Ranasinghe Vinuja, Udara Nuwan, Mathotaarachchi Movindi, Thenuwara Tharindu, Dias Dileeka, Prasanna Raj, Edirisinghe Sampath, Gayan Samiru, Holden Caroline, Punchihewa Amal, Stephens Max, Drummond Paul
Department of Electronic & Telecommunication Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka.
Joint Centre for Disaster Research, Massey University, Wellington 6021, New Zealand.
Sensors (Basel). 2024 Sep 13;24(18):5960. doi: 10.3390/s24185960.
We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab's EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1-6 s warning window, slightly behind the 1.5-6.75 s of the internet-based performance of CRISiSLab's system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.
我们引入了一种基于LoRa的新型多跳通信架构,作为地震早期预警(EEW)的公共互联网替代方案。我们研究了其在为新西兰分散式EEW传感器网络生成有意义的预警窗口方面的有效性,该网络由CRISiSLab实施,采用基于局部无阻尼运动传播(PLUM)的地震检测和节点级数据处理。LoRa在低功耗、远距离应用中很受欢迎,但对于像EEW这样对时间要求严格的任务,存在传输时间长的缺点。我们的网络通过以低扩频因子(SF)通过多个短跳广播EEW来克服这一限制。该网络包括生成预警的终端节点和广播预警的中继节点。通过模拟与CRISiSLab具有互联网连接的EEW系统性能进行基准测试表明,扩频因子为8时,可以在2.4秒内将预警传播到30公里城市区域内的所有传感器。这种方法也具有弹性,消息有多个传输路径。我们基于LoRa的系统实现了1 - 6秒的预警窗口,略落后于CRISiSLab系统基于互联网的1.5 - 6.75秒的性能。尽管如此,我们的新型网络对于及时的心理准备、简单的防护行动和自动化是有效的。展示了使用Lilygo LoRa32原型设备进行的实验作为实际演示。