AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science

Year : 2023 | Volume : 01 | Issue : 02 | Page : 9-17
By

    Ushaa Eswaran

  1. C. Pushpalatha

  2. Shaik Beebi

  1. Principal and Professor, Department of ECE, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India
  2. Assistant Professor, Department of ECE, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India
  3. Assistant Professor, Department of ECE, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India

Abstract

This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure is installed across a flood-prone river basin spanning 50 km2, with sensors streaming data to an integrated software platform. The recurrent neural network model performs accurate hourly flood predictions across multiple lead times with an average precision of 0.82 and recall of 0.79 on the testing dataset. The automated dam gate system initiates opening/closing actions based on the flood predictions, while maintaining water levels within the safe operation zone 95.6% of the deployment duration. The end-to-end system provides emergency responders 36 h of early warning on average and reduces risk of infrastructure failures and downstream inundation.

Keywords: Flood monitoring, dam gate control, machine learning, internet of things, sensors

[This article belongs to International Journal of Data Structure Studies(ijdss)]

How to cite this article: Ushaa Eswaran, C. Pushpalatha, Shaik Beebi AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science ijdss 2023; 01:9-17
How to cite this URL: Ushaa Eswaran, C. Pushpalatha, Shaik Beebi AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science ijdss 2023 {cited 2023 Dec 22};01:9-17. Available from: https://journals.stmjournals.com/ijdss/article=2023/view=130845

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Regular Issue Subscription Review Article
Volume 01
Issue 02
Received December 5, 2023
Accepted December 12, 2023
Published December 22, 2023