Abstract

Abstract. With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth’s movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

Highlights

  • Major earthquakes have significant impact on human life and built infrastructure

  • We pursue two objectives: first, we study the feasibility of our previously proposed field model abstractions by applying them to a real world problem, that is real-time earthquake event detection with sensor data streams

  • We modeled the problem of earthquake detection as a problem of processing continuous fields

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Summary

Introduction

Major earthquakes have significant impact on human life and built infrastructure. Earthquakes are created through the constant movement of the Earth’s tectonic plates and the resulting friction that is created. Earthquakes take place due to the movement of tectonic plates, and the tension between them, while moving in different directions. The San Andreas Fault is a fracture line between the Pacific Plate that moves in the North direction and the North American plate, which moves South, and both plates sitting slightly on top of each other. Friction between both plates builds up tension over time, which releases via an earthquake. Displacement along the known smaller and larger fault lines is of most interest

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