Using trained machine-learning model of an online system to predict timing of state change of variable state item

A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising:

• receiving, via a network from a device associated with a user of an online system, a signal that triggers a process of servicing an order;
• identifying an item from the order having a state that is varying over time;
• accessing a state change prediction machine-learning model of the online system, wherein the state change prediction machine-learning model is trained to predict a timing when a state of the item changes from an original state at a location of a source associated with the online system to a different state;
• applying the state change prediction machine-learning model to information about an ambient condition when servicing the order and information about the item to generate the timing when the state of the item changes from the original state to the different state;
• generating, based at least in part on the timing, a control signal that initiates at least one of a first action associated with the order or a second action associated with the item;
• and
• performing, using the control signal, at least one of the first action associated with the order or the second action associated with the item.

A computer system comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium having instructions that, when executed by the processor, cause the computer system to perform steps comprising:
• receiving, via a network from a device associated with a user of an online system, a signal that triggers a process of servicing an order;
• identifying an item from the order having a state that is varying over time;
• accessing a state change prediction machine-learning model of the online system, wherein the state change prediction machine-learning model is trained to predict a timing when a state of the item changes from an original state at a location of a source associated with the online system to a different state;
• applying the state change prediction machine-learning model to information about an ambient condition when servicing the order and information about the item to generate the timing when the state of the item changes from the original state to the different state;
• generating, based at least in part on the timing, a control signal that initiates at least one of a first action associated with the order or a second action associated with the item;
• and
• performing, using the control signal, at least one of the first action associated with the order or the second action associated with the item.