Public transportation is an important infrastructure of a city. Whether traditional passenger vehicles or today’s popular self-driving buses, they directly or indirectly require information such as the flow of people as dispatch assistance. Because bus stop has off-peak hours and peak hours, this technology The multi-front-end system combines the direction of a back-end system, and integrates the front-end system into the embedded platform to effectively reduce costs. ARTC also builds crowd estimation technology based on image processing and deep learning, which helps the efficiency of public transportation. The front-end and back-end design also provides users with the ability to configure their own structure according to their needs

1.Detect rate : ≧90%
2.False rate : ≦8%
3.Frame rate: 800ms
4.Detect range: 4.5m * 2.0m

Pedestrian flow statistics and analysis.

In general, the surveillance system can be applied for several people counting applications, such as pedestrian traffic in public transportation and tourists flow estimation on bridge. For previously, the people counting method includes manual statistics, rotary gate of mechanical equipment, infrared optoelectronic equipment. However, these traditional methods have some problems which contain labor costs increasing, inconvenient passing through of pedestrian, and inexact counting in high-flow people place.