Cornell's VibroSense makes appliances 'smart' by tracking their vibrations

A new device developed by a team of researchers at Cornell University can identify and categorize home appliances by the specific vibrations they produce in your home as those vibrations travel from room to room.

With the help of a machine learning algorithm and lasers, it can track up to 17 different household activities with 96 percent accuracy.

Those activities can be anything from a dripping faucet to an electric kettle that just brought water to a boil. The device can also differentiate between different stages of appliance usage with 97 percent accuracy.