9 Metrics Overview
We explore how WiFi gives us a snapshot of urban life. It’s about identifying where people are (Location), counting them (Count), tracking their movements (Track), identifying patterns (Identify), and understanding their actions (Activities). A graphic will illustrate these concepts step by step:
Ground Truth: What’s Really Happening?
We start with the ‘Ground Truth’—observing what’s actually happening on the ground. This real-life observation helps us validate our WiFi data findings. It’s the benchmark against which we measure the accuracy of our WiFi sensing data.
Location: Where Are People at a Specific Time?
‘Location’ is determined by analyzing the characteristics of WiFi signals at a given time, such as signal frequency and strength. Depending on the situation, we might assign locations based on sensor positions or estimate them in areas between sensors.
Before counting, we must pinpoint location. Without knowing where devices are, we just have a total count.
Imagine a room with three people, just like in the diagram above:
- Without location data, counting detected device MAC addresses only tells you there are three devices total.
- With even rough location data, you can determine that two devices are on the left and one on the right – providing much richer information.
Count: How Many Over Time?
‘Count’ focuses on tallying unique MAC addresses to estimate how many people are in an area over different timescales. This method allows for long-term tracking of device presence, offering insights into occupancy trends over extended periods.
Track: Where and When Did They Move?
‘Track’ involves recording when and where phones are detected. This data lets us follow people’s movements, highlighting the dynamic patterns of city life and offering insights into how different areas are used throughout the day.
Identify: Who Visits Regularly and What Are Their Patterns?
With ‘Identify’, we analyze data over time to recognize regular visitors and understand their movement habits. This metric provides insights into recurring traffic patterns and the behaviors of different user groups within the city.
Activities: What Are They Doing and How Does It Change?
‘Activities’ aims to understand actions by analyzing timing and movement data. We look at how people use different city areas, observing changes in activity patterns at different times and days to gain a deeper understanding of urban life.