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A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices.

Bingxian Lu1, Ruochen Wang1, Zhenquan Qin1

  • 1School of Software, Dalian University of Technology, Dalian 116000, China.

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Summary
This summary is machine-generated.

This study introduces ThunderLoc, a low-cost lightning localization system using IoT smart devices. It leverages crowdsourced dual-microphone data to accurately pinpoint lightning strikes, outperforming existing methods.

Keywords:
IoTacoustic source localizationcrowdsensingthunder localization

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Atmospheric Science

Background:

  • Traditional lightning localization relies on expensive, fixed base stations.
  • The proliferation of Internet of Things (IoT) devices offers new opportunities for distributed sensing.
  • Existing methods face limitations in cost and deployment flexibility.

Purpose of the Study:

  • To develop a low-cost, distributed lightning localization system using readily available IoT devices.
  • To leverage crowdsourced sensor data for improved lightning detection and location accuracy.
  • To address the limitations of traditional, high-cost lightning detection infrastructure.

Main Methods:

  • Utilizing dual-microphone data from IoT smart devices (e.g., smartphones) via crowdsourcing.
  • Estimating the Time Difference of Arrival (TDOA) of thunderclaps using generalized cross-correlation.
  • Transforming the localization problem into a search within Hamming space by quantifying TDOA measurements.
  • Minimizing Hamming distance against a database for precise thunder localization.

Main Results:

  • The ThunderLoc system demonstrated effective lightning position localization.
  • Extensive simulations and experiments with 30 smartphone nodes confirmed system performance.
  • ThunderLoc showed superior performance and robustness compared to existing lightning localization schemes.

Conclusions:

  • ThunderLoc offers a viable, low-cost alternative for distributed lightning localization.
  • The system effectively utilizes crowdsourced data from everyday IoT devices.
  • The proposed method provides a robust and accurate solution for real-time lightning monitoring.