Federation of Vehicular Data in Smart Villages with Socioeconomic Information

We present a dataset tailored for monitoring vehicle activity in a rural environment, specifically the Barranco de Poqueira region, covering the municipalities of Pampaneira, Bubión, and Capileira within the Sierra Nevada National Park, Granada, Spain. The dataset is generated by four Hikvision License Plate Recognition (LPR) cameras, capturing vehicle entries and exits in each village. To enrich the dataset, we include additional contextual details such as vacation calendars, vehicle origins, and socio-demographic information. Spanning from February to October 2022, the dataset is organized into three files: one with raw data directly from the cameras, another aggregated at the visit level with contextual information, and a third aggregated by vehicles with context details. With potential applications in mobility studies, urban planning, tourism, and socio-demographic analysis, the dataset is structured into three distinct files, encompassing a total of 43 different variables. The RAW_SMART_POQUEIRA.csv file contains information about 4 variables: num_plate_ID, camera_ID, date, and direction. The file VEHICLES_SMART_POQUEIRA.csv contains information about 33 variables: num_plate_ID, visit_time, distance, num_holiday, num_workday, num_high_season, num_low_season, entry_in_high_season, entry_in_holiday, nights, visits_dif_weeks, visits_dif_months, total_entries, avg_visit, std_visit, avg_nights, std_nights, avg_holiday, std_holiday, avg_workday, std_workday, avg_high_season, std_high_season, avg_low_season, std_low_season, route, country, km_to_dest, population, avg_gross_income, avg_disposable_income, autonomous_community, and province. The file VISITS_SMART_POQUEIRA.csv contains information about 26 variables: num_plate_ID, entry_cam, entry_date, entry_time, exit_cam, exit_date, exit_time, visit_time, route, distance, num_holiday, num_workday, num_high_season, num_low_season, nights, visits_dif_weeks, visits_dif_months, entry_in_holiday, entry_in_high_season, country, km_to_dest, population, avg_gross_income, avg_disposable_income, autonomous_community, and province.