Determination and alleviation of root causes for emission of pollutants from vehicles

1 . A computer-implemented method, comprising:

receiving, by a computer, emission data associated with emission of a set of pollutants by a vehicle, wherein the emission data is received from at least one of the vehicle or a set of data sources;

applying, by the computer, a machine learning (ML) model to the emission data;

determining, by the computer, a set of root causes based on the application of the ML model to the emission data, the set of root causes is associated with the emission of the set of pollutants by the vehicle; and

controlling, by the computer, a set of robots to execute a set of actions within the vehicle to alleviate the set of root causes associated with the emission of the set of pollutants.

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

determining, by the computer, location data indicative of a location of the vehicle;

obtaining, by the computer, weather data associated with the location of the vehicle based on the location data; and

determining, by the computer, the set of root causes associated with the emission of the set of pollutants by the vehicle based on the application of the ML model to the weather data.

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

determining, by the computer, the set of robots is capable of executing the set of actions to alleviate the set of root causes;

generating, by the computer, a set of instructions to control the set of robots to execute the set of actions, wherein the set of instructions is generated based on the determination that the set of robots is capable of executing the set of actions;

transmitting, by the computer, the set of instructions to the set of robots; and

controlling, by the computer, the set of robots based on the transmission of the set of instructions, wherein the set of robots is controlled to execute the set of actions within the vehicle.

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

determining, by the computer, the set of robots is incapable of executing the set of actions to alleviate the set of root causes;

generating, by the computer, a set of recommendations to alleviate the set of root causes for the emission of the set of pollutants by the vehicle, wherein the set of recommendations is generated based on the determination that the set of robots is incapable of executing the set of actions; and

rendering, by the computer, the set of recommendations on at least one of a user device or an infotainment unit associated with the vehicle.

5 . The computer-implemented method of claim 1 , wherein the set of root causes is associated with a malfunction of a set of components associated with the vehicle, and wherein the set of components comprises at least one a catalytic converter associated with the vehicle, an exhaust system associated with the vehicle, a fuel injector associated with the vehicle, a Heating, Ventilation, and Air Conditioning (HVAC) system associated with the vehicle, one or more intake valves associated with the vehicle, an ignition system associated with the vehicle, one or more piston rings associated with the vehicle, or one or more cylinder walls associated with the vehicle.

6 . The computer-implemented method of claim 5 , wherein the set of root causes comprises at least one of a clogging of the catalytic converter, a leakage in the exhaust system, a leakage in the fuel injector, a failure of the HVAC system, a deposition of carbon on the one or more intake valves, a failure of the ignition system, a damage in the one or more piston rings, or a damage in the one or more cylinder walls.

7 . The computer-implemented method of claim 1 , wherein the set of actions comprises at least one of a milling operation on a set of components associated with the vehicle, a fabrication operation of the set of components associated with the vehicle, a spraying operation on the set of components associated with the vehicle, or a repair of the set of components associated with the vehicle.

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

controlling, by the computer, the set of robots to capture one or more images of a first component of a set of components associated with the vehicle, wherein the first component is associated with a first root cause of the set of root causes;

determining, by the computer, an area of interest within the first component based on the one or more images; and

controlling, by the computer, a first robot of the set of robots to execute a first action of the set of actions within the area of interest to alleviate the first root cause of the set of root causes.

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

determining, by the computer, an emission value indicative of the emission of at least a first pollutant of the set of pollutants based on the application of the ML model to the emission data; and

determining, by the computer, the set of root causes for the emission of the set of pollutants by the vehicle, wherein the set of root causes is determined based on a determination that the emission value is greater than a threshold emission value.

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

determining, by the computer, an emission value indicative of the emission of at least a first pollutant of the set of pollutants, wherein the determination of the emission value is based on the application of the ML model to the emission data;

generating, by the computer, an emission certificate based on a determination that the emission value is less than a threshold emission value; and

rendering, by the computer, the emission certificate on at least one of a user device, an infotainment unit associated with the vehicle, or an electronic device associated with regulatory authorities.

