Abstract
Operational monitoring includes all those tasks performed to observe, survey and report all the information necessary to get an overview of the operational processes carried out during a specific field activity. The focus of this research is to develop a complete system able to collect and interpret all the operative parameters, for each different agricultural operations, in order to obtain information suitable to carry out management and strategical decisions. In short, the aim of the research is to develop a new concept of intelligent system supporting Precision Farming applications, capable to translate ex post actual operative parameters into information, so as to automatically perform an objectivity compilation of the field activities register.
Through this system the farmer is able to have, on demand, updated information to be used for certification and traceability processes, as well as to satisfy any other management task, including the estimation of the actual operative costs at the farm. The solution here proposed is based on the identification of working processes through a tractor-oriented approach, where the power unit is equipped with a GNSS-data logger and an identification system acting as a detector able to recognize the coupled implements (on their turn equipped with a RF-transmitter sending identifying codes) and the related operations. Both devices are provided with an accelerometer to allow them to switch on only when they record a vibration. The raw data are collected with a frequency of 0.2 Hz fixing and compressed in data packets formed by geographical coordinates, day and hour of detection, and coupling information.
Data-packets are then sent to a server, thanks to a GPRS-modem integrated into the GNSS-data logger, where they are finally stored into a relational database. Here, an Operational Inference Engine software (OIE) manages all these data through a set of automatic procedures to get final intelligible information on the monitored operations. The OIE results can be then uploaded by a Web-GIS client, that allows the farmer to get an easy and intuitive access to the information directly from his own private web domain.
A series of field surveys were organized in order to perform the validation of the proposed procedure, through a manual time study and assessment of the followed working sessions. The main operative information obtained automatically by this new system (i.e. speeds, hour of start and finish, working session (WS) duration, operation recognition) were compared with those manually registered. Comparisons between automatically estimated and manually registered parameters revealed high level of correlations (R2 > 0.6), especially in terms of time comparison and identification of the working session, thus it highlights the capability and reliability of the proposed system to monitor agricultural operations in an automatic way. This solution will facilitate and enable new generations of farm information systems to be specifically developed for applications on agri-environmental enterprises.
