I require to develop an machine learning algorithm to predict that if a secondary car battery should be connected to load at any given time of day based on the automobile usage profile of the user. (the output is either 1 or 0 , ON or OFF)
Some Background : My project car is equipped with a secondary battery which has to run a car Computer, LTE modem etc. So it is important that the battery is not connected to these loads all the time so as to extend the run time of the battery when the car is not in use( primary car battery charges the secondary battery when the car is running.) . These electronic parts are used for IOT operation, running alexa voice interaction etc.
So it is necessary to predict at what times user is using his car and switch the circuit ON before the driver actually gets in the car, So that it can start alexa voice interaction with user as soon as he enters the car without any delay( if it starts after user gets in , it will take some time before all the internet connections are up and running.).
Any suggestions on which existing machine learning algorithm I can use here? For the start I’m planning to predict the state based on the day, time and location only. For example if the time is 7.am, weekday, and the location is home, the car is usually ON to travel to office., if the time is 10.00am and the location is Office , the car is usually OFF.
Please help me with any ideas/ suggestions that can also improve the concept.