IOT BASED STATISTICAL APPROACH FOR HUMAN CROWD DENSITY ESTIMATION-DESIGN AND ANALYSIS
Jugal Kishor Gupta1, Sanjay Kumar Gupta2
1Vidya College of Engineering Meerut UP
2BIET Jhanshi UP
This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
In this paper we present an IoT based solution that can reduce the complexity of crowd estimation. About the human crowd estimation many techniques are in existence but now a day’s more work is going on in the field of IoT, because this is era of IoT and most of every organization is shifted towards IoT based system. So, we are also proposed this system in this field and we are using the Respberry Pi-3 which are having quad core processor that can very useful and gives better result and gives accurate number even in the humans are very close to each other. This IoT based model can easily implements in the crowded areas and monitor the same in this area. The camera module in this model also helps to differentiate between human and other bodies. As this is a mobile model it can easily fix on the walls of street light and in the time of dark or in night the camera captures clear image for process in the presence of street light. So that this model gives better result almost 70% better result in compare to exiting approaches.
VZigBee, Crowd Density, Respberry Pi-3, IoTBCET, RFID