The Ambient Home experience brings personalized, contextual, timely, and useful content into one seamless experience. The project focused on adapting to customers through presence, proximity, and personalization, using device signals such as Visual ID and Adaptive UI to display relevant content.

The current experience is only useful when customers are directly in front of the device. From across a room, content becomes too small to read, reducing many Echo Show experiences to a clock or photo display.

That limitation discourages free interaction with the device. Fewer reasons to interact lead to lower engagement across the ecosystem and fewer opportunities for customers to discover valuable content.

The adaptive system followed three core guidelines.

1. Surface valuable content when customers are nearby to support discovery, engagement, and monetization.

2. Invite nearby customers to interact by surfacing clear calls to action.

3. Present touch-forward UI when touch is possible and voice-forward UI otherwise, balancing readability, density, and satisfaction.

Proximity sensors allow the device to estimate how far away a customer is and show content appropriate to that distance. Near-field is defined as within four feet of the device; far-field is anything farther away.

In far-field, voice hints are the primary interaction model. In near-field, touch becomes primary, allowing more detailed information and greater interface complexity.

When customers enter near-field, they may be able to control the device by touch. I helped create and define unified, systematic interaction patterns for these close-range experiences.

Before the interface could be designed, the team needed to determine which elements and data belonged at each distance. I explored how current near-field designs could evolve and helped define research categories and questions for user research.

I also helped analyze the findings so the resulting priorities could guide the adaptive layouts and transitions.

Each screen can contain many kinds of metadata, but the key question was how much to show at each distance. I explored multiple screen types to identify the information that could attract attention in far-field while remaining understandable at a glance.

Once the customer’s interest is piqued and they move closer, the device transitions to a denser near-field screen with more detailed information and controls. Key interaction domains included music, Prime Video, shopping, recipes, weather, and news.

The music player was one of the key interaction domains used to apply the adaptive system, moving from a glanceable voice-forward presentation to a more detailed touch-ready player as the customer approaches.

This places prototype applies the same adaptive principles to contextual content, revealing more detail and interaction affordances when the customer is close enough to engage.

Visual ID lets customers register their faces and connect them with personal profiles. The device can then recognize who is viewing it and show information personalized to that person.

I also explored how to daypart content by surfacing it at relevant times of day. Based on a customer’s previous usage, the experience could show commute information before work or recommend recipes before dinner using personal dietary preferences.