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Development of a Cross-Building Data Analysis Platform with Machine Learning Capabilities

intechhouse.com

Real estate

Environmental Services

Information technology

Business Challenge

Need for a centralized application to enable cross-sectional comparative analysis of building data from multiple locations, with advanced anomaly detection capabilities

About the Client

International PropTech company delivering building management solutions with energy-saving technologies

Project Goals

Create a master application for device data aggregation
Implement machine learning algorithms for pattern recognition
Enable comparative analysis across multiple buildings
Develop interactive dashboards for data visualization
Support multiple deployment options (local/cloud/hybrid)

Core System Requirements

Multi-source data aggregation and normalization
Real-time anomaly detection using ML models
Comparative analysis dashboards
Automated report generation
Database replication capabilities
Customizable data visualization tools

Technology Stack

.NET

C++

InfluxDB

Kapacitor

Python

Grafana

System Integrations

Building management systems (BMS)
Cloud platforms (AWS/Azure)
Energy monitoring devices
Third-party analytics tools

Quality Attributes

High scalability for multi-tenancy support
Data security and compliance (GDPR)
Low-latency real-time processing
Cross-platform deployment flexibility
High availability architecture

Expected Business Impact

Enables 30% faster anomaly detection in building systems, reduces energy costs through data-driven optimization, improves tenant satisfaction with proactive maintenance, and supports environmental sustainability through predictive energy management