Identification of patterns and prediction of parking in the city of Lisbon to improve surveillance efficiency.



To create new models either to predict or to generate viable alternatives for illegal parking in the city.

Research question

What are the characteristics of the locations where exists an higher number of occurrences regarding irregular parking?

Where and at what time of day is expected to exist an higher number of illegalities regarding irregular parking?




Challenge Brainstorming Session


Data understanding


Information about occurrences of irregular parking for 2018 and 2019 in Lisbon registed by the municipal police (60 000 occurrences).


Less abusive parking in Easter, Summer and Christmas vacations season.



 Abusive parking during weekdays between 8h to 11h.

Less concentrated between 14h and 19h.

Abusive parking during weekdays between 8h to 11h. Less concentrated between 14h and 19h.


Abusive parking in Campo Santa Clara (56 occurrences).



Data preparation: Machine Learning


Irregular parking occurrences along with contextual data were aggregated at census tract level.


Data preparation: Time Series


Irregular parking occurrences data was aggregated at street level in time bins of 3 hours


Main characteristics of the locations where exists irregular parking


Correlation between contextual data within each census tract and irregular parking.


Modeling: Machine Learning



Literature review


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