...
首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Wireless Sensor Networks—Node Localization for Various Industry Problems
【24h】

Wireless Sensor Networks—Node Localization for Various Industry Problems

机译:无线传感器网络—各种行业问题的节点本地化

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Fast and effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Electrically powered systems in industrial settings require monitoring of emitted electromagnetic fields to determine the status of the equipment and ensure their safe operation. In situations such as these, wireless sensor nodes (WSNs) at fixed predetermined locations provide monitoring to ensure safety. A challenging algorithmic problem is determining the locations to place these WSNs while meeting several criteria: 1) to provide complete coverage of the domain; 2) to create a topology with problem-dependent node densities; and 3) to minimize the number of WSNs. This paper presents a novel approach, advancing front mesh generation with constrained Delaunay triangulation and smoothing (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine WSN locations for areas of high interest (hospitals, schools, and high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm provides significant reduction in the number of nodes, in some cases over 40%, compared with an advancing front mesh generation algorithm; maintains and improves optimal spacing between nodes; and produces simulation run times suitable for real-time applications.
机译:在空气中有毒物质释放后进行快速有效的监测对于减轻威胁人口区域的风险至关重要。工业环境中的电动系统需要监视发射的电磁场,以确定设备的状态并确保其安全运行。在此类情况下,固定预定位置的无线传感器节点(WSN)提供监视以确保安全。一个具有挑战性的算法问题是在满足几个条件的同时确定放置这些WSN的位置:1)提供域的完整覆盖; 2)创建具有与问题相关的节点密度的拓扑;和3)尽量减少WSN的数量。本文提出了一种新颖的方法,通过解决这些标准的约束Delaunay三角剖分和平滑(AFECETS)来提高前网格的生成。 AFECETS的一个独特方面是能够为那些需要更高节点密度来监视环境状况的高关注区域(医院,学校和人口稠密地区)确定WSN位置的功能,这在其他研究工作中很难找到。 AFECETS算法在几个任意形状的域上进行了测试。 AFECETS仿真结果表明,与先进的前网格生成算法相比,该算法可显着减少节点数量,在某些情况下可减少40%以上;维持并改善节点之间的最佳间距;并生成适合实时应用的仿真运行时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号