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Our customer approached us with a request to collaborate on an AI extension for one of their products.
The objective? Optimizing energy flows in their customers' homes based on dynamic pricing, charging needs, and consumption patterns. The result? Their customers can save time and money while also contributing to a sustainable future.
For example: to determine the best charging times, we implemented advanced scheduling techniques utilizing reinforcement learning. Additionally, forecasting algorithms were employed to accurately predict non-controllable energy consumption, which is crucial for effective future planning.
It's a challenging project that we're excited to be a part of!
Curious about how we did it? Adriaan and Martijn will explain you what it is all about in this TechTalk.
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