Utilizing a machine learning model to identify activities and deviations from the activities by an individual

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, to:
• receive historical information associated with an individual to be monitored,
• wherein the historical information includes at least one of:
• information associated with a health history of the individual,
• information associated with health histories of other individuals,
• information associated with activities of the individual, or
• information associated with activities of the other individuals;
• receive monitored information associated with the individual from one or more client devices associated with the individual;
• pre-process the monitored information to generate pre-processed monitored information that is understood by a trained machine learning model;
• process the pre-processed monitored information, with the trained machine learning model, to identify one or more activities of the individual and one or more deviations from the one or more activities by the individual;
• and
• perform one or more actions based on the one or more activities of the individual and/or the one or more deviations from the one or more activities by the individual.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to:
• provide an application for monitoring an individual to a client device associated with a caregiver of the individual;
• receive a machine learning model that has been trained based on configuration information and historical information,
• wherein the configuration information is associated with configuring the application and includes at least one of:
• information identifying physical characteristics of the individual,
• information identifying medications taken by the individual,
• personal information of the individual, or
• information associated with the caregiver of the individual;
• wherein the historical information includes at least one of:
• information associated with a health history of the individual,
• information associated with health histories of other individuals,
• information associated with activities of the individual, or
• information associated with activities of the other individuals;
• provide third-party application programming interfaces (APIs) to one or more client devices associated with the individual;
• receive, via the application and the third-party APIs, monitored information associated with the individual from the client device associated with the caregiver and/or the one or more client devices associated with the individual;
• process the monitored information, with the machine learning model, to identify one or more activities of the individual and one or more deviations from the one or more activities by the individual;
• and
• perform one or more actions based on the one or more activities of the individual and/or the one or more deviations from the one or more activities by the individual.