Objective

Develop a platform that makes it possible to reduce energy costs through accurate metering, forecasting and consumption management, as well as detection of anomalies and inefficient points.

Project features

Connection to smart meters and IoT sensors from various manufacturers

Dashboards with visualization of indicators and comparison with standards

Notification system for excesses and equipment failures

Forecasting tools based on machine learning

Recommendations for optimizing building engineering systems

Integration with building management systems (BMS)

Work stages

Analytics

Energy consumption scenarios in commercial and residential buildings were studied, and key performance indicators were identified. Facility operation specialists and energy managers were surveyed.

Design

Intuitive control panels were created with an emphasis on visual charts, easy access to key metrics and data filtering by time intervals and departments.

Development and testing

The backend is implemented in Python (FastAPI), the frontend in React. Algorithms for processing and analyzing data from IoT devices were developed. Pilot testing was carried out in a business center and a residential complex.

Results

Energy costs reduced by 15-25% in the first 6 months

Fewer unscheduled repairs of engineering systems

Greater transparency and control for management companies

Increased interest of residents and employees in energy saving

Client feedback

“GreenTrack helped us see exactly where we were losing energy and take action. It is a truly working tool for optimizing costs and for the environment.”