Maintenance management for vehicles having network IoT sensor data analysis enabled

1 . A computer-implemented method for dynamic vehicle maintenance management, the computer-implemented method comprising:

training, by a computer, a set of machine learning models to identify different driving behaviors, different subsystem maintenance patterns, and different subsystem issues based on historic data;

collecting, by the computer, data on a continuous basis from an Internet of Things (IoT) sensor system that includes engine and powertrain subsystem sensors, fuel subsystem sensors, exhaust subsystem sensors, cooling subsystem sensors, electrical subsystem sensors, ignition subsystem sensors, transmission subsystem sensors, suspension subsystem sensors, steering subsystem sensors, brake subsystem sensors, Heating, Ventilation, and Air Conditioning subsystem sensors, audio subsystem sensors, lighting subsystem sensors, safety subsystem sensors, navigation subsystem sensors, body and exterior subsystem sensors, interior subsystem sensors, and tire and wheel subsystem sensors onboard a vehicle;

analyzing, by the computer, utilizing the set of machine learning models, the data collected on the continuous basis from the IoT sensor system onboard the vehicle to detect driving behavior of a user of the vehicle as one of cautious, defensive, aggressive, and reckless based on speed, acceleration, and braking of the vehicle by the user and to detect an issue with a subsystem of the vehicle;

determining, by the computer, a customized maintenance schedule for the vehicle that takes into account the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

predicting, by the computer, utilizing the set of machine learning models, a potential subsystem failure based on the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

scheduling, by the computer, a maintenance appointment proactively with a vehicle repair shop computer to repair the issue with the subsystem of the vehicle to increase performance of the vehicle, wherein the maintenance appointment corresponds to the issue with the subsystem of the vehicle at a date, time, and location based on availability of the user of the vehicle and a selected vehicle repair shop as detected in corresponding online electronic calendars of the user and selected vehicle repair shop;

sending, by the computer, a notification regarding the maintenance appointment corresponding to the issue with the subsystem of the vehicle to the user of the vehicle via a network, the notification including at least the date, the time, and the location of the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle;

collecting, by the computer, user feedback from the user of the vehicle regarding the maintenance appointment; and

retraining, by the computer, the set of machine learning models utilizing the user feedback collected from the user of the vehicle to increase predictive accuracy of the set of machine learning models and provide proactive detection by addressing maintenance issues to prevent vehicle breakdown and accidents caused by failure of one or more vehicle subsystems.

2 . The computer-implemented method of claim 1 , further comprising:

determining, by the computer, whether the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at a destination; and

scheduling, by the computer, the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle at a nearest available vehicle repair shop prior to the vehicle arriving at the destination in response to the computer determining that the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at the destination.

3 . The computer-implemented method of claim 1 , further comprising:

receiving, by the computer, a confirmation regarding the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle from the user of the vehicle via the network.

4 . The computer-implemented method of claim 1 , further comprising:

collecting, by the computer, the data regarding performance of each subsystem from a plurality of subsystems from the IoT sensor system onboard the vehicle via the network.

5 . The computer-implemented method of claim 4 , wherein each subsystem of the plurality of subsystems corresponding to the vehicle includes a corresponding set of IoT sensors of the IoT sensor system.

6 . The computer-implemented method of claim 1 , further comprising:

receiving, by the computer, an input to establish a wireless connection with the vehicle via the network from the user of the vehicle;

establishing, by the computer, the wireless connection with the vehicle via the network in response to receiving the input;

receiving, by the computer, a registration of the vehicle for a vehicle maintenance management service provided by the computer from the user of the vehicle via the network; and

generating, by the computer, a record corresponding to the vehicle in a vehicle maintenance data structure of the vehicle maintenance management service in response to receiving the registration of the vehicle, wherein the record corresponding to the vehicle includes identifier of the user of the vehicle, identifier of the vehicle, the driving behavior of the user of the vehicle, vehicle subsystem condition to include identifier of the subsystem and condition of the subsystem, the issue with the subsystem, identifier of the selected vehicle repair shop, available times for the maintenance appointment, scheduled time for the maintenance appointment, and confirmation of the maintenance appointment.

