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MIT is making outlets smarter and safer using the Internet of Things

Internal arc resistance is a major part of electrical safety, right down to the ground floor of household appliances. The identification and containment of internal arc faults is the main duty of switchgear, which is built with the ability to withstand them.

New research from the Mecca of Intelligent Techs is about to make arc fault science much smarter, and thereby safer and more efficient, by using the Internet of Things. MIT engineers have developed a solution to one of the main issues with internal arc resistance—its oversensitivity—during the creation of smart outlets, the esteemed Massachusetts college announced June 15.

The problem with today’s arc-fault detectors, according to a team of MIT engineers, is that they often err on the side of being overly sensitive, shutting off an outlet’s power in response to electrical signals that are actually harmless,” Jennifer Chu of MIT News reported, citing examples such as a vacuum cleaner turning off during mid-usage, or a lamp working fine until another appliance is plugged into the same power strip. These occurrences are often known as “nuisance trips”, and they are ultimately there for your safety.

But the MIT team, as well as experienced engineers and electricians the world over, understand all too well that these arc faults are not actually dangerous, and preventing them is actually a hindrance. It’s not the first time MIT’s research has disrupted familiar fixtures of life:

Now the team has developed a solution that they are calling a “smart power outlet,” in the form of a device that can analyze electrical current usage from a single or multiple outlets, and can distinguish between benign arcs — harmless electrical spikes such as those caused by common household appliances — and dangerous arcs, such as sparking that results from faulty wiring and could lead to a fire. The device can also be trained to identify what might be plugged into a particular outlet, such as a fan versus a desktop computer.

Like so many things in our brave new world of smart technology, the device itself does the “learning” and adapting for you. In this case the smart outlet will essentially become better at discerning between arc faults and arc flashes. A quick review, condensed from a description by Schneider Electric’s Didier Fulchiron:

An internal arc fault is one that occurs inside switchgear. The internal arc resistance of switchgear denotes its ability to withstand arc faults. And, should an arc fault occur, to contain it within a single compartment in the cubicle and divert the hot gases away from personnel. Switchgear is put through arc-fault tests to ensure it complies with international standards—IEEE, EEMAC, IEC, etc.

An arc flash is the often intense light and heat produced by an arc fault. It happens when two bare live conductors come together and endangers operating and maintenance personnel. Direct exposure to such heat radiation can cause severe burn injuries.

Arc flashes have little to do with devices. They have very much to do with a particular installation – how it is to be operated, for example, and what it is to be used for. Other factors in arc flash hazards are: the installation’s short-circuit current, its protection relay settings, and the duration of the fault current flow.

Joshua Siegel, a research scientist in MIT’s Department of Mechanical Engineering, says the smart power outlet is able to connect to other devices wirelessly, as part of the IoT. He hopes this will ultimately form into a full 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 analyze and share data on their electrical usage, Chu reported: “These data, such as what appliances are plugged in where, and when an outlet has actually tripped and why, would be securely and anonymously shared with the team to further refine their machine-learning algorithm, making it easier to identify a machine and to distinguish a dangerous event from a benign one.”

“By making IoT capable of learning, you’re able to constantly update the system, so that your vacuum cleaner may trigger the circuit breaker once or twice the first week, but it’ll get smarter over time,” Siegel says. “By the time that you have 1,000 or 10,000 users contributing to the model, very few people will experience these nuisance trips because there’s so much data aggregated from so many different houses.”

Siegel and his colleagues have published their results in the journal Engineering Applications of Artificial Intelligence. His co-authors are Shane Pratt, Yongbin Sun, and Sanjay Sarma, the Fred Fort Flowers and Daniel Fort Flowers Professor of Mechanical Engineering and vice president of open learning at MIT.


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