MEDICAL TRANSPORT CONTAINER MONITORING USING MACHINE LEARNING
Systems and techniques may be used for monitoring a medical transport container. A technique may include, receiving data from a sensor, for example corresponding to a component of a medical transport container. The technique may further include generating a classification model using a machine learning technique, classifying the data using the classification model, and outputting a score from the classification model. The technique may determine whether the score has traversed a threshold value, and responsive to a determination that the score has traversed the threshold value, output an indication related to the operational status of the component of the medical transport container.
1 . A machine-readable storage medium having instructions stored thereon, which, when executed by processing circuitry, cause the processing circuitry to:
receive data from a sensor of a plurality of sensors of a medical transport container, the sensor corresponding to a component of the medical transport container;
classify the data for the component using a classification model generated using a machine learning technique;
output a score from the classification model for the data;
determine whether the score has traversed a threshold value; and
responsive to determining that the score has traversed the threshold value, output an indication related to an operational status of the component.
2 . The machine-readable medium of claim 1 , wherein the plurality of sensors include two or more of: a compressor current sensor, an accelerometer, a drive signal, an outside air temperature sensor, a fan current sensor, an internal temperature sensor, a high side refrigerant temperature sensor, a high side refrigerant pressure sensor, a low side refrigerant pressure sensor, a battery sensor, or a battery charger sensor.
3 . The machine-readable medium of claim 2 , wherein when a tilt outside an established tolerance is detected using data from the accelerometer, a compressor is disengaged.
4 . The machine-readable medium of claim 1 , wherein to determine whether the score has traversed a threshold value includes determining whether the score is within a range.
5 . The machine-readable medium of claim 1 , wherein the operational status indicates that the component is operating within an established tolerance.
6 . The machine-readable medium of claim 1 , wherein the operational status indicates that the component is operating outside an established tolerance.
7 . The machine-readable medium of claim 1 , wherein outputting the indication includes illuminating an LED of the medical transport container.
8 . The machine-readable medium of claim 1 , wherein outputting the indication includes transmitting a message to a graphical user interface.
9 . The machine-readable medium of claim 1 , wherein outputting the indication includes sending the indication to an email address or to a cloud-based server.
10 . The machine-readable medium of claim 1 , wherein outputting the indication includes sounding an audible alarm.
11 . The machine-readable medium of claim 10 , wherein the alarm sounds when an accelerometer detects a tilt outside an established tolerance.
12 . The machine-readable medium of claim 1 , wherein the operational status includes a status corresponding to a state of a battery.
13 . The machine-readable medium of claim 12 , wherein the operational status includes an information indicating that the battery has reached a level of charge capable of powering an active refrigeration system for a specified period of time.
14 . The machine-readable medium of claim 12 , wherein the operational status includes an information indicating that the battery is draining faster than a specified rate.
15 . The machine-readable medium of claim 14 , wherein the indication further includes a recommendation to recharge or replace the battery.
16 . The machine-readable medium of claim 1 , wherein the operational status includes a status of a refrigerant level.
17 . The machine-readable medium of claim 16 , wherein the indication includes a suggestion to fill refrigerant of the medical transport container at next servicing in response to the status of the refrigerant level.
18 . The machine-readable medium of claim 16 , wherein the operational status indicates a leak in a cooling system of the medical transport container.
19 . A method for monitoring a medical transport container, the method comprising:
receiving data from a sensor of a plurality of sensors of the medical transport container, the sensor corresponding to a component of the medical transport container;
classifying the data for the component using a classification model generated using a machine learning technique;
outputting a score from the classification model for the data;
determining whether the score has traversed a threshold value; and
responsive to determining that the score has traversed a threshold value, outputting an indication related to an operational status of the component.
20 . A system for monitoring a medical transport container, the system comprising:
an active refrigeration system;
a processor;
memory including instructions stored thereon which, when executed by the processor, cause the processor to:
receive data from a sensor of plurality of sensors of the medical transport container, the sensor corresponding to a component the medical transport container;
classify the data for the component using a classification model generated using a machine learning technique;
output a score from the classification model for the data;
determine whether the score has traversed a threshold value; and
responsive to determining that the score has traversed the threshold value, output an indication related to the operational status of the component.