WSN and Fuzzy Logic for Flash Flood and Traffic Congestion Detection

Floods are the most common natural disaster and source of significant damage to life, agriculture and economy. Flash Floods are particularly deadly because of short timescales on which they occur. Most flood casualties are caused by a lack of information. There is no dedicated flood sensing systems that monitor propagation of flash floods in cities. .Human being do not have power to totally uproot natural calamity but they can predict natural calamity & take major steps to prevent it. Wireless Sensor Network (WSN) and Internet of Things (IoT) technology is used for predicting & detecting flooding condition in this study. WSN is preferred due to its cost effectiveness, faster transfer of data & accurate computation of required parameter for flood prediction. IoT combines embedded system hardware techniques along with data science or machine learning models. The model uses a mesh network connection over ZigBee for the WSN to collect data, and a GPRS module to send data to the internet. Data sets are evaluated using fuzzy logic to detect floods then broadcast alerts. Floods rarely occur hence the system is dedicated for traffic congestion notifications