Earthquake Early Warning
The research theme focuses on advancing earthquake early warning (EEW) systems by developing novel, low-cost sensors and exploring decentralised networks for data processing and warning communication. Through a multi-disciplinary effort, the theme aims to increase the accessibility and effectiveness of EEW systems.
Advanced algorithms and peer-to-peer communication methods are being utilised to improve the accuracy, timeliness, and reliability of EEW systems, while also creating low-cost innovations to enhance earthquake early warning. Additionally, the research theme seeks to understand the societal benefits and challenges of EEW systems in Aotearoa New Zealand by exploring the perspectives of different sectors and the public. This includes preferred system attributes and intended responses to warnings. Understanding the human context of EEW is crucial for effective communication and interventions, emphasising the need for knowledge exchange and mobilisation to facilitate the adoption and use of EEW systems.
Building a community of practice towards the conceptualisation of citizen-led low-cost early warning
Description: This project investigates affordable socio-technical earthquake early warning (EEW) solutions for New Zealand through understanding perspectives from communities and various stakeholders. The project aims to facilitate a community of practice to address the technical and social feasibility of realising a low-cost EEW system in New Zealand using a transdisciplinary design science approach. It will also involve conducting workshops with community groups to understand their perspective towards EEW systems. The project includes Māori engagement and international collaborations to develop an EEW system, leading to a comprehensive understanding of end-user needs, technological challenges and opportunities, and a ranking of taxonomies of the required technology artefacts. Successful outcomes will lay the foundation for the investigation of establishing a viable EEW system in Aotearoa New Zealand.
Led by: Raj Prasanna
Community led low-cost micro-seismic (MS) sensor network applications for Earthquake Early Warning (EEW)
Description: The proposed research aims to investigate whether it is feasible for citizens and communities to build, own and operate low-cost earthquake early warning (EEW) applications using a network of MS sensors. The research has three objectives: (1) examine the strengths and weaknesses of existing MS sensors for EEW in New Zealand, (2) identify the specific needs of different sectors and communities for receiving EEWs, and (3) propose a self-healing and self-aligning sensor network architecture consisting of low-cost MS devices. The research will focus on low-cost, open-source solutions that can expand access to EEW technology to resource-constrained communities and enable capacity building at the local level. The study will use a community-engaged citizen science approach to explore the feasibility of citizen-led low-cost EEW applications in New Zealand.
Led by: Raj Prasanna
Understanding user perspective on Earthquake Early Warning through Twitter data
Description: The research will investigate the use of social media data in understanding people's pespectives on earthquake early warning. The following are the goals of the research: (1) Identify and assess the usefulness of social media data for understanding people’s response to earthquake early warning alerts, and (2) using social media data, develop an understanding of how people respond to earthquake warning alerts and propose ways to improve people’s responses to the warnings.
Led by: Marion Tan
Developing a framework for user's intention to using EEW
Description: This project aims to investigate the public's perception of the newly introduced Android Earthquake Alert system in New Zealand and their intention to continue using it. As earthquake early warning systems are still in their infancy in New Zealand, it is crucial to understand the factors that influence the long-term success and use of such technology. The study presents results from online surveys distributed after two separate earthquake alert events in October 2021. The findings will contribute to the development of effective earthquake mitigation tools and enhance earthquake awareness and preparedness in New Zealand.
Led by: Marion Tan
Becker, J. S., Potter, S. H., Prasanna, R., Tan, M. L., Payne, B. A., Holden, C., Horspool, N., Smith, R., Johnston, D. M. (2020). Scoping the potential for earthquake early warning in Aotearoa New Zealand: A sectoral analysis of perceived benefits and challenges. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/j.ijdrr.2020.101765
Brown, A., Parkin, T., Tan, M. L., Prasanna, R., Becker, J., Stock, K., Kenney, C., & Lambie, E. (2021). An earthquake early warning system for Aotearoa New Zealand? Community engagement findings 2020–2021. http://hdl.handle.net/10179/16735
Chandrakumar, C., Prasanna, R., Stephens, M., Tan, M.L., (2022). Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review. Frontiers in Sensors. https://doi.org/10.3389/fsens.2022.1020202
Chandrakumar, C., Prasanna, R., Stephens, M., Tan, M.L., Holden, C., Punchihewa, A., Becker, J.S., Jeong, S., Ravishan, D. (2022). Algorithms for detecting P-waves and earthquake magnitude estimation: Initial literature review findings. In T. Huggins & V. Lemaile (Eds.) Proceedings of ISCRAM Asia Pacific Conference 2022. https://idl.iscram.org/files/chanthujanchandrakumar/2023/2488_ChanthujanChandrakumar_etal2023.pdf
Hong, B., Chandrakumar, C., Ravishan, D., Prasanna, R. (2022). A Peer-to-Peer Communication Method for Distributed Earthquake Early Warning Networks: Preliminary Findings. In T. Huggins & V. Lemaile (Eds.) Proceedings of ISCRAM Asia Pacific Conference 2022. https://idl.iscram.org/files/benjaminhong/2023/2485_BenjaminHong_etal2023.pdf
Huggins, T. J., Yang, L., Zhang, J., Tan, M. L., Prasanna, R. (2021). Psychological Effects of Dominant Responses to Early Warning Alerts.. International Journal of Ambient Computing and Intelligence. http://doi.org/10.4018/IJACI.2021070101
Prasanna, R., Chandrakumar, C., Nandana, R., Holden, C., Punchihewa, A., Becker, J.S., Jeong, S., Liyanage, N., Ravishan, D., Sampath, R., Tan, M.L. (2022). “Saving precious seconds”—A novel approach to implementing a low-cost earthquake early warning system with node-level detection and alert generation. Informatics. https://doi.org/10.3390/informatics9010025
Tan, M. L., Prasanna, R., Becker, J. S., Brown, A., Kenney, C., Lambie, E., Johnston, D. M., Stock, K., & Alwis, D. De. (2021). Outlook for earthquake early warning for Aotearoa New Zealand : Insights from initiating a community-of-practice. 2021 Annual Technical Conference for the New Zealand Society for Earthquake Engineering, 55–63. https://repo.nzsee.org.nz/handle/nzsee/2350
Tan, M.L., Becker, J.S., Stock, K., Prasanna, R., Brown. A., Kenney, C., Cui, A., Lambie, E. (2022). Understanding the social aspects of earthquake early warning: A literature review. Frontiers in Communication. https://doi.org/10.3389/fcomm.2022.939242