
Features of the Software:
- Real-time Earthquake Monitoring – Uses seismic data from global sources.
- AI-Powered Prediction – Machine learning predicts the intensity before the quake happens.
- Instant Alerts – Sends notifications to users via mobile and online gadgets.
- User Safety Tips – Provides guidance on what to do before, during, and after an earthquake.
I am providing a basic Python code that uses AI to predict earthquakes and send alerts.
I
import requests import time import numpy as np import tensorflow as tf from plyer import notification
Function to get real-time earthquake data
def get_earthquake_data(): url = “https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/2.5_day.geojson” response = requests.get(url) data = response.json() return data
Load pre-trained AI model (dummy model for demonstration)
def load_ai_model(): model = tf.keras.models.load_model(“earthquake_prediction_model.h5”) return model
Function to predict earthquake severity
def predict_earthquake(magnitude, depth): model = load_ai_model() input_data = np.array([[magnitude, depth]]) prediction = model.predict(input_data) return prediction[0][0]
Function to check earthquake severity and send alerts
def check_for_earthquake(): data = get_earthquake_data() for quake in data[‘features’]: magnitude = quake[‘properties’][‘mag’] depth = quake[‘geometry’][‘coordinates’][2] # Depth of earthquake location = quake[‘properties’][‘place’]
# AI-based prediction of severity
predicted_severity = predict_earthquake(magnitude, depth)
if predicted_severity >= 5.0: # Threshold for sending alerts
message = f”Earthquake Alert!\nPredicted Severity: {predicted_severity}\nMagnitude: {magnitude}\nLocation: {location}\nTake Precautions!”
send_alert(message)
Function to send notifications
def send_alert(message): notification.notify( title=”Earthquake Warning!”, message=message, timeout=10 ) print(message)
Run the script periodically
while True: check_for_earthquake() time.sleep(3600) # Check every hour
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