Asst. Prof. Emily Bick develops tools and strategies to support data-driven precision agriculture management techniques. She has created a machine-learning algorithm to detect and identify insect infestations in crops, including boring insects that are difficult to identify without destroying crops. This non-destructive technology uses audio signals captured by inexpensive microphones to identify infestations and enables a more targeted application of pesticides.
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