Browsing by Author "Tan ML"

Now showing 1 - 7 of 7
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    An earthquake early warning for Aotearoa New Zealand?
    (2021-08-05) Brown A; Parkin T; Tan ML; Rahubadde Kankanamge R; Becker J; Stock K; Kenney C; Lambie E
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    Citizen science initiatives in high-impact weather and disaster risk reduction
    (Massey University, 20/12/2021) Vinnell LJ; Becker JS; Scolobig A; Johnston DM; Tan ML; McLaren L
    High-impact weather events cause considerable social and economic harm, with these effects likely to increase as climate change drives extremes and population growth leads to commensurate growth in exposure. As part of the World Meteorological Organization’s World Weather Research Programme, the 10-year High-Impact Weather (HIWeather) Project facilitates global cooperation and collaboration to improve weather prediction, forecasting, and warning. As part of this, the HIWeather Citizen Science Project identifies and promotes activities which involve citizens in the warning value chain, from “sensors” where they passively provide data, through to “collaborators” where they are involved in designing, running, interpreting, and applying the research. As well as benefitting global efforts to reduce societal impacts of weather and other natural hazards, citizen science also encourages hazard awareness and scientific literacy and interest. This editorial introduces the HIWeather Citizen Science Project special issue, summarizing the three papers in this issue in the broader context of high-impact weather and citizen science.
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    Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review
    (Frontiers Media S.A, 3/11/2022) Chandrakumar C; Prasanna R; Stephens M; Tan ML
    Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.
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    Exploring the potential role of citizen science in the warning value chain for high impact weather
    (Frontiers Media S.A, 27/09/2022) Tan ML; Hoffmann D; Ebert E; Cui A; Johnston D
    Preparing and delivering warnings to the public involves a chain of processes spanning different organizations and stakeholders from numerous disciplines. At each stage of this warning chain, relevant groups apply their expertise, but sharing information and transmission of data between groups is often imperfect. In diverse research fields, citizen science has been valuable in filling gaps through contributing local data. However, there is limited understanding of citizen science's role in bridging gaps in the warning value chain. Citizen science research projects could help improve the various aspects of the warning value chain by providing observations and evaluation, data verification and quality control, engagement and education on warnings, and improvement of accessibility for warnings. This paper explores the research question: How can citizen science contribute to the warning value chain? Two workshops were held with 29 experts on citizen science and the warning value chain to answer this question from a high impact weather perspective. The results from this study have shown that citizens, at individual or collective capacity, interact throughout the chain, and there are many prospects for citizen science projects for observations, weather, hazard, and impact forecasting, to warning communication and decision making. The study also revealed that data quality control is a main challenge for citizen science. Despite having limitations, the findings have shown that citizen science can be a platform for increasing awareness and creating a sense of community that adds value and helps bridge gaps in the warning value chain.
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    Online learning adoption by Chinese university students during the Covid-19 pandemic
    (School of Psychology, Massey University, 2022-12-01) Huggins TJ; Tan ML; Kuo Y-L; Prasanna R; Rea DD
    The 2019 Novel Coronavirus Pandemic has severely challenged the continuity of post-secondary education around the world. Online learning platforms have been put to the test, in a context where student engagement will not occur as a simple matter of course. To identify the factors supporting online learning under pandemic conditions, a questionnaire based on the Unified Theory of Acceptance and Use of Technology was adapted and administered to a sample of 704 Chinese university students. Structural equation modelling was applied to the resulting data, to identify the most relevant theoretical components. Effort expectancy, social influence, and information quality all significantly predicted both students’ performance expectancies and the overall adoption of their university’s Moodle-based system. Performance expectancy mediated the effects of effort expectancy, social influence, and information quality on symbolic adoption. Internet speed and reliability had no clear impact on adoption, and neither did gender. The direct impact of information quality on symbolic adoption represents a particularly robust and relatively novel result; one that is not usually examined by comparable research. As outlined, this is one of three key factors that have predicted online learning engagement, and the viability of educational continuity, during the Coronavirus pandemic. The same factors can be leveraged through user-focused development and implementation, to help ensure tertiary education continuity during a range of crises
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    “Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation
    (MDPI (Basel, Switzerland), 8/03/2022) Prasanna R; Chandrakumar C; Nandana R; Holden C; Punchihewa A; Becker JS; Jeong S; Liyanage N; Ravishan D; Sampath R; Tan ML
    This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.
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    Using citizen data to understand earthquake impacts: Aotearoa New Zealand’s earthquake Felt Reports
    (Massey University, 2021-12) Goded T; Tan ML; Becker JS; Horspool N; Canessa S; Huso R; Jonathan H; Johnston D
    Aotearoa New Zealand's national seismic network, GeoNet, administers Felt Reports, including the Felt RAPID and Felt Detailed databases, which are being collected at present. NZ has a long tradition of using earthquake Felt Reports provided by the public to analyse the damage caused by moderate to large earthquakes. From traditional paper-based Felt Reports to current online reports (using the GeoNet website or a mobile app), researchers have been using such data to obtain a geographical distribution of the damage caused by an earthquake and to assess what actions people take during shaking. Felt Reports include questions on people's reactions, indoor and outdoor effects of earthquake shaking, building damage, and tsunami evacuation. The database of long online Felt Reports (Felt Classic between 2004 and 2016 and Felt Detailed from 2016 to the present) comprises over 930,000 reports from more than 30,000 earthquakes. Current research being carried out using this data includes: 1) updating of the NZ Ground Motion to Intensity Conversion Equation and Intensity Prediction Equation, 2) understanding human behaviour for earthquakes and related hazards such as tsunami, 3) developing a predictive model of human behaviour in earthquakes to estimate injuries and fatalities, and 4) improving public education. This paper summarises the history of NZ earthquake Felt Reports as well as the research currently being carried out using this data. Finally, we discuss how citizen science helps in the understanding of earthquake impacts and contributes to the aim of improving Aotearoa New Zealand's resilience to future events.