基于低成本人工智能MATLAB的人口计数和温度记录解决方案

Asad Hindash, K. Alshehhi, AfrahA Altamimi, Hana Alshehhi, Maryam Mohammed, Shouq Alshemeili, Younis H. Karim Aljewari
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引用次数: 0

摘要

冠状病毒(COVID-19)的不利影响已经对我们生活的许多方面造成了损害。制定了预防安全措施,以遏制和减少病毒的传播。然而,在大多数情况下,全球大流行对策对金融、卫生、教育、购物、工厂、公共交通和办公楼的实际出入施加了限制。此外,基于常规身份验证和温度收集的便利访问过程可能是高风险和耗时的,特别是在近距离接触时。如今,许多监控和安全公司可以提供实用的解决方案,尽管成本很高。这种做法的优点是利用人工智能提供1)远程图像识别准确的口罩,2)温度记录和3)低成本的解决方案。本研究是应阿联酋能源和基础设施部的提案请求而开发的。这项研究与开发低成本的人口计数和温度记录系统直接相关,该系统使用增强的Viola-Jones算法和级联对象进行检测和跟踪。初步分析表明,该系统的有效性为95%,成本降低了70%以上,并有机会在全球范围内实施,以确保平稳过渡到新常态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
People Counting and Temperature Recording Using Low-Cost AI MATLAB Solution
The adverse impact of coronavirus (COVID-19) has taken a toll on many aspects of our lives. Precautionary safety measures were established to contain and reduce the widespread of the virus. However, in most cases, the global pandemic countermeasures imposed restrictions on physical access to financial, health, educational, shopping, factories, public transportation, and office buildings. In addition, the process of facilitating access based on customary identity verification and temperature collection can be high risk and time-consuming, especially if performed in a close encounter. Today, many surveillance and security companies can provide a practical solution, though with a high cost. The merit of this practice is to utilize Artificial Intelligence to provide 1) remote image recognition accurately with face masks, 2) temperature recording and 3) low-cost solutions altogether. This study is developed in response to a Request for a Proposal by the UAE Ministry of Energy and Infrastructure. The study is directly related to developing low-cost system for people counting and temperature recordings using enhanced Viola-Jones algorithm with cascade objects for detection and tracking. Rudimentary analysis indicates 95% effectiveness of system, with more than 70% cost reduction, and opportunity for global implementation to ensure smoother transitions to new normal.
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