The Problem

My intelligent connected ecosystem is designed for college commuters who rely on public transit. Many users, including myself, experience unreliable real-time updates and a lack of accessible safety reporting within the current RTD app. This project addresses those pain points by reimagining a more reliable, connected, and safety-focused commuting experience. SmartCommute is a mobile app designed to improve and enhance urban public transportation through the integration of IoT devices so commuting is more efficient, reliable, and safe while on the go.

Your Role

My first role was to create a journey map showing how the app would interact with each device for each component of the ecosystem. The method I chose to address users’ pain points was drawing from personal experience. This heavily influenced my decisions about which features to include in the app, as I’ve had firsthand experience with the RTD app’s issues over the last four years, in addition to hearing about similar frustrations from others. This approach ensured that the features were practical and aligned with users’ actual needs. Overall, it guided my design decisions, such as the screens and video demo, so that the app would be intentional and truly connect with the audience I’m designing for.

Process

The first step in creating this project, I created a journey map to plan outline what the ecosystem would look like then I thought about how each device would interact with each other and what practical features each device could handle for the kiosk, mobile, watch, AI agent, and voice experience. I did this by identifying pain points that users had with the RTD app and figured out features that would solve them. From this it drove my design decision in figuring out the main features that I would highlight for SmartCommute. My final step was creating a demo video that was based on a familiar scenario for commuters that showcased all the important features of the app from reliability to being able to use it on multiple devices. This way it connects users emotionally and tackles solving their pain points.

Ecosystem Journey

The journey begins with he mobile app by logging in at the login screen. The reason the mobile app is the only one device that requires you to log is due to the fact that most users will be using the the phone as the main device for the app. This encourages users to have a profile with all their information that they would like to include so that other devices can be synced properly to have the right personalization and maintain consistency. The main information that transfers between the phone, kiosk, and watch is the alerts, notification, and tickets, users have saved on their account. When it comes to tickets they are all transferred by clicking the share button or there are presetting users have already put in the app for the app to know where the ticket should be sent. The takes most of the control in finding what they need from the device, where as the system acts intelligently for more tedious tasks like tracking the trains location, retaining memory from a previous interaction the chatbot and so on.

The Journey Map

Components Overview

The SmartCommute ecosystem is a connected UX made up of five coordinated components that work together to support commuters end to end. The commuter kiosk serves as the physical touchpoint, enabling fast, secure, and personalized interactions for ticketing, payments, and real-time information through sensors, displays, and connectivity. The mobile/tablet app acts as the primary control surface, giving users transparent access to trip planning, schedules, alerts, tickets, reporting, and AI assistance. The watch/wearable app functions as a peripheral touchpoint, delivering glanceable, haptic, and voice-based updates and quick actions synchronized with the mobile app. At the core, the AI agent provides a consistent conversational interface across devices, offering personalized guidance, predictive alerts, and contextual assistance via voice and chat. Finally, the human-in-the-loop model balances automation and control by allowing AI to suggest and streamline actions while ensuring users can review, modify, or override decisions, building trust, clarity, and confidence throughout the commuting experience.

Components Table

Solution

Mobile Device Hi-Fi

I made the most screens for the mobile version of the app as they serve as the main device form for most users to use while commuting. The login scree was made to encourage users to make an account that holds their information safely and conveniently so that information can be synced to other devices. The home screen displays all the things most users need and often use which are alerts, a place to report, access to tickets, an ai chatbot and a live map. The trip planner screen was designed as simple as possible so that users aren’t overwhelmed or nervous when getting to their destination vis light rail or bus. Lastly, the schedule machine was meant to be simple and easy to navigate as there is an arrow to collapse all the sub-categories.

AI Agent

This is a place where users can use AI intelligence to help with their daily commute. The interface is made to look like other chatbots so it is familiar to users.

Kiosk

The Kiosk’s main page is made to be similar to the mobile app, but prioritizes making the report button and AI chatbot more visible as an effective way to help users in a rush. While the kiosk’s ticket screen is meant to be simple and communicates clearly to the user what it does.

Watch

The watch screen is very simple as it has little capabilities an shows that users can only use it for simple tasks like as a qr code ticket and alerts.

Demo Video

Reflection

What you learned about designing across devices.

I learned it is quite difficult for all devices to have the same features. This meant that I had to think carefully and practically what device was the most important for the features I want to implement. Thus, I spent more time on the interaction on one or two devices, while the rest had very little thought or was super simplified.

How could AI be used (or used better) to meaningfully solve user problems in your ecosystem?

It can help users find the solution to what they are having problems whether in app or other situations easily and fast. That way AI can help users navigate the app much easier with little to no frustrations where the users view the ecosystem as helpful.

What are the ethical implications of your system?

The ethical implications of my system is the amount of information it collects can harm others. For example, people can use the live map as a way to plan something dangerous or possible hack into the system and collect sensitive data.

Where the system could be more intelligent or more human-centered.

I think the system could be more human-centered in the AI chatbot, where the chat bot can lead users to real people for more complex problems. AI may be intelligent, but I don’t believe the it should be fully relied on for all problems users may com across.

Key tradeoffs or constraints you encountered.

The app heavily relies on real time data collection and accurate data. This means that if at anytime anything goes wrong it can result to delays, outages, or inaccurate data can directly affect route suggestions, alerts, and predictions.