Asynchronous Resilient Wireless Sensor Network for Train Integrity Monitoring

无线传感器网络 计算机科学 异步通信 节点(物理) 计算机网络 火车 无线 嵌入式系统 无线传感器网络中的密钥分配 实时计算 无线网络 工程类 电信 地图学 结构工程 地理
作者
Mihai T. Lazarescu,Pooya Poolad
出处
期刊:IEEE Internet of Things Journal [Institute of Electrical and Electronics Engineers]
卷期号:8 (5): 3939-3954 被引量:34
标识
DOI:10.1109/jiot.2020.3026243
摘要

To increase railway use efficiency, the European Railway Traffic Management System (ERTMS) Level 3 requires all trains to constantly and reliably self-monitor and report their integrity and track position without infrastructure support. Timely train separation detection is challenging, especially for long freight trains without electrical power on cars. Data fusion of multiple monitoring techniques is currently investigated, including distributed integrity sensing of all train couplings. We propose a wireless sensor network (WSN) topology, communication protocol, application, and sensor nodes prototypes designed for low-power timely train integrity (TI) reporting in unreliable conditions, like intermittent node operation and network association (e.g., in low environmental energy harvesting conditions) and unreliable radio links. Each train coupling is redundantly monitored by four sensors, which can help to satisfy the train collision avoidance system (TCAS) and European Committee for Electrotechnical Standardization (CENELEC) software integrity level (SIL) 4 requirements and contribute to the reliability of the asynchronous network with low rejoin overhead. A control center on the locomotive controls the WSN and receives the reports, helping the integration in railway or Internet-of-Things (IoT) applications. Software simulations of the embedded application code virtually unchanged show that the energy-optimized configurations check a 50-car TI (about 1-km long) in 3.6-s average with 0.1-s standard deviation and that more than 95% of the reports are delivered successfully with up to one-third of communications or up to 15% of the nodes failed. We also report qualitative test results for a 20-node network in different experimental conditions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
刚刚
彭于晏应助longer采纳,获得10
1秒前
1秒前
3秒前
3秒前
无奈又晴完成签到,获得积分10
3秒前
wzh完成签到,获得积分10
3秒前
4秒前
李健应助乐乐采纳,获得30
4秒前
晓宇发布了新的文献求助10
4秒前
沉静冰夏完成签到,获得积分10
4秒前
科研通AI6应助读书的时候采纳,获得10
5秒前
桐桐应助温柔发卡采纳,获得10
6秒前
Yuanyuan发布了新的文献求助10
6秒前
6秒前
8秒前
优美紫槐发布了新的文献求助10
8秒前
量子星尘发布了新的文献求助10
8秒前
因几完成签到 ,获得积分10
8秒前
量子星尘发布了新的文献求助30
9秒前
9秒前
10秒前
深情安青应助manjusaka采纳,获得10
10秒前
11秒前
隐形曼青应助MANI采纳,获得10
11秒前
咸鱼发布了新的文献求助10
11秒前
12秒前
fy发布了新的文献求助10
12秒前
12秒前
缓慢的含海完成签到,获得积分10
13秒前
14秒前
采蘑菇发布了新的文献求助10
14秒前
14秒前
优美紫槐发布了新的文献求助10
14秒前
南风未起发布了新的文献求助10
15秒前
迷路荷花发布了新的文献求助10
15秒前
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5720401
求助须知:如何正确求助?哪些是违规求助? 5260360
关于积分的说明 15291295
捐赠科研通 4869876
什么是DOI,文献DOI怎么找? 2615073
邀请新用户注册赠送积分活动 1565066
关于科研通互助平台的介绍 1522172