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Development of IoT-based camera system for automated in-field monitoring to support crop breeding Programs
  • +2
  • Worasit Sangjan,
  • Nisit Pukrongta,
  • Arron H Carter,
  • Michael O Pumphrey,
  • Sindhuja Sankaran
Worasit Sangjan
Department of Biological Systems Engineering, Washington State University

Corresponding Author:[email protected]

Author Profile
Nisit Pukrongta
Department of Biological Systems Engineering, Washington State University
Arron H Carter
Department of Crop and Soil Sciences, Washington State University
Michael O Pumphrey
Department of Crop and Soil Sciences, Washington State University
Sindhuja Sankaran
Department of Biological Systems Engineering, Washington State University

Abstract

Automated monitoring and evaluation systems for plant phenotyping are one of the keys to advance and strengthen crop breeding programs. In this study, the improvements of the camera-based sensor system and a weather station from a previous study-assembled mainly from Raspberry Pi products-board with dual cameras (RGB and NoIR) providing high spatial and temporal resolution data-is outlined. Hardware for the internet connection and the power supply system of the sensor were upgraded. Previously, the sensor could automatically capture plant images following user-defined time points; thus, an image processing algorithm (edge computing) was developed and installed to extract digital phenotypic traits from the images after capturing process. With the development, the new sensor system could be integrated with the internet, and a cloud server was configured to store data online (digital traits and raw images). A real-time monitoring system was created to visualize the time series data of a trait development and plant images throughout the season. With such a system, plant breeders will be able to monitor multiple trials for timely crop management and decision-making process, which is also resources efficiency.
28 Oct 2022Submitted to NAPPN 2023 Conference Papers
29 Oct 2022Published in NAPPN 2023 Conference Papers