Funded Research

AER R-43127: Automating Predictive Maintenance for Energy Efficiency via Machine Learning and IoT Sensors

Award: $82,112   Role: Co-PI

Our long-term goal is to develop an energy management decision support tool with the purpose of leveraging smart sensors to automate the prediction and optimization of energy efficiency and operational cost from the point of view of management in the context of small to medium size businesses.

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Results:

• Developed a microservice-based framework for predictive maintenance using RPi, Flask, Docker, RabbitMQ, and Scikit-Learn

• Published one paper describing this work (see publications).