At Root Technologies, we built a wall outlet attachment that interfaces with your existing plug-in window AC units from your phone to manage your home's climate control for you while saving time, money and the environment.
I led the interaction, web, and visual design. I conducted market research and user interviews to better understand how to best solve the problem for our prospective users.
Creating a Nest for plug-in window AC's at an affordable price point. Designing a hardware and software solution to help individuals save money and the environment.
Although some of that waste results from factors such as poor insulation in homes and older systems, much of it actually comes from simply using our appliances inefficiently, such as forgetting to turn them off when we leave the home and setting the temperature unnecessarily high or low. These are issues that a hardware solution, combined with software seamlessly integrated into a users' life can solve.
We randomly selected 30 individuals from different areas of Philadelphia and interviewed them about their heating/cooling systems and how they use them to make their lives more comfortable. We found three primary things:
Working with a team of two electrical engineers and three software developers, we discussed the possibilities and limitations of what could be specifically created on both the software and hardware sides. I began by sketching out potential user flows to gain a better understanding of how our users might address their own pain points, then turning these user flows to simple wireframes that quickly became hi-fidelity prototypes. There were many, many ideas that we came up with, but we narrowed them down based on a) feasability of engineering and b) if the features are core to solving real user needs. Tradeoffs were made, but this is the nature of shipping a product, especially for a startup.
In the sign up process, we accounted for the use case of pairing with a new root or existing root. Many individuals live with roommates or a family that might also want to be able to control their window AC temperature remotely as well.
If an individual decides to pair with an existing root, the phone will scan for the root then promptly send a notification to it's original owner to grant permission to use root.
From our user research, we also learned that many individuals owned multiple window AC units. As a result, the left screen below provides an option for users to add multiple roots. We believed the best way to organize this were vertical, elongated containers to best imitate the shape of the root itself.
For the screen on the right, allowing users to simply turn their window AC's on and off from their phones wouldn't fully turn their window AC's into a smart device. Using the built-in thermostat in the root, we can allow users to set the exact temperature of the room. We also provide an ETA for how long it will take, which provides users with immediate feedback of their action. By doing so, we turn a $80 window AC into a $250 Nest, which based on our research, does a great job in addressing users pain points of manually setting the temperature.
By choosing a tab styled menu bar, we display a user's potential savings as efficiently as possible, because this is probably the first need our product helps solve.
Ultimately, the savings the root provides is one of the primary reasons users buy it, so we wanted users to be able to easily get an idea of how much their saving. As their savings go up, they likely become more and more excited about using the root.
We wanted to use machine learning to help control the climate (like the Nest thermostat) based on an individual's patterns to provide convenience for users. However, we also wanted to provide users with an option of manually setting their own schedules.
The design of the scheduling system was relatively difficult. Our goal was to provide users with an intuitive way of scheduling different blocks. We decided to have users use the drag interaction to set a block of time because they found this to be the most efficient interaction (once learned).
When users leave their home Wi-Fi range, we interpret this as them leaving their home/apartment. If they leave their window AC on, we send a notification to them to remind them to turn it off. We we're initially worried that sending too many notifications to users would get annoying. In order to get around this potential frustration, we integrated ML so that after the first week or two, Root begins learning your patterns and automates this process for you. In addition, as mentioned above, users can simply set a schedule for their root or turn notifications off (in settings).
However, while we spent the entire summer hustling, we didn't end up raising the total capital we needed ($80k) to go into production. One of the biggest lessons learned here was that hardware is expensive, especially building the mold for production. Ultimately, the team disbanded in the Fall of 2016, and we were never able to bring this product into reality. This has definitely been a great learning experience. Working with a hardware startup is a new experience for me, and while it was challenging working directly with hardware and software developers, it was also extremely eye opening to learn about the technology itself, which is definitely something I wouldn't have learned otherwise.
Designed and coded with ❤. Copyright © Jeff Wang 2018.