Design and Implementation of a Data Platform for Stream Analysis: WeLASER as a Case Study"

Precision agriculture is a management strategy of agricultural activities based on data-driven decisions. This enables smarter usage of the available resources (e.g., water and crop) and ensures higher productivity. Following the integration of precision farming with the internet of things, big data, and artificial intelligence, we are witnessing the rise of ``Agriculture 5.0”. In this context, WeLASER is a European project that aims to create a system for managing weeding tasks by the adoption of robots equipped with laser technology that recognizes and burns weeds; this prevents the usage of chemical pesticides that can cause environmental damages. Such application involves the joint usage of robotic agents and data from IoT devices (e.g., weather stations) to perform effective weeding tasks. The goal of this thesis is to design, create, and test a data platform that enables the interoperability of IoT devices and robotic agents as well as data-intensive analytics on streaming data. Such data platform provides unified interfaces to collect, integrate, and analyze real-time data as well as to manage historical data.