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Floodnet: Early Flood Warning System Based on Network of Sensors

CSEF · 2023 Electronics & Electromagnetics (Junior Division)

Nikita Jain, Ira Thota

Overview

We built a networked flood warning system that uses the water level and flow rate to minimize the loss of property, livestock, and lives. It provides an early warning in two ways: local warnings with light, sound, display, and remote warnings with light, email, and Twitter alerts. Interconnected systems help distribute the warning immediately and aggregate data for storage and visualization. During floods, water may be contaminated or polluted so this system also monitors and locates sources of the pollutants in the water. All the sensors use low-power Lora connectivity, avoiding the need for a mobile network or Wi-Fi at each location. We built our own sensor to measure water level, used a Hall sensor for flow rate, and a total dissolved solids (TDS) sensor for measuring contaminants. We used statistical analysis to improve the quality of data and ensure the consistency of results.

Source coverage

This record comes from a published award list, not a complete project archive. Its abstract comes from CSEF's public project showcase as archived by the Internet Archive before judging (https://web.archive.org/web/20230401224130/https://ca-csef.zfairs.com/showcase/ShowcaseInfo?f=838e60b7-ea75-46e8-865c-fde4864244b3); the version presented may differ.

Awards (1)

  • Sponsored Award: Coding with Commitment Award

Competition history

  • CSEF 2023 Electronics & Electromagnetics (Junior Division) · Entry J1029

Resources

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