A Smart Home System That Respects Privacy

The new device from MIT’s Media Lab relies on passive carbon dioxide and infrared sensors

2 min read
Illustration shows the shape of a house. On/off power symbols and a wifi signal icon form a smiling face
A Smart Home System That Respects Privacy
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This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

By sensing human activity and adjusting the environmental settings accordingly, smart-home systems could help create more energy-efficient and sustainable buildings. However, there have been privacy concerns when it comes to these systems monitoring peoples’ activity, and smart-home systems can require heavy amounts of data crunching to learn how to respond to a given environment.

A new smart system, dubbed Chameleon, is designed to address both of these issues. It was recently tested in two different environments over the course of a month, and could predict human activity with 87 to 99 percent accuracy after just one week of training. The results are described in a study published 6 April in IEEE Internet of Things Journal.

Andres Rico is a graduate research assistant at the MIT Media Lab’s City Science Group who was involved in the study. He and his colleagues built their system around carbon dioxide and passive infrared (PIR) sensors.

“Carbon dioxide and PIR data inherently are not intrusive,” explains Rico, noting that systems based on cameras or other optical systems can raise privacy concerns.

Carbon dioxide and infrared sensing could be useful for estimating a variety of scenarios, such as the number of people in a room and how heavily they are breathing, which can indicate resting or active states. Each scenario has unique carbon dioxide and infrared signatures which can be analyzed using machine learning.

The Chameleon smart-home system uses both supervised and unsupervised machine-learning algorithms. As a result, the system already has some general knowledge on how to assess any environment, but it can also learn to distinguish the unique variables of its new environment too. This combination can reduce the time and costs associated with calibrating and maintaining the system, says Rico.

Front and back views of a sensor system showing circuit boards in a translucent shell. Holes on the front side are labelled "CO2 ventilation grid"The new Chameleon wall-mounted smart system has an infrared and CO₂ sensor modules connected to a Wi-Fi-enabled microcontroller. MIT Media Lab

The MIT researchers put Chameleon to the test in two different environments: an office with a handful of employees and a classroom that had 15 to 20 occupants on any given day. All components—including the circuit board and carbon dioxide and PIR sensors—were combined onto a single unit and mounted on a wall.

Although the study ran for a month, the results show that the smart-home system was able to classify the activities being done in the rooms with high accuracy after just one week of training. “The system delivers these results within rooms that are entirely different—this is very valuable for scaling these devices to more buildings and use cases,” says Rico.

He says his team hopes to incorporate Chameleon into more real-world spaces, helping to create smarter buildings. For example, it could help a single room be used for a wide variety of activities (for example, video meeting, exercising, sleeping, and having a meal with friends) and respond appropriately to each.

“These systems can also be integrated into digital urban-planning processes so as to inform communities on how they are using spaces in order to build consensus about policies to change, operate, and maintain offices, classrooms, parks, homes, etc.” says Rico.

The Conversation (3)
Antoni Grzanka03 May, 2022
SM

I am thinking of practicing for my Public Health students for an IoT lecture. What could it be?

Robert Klammer21 Apr, 2022
LM

What do they mean it doesn't have the privacy concerns? Just as meta data is more valuable for collecting personal information than reading the content of emails, the infrared and CO2 data will provide far more personal information than an ordinary security camera. Is it falsely being presented this way to an unsuspecting public to allow its widespread acceptance - just as the public is reassured that Homeland Security only collects meta data? I can't think of another reason other than the developers are too stupid to understand this technology's potential. But I doubt that is the case. These guys know exactly what they're doing, and who the largest consumer of the data is going to be.

1 Reply

Will AI Steal Submarines’ Stealth?

Better detection will make the oceans transparent—and perhaps doom mutually assured destruction

11 min read
A photo of a submarine in the water under a partly cloudy sky.

The Virginia-class fast attack submarine USS Virginia cruises through the Mediterranean in 2010. Back then, it could effectively disappear just by diving.

U.S. Navy

Submarines are valued primarily for their ability to hide. The assurance that submarines would likely survive the first missile strike in a nuclear war and thus be able to respond by launching missiles in a second strike is key to the strategy of deterrence known as mutually assured destruction. Any new technology that might render the oceans effectively transparent, making it trivial to spot lurking submarines, could thus undermine the peace of the world. For nearly a century, naval engineers have striven to develop ever-faster, ever-quieter submarines. But they have worked just as hard at advancing a wide array of radar, sonar, and other technologies designed to detect, target, and eliminate enemy submarines.

The balance seemed to turn with the emergence of nuclear-powered submarines in the early 1960s. In a 2015 study for the Center for Strategic and Budgetary Assessment, Bryan Clark, a naval specialist now at the Hudson Institute, noted that the ability of these boats to remain submerged for long periods of time made them “nearly impossible to find with radar and active sonar.” But even these stealthy submarines produce subtle, very-low-frequency noises that can be picked up from far away by networks of acoustic hydrophone arrays mounted to the seafloor.

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