Environmental Variables and Quality Tools Applied to the Operator of an Agricultural Microtractor

Abstract

Work in the field is characterized as unstructured because it is performed in inconvenient postures, without a fixed workstation, exposing the worker directly to the sun and other inclement weather. This may interfere in the health and the performance of the activity. The objective of this work was to characterize the environment of the agricultural microtractor operator, evaluating the thermal comfort during the activity in the municipality of Quixadá, CE. A model TC14 Super Yanmar Agritech microtractor, coupled to a rotary spindle, was used. For the measurements of the environmental variables, sensors and devices were installed on the operator and in the microtractor. The experimental design adopted the assumptions of statistical quality control. Fifteen collections were done daily at different times for three consecutive days. The data obtained were indices of thermal discomfort and thermography, both of which were analyzed by sequential graphs (run charts), control graph (Xbar-R chart), and scatter plot. At all rates, the work performed proved to be inadequate, exceeding the operator's capabilities and limitations. It was concluded that the activity performed by the microtractor operator is stressful. Measures should be taken to improve working conditions without affecting the operator's health.

Development of a Low-Cost Open-Source Platform Connected to the Internet for Acquisition of Environmental Parameters and Soil Moisture

“…In Agriculture 4.0, having reliable, real-time data has become a widespread requirement to minimize risks, maximize production results, and increase farm profit (Rawal, 2017). In this context, the use of Internet of Things (IoT) tools is important (Kansara et al, 2015), as currently almost all devices can be connected (Estevam et al, 2019). Devices such as smartphones can receive or access data in the cloud, send equipment control orders, monitor the evolution of environmental parameters, being important tools that assist in decision-making or automation (Fisher et al, 2018;Fisher & Gould, 2012;Jordão et al, 2017;Payero et al, 2017).…”