A pollution estimation system (100) for estimating pollution level caused by exhaust gas of motor vehicles is provided. The system comprises an acoustic sensor interface (110) arranged to obtain use-data from an acoustic sensor comprising an audio sample of a motor vehicle sound and a trained exhaust gas model unit (120) arranged to receive as input the audio sample of the use-data and to apply a trained exhaust gas model to the received audio sample to produce an estimated pollution level associated with the received audio sample. The trained exhaust gas model has been obtained by training an exhaust gas model on multiple training items using a machine learning algorithm, the multiple training items comprising multiple audio samples of motor vehicle sounds obtained from one or more acoustic sensors and associated pollution levels.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A pollution estimation system for estimating pollution level caused by exhaust gas of motor vehicles, the system comprising an acoustic sensor interface arranged to obtain use-data from an acoustic sensor comprising an audio sample of a motor vehicle sound, a trained exhaust gas model unit arranged to receive as input the audio sample of the use-data and to apply a trained exhaust gas model to the received audio sample to produce an estimated pollution level associated with the received audio sample, wherein the trained exhaust gas model has been obtained by training an exhaust gas model on multiple training items using a machine learning algorithm, the multiple training items comprising multiple audio samples of motor vehicle sounds obtained from one or more acoustic sensors and associated pollution levels. 2. A pollution estimation system as in claim 1, wherein the exhaust gas model comprises a classification model and at least one regression model, a list of tags being defined for the exhaust gas model, each one of the regression models being associated with a tag of the list of tags, the classification model being arranged to predict a tag from an audio sample of a motor vehicle sound, and the trained exhaust gas model unit is arranged to apply the trained classification model to the audio sample of the use-data to obtain a predicted tag from the list of tags, apply a trained regression model of the at least one regression model associated with the predicted tag to the audio sample of the use-data to produce an estimated pollution level, the multiple training items comprising multiple audio samples of motor vehicle sounds, associated pollution levels, one or more associated tags, the tags being selected from the list of tags, the exhaust gas model having been obtained by training the classification model on the multiple audio samples of motor vehicle sounds and the associated tags of the multiple training items, thus obtaining a trained classification model arranged to predict a tag from an audio sample of a motor vehicle sound, and training each particular regression model of the at least one on the audio samples of the multiple audio samples associated with the tag associated with the particular regression model, thus obtaining at least one arranged to estimate a pollution level from an audio sample of a motor vehicle sound of a particular tag. 3. A pollution estimation system as in claim 2, wherein the exhaust gas model comprises multiple regression models, at least two tags of the list of tags being associated with different regression models of the multiple regression models. 4. A pollution estimation system as in claim 2, wherein at least two tags of the list of tags indicate a fuel type of motor vehicle, said two tags distinguishing at least between motor vehicles using gasoline and diesel fuel, and/or at least two tags of the list of tags indicate a current use of a motor vehicle, said two tags distinguishing at least between motor vehicles running stationary and running non-stationary. 5. A pollution estimation system as in claim 1 wherein the exhaust gas model unit is arranged to produce multiple estimated pollution levels of at least two different pollutants. 6. A pollution estimation system as in claim 1 a sensor unit comprising an acoustic sensor arranged to obtain an audio sample of a motor vehicle sound as use-data a camera arranged to capture an image of the motor vehicle if the estimated associated pollution level is above a pollution threshold. 7. A pollution estimation system as in claim 1, comprising an outdoor luminaire, e.g., an outdoor lighting pole, wherein the outdoor luminaire comprises an acoustic sensor arranged to obtain an audio sample of a motor vehicle sound as use-data. 8. A pollution estimation system as in claim 1, comprising an audio compression unit arranged to reduce the size of the audio sample of a motor vehicle sound before transmitting the audio sample from an acoustic sensor to the trained exhaust gas model unit. 9. A pollution estimation system as in claim 1, wherein the multiple training items are obtained by continuously measuring audio during a training interval from an acoustic sensor at a roadside location, continuously measuring pollution levels during the training interval from a pollution sensor at the roadside location, obtaining multiple audio samples of motor vehicle sounds and associated pollution levels as parts of the continuously measured audio and corresponding parts of the continuously measured pollution levels. 10. A pollution estimation system as in claim 1, comprising a machine learning unit arranged to obtain from one or more acoustic sensors multiple motor sounds of multiple motor vehicles in use, and associated pollution levels of the multiple motor vehicles in use, thus obtaining multiple training items comprising multiple audio samples of motor vehicle sounds obtained from one or more acoustic sensors and associated pollution levels, and train an exhaust gas model on the multiple training items using a machine learning algorithm, thus obtaining a trained exhaust gas model. 11. A pollution estimation system as in claim 1, wherein the exhaust gas model unit is arranged to compute one or more features from the received audio sample, and to apply the trained exhaust gas model to the computed features. 12. A pollution estimation method for estimating a pollution level caused by exhaust gas of motor vehicles, the method comprising obtaining use-data from an acoustic sensor comprising an audio sample of a motor vehicle sound, applying a trained exhaust gas model to the received audio sample to produce an estimated associated pollution level, wherein the trained exhaust gas model has been obtained by training an exhaust gas model on multiple training items using a machine learning algorithm, the multiple training items comprising multiple audio samples of motor vehicle sounds obtained from one or more acoustic sensors and associated pollution levels. 13. A pollution estimation method as in claim 12, the method comprising obtaining, from one or more acoustic sensors, multiple motor sounds of multiple motor vehicles in use, and associated pollution levels of the multiple motor vehicles in use, thus obtaining the multiple training items comprising multiple audio samples of motor vehicle sounds and associated pollution levels, and training an exhaust gas model on multiple training items using a machine learning algorithm, thus obtaining a trained exhaust gas model. 14. Computer program for estimating a pollution level from exhaust gas of motor vehicles arranged to cause a processor to perform the method as claimed in claim 12. 15. A computer program as in claim 14 embodied on a computer readable medium.