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Bird Deterrence in a Vineyard Using an Unmanned Aerial System (UAS)

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Transactions of the ASABE. 62(2): 561-569. (doi: 10.13031/trans.12923) @2019
Authors:   Santosh Bhusal, Kapil Khanal, Shivam Goel, Manoj Karkee, Matthew Edmund Taylor
Keywords:   Bird deterrence, Fruit crops, Machine vision, Unmanned aerial systems, Vineyards.

Abstract. Washington State growers lose more than $80 million annually to bird damage in fruit crops such as cherries, grapes, Honeycrisp apples, and blueberries. Conventional bird deterrence techniques, such as netting, auditory devices, visual devices, chemical application, falconry, and shooting, are either costly, ineffective, or harmful to birds. At the same time, unmanned aerial systems (UAS) have become popular in military, civilian, and agricultural applications due to decreasing cost, good maneuverability, and their ability to perform multiple types of missions. This article presents an approach using UAS to deter birds and minimize their damage to wine grapes. A quadcopter UAS was flown for three days in September 2016 over a section (30 m x 30 m) of a vineyard to deter birds. The test section of the vineyard was next to a canyon with many trees that provided shelter for a large number of birds. The experimental design included different deterrence methods against birds, including auditory deterrence, visual deterrence, and varying UAS flight patterns. The test section of the vineyard was under continuous video surveillance from 7:00 to 9:00 a.m. using four GoPro cameras for five continuous days, including three days when the UAS was flown. A Gaussian mixture model-based motion detection algorithm was used to detect birds in the videos, a Kalman filter was then used for tracking the detected birds, and bird activities (incoming and outgoing birds) were counted based on the movement of birds across the plot boundary. Two accuracy measures (precision and recall) were calculated to analyze the performance of the automated bird detection and counting system. The results showed that the proposed system achieved a precision of 84% and recall of 87% in counting incoming and outgoing birds. The automated bird counting system was then used to evaluate the performance of the UAS-based bird deterrence system. The results showed that bird activity was more than 300% higher on days with no UAS flights compared to days when the UAS was flown with on-board bird deterrence measures. UAS flights covering the entire experimental plot with auditory deterrence had a better effect than flights with visual deterrence. The results showed the potential for developing an automated bird deterrence system for vineyards and other crops. Extended studies with multi-year, multi-field, and multi-platform experiments are essential to further validate the results.

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