Ag-IoT for crop and environment monitoring: Past, present, and future

Nipuna Chamara, Md Didarul Islam, Bai, Geng (Frank), Yeyin Shi and Yufeng Ge

Agricultural Systems, 2022, vol. 203, issue C

Abstract: Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task.

Keywords: Internet of things; Sensor network; Artificial intelligence; Machine learning; Precision agriculture; Wireless communication (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:203:y:2022:i:c:s0308521x22001330

DOI: 10.1016/j.agsy.2022.103497

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