## 1 Introduction
Thus, there is a growing body of evidence to suggest that real-time visual information in the form of live video is an essential element for an automation interface. With these potential benefits, it is necessary to know which regions of the agricultural machine and its surrounding environment should be targeted by visual sensors. The authors of [14] recognized seven \"look zones\" (or areas the operator is expected to visually monitor during operation) for a seeding machine, labeled as: (i) forward, (ii) right side, (iii) planter, (vi) planter edge, (v) display X (located at the top right corner from the operator's seated position), (vi) display Y (located close to the right arm rest), and (vii) other. When researching the workload associated with operating an agricultural sprayer, the authors of [15] identified four sectors: (i) field ahead, (ii) left boom, (iii) right boom, and (iv) the lightbar guidance aid. They noticed that the amount of time operators spent looking at these regions varied with (i) operator experience and (ii) the presence of navigation devices (i.e., lightbars, autosteer technology). Designers of autonomous systems have also suggested various regions of the agricultural machine that warrant observation. For example, an interface for driverless tractor seeding equipment showed the view ahead of the machine as well as the left and right sides of the seeding implement, respectively [16]. In the interface developed by [17] for monitoring multiple agricultural robots, an aerial (satellite) view of the robots in the field was included. These examples reveal that the visual information that is used by the operator to make important decisions is gathered from three primary sources: (i) the displays located inside the machine's cab (i.e., information gathered automatically by sensors and translated into visual information for the operator), (ii) external field cues, and (iii) the implement. However, these authors do not specify or explain the information that is being gleaned from looking at each of these regions or quantify the importance of the information to the operation of the machine. Considering the cost and technical challenges associated with wireless transmission of live video and the risk of overcrowding the interface with multiple video displays, it is essential to determine the visual information that is typically used by the machine operator and if the visual information could be replaced with a graphical display (consisting of icons or symbols) on the interface without impacting the perception of the information. Therefore, the primary objective of the study was to determine and evaluate the visual information that is gleaned from the machine and its surrounding environment that assists the operator with the control of an agricultural machine. A secondary objective was to assess whether visual information present in live video could be replaced with a graphical display consisting of icons or symbols to represent various machine parameters. Some examples of graphical displays in conventional agricultural machines can be found in [13; 14]; two examples are shown in Figure 1 below. Recognizing that visual information requirements will be different for distinct agricultural machines, the self-propelled agricultural sprayer was selected for this study.