14TSB_DataExpl Crowd-Sourced Prediction of Plant Pest and Disease Occurrence using Mobile Apps

该项目的行业主要合作伙伴Growing Interactive生产领先的在线软件和应用程序，园丁和小型农场使用这些软件和应用程序来规划他们种植的可食用作物，并获得更高水平的成功。超过25万园丁和农民使用了他们的软件和应用程序。它们拥有大量基于位置的信息，其中包括园丁在其所在地区种植的作物、品种和数量，今年他们将扩大记录范围，包括对农作物病虫害的过时观测(2014年5月推出)。基于事件的记录一直是他们软件最受欢迎的新功能，他们将增加社会反馈元素来奖励报道。我们建议将这些数据与气象信息一起进行统计分析，以开发作物病虫害发生的预测模型。通过开发先进的基于地图的可视化技术，可以深入分析大量从人群中获取的数据，并将其用于改进预测模型。然后，气象信息和天气预报可以为种植者提供针对其所在地区的当前生长季的显着改进的虫害预测。

Growing Interactive, the industrial lead partner of the project, produces the leading on-line software and apps that gardeners and small-scale farms use to plan the edible crops they grow and achieve increased levels of success. Over a quarter million gardeners and farmers have used their software and apps. They hold a wealth of location-based information on which crops, varieties and quantities gardeners are growing in their location and this year they are extending the recording to include dated observations of pests and diseases on crops (launching May 2014). Event-based journalling has been the most requested new feature for their software and they will be adding social feedback elements to reward reporting.We propose that this data be statistically analysed in conjunction with meteorological information to develop predictive models for pest and disease emergence on crops. By developing advanced map-based visualisations, the vast quantity of crowd-sourced data can be analysed in depth and used to refine predictive models. Meteorological information and weather forecasts can then provide significantly improved pest prediction for growers for the current growing season specific to their location.