Systems, methods, and media for optimizing maintenance of facility units

One or more non-transitory computer-readable storage medium having instructions stored thereon that, when executed by processing circuitry, cause the processing circuitry to:

• subsequent to a unit in a facility being vacated by a resident, receive an input from a first user via a first computing device, the input detailing a condition of the unit in the facility;
• generate a current grade for the unit in the facility based on the input detailing the condition of the unit in the facility;
• identify a target grade and a target time-to-occupancy for the unit in the facility;
• determine, using one or more predictive ML models, a maintenance task for completion to modify the unit in the facility such that the unit in the facility can be associated with the target grade instead of the current grade, based on the one or more predictive ML models generating an output in response to receiving an input that includes the maintenance task, the output including a predicted time-to-occupancy resulting from the completion of the maintenance task or one or more predicted likelihoods that the completion of the maintenance task will result in one or more target time-to-occupancies,
• wherein the one or more predictive ML models are trained using a dataset that includes outcome data including actual time-to-occupancies associated with historical maintenance tasks;
• and
• in response to the output of the one or more predictive ML models satisfying the target time-to-occupancy, provide the maintenance task to a second user via a second computing device such that the second user can complete the maintenance task to modify the unit in the facility such that the unit in the facility can be associated with the target grade instead of the current grade and can satisfy the target time-to-occupancy.

A system for predicting an occupancy schedule for a unit in a facility, comprising:

• memory comprising machine-readable instructions;
• and
• processing circuitry to execute the machine-readable instructions to:
• subsequent to the unit in the facility being vacated by a resident, receive an input from a first user via a first computing device, the input detailing a condition of the unit in the facility;
• generate a current grade for the unit in the facility based on the input detailing the condition of the unit in the facility;
• identify a target grade and a target time-to-occupancy for the unit in the facility;
• determine, using one or more predictive machine learning (ML) models, a maintenance task for completion to modify the unit in the facility such that the unit in the facility can be associated with the target grade instead of the current grade, based on the one or more predictive ML models generating an output in response to receiving an input that includes the maintenance task, the output including a predicted time-to-occupancy resulting from the completion of the maintenance task or one or more predicted likelihoods that the completion of the maintenance task will result in one or more target time-to-occupancies,
• wherein the one or more predictive ML models are trained using a dataset that includes outcome data including actual time-to-occupancies associated with historical maintenance tasks;
• and
• in response to the output of the one or more predictive ML models satisfying the target time-to-occupancy, provide the maintenance task to a second user via a second computing device such that the second user can complete the maintenance task to modify the unit in the facility such that the unit in the facility can be associated with the target grade instead of the current grade and can satisfy the target time-to-occupancy.