset, system, or process that uses sensors to generate data on performance and usability. 

 

Through Digital Twin Technology, enterprises can describe, diagnose, predict, and prescribe their assets’ behavior. Its success relies heavily on the voluminous data underlying it, including from past records, real-time tracking, and predictive analytics. 


Digital Twins are actively used in various sectors to predict product performance, customer modelling, supply chain optimization, and design and development processes. IoT and artificial intelligence remain the driving forces behind Digital Twin’s advancement. 

Blurring The Lines 

In the automotive sector in particular, this concept has emerged as a champion of the mobility race. Digital Twin Technology is being used for product testing, manufacturing, predictive maintenance, and sales, among other applications. It enables data unification, increased visibility between consumers and service providers, reduced downtime and failures, and predictive maintenance. 

 

Companies and researchers are continuously exploring new usage scenarios to leverage the power of Digital Twins, with predictive health monitoring being a primary application in high demand. To obtain analytical insights, this uses data from various vehicle systems, such as the engine, battery, alternator, air intake, fuel tank, gearbox, and ECU. 

 

Significant breakthroughs have been made in predictive maintenance and driver behavior monitoring, enabling features such as breakdown prevention, safety incident prediction, fuel pilferage detection, and identification of bad driving behavior and improper gear utilization. 

 

Big Data and Digital Twins are slowly closing the gap between the real and virtual worlds. As supporting pillars of the Industrial Revolution 4.0, they are bound to see rapid growth in the near future.

Mudassirkhan Pathan is Intangles’ Head of Engineering.

Picture of Mudassirkhan Pathan

Mudassirkhan Pathan

Head of Engineering, Intangles

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