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AI4DI - Artificial intelligence for Digitizing Industry

The AI4DI mission addressed bringing AI from the cloud to the edge and making Europe a leader in silicon-born AI by advancing Moore's law and accelerating edge processing adaption in different industries through reference demonstrators within the Automotive, Semiconductor, Machinery, Food and Beverage, and Transportation industrial sectors.

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The AI4DI project aimed to transfer machine learning (ML) and artificial intelligence (AI) from the cloud to the edge for several applications to accelerate the digitization of the industry. The AI4DI consortium comprised 40 partners from 11 European countries, working together to provide the technology, knowledge, and skills for developing and applying AI-based HW/SW modules, Internet of Things (IIoT), AI tools and algorithms. The AI-based technologies developed were applied to different use cases across various industry sectors. SINTEF, together with the Norwegian partners DENOFA, NXTECH AS and INTELLECTUAL LABS, focused on two demonstrators within the smart food and beverage production supply chain.

Process optimisation demonstrator

The process optimisation demonstrator offered key characteristics such as adaptive control, more detailed handling, and reusability of stored knowledge in soybean production. The AI-based system is integrated with the edge platform and improves the existing supervisory control and data acquisition (SCADA) system design, comprising programmable logic controllers (PLC), sensors/actuators, and IIoT devices. It integrates IIoT monitoring, Wi-Fi, LoRaWAN, Bluetooth low energy (BLE) technologies for intelligent wireless connectivity, and AI algorithms into an edge processing platform to provide a means to develop AI models and algorithms and deploy them in the real-time process flow.

Predictive maintenance demonstrator

The predictive maintenance demonstrator was based on the combination of technical, supervisory, and managerial actions performed during the life cycle of the equipment/motors to maintain soybean production and provide an enhancement through the introduction of AI-based, real-time sensor monitoring. The system design is based on a heterogeneous wireless sensor network consisting of sensor nodes and IIoT devices with different communication interfaces, computing power, sensing range and AI-based processing capabilities.

Key Factors

Project duration

2019 - 2022


EU H2020 ECSEL, Funded under INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Project type


AI4DI project official website

Project coordinator

Infineon Technologies AG, Germany

Technical coordinator