Collaborative Health Care Plan through Crowdsource Data using Ambient Application

• Published in: Pattern Recognition and Image Analysis (IPRIA), International Conference on pp. 1 - 6
• Main Authors: Sarwar, Muhammad Usman, Javed, Abdul Rehman
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2019
• Subjects: Accelerometers; Activity recognition; ambient intelligence; Collaboration; crowdsourcing; healthcare; human-agent interaction; Intelligent agents; Medical services; Monitoring; multi-agent system; wellness detection; Wireless sensor networks
• ISSN: 2049-3630
• DOI: 10.1109/INMIC48123.2019.9022684

A collaborative health care plan using a multi-agent system assists adult individuals to live an independent healthy life by analyzing their routine life activities. Robust recognition of activities provides services such as health monitoring and fitness assessment. In this paper, we propose Collaborative Health Care Plan a novel system, to improve the independent living of an individual using a smartphone sensor, machine learning algorithm, multiple agents i.e. doctor, gym trainer, guardian, and intelligent ranker agent. The novelty of the devised approach is that it shares the daily life assessment of activities among care provides which in return provides a care plan or recommendation to ensure good health of the individual. We use a machine learning algorithm to recognize the adult individual's daily life physical activities. This system provides recommendations by care providers as well as suggest an optimal care plan decided by an intelligent autonomous agent using crowdsource data.