AI empowered context-aware smart system for medication adherence

Abstract

Purpose: Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating. Design/methodology/approach: In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user’s contextual information through a computational abstract argumentation-based activity classifier. Findings: Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices. Originality/value: This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.