Background: In maternal and child health arena iron deficiency anaemia has been recognized as a major health issue for developing countries. This has a huge impact on maternal morbidity, childhood morbidity, and child development. There is a critical need for low cost, diagnostic capability to guide iron supplementation. There is currently a crisis in diagnosis and associated treatment guidelines, as health workers lack the tools to make immediate decisions for treatment of distressed mothers and children. Proposal: We propose development of a non-invasive device to measure body iron and also the presence of malaria non-invasively. However the World Health Organization has recently called a halt to iron supplementation in malaria endemic regions, but this stalemate will be unacceptable in the long term. Methodology: The above mentioned goals will be accomplished by a measurement of the paramagnetic properties of iron in the liver as well as in Plasmodium hemazoin. While operating, the device is simply held near the liver for a body iron measurement. It can be held near the extremities for a malaria screening. No blood or body part touching is needed for the functioning of the instrument. Results: The initial screening validates the non-invasive magnetometer model has 99% Naive Bayes accuracy and above 95% SVM accuracy in identifying iron deficiency anaemia using liver as the medium. Conclusion: If AI machine learning techniques are used to support this non-invasive approach to iron detection, it will show to be effective, economical and time-efficient. Before being put into practice, the experiments must be validated on a bigger scale.