World pandemic
The onset of the global pandemic in early 2020 radically transformed daily life, ushering in a wave of unprecedented restrictions. Governments worldwide imposed strict lockdowns, mandating stay-at-home orders and shuttering businesses deemed non-essential. Social gatherings were banned, and travel came to a virtual standstill as borders closed and flights were grounded. Schools and universities shifted to online learning, disrupting traditional education models. Mask mandates became ubiquitous, altering social interactions and public behavior. These measures aimed to curb the spread of the virus but also brought about significant disruptions to social, economic, and cultural norms.
The problem
In the context of health restrictions, many libraries implemented measures limiting the number of simultaneous visitors. Readers were often required to book a time slot in advance to access the facilities. Once inside, libraries implemented social distancing protocols, limiting the number of people in each section, and encouraging the wearing of face masks. These measures aimed to ensure the safety of visitors while allowing limited access to library resources and services.
Our objective
Based on the background, this project aims to develop a system that combines object recognition and visitor counting, and apply it to the library of Ming Chuan University's Taoyuan campus. From object recognition and real-time counting of visitors, to also detecting prohibited items and violations of internal rules. The counted visitor data is then analyzed to assist librarians in understanding the current situation within the library.
