**Abstract**

Industry 4.0 is characterized by autonomous decision-making processes, monitoring assets and processes in real time and to real-time connected networks through early involvement of stakeholders. In this scenario, there is a growing interest and a need of innovation also in the agri-food system in the production processes and quality control through the development of new interconnected sensors (IoT approach). Hardware minimization, as well as software minimization and ease of integration, is essential to obtain feasible robotic systems. A substantial change in measurement methodologies is therefore ongoing, and it is of interest the opportunity to replace the consolidated analytical techniques, based on laboratory analyses, with methods based mainly on physical approaches of rapid execution, of limited invasiveness, and with high environmental sustainability. These approaches should be applicable directly in the field or in operative environment, allowing the creation of big databases characterizing the samples, particularly large and shared through the data cloud. This chapter will aim to overview the theoretical principles of the most important technologies applied to the olive oil sector presenting some case studies and will be focused on the future perspective for all operators of the olive sector who want to use a sustainable approach and olive-growing 4.0.

**Keywords:** agriculture 4.0, optical analysis, Vis/NIR spectroscopy, chemometrics, sensors, qualitative parameters, green technology, machine learning, simplified system
