Human identification and monitoring are critical in many applications, such as surveillance, evacuation planning. Human identification and monitoring are not an easy task in the case of a large and densely populated crowd. However, none of the existing solutions consider seamless localization, identification, and tracking of the crowd for surveillance in both indoor and outdoor environments with significant accuracy. In this paper, we propose a novel and real-time surveillance system (named, SmartISS) which identifies, tracks and monitors individuals’ wireless equipment(s) using their MAC ids. Our trackers/sensing units (PSUs) are the portable entities comprising of Smartphone/Jetson-TK1/PC which are enough to capture users’ devices probe requests and locations. PSUs upload collected traces on the cloud server periodically where cloud server keeps finding the suspicious person(s). To retrieve the updated information, we propose an algorithm (named, LLTR) to select the optimal number of PSUs for finding the latest location(s) of the suspicious person(s). To validate and to show the usability of SmartISS, we develop a real prototype testbed and evaluate it extensively on a real-world dataset of 117,121 traces collected during the technical festival held at IIT Roorkee, India. SmartISS selects PSUs with an average selection accuracy of 95.3 percent.

中文翻译：

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使用无缝室内外定位进行实时人群监控

人员识别和监控在许多应用中都至关重要，例如监视、疏散规划。在人口众多且人口稠密的情况下，人员识别和监控并非易事。然而，现有的解决方案都没有考虑无缝定位、识别和跟踪人群以在室内和室外环境中以极高的精度进行监控。在本文中，我们提出了一种新颖的实时监控系统（名为 SmartISS），该系统使用他们的 MAC id 来识别、跟踪和监控个人的无线设备。我们的跟踪器/传感单元 (PSU) 是由 Smartphone/Jetson-TK1/PC 组成的便携式实体，足以捕获用户的设备探测请求和位置。PSU 定期将收集到的踪迹上传到云服务器，云服务器不断发现可疑人员。为了检索更新的信息，我们提出了一种算法（命名为 LLTR）来选择最佳 PSU 数量以查找可疑人员的最新位置。为了验证和展示 SmartISS 的可用性，我们开发了一个真实的原型测试平台，并在印度 IIT Roorkee 举行的技术节期间收集的 117,121 条轨迹的真实世界数据集上对其进行了广泛的评估。SmartISS 选择 PSU 的平均选择准确率为 95.3%。我们开发了一个真实的原型测试台，并在印度 IIT Roorkee 技术节期间收集的 117,121 条轨迹的真实数据集上对其进行了广泛的评估。SmartISS 选择 PSU 的平均选择准确率为 95.3%。我们开发了一个真实的原型测试台，并在印度 IIT Roorkee 技术节期间收集的 117,121 条轨迹的真实数据集上对其进行了广泛的评估。SmartISS 选择 PSU 的平均选择准确率为 95.3%。