JULY-AUGUST . 2023 | @ Halal
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19 simulation results , to make digital twins . It also helps monitor and analyse performance , predict maintenance , and make decisions to improve digital twins ’ accuracy , efficiency , and effectiveness .
FOOD FRAUD
Food fraud involves altering or misrepresenting food products for profit . Data science combats food fraud by analysing large amounts of data from many sources to find fraud patterns and outliers . These patterns and outliers include unusual ingredient combinations or inconsistent labelling .
The machine learning algorithms will be trained against these data to find patterns and outliers . For instance , data scientists search social media data for food fraud and other suspicious activities , allowing companies to spot issues early before it spreads , thus protecting the food supply .
Halal and non-halal food results from the reports from halal laboratory testing can also be used to establish a halal food database . Database from DNA , amino acids , fatty acids and their esters etc ., are abundant for this purpose . Shared database among accredited laboratories , especially enforcement laboratories , would allow the application of predictive modelling to curb food fraud .
From the result of predictive modelling , data scientists can identify risk factors contributing to the contamination and the traceability breach . Hence , the HCB and enforcement agencies could prevent food fraud from spreading .
CONCLUSION
Data science can help halal companies improve their operations , products , and customer service . Also , using data science , the halal certification bodies and enforcement agencies could effectively enhance their monitoring of the status of halal-certified products .
With all these benefits of data science , it is time that all stakeholders embrace this advanced technology to support and enhance the halal industry . –
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