Estimation of density level of people with wearable devices in a room

• Main Author: Wong, Damien Kee Yao
• Other Authors: Erry Gunawan
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/149654
• Institution: Nanyang Technological University

In our daily lives, there have been many tourist attractions places that we often visit such as Botanic Gardens, Orchard Road, Sentosa, Chinatown, Nature Parks & Nature Reserves, etc. which are prone to crowd disasters. In addition, the current ongoing coronavirus pandemic are also similar as crowd disasters occur due to the high densities level within people in a room. This research aims to estimate the density level of people with wearable devices in crowded places and also to direct and control the people to better alternative options to reduce such issues. We will be using a simulation software to predict and conclude the results so that we can avoid such crowded areas. This report will be applying various different methods such as machine learning algorithms to avoid the crowd and lead the user to a better way/road to the destination as it will predict the crowded areas base on Bluetooth devices within an area range of 10m. In addition, the response of the human agent model to the wearable device will also be examined in this report. For future work, a mobile application can be develop to make it just like the NPark website.