KITT4SME

KITT4SME specifically targets European SMEs and mid-caps to provide them with scope-tailored and industry-ready hardware, software and organisational kits, delivered as a modularly customisable digital platform that seamlessly introduces artificial intelligence in their production systems. Uptake of the resulting packages and of the provided services is strongly supported by the clear characterisation and market readiness of the individual components as well as by the platform grounding on the already established RAMP marketplace. Leverage on the network of Digital Innovation Hubs, three of which are represented in the consortium, ensures that KITT4SME are widely distributed to a wide audience of companies in Europe. Seamless adoption of the customised kits is made possible by a Powered by FIWARE infrastructure that flawlessly combines factory systems (such as MES and ERP), IoT sensors and wearable devices, robots, collaborative robots and other factory data sources with functional modules capable of triggering data-driven value creation.

Reason for applying to HSbooster.eu services

The project aims to find new methods to propose standardisation to technical partners as well as to have direct contact with standardisation committees and entities (e.g. CEN, CENELC, EFFRA, ETSI, IDSA, IEEE, ISO, OOEF).

Main standardisation interest

KITT4SME project has a specific task related to Standardisation activities.

Work package 9, with its Task 9.3 aims at taking care of standardisation activities, contributing, where possible, to developing standards and successfully coordinating the involved entities to access digital networks and the cross-sectoral diffusion of the KITT4SME solutions.

The main objectives are: 

• Update the set of the initially selected standards, starting from ones reported in GA
• Identify any potential standardisation needs
• Create relations and communications with other international standardisation consortia and committee
• Define a standardisation roadmap 

A methodology was developed to approach, understand and identify any gaps. Relevant standards and policies have been identified, too and partners started to get engaged with standardisation associations.

The involvement in these activities would also like to be related to Ethics in AI as a smart model on FIWARE’s repository.