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from energy_prediction.EnergyPredictionNorth import EnergyPredictionNorth
from energy_prediction.EnergyPredictionSouth import EnergyPredictionSouth
from energy_prediction.EnergyPredictionPipeline import EnergyPredictionPipeline
def main():
# Energy Prediction North wing
EnergyPredictionNorth = EnergyPredictionNorth(
model_path="src/energy_prediction/models/lstm_energy_north_01.keras"
)
# Energy Prediction South wing
def on_message(client, userdata, message):
df = EnergyPredictionPipeline.fit(message)
if not df is None:
out_vav = EnergyPredictionNorth.pipeline(
df, EnergyPredictionPipeline.scaler
)
broker_address = "localhost"
broker_port = 1883
topic = "sensor_data"
client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION1)
print("Connecting to broker")
client.on_message = on_message
client.connect(broker_address, broker_port)
client.subscribe(topic)
client.loop_forever()
if __name__ == "__main__":
main()
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