and self-driving cars ( interpreting sensor data to navigate safely ).
The technology can also have a positive effect on climate change , particularly when aimed specifically at the energy system . Energy grids , interconnected networks that generate , transmit and distribute electricity , are often a large source of domestic pollution for a country due to the fossil fuels by which they are typically powered .
The entire grid is constantly monitored and adjusted to ensure a continuous flow of electricity , balancing supply and
fluctuating demand in real time to stop blackouts . It ’ s this balancing of demand and supply where ML comes into play . “ Machine learning can be used to analyse vast amounts of data on energy consumption and predict demand ,” explains Erik Terjesen , Partner at Silicon Foundry , a subsidiary of Kearney . “ This helps optimise energy production and distribution in electricity grids , reducing reliance on fossil fuels .”
By using ML to analyse the masses of data taken from the grid , it can signal when demand will be high and changes can be made to factor this in .
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