Abstract: A harvesting machine capable of automatic adjustment, comprising a plurality of acoustic material flow sensors, a control system, a processor, and application software, wherein the plurality of acoustic material flow sensors are mounted internal to the harvesting machine at points of crop material flow and are capable of sensing an amount of crop material passing by them. The control system operates in a cause-and-affect mode for interactively enabling manual or automatic responses to Mass Material Distribution (MMD) information and equipment-related performance parameters. An interactive combine control method is also provided.

Abstract: A crop mass predictive sensor, comprising an imaging device, a laser-based device such as a LIDAR, a first radar emitting a frequency of energy that is absorbed by plant mass, and a second radar emitting a frequency of energy that passes through plant mass without being absorbed, wherein the imaging device, laser-based device, first radar, and second radar are focused on the crop material in front of an agricultural vehicle, and the information gathered from the imaging device, laser-based device, first radar, and second radar is used to calculate an estimated mass for the crop material that is about to enter the agricultural vehicle.

Abstract: A harvesting machine capable of automatic adjustment, comprising a plurality of acoustic material flow sensors, a control system, a processor, and application software, wherein the plurality of acoustic material flow sensors are mounted internal to the harvesting machine at points of crop material flow and are capable of sensing an amount of crop material passing by them. The control system operates in a cause-and-affect mode for interactively enabling manual or automatic responses to Mass Material Distribution (MMD) information and equipment-related performance parameters. An interactive combine control method is also provided.

Abstract: A harvesting machine capable of automatic adjustment, comprising a plurality of acoustic material flow sensors, a control system, a processor, and application software, wherein the plurality of acoustic material flow sensors are mounted internal to the harvesting machine at points of crop material flow and are capable of sensing an amount of crop material passing by them, wherein the control system is capable of adjusting a plurality of internal elements of the harvesting machine, wherein the software is hosted on the processor, and the processor is operatively coupled to the control system and the acoustic material flow sensors, wherein the software uses information sensed by the acoustic material flow sensors to determine if the internal elements of the harvesting machine are set for optimal machine performance, and the software sends commands to the internal elements of the harvesting machine in order to improve the machine performance.

Abstract: A crop mass predictive sensor, comprising an imaging device, a laser-based device such as a LIDAR, a first radar emitting a frequency of energy that is absorbed by plant mass, and a second radar emitting a frequency of energy that passes through plant mass without being absorbed, wherein the imaging device, laser-based device, first radar, and second radar are focused on the crop material in front of an agricultural vehicle, and the information gathered from the imaging device, laser-based device, first radar, and second radar is used to calculate an estimated mass for the crop material that is about to enter the agricultural vehicle.

Abstract: A harvesting machine capable of automatic adjustment, comprising a plurality of acoustic material flow sensors, a control system, a processor, and application software, wherein the plurality of acoustic material flow sensors are mounted internal to the harvesting machine at points of crop material flow and are capable of sensing an amount of crop material passing by them, wherein the control system is capable of adjusting a plurality of internal elements of the harvesting machine, wherein the software is hosted on the processor, and the processor is operatively coupled to the control system and the acoustic material flow sensors, wherein the software uses information sensed by the acoustic material flow sensors to determine if the internal elements of the harvesting machine are set for optimal machine performance, and the software sends commands to the internal elements of the harvesting machine in order to improve the machine performance.