PEDESTRIAN TRAFFIC TRACKING
What is BluDAR?
BluDAR, from RADAR — an acronym for RAdio Detection And Ranging — is the name given to our Bluetooth sniffing device. The device is used for tracking pedestrian movement or customer trends. It was designed to log any unique Bluetooth MAC (media access control) addresses of devices which are broadcasting their credentials in range. These devices can be anything that is Bluetooth enabled, such as mobile phones, smart scales, speakers, car sound systems, earpieces, etc.
In order to showcase the BluDAR system, a portable, battery-powered unit was positioned at a local café. The objective of this planted device was to establish a profile of the number of visitors per day, as well as the typical time spent at the café per visit. A crude introduction to some of the insights that may be drawn from the gathered data is presented below. All data has been kept anonymous by storing no more than the unique identifier (MAC address) of each device to enable device-level analysis.
Some elementary analyses are provided here in order to showcase some of the insights that can be gained from using the technology. Additional to these metrics presented, multiple meters allow for pedestrians’ movement to be tracked in order to give insight into peak times of movement and frequently used routes.
A broad overview of the visitor distribution over time at the café. This heat map shows the number of unique devices observed per hour, per day of the week. Notably, some Bluetooth devices were always in range of our BluDAR, as the number of unique devices per hour never dropped below 2. Most mornings and evenings, however, the amount of Bluetooth devices remained around 5 or 6. Furthermore, two extraordinary events were observed. The first occurred on a Thursday afternoon just after lunchtime and the second on a Friday morning. These events coincide with business mixer events hosted by the café.
The two graphs presented here show the typical distribution per hour of visitors on a weekday and weekend day respectively. Evidently, there are around 5 devices permanently in range with minimal deviation, which may indicate static devices instead of mobile phones or fitness watches. During the week a much larger deviation is observed, which is largely due to the aforementioned extraordinary events. Furthermore, it’s evident that around 20 unique devices are observed during the operating hours of the café, with peak times around 09:00 in the morning and 14:00 in the afternoon.
From the number of times each device was observed at the café over the analysis period, it seems that visitors typically visited the café 2 to 4 time during the week, with a median of 3 times.
According to the observed typical time spent per visit per Bluetooth device, the café can expect customers to typically spend 2 to 8 minutes, with a median of just under 4 minutes. This may indicate a customer preference for takeaway coffees and snacks rather than full, sit-down meals at this particular café.
The total time each device was observed at the café over the period provides further insights into the short visits seen in the previous image. Total visiting times are observed in the range of 4 to 22 minutes. This indicates frequent, short visits to the café during the week. This supports the hypothesis of an average customer’s preference for takeaway coffees and snacks as opposed to sit-down meals. Additionally, it can be said that the customers of this café are typically returning customers.