ANALYSIS OF WORKING CONDITIONS ON AGRICULTURAL FIELDS USING PAS AND THEIR CONNECTION TO ECONOMIC PRODUCTIVITY
Abstract
This paper presents an analysis of modern methods for assessing the working conditions of a machine unit (MU) in the field using precision agriculture systems (PAS) and the impact of working conditions on technical-economic indicators and direct operational expenses during field operations. The article provides an analysis of innovative methods for evaluating working conditions (overall complexity and safety of agricultural work). The evaluation methods include: analysis of soil chemical composition using sensors and sample collection for laboratory analysis; identification of obstacles and constraints through remote sensing (satellite imagery and aerial photographs), the use of radar, laser sensors, and ultrasound; modeling of weather conditions using weather sensors and geoinformation systems; risk assessment for workers using mobile applications and notification systems, emergency alarms, and the use of markers or RFID tags in hazardous areas or objects. In the study, modern foreign equipment from companies such as CASE IH and HORSCH was used to determine the impact of working conditions on the technical-economic indicators of machine unit operation. Five machine units with different compositions performing operations related to the sowing of cereal crops were investigated in the field. Based on the results of the conducted research and calculations, a graphical model of the impact of working conditions on direct operational expenses per hectare of field cultivation and tables containing comparative values of technical-economic indicators of machine unit operation under favorable and extremely challenging working conditions (work condition gradation – 1 and 7, respectively) were created. The analysis of the obtained results showed that, on average for the 5 machine units in the conditions of this experiment, there is a decrease in productivity indicators, the coefficient of operating runs, and the utilization of shift time by approximately one-third (–33 %). At the same time, the cost indicators increased in the range of +49.2 % to +129 %. However, the cost increase was not linear with each level of increased working condition complexity. The average cost increase for conducting sowing operations in the field under extremely challenging conditions (7), compared to the field under favorable conditions (1), amounted to +58.74 % on average for the 5 machine units.
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