The need for People & Traffic counting
Better understanding people, vehicle and bicycle traffic patterns is of great benefits for many stakeholders and areas of businesses. For councils, it can help understand usage of public facilities and assets (e.g. playgrounds, parks), collect benchmark data before planning or undertaking new developments, understand the effect of initiatives and measures (e.g. precinct activation initiatives, tourism advertising campaigns, lockdown) etc. But it is also useful information for local businesses and to understand foot traffic, for residents to decide when to do things. These are just a small set of examples.
There are a number of different techniques that can be used to collect data for counting people. The most commonly used, and probably the most cost effective, is to use sensors that count mobile phones within a certain radius by emitting bluetooth or Wi-Fi signals. The limitation of this method is that it cannot be used to count bicycles or vehicles (although it would detect people on a bicycle or inside a vehicle).
More advanced technique, and also likely to be more costly, is to use CCTV cameras coupled with video analytics software. This can be used to detect people, vehicles, bicycles or even wildlife and objects. Depending on the level of sophistication of the video analytics software, data collected can be precise enough to distinguish people's gender, age, mood, vehicle colours etc.
How does it work in the background?
- In the above case studies we are collecting anonymised counting data from a range of sources including Meshed mobile devices counters (nCounters), CCTV & video analytics software (e.g. Camlytics), Cisco Meraki and Telstra Purple mobile devices counters, Thermal cameras etc. The data we are receiving comes in a range of formats which we standardise in order to provide consistent views in our dashboards, irrespective of the data source.
- We are also performing a number of data processing, for example in the case of mobile devices counting data from Cisco Meraki or Telstra purple, we are removing duplicates to determine unique visitors count, we filter the data based on parameters such as the strength of the signal received by the mobile phone (RSSI).
- Data is then presented in dashboards allowing users to slice and dice data against different dimensions e.g. per location, per date, per council area etc.