当前位置: X-MOL 学术Comput. Appl. Eng. Educ. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Optical fog‐assisted cyber‐physical system for intelligent surveillance in the education system
Computer Applications in Engineering Education ( IF 2.0 ) Pub Date : 2020-04-17 , DOI: 10.1002/cae.22240
Kiran Deep Singh 1 , Sandeep K. Sood 2
Affiliation  

Nowadays, surveillance systems are becoming popular for safety and security purposes in many sectors like government organizations, private institutes, hospitals, schools, residential societies, etc. The role of intelligent surveillance in the education system fulfills diverse requirements such as general surveillance of the campus, recording of a lecture, monitoring behavior of student/teacher, tracking, students, administrative surveillance and security surveillance, etc. In the present educational system, the traditional cloud/fog‐based cyber‐physical system (CPS) and surveillance system enable remote monitoring, machine learning, analytics, and early decision making for real‐time tasks. The existing solutions are inadequate to fulfill the requirements of ultra‐low delay and minimum energy consumption of the surveillance devices. In this paper, an optical fog‐assisted CPS is presented for intelligent surveillance in the education system that uses optical resources at the optical fog layer as fog devices for facilitating early decisions or actions with no delay, minimum energy consumption, and optimum usage of the bandwidth. The proposed system provides (a) a scalable smart OpticalFog node in the middleware of cloud and surveillance devices and (b) service assurance to various CPS‐based applications through the Fog manager. An optimum placement algorithm is proposed for the Fog manager to place the CPS‐based tasks on the nearby optical fog device. The iFogSim toolkit is used for evaluating the proposed algorithm in realizing CPS‐based surveillance in the education scenario. It can be observed from the results that delay in the traditional scenarios for different configurations of surveilled blocks are varying from 210 to 7,867 ms. However, the proposed system has provided ultra‐low delay in the range of 7.6–8.93 ms. Similarly, the energy consumption of surveillance cameras is significantly reduced. Moreover, network usage by the proposed framework is also less than the traditional system. Hence, results show the effectiveness of the proposed framework.

中文翻译:

用于教育系统智能监控的光雾辅助信息物理系统

如今,监控系统在政府机构、私立机构、医院、学校、居民社团等许多部门中越来越流行用于安全和安保目的。 智能监控在教育系统中的作用满足了校园的一般监控等多种需求、讲座录音、学生/教师行为监控、跟踪、学生、行政监控和安全监控等。 在目前的教育系统中,传统的基于云/雾的网络物理系统(CPS)和监控系统使远程实时任务的监控、机器学习、分析和早期决策。现有的解决方案不足以满足监控设备超低延迟和最低能耗的要求。在本文中,提出了一种光学雾辅助 CPS,用于教育系统中的智能监控,它使用光学雾层的光学资源作为雾装置,以促进无延迟的早期决策或行动,最小的能量消耗和带宽的最佳使用。所提出的系统提供(a)云和监控设备中间件中的可扩展智能光学雾节点,以及(b)通过雾管理器为各种基于 CPS 的应用程序提供服务保证。为雾管理器提出了一种最佳放置算法,将基于 CPS 的任务放置在附近的光学雾设备上。iFogSim 工具包用于评估所提出的算法在教育场景中实现基于 CPS 的监控。从结果可以看出,在传统场景中,不同配置的被监视块的延迟在 210 到 7,867 ms 之间变化。然而,所提出的系统提供了 7.6-8.93 ms 范围内的超低延迟。同样,监控摄像头的能耗也显着降低。此外,所提出框架的网络使用率也低于传统系统。因此,结果显示了所提出框架的有效性。
更新日期:2020-04-17
down
wechat
bug