The research is focused on exploring and solving the issues that affect a Digital Twin (DTw) operating as a mimic of an active on-the-ground physical process. We present new machine learning (ML) technologies and modern strategies to meet the capability gaps identified in four DTw literature reviews. We set up simulations and tested DTw's ability to supervise local and multiple remote sites. Target domains include healthcare, fire safety, security, traffic, and a safecity.