Proof of concept AI Energy Bot

Big Blue Data Academy and SenseOne: Proof of concept AI Energy Bot for energy efficiency optimization

Big Blue Data Academy and SenseOne joined forces to create a proof of concept of an innovative Artificial Intelligence Assistant for Energy Analysis – the Generative AI Energy Bot for On-Demand Analysis. As part of the Big Blue Data Academy Data Science Bootcamp, students had a unique opportunity to apply their knowledge and skills to a real-world challenge in the energy sector.

Leveraging energy data from meters and advanced open-source language models, such as Meta’s Llama 3.3, the AI Energy Bot analyzes annual consumption trends and answers questions such as, “What is the annual trend for energy consumption related to the hotel bookings?” or “Which days show the highest energy consumption and how do they compare to the corresponding days of the previous year?”.

The AI Energy Bot has demonstrated the ability to provide user-friendly energy analytics and advanced detection capabilities for abnormal sensor readings or unusual energy consumption based on historical and real-time data. Additionally, it identifies energy inefficiencies, helping users understand and explore energy consumption patterns to identify optimization points that lead to energy cost reduction.

This initiative combined Big Blue Data Academy’s expertise in data science education and SenseOne’s profound knowledge of IoT Data Analytics solutions, which aim to improve energy efficiency and sustainability.

SenseOne, a Space Hellas Group member, provides cutting-edge IoT Data Analytics solutions through its SenseOne IoT Cloud platform. It enables resource consumption monitoring and prediction and contributes to cost reduction and environmental impact minimization for businesses and organizations. Big Blue Data Academy focuses on Data Science, Data Analytics, and Data Engineering training. Through hands-on bootcamps with industry experts, it aims to equip its students with high-demand skills through active learning methodologies.

This collaboration serves as a model of how educational institutions and enterprises can join forces and create practical Artificial Intelligence (AI) solutions that address real-world challenges in critical areas such as energy consumption.