Axross enhances existing HVAC infrastructure by integrating advanced control and optimization layers. The company deploys IoT sensors and leverages Building Management System (BMS) data to build predictive engines for energy consumption forecasting. This system utilizes machine learning algorithms to automate HVAC controls, ensuring optimal equipment sequencing and energy efficiency while maintaining precise environmental conditions.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial facilities often operate HVAC systems inefficiently, leading to excessive energy consumption, increased greenhouse gas emissions, and unstable production environments. Existing building management systems (BMS) may lack the advanced analytics and real-time optimization capabilities needed to adapt to dynamic environmental conditions and operational demands.
Solution
This startup offers an AI-driven automated HVAC control solution designed to enhance energy efficiency and stabilize production environments in industrial facilities. The system integrates with existing BMS infrastructure, leveraging historical and real-time data to build a predictive engine for forecasting energy consumption and cooling demand. IoT sensors gather data on environmental conditions and system performance, enabling dynamic, real-time adjustments to HVAC controls. Machine learning algorithms optimize energy efficiency while maintaining key environmental requirements such as temperature, humidity, and particle counts.
Target Audience
The primary target audience includes industrial facilities seeking to reduce energy consumption, lower greenhouse gas emissions, and improve the stability of their production environments.
Features
- Integration with existing Building Management Systems (BMS) for data extraction and control.
- Deployment of IoT sensors to gather real-time environmental and system performance data.
- Machine learning algorithms for intelligent optimization of energy efficiency.
- Automated HVAC controls for rapid response and optimal equipment configuration.
- Predictive engine for forecasting energy consumption and cooling demand.