A spraying system including a boom having a first end, a middle, and a second end; a plurality of nozzles disposed on the boom; a plurality of cameras (70) disposed on the boom and positioned to each view a subset of the plurality of nozzles; a plurality of lights disposed on the boom and positioned to each illuminate a subset of the plurality of nozzles.

Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include identifying an emitter of an agricultural projectile delivery system to calibrate a trajectory of an agricultural projectile to intercept a target, predicting a projectile impact site relative to the reference of alignment, determining a calibration parameter to align the projectile impact site and the target, and adjusting the trajectory based on the one or more calibration parameters.

A system and method for the detection and tracking of droplets sprayed from an agricultural spray nozzle is provided. The system includes a sensor configured to observe droplets sprayed from the nozzle, a frame extractor module, a droplet shape and size extraction module, a droplet tracking module, and a data log module. The system may provide an artificial intelligence (AI)-enabled framework capable of processing images obtained of droplets, detecting and tracking all droplets appearing across image frames, and determining the droplets' geometric and dynamic data. The system further provides for the integration of deep-learning techniques into an image processing algorithm which enables precise and reliable determination of droplet characteristics. In addition, the deep-learning framework produces consistent results under a variety of uncertain imaging conditions.

A spray pattern monitoring system includes a spray sensor disposed proximate an outlet of a spray nozzle. The spray sensor has one or more optical sensors configured to emit directional light, such as laser pulses, towards the expected position of a liquid spray emitted from the nozzle. The spray sensor can detect the absence or presence of the liquid spray based on returns of the directional light to the optical sensor.

An agricultural system can include a first nozzle assembly positioned along a boom assembly and configured to selectively dispense an agricultural product therefrom. An airflow detection system can be configured to capture data indicative of one or more airflow sources. A computing system can be communicatively coupled to the first nozzle assembly and the airflow detection system. The computing system can be configured to receive, from the airflow detection system, the data associated with the one or more airflow sources and generate a first nozzle vector for the first nozzle assembly based at least in part on the data from the airflow detection system.

An agricultural sprayer includes at least one nozzle configure to receive a fluid and direct atomized fluid to an agricultural surface in a dispersal area. A radio-frequency (RF) transmitter is disposed to generate an RF signal that passes through the dispersal area. The RF signal is detectably changed when interacting with droplets of the atomized fluid. A first RF receiver is disposed to receive the RF signal after the RF signal passes through the dispersal area and provides an output indicative of the RF signal. A controller is coupled to the first RF receiver and is configured to detect plugging of the at least one nozzle based on the output of the first RF receiver.

A spray vehicle includes at least one boom, a plurality of spray units, a plurality of sensors, a processing unit, and an output unit. The plurality of spray units are attached to the at least one boom. The spray units are configured to spray a liquid chemical. At least one sensor is configured to measure a speed of the vehicle relative to the ground. At least one sensor is configured to measure an air movement direction relative to the vehicle. At least one sensor is configured to measure an air movement speed relative to the vehicle. The processing unit is configured to determine an air movement direction relative to the ground and determine an air movement speed relative to the ground. The processing unit is configured to generate a spray record for an environment within which the vehicle is operating. The output unit is configured to output the spray record.

A system for monitoring agricultural sprayer operation includes a boom and a nozzle mounted on the boom, with the nozzle configured to dispense a fan of an agricultural fluid as the agricultural sprayer travels across a field. Additionally, the system includes an imaging device configured to capture image data depicting the dispensed fan of the agricultural fluid and a controller communicatively coupled to the imaging device. The controller is, in turn, configured to analyze the captured image data to determine a parameter associated with a shape of the dispensed spray fan. Moreover, the controller is configured to compare the determined parameter to a predetermined parameter range. Furthermore, the controller is configured to; and initiate a control action when the determined parameter falls outside of a predetermined parameter range.

An agricultural application is provided herein that includes a nozzle assembly positioned along a boom assembly and configured to selectively dispense an agricultural product therefrom. One or more sensors can be operably coupled with the boom assembly and can be configured to capture data associated with one or more application variables. A computing system can be communicatively coupled to the one or more sensors and to a display. The computing system can be configured to receive the data associated with the one or more application variables; convert the one or more application variables to a scaled integer to determine a spray quality index; generate a geo-located application map of the scaled integer; and present the geo-located application map on the display.

An agricultural application system can include a nozzle assembly positioned along a boom assembly and can be configured to selectively dispense an agricultural product therefrom. One or more sensors can be operably coupled with the boom assembly and configured to capture data associated with first and second application variables. A controller can be communicatively coupled to the one or more sensors. The controller can include a processor and associated memory. The memory can store instructions that, when implemented by the processor, configure the controller to receive the data associated with the one or more application variables and calculate the spray quality index. The first application variable can have a first scaling factor and a second application variable can have a second scaling factor. The second scaling factor may differ from the first scaling factor.