Assistive Technology for Paper Form Digitization in Resource-Limited Environments
Timothy Oates
Abstract:
In developing countries, people are now more likely to have access to a mobile phone than clean water, making cellular based technology the only viable medium for collecting, aggregating, and communicating local data so that it can be turned into useful information. While mobile phones have found broad application in reporting health, financial, and environmental data, many data collection methods still suffer from delays, inefficiency and difficulties maintaining quality. In environments with insufficient IT support and infrastructure, and among populations with limited education and experience with technology, paper forms rather than electronic methods remain the predominant means for data collection. To meet the digitization needs of paper driven data collection practices, this paper presents the development and study of a system that automatically converts unknown paper form images into text and use the SMS channel to transmit the information to a remote server for digital conversion by humans. We discuss our proposed system architecture for dealing with infrastructure constraints and human resources limitations at the local site level and present a novel framework (RLM) that decomposes the form detection task into retrieving, learning, and matching. Our goal is to significantly decrease the effort and cost of data entry, while maintaining a high level of quality.