Aerodynamically Controlled Pollination
- Polybee’s solution incorporates aerodynamically controlled pollination (ACP), a proprietary contactless mechanism for self-pollination, using off-the-shelf drones.
- The technique exploits turbulent downwash of the drone's propellers to vibrate the flower trusses at optimal frequencies.
- We apply our in-depth understanding of the fluid-structure interaction between airflow, mechanical properties of flowers, and the efficacy of pollination as a result of the vibratory motion.
- Our proprietary mechanism is patent-pending in strategic markets.
With the optimal airflow calibrated for pollination, the technique yields comparable or better results than conventional pollination methods.
Our technology stack is fully autonomous and provides a delightful user experience that addresses the key pain points of crop workers. With just a few clicks on the app, pollination operations can be initiated.
State-of-the-art AI Model trained with millions of data points
Build a digital twin of your plants by measuring yield, cluster count, fruit count and dimensions, and ripeness.
Our highly sophisticated deep learning models are trained over millions of data points from across a rich and diverse proprietary dataset.
Our solution achieves an industry-defying accuracy of ~99% on fruit count, and less than 5 mm of error for dimension measurement using state-of-the-art algorithms in 3D reconstruction, image processing, and deep learning.
3D reconstruction with cm-level resolution
Gain in-depth insights into each fruit's shape and size with less than 4 mm error on fruit dimensions by interacting with the digital twin of the plant.
Precise estimates on fruit weight (g) and plot yield (kg) allow you to confidently track and forecast crop yield.
Platform-agnostic data collection
Gather data using a simple smartphone or a drone - our pipeline is flexible and works seamlessly with any device that can record videos.
With our user-friendly dashboard, users can effortlessly delve into each plot's data, analyze time series, and compare metrics such as yield and cluster count across multiple plots.