Kapcsolat

Tel: +36-20/9315-313 
       +36-70/4085-476

Tel: 06 20/ 9-528-884  ( iroda )
E-mail: inox(kukac@)inoxtechnology.hu

Iroda/ ügyfélfogadás: 8000 Székesfehérvár, Farkasvermi út 40.  

 (csomag szálításkor kérem keressen irodai számunkon! )

Telephely: 8000 Székesfehérvár Börgöndi út 8-10.


Nyitvatartás:
Hétfő: 8.00 - 17.00
Kedd: 8.00 - 17.00
Szerda: 8.00 - 17.00
Csütörtök: 8.00 - 17.00
Péntek: 8.00 - 16.00
Szombat: Zárva
Vasárnap: Zárva

A projekt leírása

 

Az alábbiakban tekinthető meg angolul a projekt célkitűzése és tartalma:

A channel to find the true knowledge for EU companies – building and deploying a multi-lingual big data supply chain management system

The project aims to provide solutions for managing the challenges of real world “Big Data” problems, such as data capture and storage, transmission, curation, analysis and visualization. For example, in manufacturing industry, logging the output of one 8 Byte, 5MHz sampling sensor per hour yields 3600 x 5000000 x 8 Byte = 144 GB of data. For an 8 hour shift per day, the sensor will produce more than 1 TB of data. For a production line, hundreds of sensors can be in use, and PetaBytes (PB) of data are not unusual [Xun]. Industry commonly lacks adequate resources to handle this flood of data: most importantly storage, but also accessing, transferring, and processing the complete data is beyond the capacities of typical industries. It is therefore of utmost importance to manage a supply chain for this data, that keeps track of what should be kept, what should be aggregated, and what should be forgotten.

Notably, this chain can have very different requirements depending on the industry involved. Moreover, in an increasingly networked world, data will not originate from within a single company. Especially in a European context, it is also very important to deal with data in multiple languages originating from multiple countries.

The output of the proposed project will address these needs and provide an intelligent data supply chain management system as a platform for multi-lingual, multi-countries, and multi-discipline industrial use. The platform will be endowed with advanced technologies in the service oriented open framework, XML based smart data structures, complex event processing, and multi-lingual communications.

The platform will help European companies to improve their ability to manage their data supply chains and enable them to deal with large volumes and heterogeneous, variable data resources, multi-lingual data, and semantically interoperable data assets. This will allow for significant savings for the industrial users who need to use and reuse these data assets.

Unlike existing products in data technologies that are mostly standalone, single lingual, limited usages for multi-discipline and rarely applied to the big data [], this platform will enable the big data users and data providers to share the resources without expensive investments to build up their own platform. The platform will provide services for understanding semantically interoperable data assets. The platform will feature multiple EU language interfaces, especially beneficial for EU cross border users. The platform will be equipped with intelligent rules and policies that are generically expecting that users are from multiple disciplines. The major benefit is to deliver a powerful tool for industry to cope with information explosion and to utilise the big data into value adding process. This will lead to a competitive advantage for the industries involved in this digital revolution.

The platform built upon will include a set of advanced data architectures, rule engines and multilingual interfaces suitable for cross-sectorial users, multilingual users and cross-border users. It is a precursor for the future applications in Wire/wireless Automatic data collection, Domain driven pattern identification, Assessment knowledge discovery and then Decision making – WADAD for the (healthcare/education/business/manufacturing) and provides solutions within a programme involving all collaborators in the consortium. 

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