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Aerial sensing system for wildfire detection: Demo abstract
SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
  • Tomasz Lewicki, San Jose State University
  • Kaikai Liu, San Jose State University
Publication Date
11-16-2020
Document Type
Conference Proceeding
DOI
10.1145/3384419.3430399
Abstract

Every day in the summer here in California, we are exposed to extreme wildland firefighting incidents. To fight such wildfires, thousands of firefighters need to spread across hundreds of square miles. Recent years have witnessed an aggressive push towards building Unmanned Aerial Systems (UASs) for helping the fire-fighting missions. In this demo, we present a vision-based aerial sensing system for early fire detection with on-board intelligent processor. We propose a new open source perception system for joint autopiloting and multi-sensory object detection with a tight power budget. The technical approach focuses on developing a robust aerial sensing pipeline for fire detection in low-visible and smoky environments based on multi-cameras and thermal image sensor.

Citation Information
Tomasz Lewicki and Kaikai Liu. "Aerial sensing system for wildfire detection: Demo abstract" SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (2020) p. 595 - 596
Available at: http://works.bepress.com/kaikai-liu/36/