Internet of Things based Automated Water Level Monitoring and Alert System
The proposed system for monitoring floods provides real-time information on flood threats using advanced water level and flow sensing devices. It can give you sustainable and up-to-date condition monitoring by continuously monitoring water levels and flow rates. By employing IoT technology, they can send data easily by a cloud-based platform that enhances remote access and an in-depth analysis. This feature is particularly useful for stakeholders and authorities who are required to make efficient and timely decisions for minimizing damage and risks. When the levels of the water reach a certain dangerous level, it sends trigger alerts by GSM texting automatically to the local people, emergency and authority personnel. Such anticipation enhances preparation, response, and general disaster management. Reducing manual surveillance and capitalizing on the automated data aggregation, are large enhancements to minimize delays and human errors, enabling access to the more precise flood risk determination. In addition, the patterns of the past flood events collected by the system could be analyzed to predict patterns of the future and can serve as the basis of its long-term planning and decentralized rapid response through resource mobilization. When combined with forecasting equipment, it becomes even more reliable, leading to accurate forecasts and timely response. Using modern technology, this system for monitoring floodwater represents an inexpensive, reliable, and scalable solution Keywords— Water Level and Flow Sensors, Internet of Things (IoT) Technology, GSM (Global System for Mobile Communications) Alerts, Automated Data Collection, Historical Data Analysis
Authors
- P. Ezhumalai
- Jorge Pavani
- V. Sharmila (ORCID: https://orcid.org/0000-0001-6419-4869)
- Daniela Selvi (ORCID: https://orcid.org/0000-0002-3280-4391)
- Manchinella Pranavi
- Penubolu Sadhvika
Publication Details
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1109/ictmim65579.2025.10988382
- Primary Topic
- Water Quality Monitoring Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00