Phoenix Energy Technologies has come up with a new AI model that is particularly designed to streamline the classification of data from various Internet of Things (IoT) devices. It is named as ClassifyAI model and mainly focus on addressing the difficulties which are associated with the integrating IP-enabled devices across the IoT landscape. It basically does the job by providing accurate classification of data.
Integrating different IP-enabled devices into a single platform poses challenges. Accessing relevant third-party data streams remains limited. This limits the decision-making regarding energy consumption, occupant comfort and asset performance for smart building rollouts.
ClassifyAI tool is capable in handling such challenges. It is dedicatedly trained to discover and classify data points from various sources within minutes and with high accuracy rate.
It harmonizes descriptions and unifies data from different systems. It simplifies and speeds up the integration process and reduces the transition time from system connectivity to live operations. This addresses complexities in connecting to multiple building management systems and IoT devices by utilizing Machine Learning algorithms and a proprietary dataset.
It is learned that the system can process 50,000 data points in 30 minutes and the accuracy rate is claimed to be more than 99%. Hence, it significantly improves decision-making in IoT systems and optimizes building performance.
Phoenix Energy Technologies CEO Glen Schrank expressed his excitement about the launch of ClassifyAI. He emphasized the potential of the model to revolutionize the multi-site commercial IoT landscape. He simultaneously highlighted the importance of understanding the complexities which are faced by customers in integrating diverse portfolios of IP-enabled devices. He noted that the model empowers proactive decision-making, optimizes operations and enhances building performance, representing a significant advancement in industry standards.
