FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu
- Title
- FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu
- Creator
- Indrakumari R.; Sriramulu S.; Partheeban N.; Rajavel R.
- Description
- Floods continue to pose significant threats to communities worldwide, causing loss of life, property damage, and disruption of vital services. Timely and accurate flood monitoring and early warning systems play a critical role in mitigating these impacts. This chapter presents FloodWatch, an innovative IoT-based flood monitoring and early warning system designed to enhance community resilience and response capabilities for the Cuddalore district, classified as one of the multi-hazard-prone districts of Tamilnadu. The Cuddalore district has a coastal line of 68 km, hence it is vulnerable to cyclones, and heavy rainfall, in turn causing floods. FloodWatch leverages the power of the Internet of Things (IoT) technology and provides real-time data collection, analysis, and dissemination for flood-related parameters. FloodWatch integrates a network of smart sensors strategically deployed in flood-prone areas, including rivers, streams, and urban drainage systems. These sensors continuously measure key variables, such as water level, rainfall intensity, weather conditions, and soil moisture content. The collected data is transmitted to a centralized cloud-based platform, where advanced data analytics and machine learning algorithms are employed to process and analyze the information. FloodWatch utilizes historical data and predictive modeling to assess the risk of flooding and generate accurate early warnings. Through intuitive interfaces and mobile applications, relevant stakeholders, including local authorities, emergency responders, and residents, receive real-time alerts and notifications, enabling timely decision-making and appropriate response actions. Key features of FloodWatch include its scalability, adaptability, and user-friendliness. The system can be easily customized to cater to different geographical and environmental conditions, ensuring its applicability in diverse regions. Additionally, FloodWatchs intuitive interfaces provide actionable insights in a visually comprehensible manner, facilitating effective communication and community engagement. The implementation of FloodWatch offers several notable benefits, including improved flood preparedness, reduced response time, and enhanced disaster management. By equipping communities with the tools to monitor, predict, and respond to floods, FloodWatch contributes to minimizing the impact of flood-related disasters, ultimately fostering greater resilience and safeguarding lives and property. FloodWatch represents a significant advancement in flood monitoring and early warning systems, harnessing IoT technology to provide accurate and timely information to communities at risk. This chapter highlights the architecture, functionality, and advantages of FloodWatch, underscoring its potential to enhance resilience and contribute to more effective flood management strategies on a global scale. 2025 selection and editorial matter, A. Daniel, Srinivasan Sriramulu, N. Partheeban, and Santhosh Jayagopalan; individual chapters, the contributors.
- Source
- Digital Twin Technology and Applications, pp. 374-387.
- Date
- 2024-01-01
- Publisher
- Taylor and Francis
- Coverage
- Indrakumari R., Galgotias University, Greater Noida, India; Sriramulu S., School of Computing Science and Engineering, Galgotias University, India; Partheeban N., School of Computer Science and Engineering, Galgotias University, India; Rajavel R., Department of CSE, Christ University, Karnataka, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-104011900-6; 978-103243059-1
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Indrakumari R.; Sriramulu S.; Partheeban N.; Rajavel R., “FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/17970.