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SOUTHPARK - SOcial and Universal Technology HelPing to detect ARrivals via sdK

Total Cost €


EC-Contrib. €






Project "SOUTHPARK" data sheet

The following table provides information about the project.


Organization address
address: ENGELDAMM 64 B
city: BERLIN
postcode: 10179
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Project website
 Total cost 1˙984˙718 €
 EC max contribution 1˙389˙297 € (70%)
 Programme 1. H2020-EU.3.4. (SOCIETAL CHALLENGES - Smart, Green And Integrated Transport)
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-2-2014
 Funding Scheme SME-2
 Starting year 2015
 Duration (year-month-day) from 2015-08-01   to  2018-07-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    PREDICT.IO GMBH DE (BERLIN) coordinator 1˙389˙297.00


 Project objective has been set up as a company to address individual, as well as societal problems related to urban mobility and road congestion by building a smart, integrated, technology-based, easy to use system that renders the traffic more efficient thereby decreasing negative effects on humans and the environment while at the same time fulfilling today's need for fast and individualised urban mobility. The technology is based upon an elaborated set of algorithms that can detect on mobile devices when a user arrives at a location in order to improve different kinds of traffic and mobility apps.

The SOUTHPARK project is set up to fulfil two overall objectives:

First, will integrate the technology, with its automated start and stop detection in different mobility apps (including parking apps). This will be achieved when the SDK generates at least 1 million mobility data points a day for real-time applications as well as business analytics. These efforts will cover countries across the European Union. The goal is to enable more convenient, more reliable, safer, environmentally friendlier, and efficient mobility solutions.

Second, the SOUTHPARK project will bring the arrival detection close to perfection. This will be reached by the reduction of localisation costs and implementation time. will build up significant machine learning capacities that constantly improve the existing algorithms in order to provide faster, better anticipating, more adaptive and less battery consuming STOP detection. Fulfilling this objective will reduce the adaptation costs and time to localise to new settings by estimated 75%.

The outcome of the project will be an ensemble of algorithms that had been tested on large scale in the operational environment. The arrival detection can be used in various mobility use cases and provide data that helps city planners and public transport authorities to better plan the future of urban transportation.

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The information about "SOUTHPARK" are provided by the European Opendata Portal: CORDIS opendata.

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