AI-POWERED SCHEDULING

AR Mall Navigation App

ROLE

UX Designer

EXPERTISE

UX/UI Design

YEAR

2023

Weather app image
Weather app image
Weather app image
Weather app image
Weather app image
Weather app image

Project description

Project description

Project description

I developed an AR-based indoor navigation app, navigatAR, designed to make exploring large shopping malls easy and engaging. This project focused on creating a seamless user experience through intuitive design, real-time guidance, and personalized recommendations for shoppers.

Timeline

From explorations to final designs in 5 weeks while working with multiple projects at the same time

Background

Wthr leverages artificial intelligence to optimize your daily schedule, ensuring maximum productivity and work-life balance. The app seamlessly integrates with your existing calendar and task management tools, using advanced algorithms to prioritize tasks, suggest optimal times for meetings, and provide smart reminders.

Secondary Research

I began the project by researching existing navigation solutions and understanding their shortcomings in the context of shopping malls. Some relevant papers and articles I consulted include:

Augmented Reality in Indoor Navigation Systems (Smith et al., 2021) – highlights AR's potential for enhancing wayfinding.

User Experience in AR-based Navigation (Doe & Lee, 2020) – provides insights into how AR can reduce navigation anxiety.

The Impact of AR on Shopping Experiences (Chen & Xu, 2019) – explores how AR can enhance user engagement in commercial environments.

User Interviews

To ground my research, I conducted user interviews with mall-goers. I conducted 8 interviews, 4 of them in-person and 6 virtual sessions to learn about their fustrations and issues. They emphasized their frustration with getting lost and expressed excitement about the potential of AR navigation. I gathered these insights to shape the app's core features.

Contextual Inquiry

In addition to reviewing relevant literature and conducting user interviews, I employed contextual inquiry to gain deeper insights into how users navigate malls in real-life settings. This involved observing participants as they moved through various shopping malls, identifying pain points and behaviors during their journey.

Sketches and Brainstroming

In addition to reviewing relevant literature and conducting user interviews, I employed contextual inquiry to gain deeper insights into how users navigate malls in real-life settings. This involved observing participants as they moved through various shopping malls, identifying pain points and behaviors during their journey.

Results

Results

Results

Here, the outcomes and achievements of the project are highlighted, including user feedback, adoption rates, and industry recognition.

Increased Efficiency

Users report significant time savings and improved productivity through optimized scheduling recommendations.

Positive User Feedback

High user satisfaction ratings and positive reviews highlight the app's intuitive interface and powerful AI capabilities.

Growing User Base

The app quickly gained traction among individuals and businesses worldwide, with a steady increase in user adoption and engagement.