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IT-TRAS SIGNED

INTEGRATED TIME TRACKING SYSTEM

Total Cost €

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EC-Contrib. €

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Partnership

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Project "IT-TRAS" data sheet

The following table provides information about the project.

Coordinator
KOINONIKI SUNETAIRISTIKI EPICHEIRISI SYLLOGIKIS KAI KOINONIKIS OFELIAS-RODIAKO KENTRO ISTOPIKON KAI KOINONIKON EREYNON 

Organization address
address: ROMANOU MELODOU 21
city: RODOS
postcode: 851 33
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 Greece [EL]
 Total cost 105˙275 €
 EC max contribution 105˙275 € (100%)
 Programme 1. H2020-EU.2.3.2.2. (Enhancing the innovation capacity of SMEs)
 Code Call H2020-INNOSUP-2019-02
 Funding Scheme CSA
 Starting year 2019
 Duration (year-month-day) from 2019-12-09   to  2020-12-08

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOINONIKI SUNETAIRISTIKI EPICHEIRISI SYLLOGIKIS KAI KOINONIKIS OFELIAS-RODIAKO KENTRO ISTOPIKON KAI KOINONIKON EREYNON EL (RODOS) coordinator 105˙275.00

Map

 Project objective

Time tracking constitutes a key feature of efficiency evaluation. Nevertheless, the production of Global Time Sheets is a cumbersome task usually ignored or improperly produced by the workers leading to inability to evaluate efficiency or accurately calculate the billable hours of work. The main reason behind that is the need of constant user intervention to set, pause or stop a timer per task or project which is impossible for those working away from the business premises. Integrated Time Tracking system (IT-TRAS) will minimise the need for user intervention in accurately calculating the working hours by operating seamlessly regardless of the location of the worker, by automatically adjusting to operational features of different tasks and by making smart distribution of time per task. Artificial Intelligence and specifically Machine Learning will be employed to gradually minimise user intervention through supervised learning and classification algorithms applied in a defined pool of training data containing the actual working hours per task and project. To achieve this, an Innovation Associate will be hired by the Rhodes Centre for History and Social Research – Rhodes Project SCE. The successful candidate will have a PhD in informatics, background in AI and ML, specialisation in supervised learning and classification algorithms as well as working experience in programming and software development. The Innovation Associate will receive tailored and certified training in the methodology of social research adding to his/her transferrable skills. He/she will be working in the multinational and multidisciplinary environment of Rhodes Project SCE for one year, with competitive salary and actual prospects of career development within the SME.

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The information about "IT-TRAS" are provided by the European Opendata Portal: CORDIS opendata.

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