Monitoring system and method of using same

A monitoring system comprising:

• a first sensor adapted to detect a first characteristic of a subject and generate data representative of the first characteristic of the subject, wherein the first characteristic comprises a first physiological characteristic of the subject
• a second sensor adapted to detect a second characteristic of the subject and generate data representative of the second characteristic of the subject;
• a controller operatively connected to the first and second sensors, wherein the controller is adapted to:
• receive data representative of the first characteristic of the subject from the first sensor;
• determine statistics for a first condition substate of the subject over a monitoring time period based upon the data received from the first sensor;
• receive data representative of the second characteristic of the subject from the second sensor;
• determine statistics for a second condition substate of the subject over the monitoring time period based upon the data received from the second sensor;
• compare the statistics of the first condition substate to the statistics of the second condition substate;
• confirm the first condition substate of the subject when the first condition substate is substantially similar to the second condition substate;
• and
• determine the statistics of an overall condition state of the subject over the monitoring time period based upon the confirmed first condition substate;
• and
• utilize a machine learning model to determine a fall risk value based upon the determined overall condition state of the subject;
• generate a fall prevention output when the fall risk value crosses a fall risk threshold, the fall prevention output comprising modifying, via mesh networks or the internet of things, the lighting within an area proximate to the subject;
• wherein the machine learning model is further configured to predict a time at which the subject will ingest a particular medication based on location information, and to learn the effects that the particular medication has on the subject based on changes in the data representative of the first characteristic or data representative of the second characteristic in a time period after the time at which the subject is predicted to ingest the particular medication.