Community-led low-cost micro-seismic (MS) sensor network applications for Earthquake Early Warning (EEW) Toka Tū

Toka Tū Ake EQC - Biennial Grant funded project No. 20794 - 1973

Lead Investigator: A .Prof. Raj Prasanna

Research team: A.Prof. Julia S Becker, Dr. Caroline Holden, Dr. Amal Punchihewa, Dr. Seokho Jeong, Dr. Marion L Tan, A.Prof. Kristin Stock, Prof. Anna Brown, Prof. Christine Kenney, Chanthujan Chandrakumar, Rasika Nandana, Emily Lambie, Alicia Cui, Rangana Sampath, Danuka Ravishan, Ben Hong, Nandika Liyanage, Zade Viggers, Jeff Lin and Nuwan Waidyanatha.

Executive summary

This research has investigated the feasibility of a decentralised network of low-cost Microelectromechanical Systems (MEMS) based ground motion detection sensors hosted by the general public to generate EEW applications for Aotearoa New Zealand. The research has taken the design science approach supported by the active participation of members of the general public and a number of relevant stakeholders including researchers, practitioners and members from the civil defence and emergency management community. As the first step, potential user needs, views and concerns with regard to implementing EEW systems and receiving EEW in NZ were identified by engaging with the communities and stakeholder groups. Subsequently, a Community of Practice (CoP) for EEW was formed as a knowledge-sharing platform. In parallel, this research has investigated the strengths and weaknesses of existing low-cost sensors and sensor networks to issue EEW. As the final step, on an experimental basis, a self-configurable EEW sensor network architecture consisting of low-cost MEMS devices hosted by the members of the general public was deployed in the Wellington Region and its performance was evaluated. The research findings highlighted the essential need for close and continuous engagement with various potential end-user groups throughout the design, development and implementation of any EEW system. Further, the findings of this research provided clear evidence to confirm that the proposed type of low-cost EEW sensor network can successfully be implemented by choosing the appropriate sensors and algorithms. The outcomes of the research provide a comprehensive guide to constructing an EEW sensor network with decentralised processing and can be used as a benchmark, which is beneficial in building similar networks in the future. Furthermore, the proposed concept of a decentralised, low-cost sensor network architecture can be applied to implement community-engaged warning applications in other disaster domains, such as developing low-cost warning systems for bushfires.

Keywords: Earthquakes, earthquake early warning, microelectromechanical systems, low-cost, design science, the community of practice, sensor network, public engagement

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