BLRMap

A Bengaluru focused iteration of OpenStreetMap, with a lot of cool features in store!

Description

StreetMap Bengaluru - Time-Aware Community Map for Bengaluru

Overview

StreetMap Bengaluru is a community-driven, time-aware mapping platform designed to help users discover places in Bengaluru based on what they want, where they are, and what time it is.

It enhances traditional maps by introducing contextual, time-based discovery and local insights.

Problem Statement

Users often struggle to find relevant places at specific times of the day due to:

  • Inaccurate or outdated timings

  • Lack of time-based filtering

  • Poor visibility of local and niche spots

  • Static map experiences

Solution

StreetMap Bengaluru provides:

  • Time-based discovery (morning, noon, evening, night)

  • Category-based maps (cafes, parks, metro, BMTC)

  • Location and tag-based filtering

  • Community-driven place contributions

Also, it intends to provide the functionality for users to find places and leave

Core Concept

The system is structured around three dimensions:

WHAT → Navbar (Map Type)
WHERE → Sidebar Filters
WHEN → Footer Modes

Features

Map Interface

  • Interactive map using Leaflet

  • Dynamic markers with popups

Map Layers (Navbar)

  • Normal Map

  • Cafe Map

  • Park Map

  • Metro Map

  • BMTC Map

Time Modes (Footer)

  • Morning: breakfast, parks, gyms

  • Noon: lunch, workspaces

  • Evening: snacks, bakeries

  • Night: dinner, nightlife

Filters

  • Area

  • Category

  • Open Now

  • Tags

Community Features

  • Add places

  • Add tags and descriptions

Community Layer (In Progress)

We are building a social layer on top of the map where users can leave comments, recommendations, photos, and short videos tied to specific places. The goal is to turn each place entry into a living discussion thread — part review platform, part local forum. Think of it as community-sourced ground truth for a city, where regulars can share things that never make it onto Google Maps: the best seat in a café, which hours to avoid, or a hidden entrance to a park.

Mood-Based Recommendation Engine (Planned)

We are working on a lightweight recommendation engine that takes user-defined inputs — mood, energy level, preferred vibe, time of day — and surfaces relevant places including lesser-known spots that would otherwise not appear in standard searches. The intent is to move beyond category filters and into intent-aware discovery, so the map can answer questions like "I want somewhere quiet and green, post-lunch, near Koramangala" without the user needing to manually configure every filter.

Verified Local Contributions

A structured way for locals and regulars to submit edits, flag outdated timings, and add context that static data sources miss. Contributions will be community-reviewed before going live.

Activity Signals

Surface real-time or historically-derived signals like crowd levels, typical wait times, and best-visit windows — sourced from community input rather than proprietary APIs, keeping the project fully open.

Tech Stack

Frontend

  • Next.js

  • React

  • Tailwind CSS

  • React Leaflet

Backend

  • Next.js API Routes

Database

  • MongoDB (Mongoose)

Maps

  • OpenStreetMap

Data Model

{
  "name": "CTR Malleshwaram",
  "category": "cafe",
  "location": {
    "type": "Point",
    "coordinates": [77.5706, 12.9916]
  },
  "area": "malleshwaram",
  "tags": ["breakfast", "dosa"],
  "openTime": "07:00",
  "closeTime": "11:00",
  "description": "Best benne dosa"
}

API Endpoints

GET /api/places

Supported Filters

/api/places?category=cafe
/api/places?mode=morning
/api/places?area=indiranagar
/api/places?openNow=true

Development Progress

Day 1–2

  • Project setup

  • Map rendering

Day 3

  • Database schema

  • API setup

  • Starter dataset

Day 4

  • Marker rendering

  • Popups

Day 5

  • Filters

  • Category switching

Day 6

  • Time-based modes

Day 7

  • UI improvements

  • Testing

Unique Value

StreetMap Bengaluru introduces time-aware mapping, enabling users to explore the city based on real-world usage patterns rather than static data.

Future Scope

  • User reviews and ratings

  • Real-time activity indicators

  • AI-based recommendations

  • Transit integration

Contributors

  • Nandita — Frontend, Backend, Database, Map UI

  • Amrita — Backend, Database, APIs

Conclusion

StreetMap Bengaluru transforms static maps into a dynamic, community-driven discovery platform tailored to how people actually experience a city.

Issues & PRs Board
No issues or pull requests added.