Climate change, CSR, rising energy prices and GHG emission limits contribute to increasing investments and adaptation of renewable energy as well as green and smart solutions that decrease resource consumption, introduce efficiency and sustainable use of resources. In results, variety of sensors are placed in green/smart cities, smart buildings, smart grids or assets producing renewable energy, which generate vast amount of data. By applying advanced analytics and artificial intelligence to that data we can discover hidden patterns, predict further states, simulate potential outcomes and foster autonomous decision making.

– Resilience – impact of weather changes on environment, cities, businesses and buildings with simulations, reinforcement learning and autonomous numerous agents & data sources.
– Smart grids –  optimising grid stability, demand forecast, storage and peak management of different source of energy (including wind, solar, hydro, gas) with support of weather data, predictive ML algorithms and simulations.
– Asset failure – analyse data from various asset sensors and predict potential failure (predictive maintenance) of smart grid components based on IIoT, asset vibration, temperature and other symptoms of degradation. In result, reduce downtime of wind turbines, solar panels, smart meters, storage and other components.
– Smart building – with sensor data in relation to energy consumption, water usage, occupancy and weather optimize building automation to adapt to tenants’ behaviour, increase their wellbeing and substantially, reduce resource usage (electricity, gas, water and waste production).

For more examples of our custom solutions for CleanTech, sustainability and renewable energy please navigate to smart building, smart cities and energy sections.