The open, non-proprietary ‘plug and play’ PoE technology, allows for decreased installation and retrofitting costs, lower upfront costs and ongoing savings via lowered maintenance requirements and energy usage controls. For retrofits of existing structures such as schools, retail buildings, offices and healthcare facilities, universal adaptability is necessary to realize the benefits of connected lighting. Igor’s PoE technology is fully integrated, yet modular, connecting any lighting manufacturer’s “off-the-shelf” LED fixtures with sensors. Igor’s solution also includes a powerful cloud analytics option, which can provide customizable dashboards detailing energy usage, and sensor data to monitor facility costs and efficiency.
Igor has developed our PoE Intelligent Lighting Control Systems with an open platform. This allows for universal adaptability, providing businesses with intelligent, scalable PoE technology that enables a proven, highly configurable, yet simple AI-driven enterprise software solution. This elegant technology delivers a clear path for future AI–enabled smart building deployment.
Recognized by Cisco for its technology on the forefront of digital smart building transformation, Igor is part of Cisco’s Digital Building Partnership, a select group of organizations endorsed by Cisco in their Digital Ceiling initiative.
It’s all about intelligence
Building and operating successful smart buildings is not just getting data from linked multi-node devices talking to each other. While it may be obvious that data is not the same as intelligence, converting IoT data into actionable intelligence is a serious challenge to most intelligent lighting companies. Actionable insights for a building manager requires much more than linked multi-node devices and access to data. Building managers require a deep analysis of a huge amount of data in real-time. It requires 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.
Igor’s fully integrated PoE communication platform not only connects any lighting manufacturers’ LED fixtures with sensors but also connects devices to a powerful AI-enabled 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 intelligent LED lighting controls, settings and action sets, and retrieve powerful surveillance and monitoring data for planning at unprecedented levels of control.
How does P.O.E 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:
Wrong data – not collecting the right data, enough data, or high-quality data to make accurate predictions.
Wrong tools – not having the right tools or computing infrastructure to analyze the volume, velocity or variety of data.
Wrong people – not having the people skills necessary to transform raw data into actionable insights.
To address these challenges, Igor decided to utilize machine learning in its intelligent lighting 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 advanced AI programming through the use of advanced machine learning capabilities.
How can machine learning improve smart buildings?
Energy optimization – fine-tuning specific fixtures to maintain illumination levels based on ambient lighting conditions or specific tasks.
Occupant experience – recognize voice commands or gestures and have the building respond according to the occupant’s intentions.
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.