The quick and accurate detection of malnutrition, especially with children under 5, saves lives!
The Child Growth Monitor is a fool-proof solution based on a mobile app using augmented reality in combination with AI/machine learning.
The mobile app scans children under 5 in 3D point clouds and video data from children to extract anthropometric measurements like height,
head-circumference, middle-upper-arm-circumference, body volume / body composition / weight to determine height and weight and
therefore establishes the wasting rate. This is the main indicator for detecting moderate acute malnutrition (MAM) and severe acute
malnutrition (SAM).
Measuring and following up malnourished children will be made easier, quicker, cheaper and more accurate.
Mothers and governmental frontline workers often fail to detect severe malnutrition of children. As a result, they do not help the child in the
right way.
The magnitude of a nutrition crises both in emergencies and chronic hunger situations – is often blurred. This hinders a determined response
by emergency workers as well as policy makers.
For aid agencies such as UNICEF or Welthungerhilfe, nutrition assessments will become much cheaper, quicker and more accurate.
Immediate data and response may transform the way we deal with nutrition crisis.
For state services such as the Integrated Child Development Services in India, accuracy and accountability in managing nutrition data and
responses is dramatically improved, so that no malnourished child is left behind.
We make it OpenSource 8 GNU General Public License v3.09 to let everyone participate.
https://github.com/Welthungerhilfe/ChildGrowthMonitor