旅游景点游客密度监测平台

N. Rosyida, R. A. Atmoko, Galih Panji Handoko, I. M. Widia, Salnan Ratih Asriningtyas
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摘要

旅游业是当前Covid-19大流行期间遭受重创的行业之一。然而,到2021年,随着严格的卫生协议的实施,旅游景点的数量开始向公众开放,旅游业正在缓慢增长。然而,在实践中,各种旅游景点仍有许多违反卫生规程的情况,包括无纪律地使用口罩,不保持距离(社交距离),以及在像当前这样的大流行期间没有设定理想的游客人数。由于缺乏管理制度,旅游景点的管理者往往会忽视对游客数量的限制。需要有一个应用程序,可以实时告知游客到旅游景点的情况,让人们对自己的个人健康有自我意识,这样人们就可以在旅行前提前做好计划。在良好治理中,这一应用程序有助于控制从拥挤的中心(旅游景点)传播Covid-19的风险。政府可以很容易地监测该地区的游客密度分布,从而可以将其作为执行政策和现场处理的依据。本研究提出利用基于图像处理和深度学习的目标检测概念,开发一个监测旅游景点游客密度的应用平台(软硬件)。将硬件与基于网络的软件相结合,将提供公众容易到达的旅游景点的游客密度信息,从而有望为应对当前的Covid-19大流行做出贡献。
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Tourist Attractions Visitor Density Monitoring Platform
Tourism is one of the sectors that have been hit hard during the current Covid-19 pandemic. However, in 2021 the tourism sector is slowly rising marked by the number of tourist attractions that are starting to open to the public with the implementation of strict health protocols. However, in practice there are still many cases of violations of health protocols in various tourist attractions, ranging from the undisciplined use of masks, not keeping a distance (social distancing), and the absence of setting the ideal number of visitors during a pandemic like the current one. Managers of tourist attractions tend to ignore restrictions on the number of visitors due to the absence of an management system to run. There needs to be an application that can inform the condition of visitors to tourist attractions in real-time so that people have self-awareness of their personal health so that people can make early plans before traveling. In good governance, this application contributes to controlling the risk of Covid-19 transmission originating from crowded centers (tourist spots). The government can easily monitor the distribution of tourist visitor density in the area so that it can then be used as a basis for carrying out policies and handling in the field. This study proposes the development of an application platform (software and hardware) monitoring the density of visitors to tourist attractions using the concept of object detection based on image processing and deep learning. The integration of hardware with web-based software will provide information on the density of visitors to tourist attractions that are easily accessible to the public so that they are expected to contribute to the handling of the current Covid-19 pandemic.
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