Comparative Analysis of Communication Technologies for Cloud-Based Flood Risk Predictive Modeling in Urban Areas

Abstract

The increasing occurrence and severity of natural disasters worldwide have emphasized the pressing want for sophisticated technology to enhance catastrophe management and response efforts. The Internet of Things (IoT) has gained significant interest for its ability to potentially transform early warning systems and improve predictive modeling in places prone to disasters. This research article explores the comparison of several communication technologies in the context of a cloud-based predictive modeling system designed for flood risk assessment. The evaluation of cost-effectiveness and performance indicators of various communication systems is centered on a case study. The chosen technologies include Bluetooth, WiFi, LoRa, Zigbee, NB-IoT, and 4G Cellular, each exemplifying distinct methodologies for IoT-enabled communication in crisis management situations. This case study takes place in an area that is prone to flooding. The goal is to use sensor nodes with advanced communication technologies to gather and analyze real-time data. This data will be used to evaluate flood risks and quickly share warnings. This research attempt relies on a well constructed cost analysis framework. The framework provides a thorough overview of expenses associated with each communication method, encompassing hardware acquisition, installation, ongoing maintenance, and data transfer. The project seeks to give stakeholders with practical insights into the economic feasibility of implementing certain communication technologies in the context of flood risk assessment by carefully measuring these cost elements. Moreover, certain criteria for evaluating performance are carefully defined in order to analyze the effectiveness and dependability of any communication technology. Parameters such as range, data rate, power consumption, and overall dependability are analyzed to establish the operational effectiveness of the installed sensor networks. Through rigorous performance assessment, the study aims to reveal the fundamental strengths and limits of each communication technology, therefore aiding decision-makers in their quest to enhance disaster management infrastructure. The outcome of this study endeavor gives significant insights that transcend basic technology comparison. By shedding light on the nuanced interplay between cost considerations, technological capabilities, and performance metrics, the research equips disaster management authorities with the requisite knowledge to make informed decisions regarding the adoption and deployment of IoT-enabled communication technologies. Ultimately, the results of this research effort carry important implications for strengthening disaster resilience and shielding vulnerable populations from the ravages of natural disasters.