It’s all about intelligence

Constructing and operating successful smart buildings is about more than just getting data from connected devices. While it may be obvious that data is not the same as intelligence, converting data from the Internet of Things (IoT) into actionable insights is a serious challenge for most companies seeking to build a smart building.  Building managers require a deep analysis of a huge amount of data in real-time. To be effective at finding insights to achieve operational efficiencies, building managers require customizable dashboards detailing energy usage and sensor data to monitor (and ultimately enhance) facility costs and efficiency. It requires a clear understanding and presentation of what the data means.

Nexos, Igor’s fully integrated PoE communication platform, not only connects devices, fixtures, and systems into one central location for granular control, but also connects devices to a powerful AI-ready cloud analytics option. The result is a customizable dashboard that details energy usage and sensor data while providing real actionable intelligence for facility managers or owners. This enables both users and vendors to tap into the control platform to create their own custom smart building controls, settings and action sets, and retrieve powerful surveillance and monitoring data for planning at unprecedented levels of control.

How does Igor achieve this?

Machine Learning AI Algorithms

The key is that Igor is a cutting-edge software company addressing the application of the IoT to smart building infrastructure. The team looked at the primary challenges in implementing Power over Ethernet into smart buildings and discovered three major issues:
  1. Wrong data – not collecting the right data, enough data, or high-quality data to make accurate predictions.
  2. Wrong tools – not having the right tools or computing infrastructure to analyze the volume, velocity or variety of data.
  3. Wrong people – not having the people skills necessary to transform raw data into actionable insights.

To address these challenges, Igor utilizes machine learning in its smart building platform. Machine learning is an artificial intelligence technology that provides systems with the ability to learn without being explicitly programmed. Even Igor's industry-leading software is just beginning to tap the possibilities of artificial intelligence. However, Igor is committed to an AI future and has already built in the capabilities needed to support AI programming through the use of advanced machine learning capabilities. 

How can machine learning improve smart buildings?

  1. Energy optimization – fine-tuning specific fixtures to maintain illumination levels based on ambient lighting conditions or specific tasks.
  2. Occupant experience – recognize voice commands or gestures and have the building respond according to the occupant’s intentions.
  3. Anomaly detection – detect and report unusual activities within the building.
Machine learning allows for the Igor software to learn, on its own, patterns and opportunities to improve building efficiencies and safety. It's through machine learning that buildings can fully optimize the efficiencies promised through PoE technology.