{"id":389,"date":"2018-06-19T15:25:08","date_gmt":"2018-06-19T15:25:08","guid":{"rendered":"http:\/\/jpelectricalcompany.com\/blog\/?p=389"},"modified":"2021-02-12T16:06:51","modified_gmt":"2021-02-12T16:06:51","slug":"mit-engineers-build-smart-power-outlet","status":"publish","type":"post","link":"https:\/\/www.jpelectricalcompany.com\/blog\/uncategorized\/mit-engineers-build-smart-power-outlet\/","title":{"rendered":"MIT engineers build smart power outlet"},"content":{"rendered":"<div class=\"view view-news-article-top-slideshow-flexslider view-id-news_article_top_slideshow_flexslider view-display-id-block article-top-slideshow-flexslider view-dom-id-2dc4a7e74ece6a1cef2fece0250f9600\">\n<div class=\"view-main-section\">\n<div class=\"view-content\">\n<div class=\"flexslider\">\n<div class=\"flex-viewport\">\n<ul class=\"slides\">\n<li class=\"clone\" aria-hidden=\"true\">\n<div class=\"slide-wrapper\">\n<div class=\"descr\">\n<div class=\"text\">\n<p class=\"caption\">A team of MIT engineers has developed a \u201csmart power outlet\u201d in the form of a device that can analyze electrical current usage from a single or multiple outlets.<\/p>\n<p class=\"credits\">Image: Christine Daniloff, MI<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<header>\n<div class=\"content-sides-padding\">\n<div class=\"article-header\">\n<p id=\"article-summary\">Design can \u201clearn\u201d to identify plugged-in appliances, distinguish dangerous electrical spikes from benign ones.<\/p>\n<\/div>\n<\/div>\n<\/header>\n<div class=\"columns-container-1 clearfix\">\n<div class=\"column-1\">\n<div id=\"article-body-main\" class=\"content-sides-padding\">\n<div class=\"region region-content\">\n<div id=\"block-system-main\" class=\"block block-system\">\n<div class=\"content\">\n<div class=\"field field-name-field-article-content field-type-text-long field-label-hidden\">\n<div class=\"field-items\">\n<div class=\"field-item even\">\n<p>Have you ever plugged in a vacuum cleaner, only to have it turn off without warning before the job is done? Or perhaps your desk lamp works fine, until you turn on the air conditioner that\u2019s plugged into the same power strip.<\/p>\n<p>These interruptions are likely \u201cnuisance trips,\u201d in which a detector installed behind the wall trips an outlet\u2019s electrical circuit when it senses something that could be an arc-fault \u2014 a potentially dangerous spark in the electric line.<\/p>\n<p>The problem with today\u2019s 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\u2019s power in response to electrical signals that are actually harmless.<\/p>\n<p>Now the team has developed a solution that they are calling a \u201csmart power outlet,\u201d in the form of a device that can analyze electrical current usage from a single or multiple outlets, and can distinguish between benign arcs \u2014 harmless electrical spikes such as those caused by common household appliances \u2014 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.<\/p>\n<p>The team\u2019s design comprises custom hardware that processes electrical current data in real-time, and software that analyzes the data via a neural network \u2014 a set of machine learning algorithms that are inspired by the workings of the human brain.<\/p>\n<p>In this case, the team\u2019s machine-learning algorithm 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 \u201cfingerprints\u201d used to differentiate good from bad, or even to distinguish one appliance from another.<\/p>\n<p>Joshua Siegel, a research scientist in MIT\u2019s Department of Mechanical Engineering, says the smart power outlet is able to connect to other devices wirelessly, as part of the \u201cinternet of things\u201d (IoT). He ultimately envisions 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 analyze and share data on their electrical usage. 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.<\/p>\n<p>\u201cBy making IoT capable of learning, you\u2019re able to constantly update the system, so that your vacuum cleaner may trigger the <a href=\"https:\/\/www.jpelectricalcompany.com\">circuit breaker<\/a> once or twice the first week, but it\u2019ll get smarter over time,\u201d Siegel says. \u201cBy 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\u2019s so much data aggregated from so many different houses.\u201d<\/p>\n<p>Siegel and his colleagues have published their results in the journal <em>Engineering Applications of Artificial Intelligence. <\/em>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.<\/p>\n<p><strong>Electrical fingerprints<\/strong><\/p>\n<p>To reduce the risk of fire, modern homes may make use of an arc fault circuit interrupter (AFCI), a device that interrupts faulty circuits when it senses certain potentially dangerous electrical patterns.<\/p>\n<p>\u201cAll 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,\u201d Pratt says.<\/p>\n<p>Pratt and Siegel set out to design a more discerning detector that can discriminate between a multitude of signals to tell a benign electrical pattern from a potentially harmful one.<\/p>\n<p>Their 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\u2019s wire without actually touching it, which senses the passing current as a changing magnetic field.