Swivel - IoT

Swivel is a smart chair that collects data using weight sensors to improve the workplace environment. Swivel can monitor occupant's sitting habits to enhance employee health, prevent security risks, utilize workplace, and support flexible work space.


Clare Carroll, Bo Kim, Shannon Sullivan


Matchmaking, Scenarios and storyboard, Video production, Making a pitch

My Role

Collaboration on ideation, overall design process and video making. Individual work on creating animation and video editing.


3.5 weeks in 2016

Project for the course Interaction Design Studio I instructed by Professor Skip Shelly


Finding an audience, context, and purpose for a new or emerging technology.

Many UX projects begin from studying people's needs. However, sometimes companies have a technology that they want to exploit. The prompt was to select a technology and find a good intersection between a target set of users and the abilities of the selected technology. Among the list, we chose weight sensors.

So, how can we use weight sensors to create value?


Considering the capabilities and limitations of weight sensors, each of us generated ideas that can deliver value by implementing this technology.

We thought Shannon's idea about an office chair had some interesting potential. Since ergonomics is a big issue in many companies, a smart chair can make an effective pitch addressing many health problems in the workplace.

Floorboards in a building that detect how crowded a room is.

Tables in restaurants that track progress based on weight on the table.

An office chair that detects how long user has been sitting and prompt to stand.


Then, we went back and observed activities and behaviors related to office chairs in the workplace to ask the following questions:


What does it mean to sit on a chair?

People usually sit on a chair when they engage in a timely activity. Unlike fingerprint or face recognition, sitting allows constant and tangible interaction.


What kind of data can weight sensors + chair collect?

Time occupied, whether it is occupied or not, weight, posture, and other sitting habits.


How could this data deliver value to the workplace?

Through machine learning, the chair can use data collected to identify who is in the chair. This could lead to a novel way of interaction in the workplace.

We developed our initial focus on weight sensors to a smart chair concept. From there, we did a second round of matchmaking.

Opportunity space

We conducted more research on the struggles that exist in the office space that could be solved by our smart chair concept.

Among many, following are the opportunities that we decided to focus on.

By touching these different opportunities that the smart chair can solve, our concept became stronger and more desirable. We named our product Swivel and created a Kickstarter video to narrate Swivel's roadmap.



Swivel monitors user's posture and alerts suggestions. It detects how long user has been sitting and gives reminders to stand up and move around at regular intervals.


Users are able to sync Swivel's data with other health apps to keep track of their progress.

Mobile workplace

Through machine learning, Swivel is able to identify who is in the seat. When the user sits down, it automatically loads their personal desktop from the cloud.


When the user leaves the seat for a period of time, Swivel automatically locks the screen to avoid security risks.

Swivel can also be incorporated in the log-in process for two-factor authentification since it can identify who is in the chair.

Office space utilization

Swivel can detect how many seats are occupied in the room and when it is occupied. Companies can use this data to monitor if the workspace is used efficiently and if there is an opportunity to adjust the facility to create a better environment.


What worked

At the end of the project, all students in the class were given imaginary $5000 to invest on other student projects. Swivel was top funded in the weight sensor category and 2nd highest overall, receiving over $40K investment. As a Kickstarter project, the main goal was to match contexts where weight sensors could be utilized and I think we successfully pitched its potential.

What could have been better

I really wish we had done more research for this project. If there was more time, we could have done contextual inquiries in an actual office space with employees and conduct interviews with members of a startup or experts in ergonomics.

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