However, according to MIT current AFCIs are overly sensitive, switching off an outlet’s power in response to electrical signals that are in fact harmless.
In response, MIT has developed what it’s calling a ‘smart power outlet,’ designed to analyse electrical current usage from a single or multiple outlets, and distinguish between benign fault-arcs and dangerous ones.
The device can also be trained to identify what might be plugged into a particular outlet, such as a fan versus a desktop computer, MIT adds.
The team’s design comprises custom hardware that processes electrical current data in real-time, and software that analyses the data via a neural network – a set of machine learning algorithms. This is programmed to determine whether a signal is harmful or not by comparing a captured signal to others that the researchers previously used to train the system. The more data the network is exposed to, the more accurately it can learn characteristic ‘fingerprints’ used to differentiate good from bad, or even to distinguish one appliance from another.
“All the AFCI models we took apart had little microprocessors in them, and they were running a regular algorithm that looked for fairly primitive, simple signatures of an arc,” explains co-author Shane Pratt.
The MIT hardware setup consists of a Raspberry Pi Model 3 microcomputer, a low-cost, power-efficient processor which records incoming electrical current data; and an inductive current clamp that fixes around an outlet’s wire without actually touching it, which senses the passing current as a changing magnetic field.
Between the current clamp and the microcomputer, the team connected a USB sound card to read the incoming current data. According to MIT, sound cards are ideally suited to capturing the type of data that is produced by electronic circuits, as they are designed to pick up very small signals at high data rates.
The sound card also came with other advantages, including a built-in analog-to-digital converter which samples signals at 48KHz, meaning that it takes measurements 48,000 times a second, and an integrated memory buffer, enabling the team’s device to monitor electrical activity continuously, in real-time.
The smart power outlet is able to connect to other devices wirelessly, as part of the Internet of Things and the team ultimately, envision a pervasive network in which customers can install not only a smart power outlet in their homes, but also an app on their phone, through which they can analyse and share data on their electrical usage.
“The challenge,” Joshua Siegel, a research scientist in MIT’s Department of Mechanical Engineering, says, “is if we’re trying to detect a million different devices that get plugged in, you have to incentivise people to share that information with you.”
