Earthquake is sudden shaking of the ground surface caused by the movement of seismic waves through Earth’s rocks. Earthquakes are one of the major disasters and their unpredictability causes even more destruction in terms of human life and financial losses. The aim of the project is to predict the chances of earthquake using wireless sensor network data and machine learning and to alert people before the disaster occurs and save their lives.  In the project a simpler way of detecting the occurrence of earthquake has been introduced. It is based on collecting WSN data using the API’s and Machine learning algorithms where weather information API is used to fetch live weather details. The collected live weather data and the previous details of the weather in a particular place are passed to Machine learning algorithms i.e. SVM, KNN, Random Forest, Decision tree and the algorithm which gives more accuracy is chosen and is applied on it to predict the current chances of disaster occurrence. If there is a chance of occurrence of the disaster (Earthquake) then an alert message is sent to the concerned authority to create awareness among people.

WSN, SVM, KNN, Decision tree

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