Home gardening isn’t just a hobby for Kevron Rees, it’s a way to support his family by growing enough produce to feed his family and save money. He used his background in technology to make a value proposition for the home greenhouse.
Kevron integrated the ScienceLogic platform to monitor what was happening in his garden and automate some of the processes to take care of it. Machine learning was key to refine and advance the capabilities of ScienceLogic. For instance, the temperature in the greenhouse was getting too high. Kevron wanted to proactively cool his water reservoir during the night hours, but that meant closely monitoring and being able to predict the future temperature in his greenhouse. He gathers input data from ScienceLogic and uses machine learning to accurately predict the temperature inside the greenhouse.
ScienceLogic’s open API means Kevron can use any machine learning software to manage his garden. Feeding that machine learning data back into ScienceLogic allows for automations that make the greenhouse even more efficient and successful than before.Watch our earlier video, IoT Gardening Using ScienceLogic