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US-based start-up started by NRI uses AI to track food wastage; reduce Global Hunger Index

AgShift is currently working with a select group of food industry leaders to bring this innovative solution to market

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In 2017, India ranked 100th out of 119 countries on the global hunger index — behind North Korea, Bangladesh and Iraq but ahead of Pakistan.

The country’s serious hunger level is driven by high child malnutrition and underlines need for stronger commitment to the social sector, the International Food Policy Research Institute (IFPRI) said in its report.

“India’s high ranking on the Global Hunger Index (GHI) again this year brings to the fore the disturbing reality of the country’s stubbornly high proportions of malnourished children,” the statement said.

There have been several individuals across the nation working to battle the issue, including those who ensure that food isn't wasted by collecting unconsumed food from wedding halls and restaurants.

Now, a US-based start-up is building the world’s first autonomous food inspection system leveraging Deep Learning and Computer Vision, to reduce global food waste. The company recently announced US$2 million in seed funding to strengthen product development and expand customer reach. AgShift is currently working with a select group of food industry leaders to bring this innovative solution to market.

“Current food inspection processes are paper-based and tedious, needing continuous personal training. Inconsistent subjective inspections result in a loss of $15.6 billion a year for the organisations responsible - not counting the millions of dollars in recovery costs, claim management and loss of brand reputation incurred by the companies involved”, said Miku Jha, Founder and CEO of AgShift.

How does it work?

Speaking to DNA, Jha added that the technology blends Deep Learning with Computer Vision to autonomously inspect produce and other commodities for defects. "It does quality assessments and makes judgements as per USDA specifications or organizations’ own specifications. The patented deep learning models analyze the defects in the sample images and predict the overall quality of the sample. The platform relies on curated, extensive real-world image data sets to teach our software to analyze defects with high consistency and accuracy – every time.  The solution augments manual inspections – providing objective, consistent and standardised quality interpretation across the supply chain – every single time," she added.

Jha aims to introduce AgShift to India, given its global ranking index. "We are taking a step-by-step process to tackle the food wastage in India. First we want to understand the dynamics of how food inspections impact food wastage in India since these dynamics are potentially different from US. Next, we want to analyze the commodities which can benefit the most from consistent quality assessment across the food value chain in India. We will first optimise our solutions for these selected commodities," she added.

On asked how the compnay would work in India, Jha said, "Weare also expanding our deep-learning models to do shelf-life analysis and freshness analysis -which will empower food value chain to make optimal decisions on food with real-time insights – significantly reducing food waste."  

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