Semios is a Vancouver-based data analytics company for growers of high-value crops such as almonds and apples. It uses a combination of machine learning, in-crop wireless networks and half a million IoT sensors across 80,000 acres to offer real-time monitoring that helps predict, identify and prevent pests and diseases while reducing pesticide use.
Along with other data piped in from third-party sources, this all adds up to more than 200,000 data points coming into its system every day – a number expected to double this year.
So when Semios needed to migrate from an on-premises solution to Google Cloud Platform, the company worked with Pythian, a Google Premium Partner, to transition and implement the company’s new data solution.
Semios now uses Google BigQuery to connect, integrate and analyze its data in real time. And along with the well-established benefits of moving their data warehouse to the cloud, the company can now also take advantage of features like Google’s Cloud Machine Learning Engine to use AI to identify pests, and Google Earth Engine to add geospatial information to the mix.
Check out the full case study at Google Cloud.
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