Docker-Based Downtime Prediction Framework

I am developing a Docker-based federated learning solution for industrial predictive maintenance to greatly enhance machine downtime prediction. The purpose of this system is to more accurately anticipate necessary maintenance and reduce unexpected downtime in industrial machinery by analysing operational data such as speed, temperature, equipment running time, and so on.

We have the code available with us, you just need to make it work for another dataset and run it in Ubuntu.

Prospective freelancers must have skills and experience in the following areas:

- Docker, for providing the backbone of our decentralized system

- Federated Learning, to collectively improve our model's performance without sharing raw data

- Working with and analyzing operational data

- Implementing predictive models, in this case a 3-layer feed-forward neural network and stochastic gradient descent (SGD)

The final deliverable will be a robust and efficient predictive maintenance system that effectively uses operational data to improve machine downtime prediction. Your contribution will be essential in minimizing these unexpected halts in industrial activities. Please refer to the linked PPT for more details.

I look forward to a great collaboration!

Machine Learning (ML) Docker MQTT Tensorflow Ubuntu

Projekt-id: #38067001

About the project