In smart cities, intelligent learning environment is an important application scenario, and class attendance checking is an important measure to urge students to attend on time and ensure the quality of learning. Aiming at the existing problems in class attendance checking, such as low efficiency and easy to cheat, this paper proposes a student attendance management method named AMMoC (Attendance Management Method based on Crowdsensing). AMMoC includes two phases, i.e., the initialization phase and the authentication phase. In the initialization phase, a teacher sends an attendance checking request to the server. After receiving the request, the server sends a request to tell students to submit their location information, and then forms the student location map once the server receives all the response from students. In the authentication phase, the server verifies the truth of the location information by sending requests to several students to count the number of students. The authentication phase includes two modules, i.e., the task assignment module and the attendance verification module. In the task assignment module, AMMoC first finds the optimized sequence of subregions and verifiers by using the Monte Carlo algorithm, and then requires the verifiers to count the number of students in the subregion. Finally, the statistics results will be verified in the attendance verification module. Experiment comparisons and analyses show that AMMoC has the advantages of good anti-cheating performance, fast speed, and little disturbance to class, and is suitable for attendance checking applications in classroom environment.

中文翻译：

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课堂环境中基于人群感知的学生出勤管理方法

在智慧城市中，智能学习环境是重要的应用场景，班级出勤率检查是督促学生按时参加并保证学习质量的重要措施。针对班级出勤检查中存在的效率低，易作弊等问题，提出了一种名为AMMoC的学生出勤管理方法。AMMoC包括两个阶段，即初始化阶段和身份验证阶段。在初始化阶段，教师将出勤检查请求发送到服务器。收到请求后，服务器发送请求以告知学生提交其位置信息，然后一旦服务器收到来自学生的所有响应，便形成学生位置图。在身份验证阶段，服务器通过向几个学生发送请求以计算学生人数来验证位置信息的真实性。认证阶段包括两个模块，即任务分配模块和出勤验证模块。在任务分配模块中，AMMoC首先使用蒙特卡洛算法找到优化的子区域和验证者序列，然后要求验证者对子区域中的学生人数进行计数。最后，统计结果将在出勤验证模块中进行验证。实验比较分析表明，AMMoC具有良好的防作弊性能，速度快，对课堂的干扰小，适用于教室环境的考勤应用。