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CropEYEs: A Low-Cost Camera IoT Network to Intelligently Track Crop Productivity

Project Team

Abstract

Photosynthesis is the process that plants uptake carbon for growth that directly determines crop productivity. However, existing crop growth monitoring solutions only provide vegetation index, canopy height, or leaf area index, but not photosynthesis. Moreover, many of them are neither spatially-representative nor temporally-continuous, due to the high costs of the platforms, which has severely hampered the promotion of precision agriculture. To fill this gap, we propose to create a novel low-cost camera network, CropEYEs, to track crop photosynthesis by integrating Internet of Things (IoT), computer vision, machine learning, and agro-ecosystem models. CropEYEs will observe crops at different positions in different times from different directions with different types of cameras, analyze the acquired big data to enable a comprehensive and deep understanding of crop growth, and finally predict crop photosynthesis at field level in real time. To achieve this objective, we will deploy two camera networks in the University of Illinois Energy Farm for soybean and corn monitoring, respectively. We will use Amazon Web Service (AWS) to extract useful information from images, estimate essential crop biophysical variables, and predict crop photosynthesis. We will also use carbon flux observed by eddy covariance towers in the University of Illinois Energy Farm to evaluate CropEYEs-derived crop photosynthesis. The estimated cost of one CropEYEs node is about $600, which is only about half of the most popular solution in the market (e.g., Arable Mark), but with a much more powerful feature as CropEYEs watches crop photosynthesis (e.g., Arable Mark only provides a proxy indicator, NDVI). This proposal directly addresses the targeted topic area of CDA’s Animals and Crops theme: “real-time on-farm data can facilitate research on field performance and improved cultivation practices.” We plan to disseminate CropEYEs to a broad range of users and occupy the big market of precision agriculture.