Abstract Detail



Biodiversity Informatics & Herbarium Digitization

Grindstaff , Brandin Alexander,Gage [1], Mabry, Makenzie [2], PIRES , JOSEPH CHRIS [3].

Big Data Revolution in Plant Science: Affordable Remote Sensing using Raspberry Pi’s.

Using the Raspberry Pi as a platform, we have been developing affordable ways to remotely monitor plants in growth chambers and greenhouses. The primary data being collected has been photographs, short videos, temperature, and humidity. The small, credit card sized computer, paired with a mobile phone sized camera, a DHT temperature/humidity sensor, and access to the internet allows for precise monitoring of experiments for around 100 dollars. The programming of cameras, sensors, and other components that would have required an advanced understanding of computer science a decade ago, can now be done with ease using free, open source Python function libraries such as “ADAfruit_Python_DHT” from GitHub, or “python-picamera”, a python library from raspberrypi.org.  The camera will be set up to collect live video and photos in a multitude of configurations and be able to log that data onboard or remotely as backup. Most of these functions can be utilized through Putty, a secure Shell program, which is essentially a remote command prompt.  These devices are revolutionizing the affordable acquisition of “Big Data” by collecting data at any time of the day, autonomously, that can be viewed from anywhere with internet access. 


1 - University of Missouri, Biological Science, Columbia, MO, 65201, USA
2 - University Of Missouri, Biological Sciences, 1201 Rollins St., Columbia, MO, 65201, United States
3 - University Of Missouri, 371 Bond Life Sciences Center, 1201 Rollins Street, Columbia, MO, 65211, United States

Keywords:
Raspberry Pi
Remote Sensing
Phenotyping.

Presentation Type: Poster
Number: PBI001
Abstract ID:123
Candidate for Awards:None


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