We recently covered Osram's acquisition of Fluence Bioengineering, but Osram made another acquisition in May that could prove to be a major boon in efficiency for their bid to be a leading supplier of horticultural lighting. Last month, Osram's venture capital firm, Fluxunit invested in Motorleaf, gaining a stake in the company.
Motorleaf is an artificial intelligence company based out of Montreal, Canada. Motorleaf uses data collected from their own greenhouses to implement predictive algorithms for similar growing situations. These algorithms are used to predict crop yields and ideal growing conditions using an array of cameras and sensors to collect data.
Although Motorleaf originally launched to help small-scale growers, the potential savings it can pass on to large-scale growers has attracted outside investors like OSRAM.
“We’re ultimately producing dynamic grower protocols, which help manage everything from light and nutrients to predicting crop diseases before they happen, and optimized growing conditions that increase ROI – all based on real-time data.” -Ulrich Eisele, Managing Director of Osram’s Fluxunit.
These boxes store and transmit data growth collected by the cameras and sensors around a facility. Image courtesy of Motorleaf.
|The Effect of Predictive Analysis for Indoor Grow Facilities|
When Osram acquired Fluence in May, their leadership emphasized the transition in agriculture from large, remote farms to grow houses in urban areas. They estimate that 40 percent of food is spoiled during the journey from where it's grown to supermarkets, and cited localized greenhouses as a solution to this problem. This is not so much of an issue for commercial cannabis growers, but the industry has its own pain points that Osram hopes to tackle.
Many greenhouses (For food products and cannabis) pre-sell their produce. If a crop yields less than predicted or takes longer to grow and harvest than originally predicted, growers can lose a lot of money. Motorleaf hopes their algorithms can reduce the margin of error in these processes in order to make indoor growing more profitable and less volatile. In an interview with the Montreal Gazette, Alastair Monk, co-founder of Motorleaf, estimated that current predictive analysis methods have an error rate of 20 to 30 percent, while Motorleaf's product, Agromist.AI has an error rate of less than 10 percent.
This graph shows the algorithm predicting on a weekly basis, compared to how a Motorleaf customer’s greenhouse predicted their yield. Courtesy of Motorleaf.
|What’s Next For OSRAM and Motorleaf?|
Osram already has a system for automating control of a facility called Lightelligence, which allows a user to control a facility with just a smartphone. Adding data from Agronomist.AI to their interface will make Osram's systems a comprehensive but modular “out of the box” solution for automated indoor growing systems, allowing growers to scale their systems gradually while maintaining efficiency.
As Osram continues to upgrade their software platforms for horticultural lighting, they hope to provide the standard solution for newer/smaller operations and large-scale growers alike. If these systems prove to be commercially successful, Lightelligence and Agronomist.AI could end up being the standard software interface for cannabis growers.
Are there any AI programs for horticultural lighting that you're excited about? Let us know in the comments!
