With transforming times, energy consumption is also transforming. Machine learning systems and smart meters can dramatically change energy consumption.
Fremont, CA: For decades, the government has been running a drive to help consumers cut their fuel bills. The government has introduced intelligent meters to show consumers how much energy they are utilizing with modern technology. The first step to inducing change is getting exact data and building machine learning models to understand how energy is used.
Energy companies are working tirelessly to develop products that help households save as much energy as possible. The machine learning models developed by these companies inform house owners about their energy usage and how their heating can be improved to reduce gas. One of the issues the innovative energy companies face is building a utilization model. Data is paramount when it comes to constructing a machine learning model.
These intelligent energy companies collect terabytes of raw data from customers who installed smart plugs in their houses to give detailed information on energy consumption. This granular data helps create a training set used to build the machine learning models.
Though, not all customers are willing to install smart plugs. As a substitute, energy companies gather data with the support of housebuilders to add smart data devices to fuse boxes that give granularity based on what each fuses control. The detailed data clarifies the identification of usage patterns and classes of devices.
The government needs accurate insights to change the behavior of consumers. The government had limited success in inflicting change due to the inability to show the dissimilarity between old energy-guzzling and energy-saving appliances. Smart energy companies can offer accurate data on the cost of using specific machines. This signifies that they can inform customers about the consumption of a particular device and give a reasonable estimate of savings.
Smart energy companies guarantee that the collected customer data is encrypted and sent back through a VPN over the customer’s internet connection. Data securities prevent criminals from accessing data and use it to know when a household is unoccupied.
Machine learning systems are used to help organizations improve their revenue and profits. It is uncommon to witness these systems used to help households save money. Still, in the long-term, leveraging machine learning models will assist in reducing energy consumption which will further promote the usage of renewable energy.
