Cel 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. Dziedzina nauki social sciencessocial geographytransportpublic transportnatural sciencescomputer and information sciencesartificial intelligencemachine learning Program(-y) 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 Temat(-y) IT-1-2014 - Small business innovation research for Transport Zaproszenie do składania wniosków H2020-SMEInst-2014-2015 Zobacz inne projekty w ramach tego zaproszenia Szczegółowe działanie H2020-SMEINST-2-2014 System finansowania SME-2 - SME instrument phase 2 Koordynator PREDICT.IO GMBH Wkład UE netto € 1 389 297,70 Adres ENGELDAMM 64 B 10179 BERLIN Niemcy Zobacz na mapie MŚP Organizacja określiła się jako MŚP (firma z sektora małych i średnich przedsiębiorstw) w czasie podpisania umowy o grant. Tak Region Berlin Berlin Berlin Rodzaj działalności Private for-profit entities (excluding Higher or Secondary Education Establishments) Linki Kontakt z organizacją Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 1 984 718,56