In-house Developed AI and ML Program to Improve Building Efficiency and Asset Management

Abstract

Machine learning (ML) and artificial intelligence (AI) have become rooted in virtually all aspects of a business. Neural networks, regression modeling, event monitoring, and other Data Science techniques are the new tools that Data Science can apply to produce opportunities within facilities operations to reduce the risk of equipment failure, resource optimization, and infrastructure useful life maximization while driving energy efficiency. This presentation will cover some of the methods for developing an in-house program that utilizes programming languages (RStudio, Python, PostgreSQL) to gather data from building automation systems (BAS), external data and other disparate data sources to produce actionable insights and easily interpretable visualizations (Tableau).

Presented By

Sean W. Hyland, C.E.M., CFM, PMP
Facilities Program Administrator
American Family Insurance

Sean Hyland, C.E.M., C.F.M., P.M.P. is the facilities program administrator for American Family Insurance. Sean holds a B.A. from Edgewood College in Business Administration and is currently pursuing a M.S. in Data Science from UW Eau Claire. He is a former nuclear engineer and electronics technician in the US Navy. Sean applies his facilities experience and analytical skills to drive initiatives that drive energy efficiency, equipment life optimization, risk mitigation, and the application of data science within facilities operations. He is also managing the integration of facilities data into data governance programs and the data lake. Sean can be contacted at shyland@amfam.com or 608-242-4100 X 34840.