TOQO: A new Tillage Operations Quality Optimization model based on parallel and dynamic Decision Support System

Abstract

Abstract Mechanization in agriculture involves all stages of cultivating and preparing innovations, from basic and essential hand devices and tools to more complex and mechanized implements. Fundamentally, such devices and tools enable agricultural activities to initiate different crop yields in many different neighborhoods in the world s ecological system. Due to the unstable nature of fuel prices, market demands, and damaging effects of tillage machinery vibrations on the operator, exploring efficient methods of preventing these situations has become indispensable. There are many existing methods related to tillage optimization, including fast, high quality, and cost-effective tilling. However, none of the existing methods perform real-time and dynamic recommendations due to the inability to provide real-time tillage data. Another issue is the unavailability of a tillage recommendation model that acts based on the changes of a fixed set of tillage parameters and provides the necessary guidance to the tractor driver during the tillage operation. This paper proposes a Tillage Operations Quality Optimization (TOQO) model that aims to improve the efficiency of tillage operations. The model provides real-time tillage data through integrating the Internet of Things (IoT) technology and a dynamic Decision Support System (DSS) for tillage machinery operation and process optimization. The proposed model has been successfully implemented, tested, and evaluated in real-world tillage operations. The results of this TOQO study clearly show improvements in the tillage operations. This is because the TOQO gives online recommendations in real-time based on dynamic measurements of six tillage performance evaluation parameters. The parameters are vibration, bulk density, slippage ratio, fuel consumption, real tillage depth, and field efficiency. The TOQO model successfully handles more than one tillage machinery tractor by using cloud computing services. Vibration increases when using the system on the X-axis at 46.63843 rms, Y-axis at 23.23612 rms, and the Z-axis at 51.47240 rms. Vibration fractures the soil, reducing soil cohesiveness when using an oscillating tillage tool and producing smaller soil aggregates than a non-oscillating one. When using the system, the value of the virtual density increases by 0.23821\xa0g/cm3. Most of the bulk density values for the optimized phase are within the recommended or required growth range. There is a slight increase in depth by 0.4279\xa0cm and a decrease in slippage ratio by 0.64364%. Tractor fuel consumption decreases by 1.2169\xa0L per hour, indicating a reduction in tractor wheel slippage. Reduced fuel consumption and wheel slippage of tillage operation are essential parameters to increase field efficiency and reduce tillage operation costs.