As air quality expert I would like that the automatic computation of the emissions done by an AI model of the Open Data Hub is also applied to a new type of traffic measurement technology, i.e. cameras

[rcavaliere]

With CISMA and u-hopper we have developed an AI model that reads the traffic data of traffic stations and provides as output the emissions generated by traffic. The model is this: https://github.com/noi-techpark/bdp-elaborations/tree/main/pollution_v2

The model currently considers in its white list only "reliable" traffic measurement stations, in particular the one based on the traditional inductive loops technology. A22 has recently introduced new traffic measurement stations based on cameras. Based on deep analysis made with CISMA we found out that the technology is now much more reliable in the past. Therefore the decision, also shared with the BrennerLEC partners, to extend the computation to these kind of stations.

In the code of the elaboration, it's just needed to change this file: https://github.com/noi-techpark/bdp-elaborations/tree/main/pollution_v2/src/dags/common.py You should in particular extend the filter to stations which have sensor_type = camera

Please also check if some adaptations are also needed in the source code, in particular there: https://github.com/noi-techpark/bdp-elaborations/blob/main/pollution_v2/src/validator/Validator.py