Whitepapers

Machine learning algorithms, AI and IoT devices: the recipe for innovating the vending sector is CLEA, a concentrate of hi-tech, data analysis and customer experience.

What does it mean to be a data-driven company? At the basis of the concept is a data culture. Here is why it is essential.

Production data collection must lead to the development of a more sustainable factory in which AI, IoT and a cloud support the transition path.

Processing data via edge computing directly where it is detected has great benefits for healthcare. Here are some examples.

The characteristics of the ideal smart device for the productive world? Ease of integration, maximum efficiency, flexibility and above all safety.

Edge AI ​​edge allows you to bring computing capacity directly to the source, reducing latency and energy spent on moving processing to the cloud.

IoT sensors transform a vending machine into a smart machine, which communicates with the customer to offer him the best possible purchasing experience.

With data monetization - the monetization of data, which is the process of strategic analysis and practical implementation that allows you to use data as a source of revenue - companies can transform data they have collected into monetizable value just like other assets. In fact, data monetization becomes a strategy that allows companies to virtuously recover the investments made on IoT and IIoT infrastructure, systems and platforms, accelerating their evolutionary path and designing new business scenarios.

Big data monetization - literally, data monetization, that is the process of strategic analysis and practical implementation that allows you to use data as a source of revenue, is one of the most rewarding objectives for any company that wishes to undertake a virtuous data-driven business path. However, its achievement can be hindered not only by a misinterpretation of the data already available but, above all, by a lack of correct investments in emerging technologies.

Edge computing enhanced by AI has countless applications. Let’s take a closer look at its positive impact on data analysis and how businesses can put such data to use.