The Deep Learning-Based Person & Passenger Counting and Analysis System has been developed for use in enclosed areas with regular entrances, such as stores, shopping malls, hospitals, factories, etc. to count the number of people entering and leaving the location, to analyze the age and gender of such people, to plot a heat map based on densities in the respective area, and to make a sentiment analysis of the people in the area. The system can also make a glass analysis, allowing the number of people passing by and looking at a display to be counted, and to offer tailor-made shopping alternatives through integration with loyalty programs. All of the obtained data are processed to produce meaningful reports on a store and/or time basis for sector managers. Processing the obtained data, especially in the retail sector, allows more accurate planning, and provides sector managers with value-added services for use in decision support systems. For example, the time period for peak the hours of a store can be determined, and the working hours of the staff and sales opportunities can be arranged to suit. The effects of marketing activities and advertisements can be verified with the data obtained from these systems.
Furthermore, the Deep Learning-Based Person & Passenger Counting and Analysis System allows instant tracking and analysis of the number of passengers using public transport, the age and gender of the passengers, and the vehicle occupancy rates. The system is of critical importance for the efficiency of public transport administrations and vehicle operator enterprises (Cooperatives, etc.). It helps determine locations and times of high passenger density, allowing better scheduling of public transport vehicle journeys, and provides information about the occupancy rates of public transport vehicles during their trips. The Passenger Counting and Analysis System allows trips to be scheduled more effectively, thus ensuring passengers travel more comfortably and save time. It can produce reports on a station/line/route basis. No external camera is required, as the existing cameras both at the respective points and in the vehicles can be used by the system. The person-counting solutions offered by ASİS CT are actively working at more than 3500 stores in 81 provinces.
FEATURES OF DEEP LEARNING-BASED PERSON & PASSENGER COUNTING AND ANALYSIS SYSTEM
DEEP LEARNING-BASED PERSON & PASSENGER COUNTING AND ANALYSIS SYSTEM MODULES