Placement of data transmission equipment in the flood warning system based on the Internet of Things (case study : Jiroft Dam Basin)

Floods are one of the most damaging natural disasters that have increased in frequency, severity and resulting damages in recent years in Iran and around the world. One solution to reducing flood damages is to develop a flood monitoring and management system to quickly and widely communicate information and warnings to residents. Conventional methods of flood monitoring cannot provide rapid and widespread community notification. As a solution, this study focuses on an Internet of Things-based flood warning system, which is an intelligent technology capable of sending real-time information using smartphones and web services. Jiroft dam basin has been chosen for the implementation of this system. A key challenge in establishing Internet of Things-based flood warning systems lies in the strategic distribution of equipment for data collection and transmission. To address this, a hexagonal algorithm was employed for equipment placement in this study. By identifying the most flood-prone areas within the basin through the use of the K-means clustering algorithm and flood index(f), the study reveals the efficacy of combining these tools in determining flood potential and optimal locations for implementing flood warning systems. Following the identification of sensitive points within the basin, the study selects the Maidan sub-basin as the most susceptible to floods. Through the application of the hexagonal algorithm and a WSN-03 module with a 3.5-kilometer data transmission range, 192 suitable locations for equipment installation are pinpointed for data reception and transmission. This study will be useful for the development of early flood warning systems and reservoir management.