A bin level monitoring system utilizes an optical sensor housed in a housing. The housing is attached at or near the opening of a bin or other storage structure without the need for a hanging bracket. The sensor housing can be clipped or directedly attached to the bin opening or lid of the bin, such as at the lip of the opening. The shape of the housing aids in directing the particulate material into the bin housing, while protecting the sensor. The location of the sensor and housing provides ideal location to best monitor and evaluate the amount or volume of material product in the bin at a given time.

One or more techniques and/or systems are disclosed for automating the collection aggregation, and processing of data relating to harvesting or dispersion of an agricultural product. During harvesting and planting operations, data related to the product harvested or planted can be collected, aggregated, and used to improve the operation, and to help identification of the product at point of sale or point of dispersion. Further, certain operations can be automated during the harvesting or planting, such as automatic deployment of a field cart to offload/load product from/to the agricultural vehicle in the field. Additionally, load data can be automatically collected, aggregated, and identified, to follow the product through all stages.

A combine that can accurately measure the weight of grain retained in a grain tank is provided. When a weight measurement signal is output from a measurement switch 66, a weight measurement decision unit 75 instructs a working state determination unit 71 to perform working state determination. If it is determined that the combine is in the working state, the weight measurement decision unit 75 does not instruct a load cell 39 to perform weight measurement.

Embodiments of a kernel-level grain monitoring system include a grain camera positioned to capture bulk grain sample images of a currently-harvested grain taken into and processed by a combine harvester, a moisture sensor, and a display device. A controller architecture is coupled to the grain camera, to the moisture sensor, and to the display device. The controller architecture is configured to: (i) analyze the bulk grain sample images, as received from the grain camera, to determine an average per kernel (APK) volume representing an estimated volume of a single average kernel of the currently-harvested grain; (ii) repeatedly calculate one or more topline harvesting parameters based, at least in part, on the determined APK volume and the moisture sensor data; and (iii) selectively present the topline harvesting parameters on the display device for viewing by an operator of the combine harvester.

An automation system is configured to automatically adjust an operational setting of an agricultural vehicle while performing an operation in a field in order to adjust an operational output parameter of the agricultural vehicle. A method of training the automation system comprises receiving operational information including at least a location of the agricultural vehicle and georeferenced field information. The method further comprises, based on the location of the agricultural vehicle and the georeferenced field information, deciding to run a training sequence. The training sequence comprises measuring the operational output parameter, changing the operational setting, monitoring a subsequent change of the operational output parameter, and updating the automation system based on the changing of the operational setting and the subsequent change of the operational parameter.

During harvesting operations, the operator of an agricultural harvester must generally monitor various operating parameters of the harvester. However, such monitoring of operating parameters can direct the focus of the operator away from the harvesting operation, thereby leading to harvesting inefficiency, harvesting losses, and operator strain and fatigue. This may, in turn, distract the operator from the harvesting operation. Therefore, the agricultural harvester may include a light-emitting device positioned within a field of view of an operator of the agricultural harvester when the operator is viewing unloading operations. The light-emitting device may provide an indication of a fill level of the harvester storage compartment and/or an unloading rate of the harvested material from the storage compartment.

An agricultural crop harvester (1) includes a tank in which harvested crops are stored, a stored amount calculation section (51) that calculates a current stored amount of harvested crops stored in the tank, a communication section (61) which receives drier operation information indicative of a drier operational status transmitted from a drying facility 7, a work management section 62 that determines completion timing of a harvesting work based on the current stored amount and the drier operation information, and a notification section 63 which notifies the completion timing.

A combine including: a measurement sensor that measures a retention volume amount of a grain retained in a grain tank; a determination unit that determines whether or not the retention volume amount measured by the measurement sensor exceeds a preset threshold; a notification unit that, if it is determined by the determination unit that the retention volume amount exceeds the threshold, notifies an operator of information indicating that the amount of the grain exceeds the threshold; a change unit that can change the threshold; and a communication unit that communicates with an external server. The change unit changes the threshold based on data received from the external server.

A system includes an agricultural vehicle having a first storage container configured to store an agricultural product, a support vehicle having a second storage container, and an aerial vehicle having one or more sensors configured to monitor a fullness of the second storage container. The aerial vehicle is configured to provide a first signal indicative of the fullness of the second storage container to the agricultural vehicle.

One or more information maps are obtained by an agricultural system. The one or more information maps map one or more characteristic values at different geographic locations in a worksite. An in-situ sensor detects a material dynamics characteristic value as a mobile machine operates at the worksite. A predictive map generator generates a predictive map that predicts a predictive material dynamics characteristic value at different geographic locations in the worksite based on a relationship between the values in the one or more information maps and the material dynamics characteristic value detected by the in-situ sensor. The predictive map can be output and used in automated machine control.