About clientInternational company, which delivers a wide range of services in the PropTech sector. Innovative solutions make possible effective management of buildings and cost optimization, increasing tenant safety and satisfaction. Thanks to the use of energy-saving technologies, the activities of the company have also a positive impact on environmental protection.
Climate change increasing pressure on energy efficiency in both- commercial buildings and industrial production. It’s crucial to gather data and knowledge based on information from energy meters and experts. It enables the effectively translate of these data into satisfying results.
There is a global need to provide solutions that support optimization activities for existing objects, with different levels of technical installations.
- Project manager,
- Business analyst,
- Programmer C++ (data acquisition),
- Programmer .Net (Web interface),
- Electronic engineer,
- AI scientist (ML algorithm),
- Power engineer (know-how for media consumption analysis),
- Mechanic constructor (dedicated case).
The goal of the project was an autonomous device that analyzes the consumption of energy and water in managed buildings.
Media Consumption Analyzer is an innovative system designed for data collection, recording, and analysis of local data from devices belonging to one machine, installation, or switching station. It is completely autonomous and enables the acquisition, archiving and data processing as well as the presentation of analysis results. The user receives dashboards that enable them to find out fields of energy losses and determine the potential for optimization.
Technology used in project
.Net – web application, C++ – aplication for data acquisition, InfluxDB – time series database, Kapacitor + Python – algorithms for data analisis with ML, Grafana – technology for data visualisation, 3D printer – case prototyping
Value we added
The autonomous solution that analyzes data from utility meters to diagnose where and why energy is being lost.
An overarching analytics system that compares data from multiple facilities to:
– prioritize modernization investments,
– predict machine failures based on historical data.