AI for Precision Orchard Yield Estimation & Harvest Planning
AI-powered computer vision and sensing deliver accurate orchard yield estimates and optimize harvest labor, logistics, and packhouse planning.
Orchard yields are hard to predict with manual sampling. AI uses CV counts, size/color estimation, and growth models to forecast yields, improving labor planning, logistics, and sales commitments.
Picker allocation and productivity tracking.
Bin logistics and cold chain planning.
Packhouse capacity and SKU mix planning.
Labor logs, picker performance, harvest dates.
Imagery pipelines (UAV, tractor cams, handheld).
Weather and phenology tracking.
Frequently asked questions
What APIs are available for integrating with packhouse planning and sales systems?
APIs to packhouse planning and sales systems.
What types of reports does mysimulator.uk provide regarding accuracy, confidence levels, and utilization metrics?
Reports on accuracy, confidence, and utilization.
How can imagery be captured across sample blocks, and how is alignment with ground truth counts ensured?
Capture imagery across sample blocks; align with ground truth counts.
What steps are involved in training computer vision detection/size models, and how should calibration be performed per variety or block?
Train CV detection/size models; calibrate per variety/block.
▶ Try it live
Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.