Real-time Geoinformation Systems to Improve the Quality, Scalability, and Cost of Internet of Things for Agri-environment Research
arxiv(2024)
摘要
With the increasing emphasis on machine learning and artificial intelligence
to drive knowledge discovery in the agricultural sciences, spatial internet of
things (IoT) technologies have become increasingly important for collecting
real-time, high resolution data for these models. However, managing large
fleets of devices while maintaining high data quality remains an ongoing
challenge as scientists iterate from prototype to mature end-to-end
applications. Here, we provide a set of case studies using the framework of
technology readiness levels for an open source spatial IoT system. The spatial
IoT systems underwent 3 major and 14 minor system versions, had over 2,727
devices manufactured both in academic and commercial contexts, and are either
in active or planned deployment across four continents. Our results show the
evolution of a generalizable, open source spatial IoT system designed for
agricultural scientists, and provide a model for academic researchers to
overcome the challenges that exist in going from one-off prototypes to
thousands of internet-connected devices.
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