Artificial Intelligence in Manufacturing for Sustainable Applications at SMEs
Sector: Manufacturing (Industrial) • Location: Greece, Germany, Netherlands, Belgium, Spain, France, Norway, Czechia, Lithuania, Bulgaria, Hungary
Source: EU Funding & Tenders Portal
The AIRISE project will support European SMEs in the uptake of Artificial Intelligence applied to manufacturing, with a specific focus on the use of AI-enabled applications at the edge. The key objective for applications is a reduction of waste and carbon footprint while ensuring the resilient operation of manufacturing. The consortium will create an eco-system where the project’s AI experts will
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Participants
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Company | Obfuscated Data |
Status
Original status | ongoing |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Description
Description | The AIRISE project will support European SMEs in the uptake of Artificial Intelligence applied to manufacturing, with a specific focus on the use of AI-enabled applications at the edge. The key objective for applications is a reduction of waste and carbon footprint while ensuring the resilient operation of manufacturing. The consortium will create an eco-system where the project’s AI experts will support experimenting SMEs and connect them to Digital Innovation Hubs and commercial companies to achieve real-world applications. Open Calls will allow SMEs to easily access AI expert competence through first-stage assessments that identify the status and potential and through further proposals that support them in running pilot applications and validation experiments. The ambition of AIRISE is to support more than 500 cases from SMEs and mid-caps on key AI applications at the edge. Support from the consortium will be complemented on security and connectivity by involving external resources in cybersecurity and IoT and on smart working environments by offerings on operator interfaces and collaborative robots. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
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Location
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Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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