The main objective of the project is to establish a means of automatically detecting and reporting associations between streams of data from a wide assortment of sensors. Our system will monitor the sensor data constantly in the background, maintaining an assessment of the relationships between each pair of sensors.

Written for Python 3.6 or later

This example comes with a compressed version of NOAA weather data for Birmingham (AL), Columbus (MS), Biloxi (MS), and Las Vegas (NV). The Docker image will immediately launch a server on 5000 which runs the Association Engine on a sped-up simulation of the data.

docker run -p 5000:5000 -it jacobamason/association-engine

To get Association Engine as a Python package:

pip install association-engine

You can then import AssociationEngine and use AssociationEngine.Manager and AssociationEngine.Sensor for whatever you need.

import AssociationEngine

class MyCustomSensor(AssociationEngine.Sensor):

    def some_function(self):
        self.publish(some_data, some_time)


class MySubscriber:

    def on_data(self, value):
        print("The association value is: " + str(value)):


AE = AssociationEngine.Manager()
sensor_one = MyCustomSensor()
sensor_two = MyCustomSensor()

AE.add_sensor(sensor_one)
AE.add_sensor(sensor_two)

relationship = AE.get_relationship_from_sensors(sensor_one, sensor_two)
relationship.subscribe(MySubscriber())

git clone https://github.com/EliCDavis/AssociationEngine
pip install -e .

After everything has been installed, try running tests to make sure everything is working correctly

pytest