The Project

The customer is a Norwegian service company, specializing in smart energy solutions with the overarching goal of enhancing system efficiency and promoting sustainable resource utilization worldwide.

The company’s AI-driven platform optimizes energy consumption in buildings and factories by leveraging real-time data from strategically placed sensors. Using machine learning algorithms, it analyzes key factors such as temperature, CO2 consumption, electricity prices (sourced from energy exchanges), weather forecasts, and other relevant parameters. Based on this data, the system intelligently adjusts set points for HVAC systems, heating, and other energy-consuming devices to maximize efficiency and reduce costs.

Our partner embarked on the development of this platform from the ground up. Today, it has evolved into a full-scale, feature-rich solution offering extensive functionality and customization options.

Additionally, their team has been dedicated to refining algorithms for ventilation and temperature regulation, further enhancing the system’s performance.

Currently, the client’s solutions are deployed across 45 buildings, covering a total area of 240,489 m² — a number that continues to grow steadily.

Technologies

Ruby on Rails, Influx, Esbuild, React, Grafana, Ruby, JS, Flux, Python, Mqtt, WSDL, pandas, numpy, sklearn, plotly, Honeybadger, Telegraf

Team

TM, 1-3 developers