# SpaceFlow Analyzer

> Transit Tower:Rush+metrics

Canonical page: [https://chrome-stats.com/d/id6761461311](https://chrome-stats.com/d/id6761461311)

## Overview

- **ID:** `id6761461311`
- **Platform:** Apple
- **Type:** Apple app
- **Status:** Removed
- **Publisher:** Jakub Sadowski
- **Category:** Utilities
- **Version:** 1.1
- **Last updated:** 2026-05-17
- **First published:** 2026-04-01
- **Size:** 5.19 MB
- **Data as of:** 2026-06-22
- **Store listing:** [Apple App Store](https://apps.apple.com/fr/app/spaceflow-analyzer/id6761461311?l=en-GB)
- **Website:** [https://guardprivacy.top/spaceflow-analyzer](https://guardprivacy.top/spaceflow-analyzer)
- **Privacy policy:** [https://guardprivacy.top/spaceflow-analyzer](https://guardprivacy.top/spaceflow-analyzer)

## Description

Space is not static. It moves, breathes, and reacts. This application gives you a precise, data-driven way to understand how people actually flow through real environments such as offices, malls, and transport hubs, and turns observation into measurable insight.
Start with exploration. Walk the space or observe movement and record real paths using device sensors. Define entry and exit points, mark obstacles, and capture density manually or automatically. Every session becomes structured data that reflects real behavior, not assumptions.
Then move to analysis. Recorded paths are transformed into dynamic heatmaps that reveal intensity, direction, and congestion. Bottlenecks emerge visually, supported by density graphs and zone-based breakdowns. You can filter sessions, compare time periods, and inspect specific zones with detailed metrics like load level and average speed.
The system evolves further with simulation. Adjust flow parameters, configure zones, and launch virtual agents that recreate movement patterns. Watch how changes affect travel time, overload zones, and overall distribution. Iterate, test, and refine layouts through a continuous loop: trace, visualize, simulate, improve.
All interactions are centered around a layered map interface with recording, analysis, and simulation modes. Sessions are stored locally, enabling offline-first workflows with reliable recovery and history comparison.
After extended use, predictive capabilities activate, allowing the system to forecast congestion, run automatic simulations, and suggest layout improvements. What begins as observation becomes a structured decision-making process grounded in real data and modeled outcomes.

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Source: [Chrome-Stats](https://chrome-stats.com/d/id6761461311)
