Modeling and Monitoring Crop Disease in Developing Countries

Information about the spread of crop disease is vital in developing countries, and as a result the governments of such countries devote scarce resources to gathering such data. Unfortunately, current surveys tend to be slow and expensive, and hence also tend to gather insufficient quantities of data. In this work we describe three general methods for improving the use of survey resources by performing data collection with mobile devices and by directing survey progress through the application of AI techniques. First, we describe a spatial disease density model based on Gaussian process ordinal regression, which offers a better representation of the disease level distribution, as compared to the statistical approaches typically applied. Second, we show how this model can be used to dynamically route survey teams to obtain the most valuable survey possible given a fixed budget. Third, we demonstrate that the diagnosis of plant disease can be automated using images taken by a camera ph...

• Type: Journal
• Year: 2011
• Where: AAAI
• Authors: John Alexander Quinn, Kevin Leyton-Brown, Ernest Mwebaze
• Keywords: AAAI 2011, Density Model, Intelligent Agents, Staple Crops, Subsistence Farmers