MapIt — Restaurant Discovery & Social Map

Apr 2026 - PresentIn Progress

Why this project exists

The problem

Restaurant recommendations get buried across social posts and saved links. Even after saving them, finding a place that fits the moment and agreeing on it with friends takes another round of searching.

The product idea

Turn a link into a place on a personal map, then connect that saved place to discovery, invitations, and shared visit records. The product follows the decision from “that looks good” to “we went there.”

OVERVIEW

Project Overview

MapIt is a National Taiwan University Information Management capstone project. It helps people save restaurants they discover in social posts or web links, organize them on a personal map, and plan visits with friends.

Users can import a link or search for a place. An AI-assisted backend extracts restaurant information; the Flutter app then presents saved places on a Mapbox map. Friends can share places through a feed, invite each other to visit, and keep a record of places they visited together.

I proposed the product concept and contribute to implementation as part of the team. The work also studies human–computer interaction and the feasibility of the save-to-visit flow: whether saved places are reused, how friends reach a shared choice, and what helps or prevents an actual visit. This is an ongoing team capstone and research project.

DESIGN & DECISIONS

Key Features & Design

Problems, approaches & trade-offs

Connect discovering a place to actually going together

I proposed the MapIt product concept: organize restaurant links from social platforms on a map, then connect retrieval, choosing places with friends, invitations and shared visits.

Why it matters

Restaurant ideas are scattered across social bookmarks and chats. Planning with friends still requires finding, choosing and coordinating.

Design considerations

Design around discovery, saving, retrieval, shared choice, invitations and visits, with each feature supporting a step from online information to real-world action.

Bring personal collections into shared decisions

Maps, friends’ activity, invitations and random place selection bring individually saved places into discussion and choice with friends.

Why it matters

Organizing personal bookmarks still leaves people to reach agreement with friends before arranging a visit.

Design considerations

Connect saved places, friends’ interests and choosing a venue in one flow. Maps provide geographic context, while social interactions and random selection provide ways to choose together.

Study flow feasibility and human–computer interaction

Study whether the flow can support shared decisions and actual visits, and where users encounter barriers, through a human–computer interaction perspective.

Why it matters

Working features still need to be examined in the context of people’s existing saving, venue selection and invitation habits.

Design considerations

Focus on whether saved places are reused, how friends’ social signals influence venue selection, and how shared interest leads to invitations and visits. Interaction and flow feasibility remain under study.

THE USER JOURNEY

How it works

Share or paste a restaurant link
Review extracted places and save one to the map
Find a place with map filters or a friends feed
Invite friends or draw from saved places
Record the visit together

BUILT WITH

Technologies Used

FlutterFastAPIMapboxSupabasePostgreSQLOpenAI API

EXPERIENCE & OUTCOMES

Project Milestones

Product concept

Achievement

Proposed a social-map concept that connects discovering and saving places to shared choice, invitations and visits.

Product implementation

Skill

Contribute to the mobile product with the capstone team, supporting the complete save-to-visit experience.

HCI and flow feasibility

Learning

Study how the product flow fits existing habits and supports collaborative decisions and real-world visits. Research is ongoing.