Page 57 - U4SSC Compendium of survey results on integrated digital solutions for city platforms around the world
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geofences (an alarm sounds when a vehicle passes through a geographical area, which is useful
            for things like garbage dump monitoring and fleet control), and displays on control panels.

            Open data and services

            The Montevideo API public portal  provides a service API with platform information (including in
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            real time) to developers through a self-managed portal. This mechanism is used for the publication
            of information for third parties such as the estimated time of arrival (ETA) at the bus stop of public
            transport units, which is used by the ComoIr application of the IdeM, as well as by applications from
            external companies. The same mechanism is used for interconnection with other platforms such
            as Moovit, Waze, the National Port Administration and the Institute of Meteorology.

            Data analysis applications


            The Big Data tools associated with the smart city platform, along with the ability to integrate different
            sources and verticals have made it possible to work with data from the Metropolitan Transport
            Systems STM (electronic ticket sales), including the real-time positions of buses and the systems
            associated with the Mobility Management Centre or corporate systems of the Montevideo City
            Council (city sewer and sanitation system, Unique Claims System and the GRP). By applying data
            analysis techniques, different applications have been developed:


            •  Algorithm to deduce the destination bus stop from users of the public transport system, based
                on upcoming trips and historical card information.
            •  Origin/destination matrix with visualizations according to neighbourhoods, lines, schedules or
                time periods.

            •  Service levels of the fleet, compliance with schedules, routes and times of passage by stops.
            •  Line-occupancy levels, occupancy prediction, and application as an aid to control during the
                COVID-19 pandemic.

            •  Model of bus stop occupancy levels.
            •  Analysis of travel times.

            •  Analysis of use by type of user served to establish frequent user policies.

            •  Traffic, accident and speed applications.
            •  Applications on the cleaning and waste collection system of the city, location of the garbage
                containers and lifting control.

            •  Analysis of consumers of city sewer and sanitation systems.

            •  Real-time analysis of alarms and indications of data network equipment (logs) for prediction of
                failures.








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