Machine Learning and Embedded Sensor-Based Flood Monitoring System

Abstract

Asphyxiation and flooding will have a profound adverse effect on humanity and its framework. Choking may occur as the patient moves to a deeper area or may be caused by a patient's underlying medical condition. Floods are catastrophic events typically caused by waterway flow, weather patterns, or unnatural climatic effects resulting from extreme weather conditions. From now on, IoT, driven by sensory innovation, will help effectively mitigate this impact on humanity. This is a test guide for everyone to avoid the risk of suffocation and can help people avoid disasters like floods. This study offers IoT devices equipped with sensors and looking at systems to judge the flood level, the customer situation, and water level, even while the consumer is in the water. Then, using the portable software to become aware and inform the consumer. AI calculations were performed to determine the quantity order.