7 . The computer-implemented method of claim 6 , further comprising:

enabling, by the computer, the user to customize settings of the vehicle maintenance management service according to user preference for the vehicle.

8 . A computer system for dynamic vehicle maintenance management, the computer system comprising:

a communication fabric;

a storage device connected to the communication fabric, wherein the storage device stores program instructions; and

a processor connected to the communication fabric, wherein the processor executes the program instructions to:

train a set of machine learning models to identify different driving behaviors, different subsystem maintenance patterns, and different subsystem issues based on historic data;

collect data on a continuous basis from an Internet of Things (IoT) sensor system that includes engine and powertrain subsystem sensors, fuel subsystem sensors, exhaust subsystem sensors, cooling subsystem sensors, electrical subsystem sensors, ignition subsystem sensors, transmission subsystem sensors, suspension subsystem sensors, steering subsystem sensors, brake subsystem sensors, Heating, Ventilation, and Air Conditioning subsystem sensors, audio subsystem sensors, lighting subsystem sensors, safety subsystem sensors, navigation subsystem sensors, body and exterior subsystem sensors, interior subsystem sensors, and tire and wheel subsystem sensors onboard a vehicle;

analyze, utilizing the set of machine learning models, the data collected on the continuous basis from the IoT sensor system onboard the vehicle to detect driving behavior of a user of the vehicle as one of cautious, defensive, aggressive, and reckless based on speed, acceleration, and braking of the vehicle by the user and to detect an issue with a subsystem of the vehicle;

determine a customized maintenance schedule for the vehicle that takes into account the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

predict, utilizing the set of machine learning models, a potential subsystem failure based on the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

schedule a maintenance appointment proactively with a vehicle repair shop computer to repair the issue with the subsystem of the vehicle to increase performance of the vehicle, wherein the maintenance appointment corresponds to the issue with the subsystem of the vehicle at a date, time, and location based on availability of the user of the vehicle and a selected vehicle repair shop as detected in corresponding online electronic calendars of the user and selected vehicle repair shop;

send a notification regarding the maintenance appointment corresponding to the issue with the subsystem of the vehicle to the user of the vehicle via a network, the notification including at least the date, the time, and the location of the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle;

collect user feedback from the user of the vehicle regarding the maintenance appointment; and

retrain the set of machine learning models utilizing the user feedback collected from the user of the vehicle to increase predictive accuracy of the set of machine learning models and provide proactive detection by addressing maintenance issues to prevent vehicle breakdown and accidents caused by failure of one or more vehicle subsystems.

9 . The computer system of claim 8 , wherein the processor further executes the program instructions to:

determine whether the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at a destination; and

schedule the maintenance appointment corresponding to the issue with the subsystem of the vehicle at a nearest available vehicle repair shop prior to the vehicle arriving at the destination in response to determining that the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at the destination.

10 . The computer system of claim 8 , wherein the processor further executes the program instructions to:

receive a confirmation regarding the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle from the user of the vehicle via the network.

11 . The computer system of claim 8 , wherein the processor further executes the program instructions to:

collect the data regarding performance of each subsystem from a plurality of subsystems from the IoT sensor system onboard the vehicle via the network.

12 . The computer system of claim 11 , wherein each subsystem of the plurality of subsystems corresponding to the vehicle includes a corresponding set of IoT sensors of the IoT sensor system.

13 . The computer system of claim 8 , wherein the processor further executes the program instructions to:

receive an input to establish a wireless connection with the vehicle via the network from the user of the vehicle;

establish the wireless connection with the vehicle via the network in response to receiving the input;

receive a registration of the vehicle for a vehicle maintenance management service provided by the computer system from the user of the vehicle via the network; and

generate a record corresponding to the vehicle in a vehicle maintenance data structure of the vehicle maintenance management service in response to receiving the registration of the vehicle, wherein the record corresponding to the vehicle includes identifier of the user of the vehicle, identifier of the vehicle, the driving behavior of the user of the vehicle, vehicle subsystem condition to include identifier of the subsystem and condition of the subsystem, the issue with the subsystem, identifier of the selected vehicle repair shop, available times for the maintenance appointment, scheduled time for the maintenance appointment, and confirmation of the maintenance appointment.

