A method for crowd detection in an area includes determining moving patterns of persons in the area and the number of persons within and/or moving from and/or to the area over a certain time period to obtain model training data sets; assigning each model training data set to represent one of one or more predefined crowd levels in the area; generating a crowd detection model based on the model training data sets; and estimating an actual crowd level for the area using the generated crowd detection model with actual data of moving profiles and/or the actual number of persons within and/or moving from and/or to the area over a certain time period.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for crowd detection in an area, comprising: determining moving patterns of persons in the area and the number of persons within an/or moving from and/or to the area over a predetermined time period to obtain model training data sets; assigning each model training data set to represent one of one or more predefined crowd levels in the area; generating a crowd detection model based on the model training data sets; and estimating an actual crowd level for the area using the generated crowd detection model with actual data of moving profiles and/or the actual number of persons within and/or moving from and/or to the area over the predetermined time period. 2. The method according to claim 1, wherein the crowd detection model is generated using a machine learning algorithm on the model training data sets. 3. The method according to claim 1, wherein for estimating the actual crowd level, a machine learning algorithm is used with the actual data based on the generated crowd detection model. 4. The method according to claim 1, wherein the model data sets are analyzed with regard to an association between crowd level and regions in which persons move with a probability greater than or equal to a predetermined threshold in the area and that based on the analyzed data the area is divided into one or more moving regions and one or more non-moving regions. 5. The method according to claim 4, wherein the non-moving regions are determined based on a predefined distance to one or more borders of the area. 6. The method according to claim 4, wherein one or more sensors are arranged in the non-moving regions the area. 7. The method according to claim 1, wherein one or more corridors are defined for moving to or leaving the area, wherein one or more sensors are arranged in at least one of the corridors. 8. The method according to claim 1, wherein a privacy-preserving sensor is provided in a form of one or more of an environmental sensor, a temperature sensor, a humidity sensor, a noise sensor, and a location sensor. 9. A system for crowd detection in an area comprising: a data collector connected to one or more sensors operable to determine moving patterns of persons in the area and the number of persons within and/or moving from or to the area over a predetermined time period; a data set creator operable to prepare the collected data of moving patterns of persons in the area and the number of persons within and/or moving from or to the area; a classifier operable to classify one of predefined crowd levels in the area for the prepared data; and a crowd detector operable to estimate an actual crowd level for the area based on actual data of moving profiles and/our the actual number of persons within and/or moving from or to the area over the predetermined time period. 10. The system according to claim 9, further comprising: an analyzer operable to analyze the classified data with regard to an association between crowd level and regions in which persons move with a probability greater than or equal to a predetermined threshold in the area and that based on the analyzed data the area is divided into one or more moving regions and one or more non-moving regions. 11. The system according to claim 10, further comprising one or more sensors are arranged in the non-moving regions of the area. 12. The system according to claim 9, further comprising a privacy preserving sensor that is one or more of an environmental sensor a temperature sensor, a humidity sensor a noise sensor, and a location sensor. 13. The method according to claim 1, further comprising detecting anomaly or violence behavior. 14. The method of claim 6, wherein the one or more sensors are privacy preserving sensors. 15. The method of claim 8, wherein the environmental sensor is a CO2 sensor and wherein the location sensor is one or more of a proximity sensor and a movement sensor, 16. The system of claim 11, wherein the one or more sensors are privacy preserving sensors. 17. The system of claim 12, wherein the environmental sensor is a CO2 sensor and wherein the location sensor is one or more of a proximity sensor and a movement sensor. 18. The system of claim 9, further comprising a detector configured to detect anomaly or violence behavior.