Computer Vision Based PPI Tool Version 2.0

The Poverty Probability Index (PPI) is a poverty measurement tool for organizations and businesses with a mission to serve the poor. A PPI survey consists of 10 questions about a household’s characteristics using which asset ownership is scored to compute the likelihood that the household is living below the poverty line.

Leveraging Cloud Vision, a field officer would simply have to take a series of photos with their smartphone camera inside and outside of the house and then the Cloud Vision would be able to deduce based on the images the response to the 10 questions by detecting whether the objects mentioned in the survey are present in the household or not.

This year the project aims to do the following:

• Increase the accuracy of the models for object detection
• Train more models using the Google Cloud Vision platform to recognize more objects
• Improve the current augmentation procedure to include more techniques and hence build a better dataset
• Integrate the AutoML API with the android client
• Implement auto-filling of the survey based on the results received from the AutoML API when it detects objects in the images uploaded
• Enhance the UI/UX of the android client