The immense traffic on the roads is haunting the civil planners, car manufacturers, and fluid dynamic professors. Just counting cars on the road doesn’t give a solution, but the analyzing the data behind the number of cars can find the solution. CMU researchers show that electricity usage may be key to understand high movement in the city.

The idea of relating the traffic and electricity is fare as when the user is at home, they turn the lights on which indicates that they are at home. Likewise, the morning peak congestion times are clearly related to the theory of usage of electricity pattern.

Sean Qian, who led the study explained the theory they observed the electricity usage from 322 houses over 79 days, they trained the machine learning models and saved the usage of patterns within it. The model learned the pattern including the number of household power use former than usual.

The researchers claimed that their predictions of traffic pattern were accurate with this idea than actual data like a number of cars. Particularly, it requires the electricity usage, said Qian. It doesn’t require any other personal data. They just required to know the pattern of the usage of the electricity.

The correlation between electricity usage and traffic pattern could predict the usage of the electricity and its demand. There are numerous factors like water use and mobile phone connections usage which sign the dynamic and motivation of city life. Traffic is just a small factor to which is the city is struggling to operate and dealing with.

This study was limited to electricity usage and providers are unwilling to share their data of usage.