<\/p>\n<p>Between the current clamp and the microcomputer, the team connected a USB sound card, commodity hardware similar to what is found in conventional computers, which they used to read the incoming current data. The team found such 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, similar to what would be given off by an electrical wire.<\/p>\n<p>The sound card also came with other advantages, including a built-in analog-to-digital converter which samples signals at 48 kiloherz, meaning that it takes measurements 48,000 times a second, and an integrated memory buffer, enabling the team\u2019s device to monitor electrical activity continuously, in real-time.<\/p>\n<p>In addition to recording incoming data, much of the microcomputer\u2019s processing power is devoted to running a neural network. For their study, they trained the network to establish \u201cdefinitions,\u201d or recognize associated electrical patterns, produced by four device configurations: a fan, an iMac computer, a stovetop burner, and an ozone generator \u2014 a type of air purifier that produces ozone by electrically charging oxygen in the air, which can produce a reaction similar to a dangerous arc-fault.<\/p>\n<p>The team ran each device numerous times over a range of conditions, gathering data which they fed into the neural network.<\/p>\n<p>\u201cWe create fingerprints of current data, and we\u2019re labeling them as good or bad, or what individual device they are,\u201d Siegel says. \u201cThere are the good fingerprints, and then the fingerprints of the things that burn your house down. Our job in the near-term is to figure out what\u2019s going to burn down your house and what won\u2019t, and in the long-term, figure out exactly what\u2019s plugged in where.\u201d<\/p>\n<p><strong>\u201cShifting intelligence\u201d<\/strong><\/p>\n<p>After training the network, they ran their whole setup \u2014 hardware and software \u2014 on new data from the same four devices, and found it was able to discern between the four types of devices (for example, a fan versus a computer) with 95.61 percent accuracy. In identifying good from bad signals, the system achieved 99.95 percent accuracy \u2014 slightly higher than existing AFCIs. The system was also able to react quickly and trip a circuit in under 250 milliseconds, matching the performance of contemporary, certified arc detectors.<\/p>\n<p>Siegel says their smart power outlet design will only get more intelligent with increasing data. He envisions running a neural network over the internet, where other users can connect to it and report on their electrical usage, providing additional data to the network that helps it to learn new definitions and associate new electrical patterns with new appliances and devices. These new definitions would then get shared wirelessly to users\u2019 outlets, improving their performance,and reducing the risk of nuisance trips without compromising safety.<\/p>\n<p>\u201cThe challenge is, if we\u2019re trying to detect a million different devices that get plugged in, you have to incentivize people to share that information with you,\u201d Siegel says. \u201cBut there are enough people like us who will see this device and install it in their house and will want to train it.\u201d<\/p>\n<p>Beyond electrical outlets, Siegel sees the team\u2019s results as a proof of concept for \u201cpervasive intelligence,\u201d and a world made up of everyday devices and appliances that are intelligent, self-diagnostic, and responsive to people\u2019s needs.<\/p>\n<p>\u201cThis is all shifting intelligence to the edge, as opposed to on a server or a data center or a desktop computer,\u201d Siegel says. \u201cI think the larger goal is to have everything connected, all of the time, for a smarter, more interconnected world. That\u2019s the vision I want to see.\u201d<\/p>\n<p>Original Source: http:\/\/news.mit.edu\/2018\/mit-engineers-build-smart-power-outlet-0615<\/p>\n<p>Original Date: June 15, 2018<\/p>\n<p>Written BY: Jennifer Chu | MIT News Office<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>A team of MIT engineers has developed a \u201csmart power outlet\u201d in the form of a device that can analyze electrical current usage from a single or multiple outlets. Image: Christine Daniloff, MI Design can \u201clearn\u201d to identify plugged-in appliances, distinguish dangerous electrical spikes from benign ones. Have you ever plugged in a vacuum cleaner,&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-389","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MIT engineers build smart power outlet - Blog | J&amp;P Electrical<\/title>\n<meta name=\"description\" content=\"MIT engineers build smart power outlet - A team of MIT engineers has developed a \u201csmart power outlet\u201d in the form of a device that can analyze electrical current usage from a single or multiple- Read up on some news and events occurring in the electrical component industry.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.jpelectricalcompany.com\/blog\/uncategorized\/mit-engineers-build-smart-power-outlet\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MIT engineers build smart power outlet - 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