Understanding how people move through the spaces where they live and work can make those environments safer and more efficient. But privacy concerns make traditional surveillance methods, like cameras, less than ideal. Two former MIT Media Lab researchers believe they’ve found a better way.
Butlr uses insights from low-resolution thermal cameras and an analytics platform to make buildings more efficient and safe. Image Credit: Butlr
Their company, Butlr, provides skilled nursing facilities, offices, and senior living communities with a way to analyze space usage without compromising privacy.
Using low-resolution thermal sensors and an analytics platform, Butlr helps detect falls among elderly individuals, reduce energy consumption, and optimize workspaces.
We have this vision of using the right technology to understand people’s movements and behaviors in space. So many resources today go toward cameras and AI that take away people’s privacy. We believe we can make our environments safer, healthier, and more sustainable without violating privacy.
Jiani Zeng, Co-Founder, Butlr
Jiani Zeng SM ’20 co-founded Butlr with former Media Lab research affiliate Honghao Deng
Since its launch, Butlr has sold more than 20,000 of its privacy-focused sensors to senior care facilities and businesses with extensive building footprints, including Verizon, Netflix, and Microsoft. Looking ahead, the company aims to create dynamic spaces that adapt to users’ needs in real time.
Space should be like a digital user interface: It should be multi-use and responsive to your needs. If the office has a big room with people working individually, it should automatically separate into smaller rooms, or lights and temperature should be adjusted to save energy.
Honghao Deng, Research Affiliate and Project Lead, Media Lab
Building Intelligence, With Privacy
Deng’s journey into building intelligence began in 2016 when he joined the Media Lab’s City Science Group as a visiting student from Tianjin University. He later completed a master’s degree at Harvard but returned to the Media Lab as a research affiliate, leading projects on what he calls responsive architecture—spaces that understand users' needs without relying on intrusive cameras.
My vision of the future of building environments emerged from the Media Lab. The real world is the largest user interface around us — it’s not the screens. We all live in a three-dimensional world and yet, unlike the digital world, this user interface doesn’t yet understand our needs, let alone the critical situations when someone falls in a room. That could be life-saving.
Honghao Deng, Research Affiliate and Project Lead, Media Lab
Zeng joined MIT as a master’s student in the Integrated Design and Management program, a collaboration between the MIT Sloan School of Management and the School of Engineering.
He also conducted research at the Media Lab and the Computer Science and Artificial Intelligence Lab (CSAIL). The two met during a hackathon at the Media Lab and continued collaborating on various projects, eventually founding Butlr in 2019 with early funding from the Media Lab-affiliated E14 Fund.
“I tell every single MIT founder they should have the E14 Fund in their cap table. They understand what it takes to go from an MIT student to a founder, and to transition from the ‘scientist brain’ to the ‘inventor brain.’ We wouldn’t be where we are today without MIT,” said Deng.
Ray Stata ’57, SM ’58, founder of Analog Devices, is also an investor and serves on Butlr’s board.
“We would love to give back to the MIT community once we become successful entrepreneurs like Ray, whose advice and mentoring has been invaluable,” said Deng.
After launching, Butlr needed to find the right early adopters for its real-time sensors, which detect movement patterns without capturing personally identifiable information. The team interviewed hundreds of stakeholders before starting with office space owners.
“People have zero baseline data on what’s happening in their workplace. That’s especially true since the Covid-19 pandemic made people hybrid, which has opened huge opportunities to cut the energy use of large office spaces. Sometimes, the only people in these buildings are the receptionist and the cleaner,” said Deng.
Butlr’s battery-powered sensors, which last multiple years, track occupancy and space utilization to help reduce energy consumption. For companies managing extensive real estate, the potential savings are significant. One Butlr customer with 40 building leases could save millions of dollars simply by optimizing HVAC controls based on real usage.
“We can be like the Google Analytics for these spaces without any concerns in terms of privacy,” said Deng.
Beyond office spaces, Butlr’s technology has significant implications for senior care facilities.
“In skilled nursing facilities, instead of office spaces it’s individual rooms, all with people who may need the nurse’s help. But the nurses have no visibility into what’s happening unless they physically enter the room,” said Deng.
Butlr’s platform can detect falls or recognize when someone isn’t getting out of bed, sending alerts through nurse call systems to ensure timely intervention.
The “Nerve Cells” of the Building
Butlr continues to refine its analytics capabilities. For instance, the system can analyze movement patterns among elderly individuals to identify early signs of health issues like urinary tract infections.
The company has also partnered with Harvard Medical School’s Beth Israel Deaconess Medical Center and the University of Massachusetts Amherst’s AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease. This collaboration aims to detect subtle changes in movement that could indicate cognitive or physical decline, allowing for earlier interventions.
“In the near term we are preventing falls, but the vision is when you look up in any buildings or homes, you’ll see Butlr. This could allow older adults to age in place with dignity and privacy,” said Deng.
More broadly, Butlr’s founders see their work shaping the future of AI-driven spaces.
“We’re the nerve cells in the building, not the eyes. That’s the future of AI we believe in: AI that can transform regular rooms into spaces that understand people and can use that understanding to do everything from making efficiency improvements to saving lives in senior care communities. That’s the right way to use this powerful technology,” said Deng.