An approach to digitalise activities of combine harvesters through CANBUS

The increase in the efficiency of agricultural machinery is a theme that attracted the attention and investments of the industrial and research community. In addition, in a global market, where the prices of agricultural commodities are so volatile and the prices of the inputs increase, farmers and agricultural contractors struggle to obtain at the end of the agricultural season a consolidated profit. For these reasons, it is important to carefully plan the usage of combine harvesters, to reduce the unproductive time and the input usage such as the fuel, that at the end of the harvesting season could increase costs. This study aims to develop an algorithm able to automatically identify and evaluate the time spent by the combines in each of the identified activities, identify the field boundaries of the harvested fields and perform a performance evaluation. To be able to develop the algorithm, during the harvesting seasons of 2020 and 2022, two combine harvesters operating in real-world conditions in Bologna’s Province were monitored. The data necessary to perform the analysis were acquired as CANBUS data and processed by using the MATLAB ® suite. The results obtained from this analysis show that the monitored combines have spent over 60% of the time performing harvesting activities, 13% of the time idling at the field, 10% performing headland turn, the 3% and 4% of the time respectively in transport on the field and road and 2% of the time in unloading. In addition, the performance of the monitored combines resulted similarly to the performance reported in other studies

Sensors Application in Agriculture

Novel technologies are playing an important role in the development of crop and livestock farming and have the potential to be the key drivers of sustainable intensification of agricultural systems. In particular, new sensors are now available with reduced dimensions, reduced costs, and increased performances, which can be implemented and integrated in production systems, providing more data and eventually an increase in information. It is of great importance to support the digital transformation, precision agriculture, and smart farming, and to eventually allow a revolution in the way food is produced. In order to exploit these results, authoritative studies from the research world are still needed to support the development and implementation of new solutions and best practices. This Special Issue is aimed at bringing together recent developments related to novel sensors and their proved or potential applications in agriculture