An automated healthcare intervention system includes biometric and activity sensors in a residential area. A server stores base data for an associated healthcare subject in a data storage network, and leverages the base data to infer temporal relationships with respect to potential conditions for the subject. The server determines that an event requiring intervention has occurred by comparing combinations of base data and inferred temporal relationships with associated time ranges and threshold values, and delivers an intervention prompt to an associated healthcare provider. Post-event monitoring allows for predictive analysis with respect to future occurrences of a similar event, and further enables determination of a severity of the event, for example a fall. Defined sleeping areas or food storage areas may be monitored over time and with respect to defined patterns and healthcare conditions of the subject to identify sleeping or eating disorders.