Optimizing Industrial Water Pollution Warning Mechanism Using Narrowband IoT Technology

Abstract

With the acceleration of industrialization, water pollution is becoming increasingly severe, and traditional pollution warning mechanisms have obvious deficiencies in sensitivity, response speed, and coverage. The emergence of Narrowband Internet of Things (NB IoT) technology provides a new technological approach for environmental monitoring. This article focuses on how to combine NB IoT communication capabilities with intelligent warning models to build a more sensitive and stable industrial water pollution warning mechanism. This study proposes an improved hierarchical data processing and dynamic warning mechanism to achieve early identification and more effective intervention of pollution events in industrial environments. Research has shown that this method significantly improves the efficiency of early warning response and system stability. This study not only fills the application gap of NB IoT in water pollution warning mechanisms but also provides new ideas for the intelligence and wide area of future environmental monitoring systems.