Advancing an Artificial Intelligence Platform for Crop-Health Monitoring

Plants can respond to changes in their surroundings and can convey precise information about their health state. Ecoation has developed a multi-sensory data acquisition device to capture this information and has been collecting in-field sensor data along with data labels produced by human experts during data collection. In addition, images of various parts of plant canopy has also been collected to supplement the sensory information and to provide insights into plant physical features such as vegetation. There is a wide spectrum of data types available, but only a few have been explored due to the novelty of the data type and the application. The focus of this project will be (i) conducting research and developing new data processing methods for our data and (ii) investigating machine learning and deep learning procedures to build deployable models for plant health diagnosis, vegetation detection and other grower’s task using collected labeled data.

Faculty Supervisor:

Lang Wu


Tingting Yu


Ecoation Innovative Solutions Inc


Statistics / Actuarial sciences


Environmental industry




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