We are still at the dawn of Machine Learning and Artificial Intelligence in the Industry. Still, as we envision new use cases and develop them in our environment, we realise success in the future depends on the proper implementation today.

Moving towards a decentralized, intelligent and cybersecure Smart Grid involves a series of challenges that we explain in our new site

Advances in Artificial Intelligence continue to act as a driver of the industry's digital transition. With the power of AI and analytics pushing into IT operations, it is only a matter of time before artificial intelligence is integrated throughout all industrial processes.

The growth of Edge technology is causing a revolution on the path to Industry 4.0, and the need has arisen to define different parts of the Edge and their functionalities. Concepts such as thin edge and thick edge have emerged from the exponential growth of Edge Computing technology, which industry experts claim is the key to the digital transformation of critical industrial infrastructures.

An increasingly complex Smart Grid requires two main aspects: visibility and, above all, the ability to automate decisions. This ability to make decisions autonomously is made possible through virtual applications on the edge nodes.

«We already work with multinationals in sectors such as electricity, water management, critical infrastructure and telecommunications. This financing round will allow us to grow in these markets and accelerate our European expansion.” David Purón CEO and Co-founder

The energy sector is undergoing a profound transformation and Edge Computing is positioned as one of the enabling technologies to manage an increasingly distributed energy.

Barbara has been selected amongst 12 startups to take part in this cohort of the accelerator out of over 424 applicants from 58 countries. The programme will connect startups with leading energy organizations including ENEL, ENI, Iberdrola, GALP, Siemens Gamesa and Total Energies, to work together in solving complex clean energy and decarbonization challenges.

Fog Computing models are facilitating the creation of industrial IoT systems with lower latencies and lower bandwidth requirements, resulting in more cost-effective operations..