Quby is the technology company behind Toon, the smart energy management device that gives people control over their energy usage, their comfort, the security of their homes, and much more. Quby's smart devices are in hundreds of thousands of homes across Europe. As such, they maintain Europe’s largest energy dataset, consisting of petabytes of IoT data, collected from sensors on appliances throughout the home. With this data they are on a mission to help their customers live more comfortable lives while reducing energy consumption through personalized energy usage recommendations.
Personalized Energy Usage Recommendations – Leverage machine learning and IOT data to power their Waste Checker app which provides personalized recommendations to reduce in-home energy consumption.
Through their connected home platform Quby is on a mission to improve the lives of their customers while helping reduce their energy footprint. Core this strategy is analyzing the 3+ petabytes of appliance and energy usage data they’ve collected from hundreds of thousands of homes in Europe. On top of that is managing over 1 million unsupervised machine learning models to power the personalized recommendations delivered through their Waste Checker app. As Quby built out these capabilities they ran into a number of challenges:
Databricks provides Quby with a Unified Data Analytics Platform that has fostered a scalable and collaborative environment across data science and engineering, allowing data teams to more quickly innovate and deliver ML-powered services to Quby’s customers.
With Databricks, Quby has been able to deliver on their mission: leverage machine learning to improve the comfort and lives of their customers while helping reduce energy consumption.
Databricks, through the power of Delta Lake and Structured Streaming, allows us to deliver alerts and recommendations to our customers with a very limited latency, so they’re able to react to problems or make adjustments within their home before it affects their comfort levels.