MNFL: the monitoring and notification flow language for assistive monitoring

Abstract

Assistive monitoring analyzes data from sensors and cameras to detect situations of interest, and notifies appropriate persons in response. Customization of assistive technology by end-users is necessary for technology adoption and retention. We introduce MNFL, the Monitoring and Notification Flow Language, developed over the past several years to allow lay people without programming experience, but with some technical acumen, to effectively program customized monitoring and notification systems. MNFL is a graphical flow language having intuitive yet sufficiently powerful execution semantics and built-in constructs for assistive monitoring. We describe the language's semantics and built-in constructs, demonstrate the language's use for customizing several common assistive monitoring tasks, and provide results of initial usability trials showing that lay people with almost no training on MNFL can more than 50% of the time and in just a few minutes select and connect the right 1-2 blocks to complete basic applications that have 4-5 blocks total.