By Morgen Henderson

Smart Homes and AI for humans is monitoring our energy use. We think it is tough because our lives are in constant flux. Weather conditions change, our energy needs shift, and technology evolves. To maximize energy efficiency, we have to be good at predicting future needs and making adjustments.

That’s where artificial intelligence (AI) excels.

For it can help us live greener lives. AI helps automate tasks and also meet the customized energy needs of consumers and businesses. It can also predict our resource consumption. As well as help promote renewable energy. So here are some specific ways AI can help the planet.

Smart home energy savings

Smart Home Energy Savings

Artificial intelligence is also a key ingredient in running devices and homes. All connected to the internet. These “smart” homes save energy by automating tasks and predicting resource needs based on past activity. Over time, this can lower your monthly utility bills. 

Your home’s thermostat is a great example of the green benefits that AI and smart homes provide. It’s common to adjust your thermostat based on the time of day or season. We adjust our thermostat when we’re on vacation, at night, or when the weather changes. And we only turn the thermostat back down when it’s too warm, or we leave for work without turning it down at all. These ups and downs use extra energy that affects our energy bills. Smart thermostats help us avoid these mistakes by automating the process, and they let us control our HVAC systems from our smartphones when we forget

nest thermostat

Predicting Problems Before They Happen

Energy conservation involves avoiding the high energy and financial costs of equipment breakdown. If our lawn sprinklers are leaking, they will still keep our grass green. However, the leak means they’re not efficient. The longer the problem persists, the more water wasted and damage done to the entire system.

Today’s AI technology can monitor home appliances for breakdowns and even “listen” to wind turbines noises to detect problems. The rise of AI and “predictive maintenance” is helping traditional industries like manufacturing cut financial costs and energy wastes. That means less expensive goods and fewer resources used. For homeowners, devices like leak detectors save water and halt damage to interior floors and walls.

Customizing Energy Use

Along with all its power to predict and automate, AI’s biggest promise is its ability to customize energy use. The same predictive algorithms that run the electrical grids and water networks are becoming standard in homes and businesses. Today’s virtual “assistants” for consumers (e.g., Google Home Hub, Amazon Alexa) all use AI to predict our future needs. More importantly, these assistants are being used to run all our smart devices. 

Alexa customizing energy use

We already experience these types of AI monitoring for many of our devices — like our smartphones. Google’s Android algorithm studies what apps you use and how you use them. It optimizes frequently accessed apps and turns off less popular ones to conserve battery energy. Given that two-thirds of the world’s population is now connected by mobile device, smartphone AI offers significant energy savings.

Smart home appliances can also customize our energy consumption. Smart home hubs can manage smart devices like hot water tanks and HVAC systems — running them during “off-peak” hours when demand and costs are lower. And devices like smart sprinkler systems use weather forecasts to determine the best times to water your lawn. 

Moving Us to Renewable Energy

There are plenty of reasons to be skeptical about turning over our energy decisions to machines. But there’s no denying that AI is better at predicting and customizing our energy uses. And the interconnectivity that AI offers will make renewable energy sources like wind and solar more popular. Complex machine learning combined with weather forecasting models will be able to predict the best times to switch to wind and solar. This will normalize renewable energy — something critical to widespread adoption.

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