How M5Stack’s M5Stamp-Pico Powers a Smart, Wireless Plant Health Monitor with Color-Coding

by Anna

Researchers from Tohoku University’s Graduate School of Life Sciences and the Department of Electronic Engineering have developed an affordable wireless plant sensor that could improve agricultural monitoring. The sensor, which costs just “a few tens of dollars,” is built around an M5Stack M5Stamp-Pico and could offer more efficient plant health monitoring than current methods.

Kaori Kohzuma, first and co-corresponding author of the study, explained that while traditional monitoring methods are effective in some cases, they are often difficult to use and expensive. “To monitor small changes continuously, we needed a new solution,” she said. “This affordable sensor provides a promising way to monitor plant health and stress by analyzing leaf color and light reflection. Its low cost also makes it possible to place multiple sensors in different locations, creating a network for simultaneous monitoring.”

Ko-ichiro Miyamoto, co-corresponding author, emphasized the time-saving benefits of smart agriculture. “Farmers don’t have time to check each plant manually. This sensor offers real-time, detailed readings, allowing them to respond quickly to areas where plants are under stress.”

The sensor consists of two main components: a sensor head and a microcontroller. The sensor head, which attaches to the underside of leaves to avoid blocking sunlight, uses a DFRobot Gravity OSRAM AS7341 11-channel visible light sensor. It connects to an M5Stack M5Stamp-Pico Espressif ESP32-PICO-D4 microcontroller board via a custom carrier board. The entire unit is housed in 3D-printed cases, sealed with silicone to protect against weather, and powered by CR2 lithium batteries, which last for over a month.

Despite its low cost, the sensor system performed well in tests compared to a much more expensive commercial spectrometer. In field trials, the sensor tracked the chlorophyll levels and sunlight response of a birch tree’s leaves, demonstrating its potential for accurate agricultural monitoring.

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