14 . A computer program product for dynamic vehicle maintenance management, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:

train a set of machine learning models to identify different driving behaviors, different subsystem maintenance patterns, and different subsystem issues based on historic data;

collect data on a continuous basis from an Internet of Things (IoT) sensor system that includes engine and powertrain subsystem sensors, fuel subsystem sensors, exhaust subsystem sensors, cooling subsystem sensors, electrical subsystem sensors, ignition subsystem sensors, transmission subsystem sensors, suspension subsystem sensors, steering subsystem sensors, brake subsystem sensors, Heating, Ventilation, and Air Conditioning subsystem sensors, audio subsystem sensors, lighting subsystem sensors, safety subsystem sensors, navigation subsystem sensors, body and exterior subsystem sensors, interior subsystem sensors, and tire and wheel subsystem sensors onboard a vehicle;

analyze, utilizing the set of machine learning models, the data collected on the continuous basis from the IoT sensor system onboard the vehicle to detect driving behavior of a user of the vehicle as one of cautious, defensive, aggressive, and reckless based on speed, acceleration, and braking of the vehicle by the user and to detect an issue with a subsystem of the vehicle;

determine a customized maintenance schedule for the vehicle that takes into account the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

predict, utilizing the set of machine learning models, a potential subsystem failure based on the driving behavior of the user of the vehicle and the issue with the subsystem of the vehicle;

schedule a maintenance appointment proactively with a vehicle repair shop computer to repair the issue with the subsystem of the vehicle to increase performance of the vehicle, wherein the maintenance appointment corresponds to the issue with the subsystem of the vehicle at a date, time, and location based on availability of the user of the vehicle and a selected vehicle repair shop as detected in corresponding online electronic calendars of the user and selected vehicle repair shop;

send a notification regarding the maintenance appointment corresponding to the issue with the subsystem of the vehicle to the user of the vehicle via a network, the notification including at least the date, the time, and the location of the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle;

collect user feedback from the user of the vehicle regarding the maintenance appointment; and

retrain the set of machine learning models utilizing the user feedback collected from the user of the vehicle to increase predictive accuracy of the set of machine learning models and provide proactive detection by addressing maintenance issues to prevent vehicle breakdown and accidents caused by failure of one or more vehicle subsystems.

15 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:

determine whether the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at a destination; and

schedule the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle at a nearest available vehicle repair shop prior to the vehicle arriving at the destination in response to the computer determining that the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle is needed prior to the vehicle arriving at the destination.

16 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:

receive a confirmation regarding the maintenance appointment corresponding to the issue detected in the subsystem of the vehicle from the user of the vehicle via the network.

17 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:

collect the data regarding performance of each subsystem from a plurality of subsystems from the IoT sensor system onboard the vehicle via the network.

18 . The computer program product of claim 17 , wherein each subsystem of the plurality of subsystems corresponding to the vehicle includes a corresponding set of IoT sensors of the IoT sensor system.

19 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:

receive an input to establish a wireless connection with the vehicle via the network from the user of the vehicle;

establish the wireless connection with the vehicle via the network in response to receiving the input;

receive a registration of the vehicle for a vehicle maintenance management service provided by the computer from the user of the vehicle via the network; and

generate a record corresponding to the vehicle in a vehicle maintenance data structure of the vehicle maintenance management service in response to receiving the registration of the vehicle, wherein the record corresponding to the vehicle includes identifier of the user of the vehicle, identifier of the vehicle, the driving behavior of the user of the vehicle, vehicle subsystem condition to include identifier of the subsystem and condition of the subsystem, the issue with the subsystem, identifier of the selected vehicle repair shop, available times for the maintenance appointment, scheduled time for the maintenance appointment, and confirmation of the maintenance appointment.

20 . The computer program product of claim 19 , wherein the program instructions further cause the computer to:

enable the user to customize settings of the vehicle maintenance management service according to user preference for the vehicle.