Here's the full ground report for @livemint based on records of ASHAs, founders, public health experts and scientists on how AI is reshaping child growth monitoring in India:

This is AI build for rural India. It works offline, on low-end phones, with local languages and minimal props. They are designed for where the gaps in public health are real and where the difference between 1.9kg and 1.8kg can be life or death.

And Shishu Mapan is just one of several AI tools making an impact:. MAAP (by @RevolutionAIze) flags child malnutrition from a single phone photo. IIIT-Hyderabad’s tool uses two images to estimate growth. @Welthungerhilfe + @Microsoft built a 3D scanner.

Why does it matter?. Because in India, 4 million+ babies are born underweight every year. In rural areas, follow-up checks are patchy. And one wrong reading can delay care. Spring scales can deviate by 183g. This app’s error margin? Just 114g.

The app, Shishu Mapan, uses computer vision to estimate a newborn’s weight, length & head circumference from a short video. It doesn't need internet, works in low light & is built for the chaos of rural homes. The app is trained on 30k+ infants by @WadhwaniAI @gatesfoundation.

In rural Daman, ASHA worker Jyotsna Patel used to weigh babies using spring balances that flickered and failed. Now, she uses her phone to record a short video and an AI app does the rest. This is how India’s AI steps into child healthcare

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