Objective predict.io 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, predicto.io 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. predcit.io 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. Fields of science social sciencessocial geographytransportpublic transportnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.3.4. - SOCIETAL CHALLENGES - Smart, Green And Integrated Transport Main Programme H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument Topic(s) IT-1-2014 - Small business innovation research for Transport Call for proposal H2020-SMEInst-2014-2015 See other projects for this call Sub call H2020-SMEINST-2-2014 Funding Scheme SME-2 - SME instrument phase 2 Coordinator PREDICT.IO GMBH Net EU contribution € 1 389 297,70 Address ENGELDAMM 64 B 10179 BERLIN Germany See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Berlin Berlin Berlin Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 984 718,56