Our project aims to deploy and evaluate a new approach using a Remote Patient Telemonitoring (RPM) and artificial intelligence (AI) solutions at the Lakeshore General Hospital (HGL). It will be based on the integration of coaching and self-management strategies using machine learning and algorithms, to predict and prevent emergency room visits and admissions to the hospital. The primary endpoints will be the occurrence of exacerbation of the condition and the number of emergency room visits or hospitalizations for exacerbation of COPD within 15 months of study enrollment (12 months of monitoring using the proposed solution and three monitoring after disconnection to check the number of occurrence of exacerbations if there were any). Secondary measures will include satisfaction of patients and health care providers with services, health-related quality of life, COPD-related symptoms, social support, level of anxiety and depression. The direct and indirect costs of services will be collected to analyze the financial viability of this solution in relation to regular health services with an average goal of 55% in reducing current costs for emergency department visits and combined hospitalizations.