11 . The computer-implemented method of claim 10 , further comprising:

applying, by the computer, a language model to the emission data and vehicle data associated with the vehicle; and

generating, by the computer, the emission certificate based on the application of the language model to the emission data and the vehicle data.

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

obtaining, by the computer, historical emission data associated with the emission of the set of pollutants by a set of vehicles;

obtaining, by the computer, a historical set of root causes for the emission of the set of pollutants by the set of vehicles;

generating, by the computer, a training dataset based on the historical emission data and historical set of root causes; and

training, by the computer, the ML model based on the training dataset.

13 . The computer-implemented method of claim 1 , wherein the set of robots comprises at least one parent robot and at least one child robot, the at least one child robot is associated with the at least one parent robot, and wherein at least one robot of the set of robots is docked in an engine of the vehicle.

14 . A system, comprising:

a processor set configured to:

receive emission data associated with emission of a set of pollutants by a vehicle, wherein the emission data is received from at least one of the vehicle or a set of data sources;

apply a machine learning (ML) model to the emission data;

determine an emission value indicative of the emission of at least a first pollutant of the set of pollutants, wherein the determination of the emission value is based on the application of the ML model to the emission data;

determine a set of root causes based on a determination that the emission value is greater than a threshold emission value, the set of root causes is associated with the emission of the set of pollutants by the vehicle; and

control a set of robots to execute a set of actions within the vehicle to alleviate the set of root causes associated with the emission of the set of pollutants.

15 . The system of claim 14 , wherein the set of root causes is associated with a malfunction of a set of components associated with the vehicle, and wherein the set of components comprises at least one a catalytic converter associated with the vehicle, an exhaust system associated with the vehicle, a fuel injector associated with the vehicle, a Heating, Ventilation, and Air Conditioning (HVAC) system associated with the vehicle, one or more intake valves associated with the vehicle, an ignition system associated with the vehicle, one or more piston rings associated with the vehicle, or one or more cylinder walls associated with the vehicle.

16 . The system of claim 15 , wherein the set of root causes comprises at least one of the catalytic converter being clogged, a leakage in the exhaust system, a leakage in the fuel injector, a failure of the HVAC system, a deposition of carbon on the one or more intake valves, a failure of the ignition system, a damage in the one or more piston rings, or a damage in the one or more cylinder walls.

17 . The system of claim 14 , wherein the set of actions comprises at least one of a milling operation on a set of components associated with the vehicle, a fabrication operation of the set of components associated with the vehicle, a spraying operation on the set of components associated with the vehicle, or a repair of the set of components associated with the vehicle.

18 . The system of claim 14 , wherein the processor set is further configured to:

determine the set of robots is able to execute the set of actions to alleviate the set of root causes;

generate a set of instructions to control the set of robots to execute the set of actions, wherein the set of instructions is generated based on the determination that the set of robots is able to execute the set of actions to alleviate the set of root causes;

transmit the set of instructions to the set of robots; and

control the set of robots based on the transmission of the set of instructions, wherein the set of robots is controlled to execute the set of actions within the vehicle.

19 . The system of claim 14 , wherein the processor set is further configured to:

determine the set of robots is unable to execute the set of actions to alleviate the set of root causes;

generate a set of recommendations to alleviate the set of root causes for the emission of the set of pollutants by the vehicle, wherein the set of recommendations is generated based on the determination that the set of robots is unable to execute the set of actions to alleviate the set of root causes; and

render the set of recommendations on at least one of a user device or an infotainment unit associated with the vehicle.

20 . A computer program product for an alleviation of a set of root causes associated with emission of a set of pollutants by a vehicle, comprising:

one or more computer-readable storage media; and

program instructions stored on the one or more computer-readable storage media to perform operations comprising:

receiving emission data associated with the emission of the set of pollutants by the vehicle, wherein the emission data is received from at least one of the vehicle or a set of data sources;

applying a machine learning (ML) model to the emission data;

determining the set of root causes based on the application of the ML model to the emission data, the set of root causes is associated with the emission of the set of pollutants by the vehicle based on the application of the ML model to the emission data; and

controlling a set of robots to execute a set of actions within the vehicle for the alleviation of the set of root causes associated with the emission of the set of pollutants.