Case Study
Edge Computing in HVAC
IoT and edge computing integration in HVAC systems led to energy savings, improved comfort, and continuous data-driven optimization.
IoT and edge computing integration in HVAC systems led to energy savings, improved comfort, and continuous data-driven optimization.
This innovative project aimed at transforming traditional HVAC systems into intelligent, data-driven systems. By incorporating IoT sensors and edge computing, the goal was to achieve real-time optimizations, improving both energy efficiency and the comfort of building occupants.
Our client is an innovative organization focused on transforming building climate control systems through advanced technologies like IoT and edge computing, aiming to optimize energy usage, improve comfort, and promote sustainability.
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Abhay Mathur
Head of Mobile Development
> Traditional HVAC systems were energy-inefficient.
> Difficulty in maintaining optimal room temperatures and humidity levels.
> High energy costs and environmental impact.
> Need for a system capable of making real-time adjustments for better efficiency.
The project team implemented temperature and humidity predictions for individual rooms using Ekkono, a machine learning platform at the edge. The predictions were converted into edge-based models for real-time decision-making at the device level. Exploratory Data Analysis (EDA) was used to uncover insights, further enhancing the system’s optimization.
The integration of IoT and edge computing led to significant energy savings, reduced operational costs, and a more sustainable building operation. The system’s ability to adjust room temperature and humidity levels in real time greatly improved occupant comfort, boosting productivity and satisfaction. The data-driven insights ensured the HVAC system continued to optimize over time, demonstrating the potential of IoT and edge computing for energy-efficient and comfortable building management.
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