Predictive Maintenance Cost Optimization for Commercial Properties

Develop a Python-based predictive maintenance optimization system using time series analysis and machine learning techniques. Utilize libraries like Prophet for forecasting, create a comprehensive dataset tracking building age, repair history, equipment specifications, and maintenance logs. Implement a recommendation engine that predicts potential failure points, estimates repair costs, and suggests proactive maintenance strategies to minimize long-term expenses. Include a dashboard visualization component using Dash or Streamlit.