The technology of handling big data has opened up the possibility of optimizing processes that we have
known about and that we have been perfecting for centuries. This new data-driven perspective of looking at problems, allows us to look at problems more concretely and realistically, solve them in real-
time, and by using mathematical models, predict yields and find the best solutions. In short, we want to
get more and invest less – less space, less water and nutrients, and less mechanization but have more
yields and better utilization.
The BioSens Institute has developed the Plant-o-meter, a device that uses machine learning algorithms
and big data analytics to analyse crops and monitor plants in real-time. Through optical sensors, the
device collects in real time more than 20 vegetation indices that signal the existence of drought, heat,
poor nutrition or stress caused by pests in different stages of crop growth. The device allows
observation of plants outside the visible spectrum, detection of stress due to lack of water or nutrients,
as well as assessment of plant health. The Plant-o-meter uses four wavelengths (infrared, red, green and
blue) to analyse plants and transmits the measured data via Bluetooth connection to a smartphone,
which calculates optical vegetation indices that are indicators of the plant’s condition. The result is a
reduction in fertilizer costs of up to 25%, a 3-4% crop yield increase for grains and oilseeds and, perhaps
most importantly, a reduction in carbon footprint.