Integration and Application of RTK-PPP Technology in Precision Agriculture

This thesis identify the research of a system able to be developed in the precision agriculture field for a company based in Turin called WiRail. The core business of this company is the development of modular control units able to store and process the telemetry of moving vehicles. This work is based on the implementation of a system able to perform specific efficient operations starting from a precise knowledge of the current position. For this reason, the base to be explored starts from the available Positioning Systems and Correction methods used to reach a precision in the order of centimeters. Based on previous tests, the PPP-RTK technology ensures a perfect solution considering the accuracy reached and the time elapsed to reach it. The corrections were obtained by connecting the device, equipped with a GNSS receiver, to the SPIN3 GNSS network: a free service available in Piemonte, Lombardia and Valle d'Aosta. Once the position of the device (and then the machine in general) is known, it is possible to elaborate it relatively to the morphology of the working field (comprehensive of criticalities) and the operations to be performed. The mapping of the field is based on a matrix, where each cell identify characteristics of a specific region (such as type of operations to be done, type of crops, criticalities and so on). The mapping can be performed by the WiRail portal and so transmitted from the server to the on site control unit or, in future implementations, scanned, stored and/or updated autonomously during normal operations. As output the control unit can transmit in cloud important process parameters (such as specific fuel consumption, engine load, vehicle speed) relative to high accurate positions. The collection of all of this data is essential for the elaboration of models able to enhance the processes efficiency. The aim is to supply a working ready-to-market tool able to elaborate sets of data, compute, and display indications about the job to perform, and return in cloud working results in real-time. In a perfectly stable system, this can be used not only to give indications, but also to pilot efficiently autonomous rovers or drones.