BI-MADE: BIM-based platform for real-time AI-based anomaly detection of energy-consuming systems consumption within data centers.
CUP: F89J23000940007 (LaSia) , J83D23000280002 (Unitus)
TOTAL AMOUNT OF THE PROJECT: €694,852.75
AMOUNT FINANCED: €360,995.29
SOURCE: PR ERDF Lazio 2021-2027
The BI-MADE project aims to develop an innovative ICT platform to detect anomalies in consumption and enable preventive/predictive maintenance processes in data centers. The combination of IoT monitoring, AI models and BIM information will provide a comprehensive solution enabling greater energy efficiency, enhanced security and environmental sustainability of IT assets.
BI-MADE is an ambitious initiative designed to improve the energy efficiency of European data centers. The project uses advanced digital technologies, including Artificial Intelligence (AI) and Building Information Modeling (BIM), to optimize performance, reduce maintenance costs, and improve energy resource utilization.
In the context of the energy transition, BI-MADE plays a crucial role. Data centers account for 4 percent of global energy consumption at the European level and have a significant impact on greenhouse gas emissions. The project addresses this challenge by developing solutions to monitor and optimize energy consumption, reducing environmental impact and operational costs.
BI-MADE aims to monitor and optimize data center energy consumption through AI models for data analysis and inefficiency detection. It uses sensors and wireless networks to create a distributed measurement system, enabling real-time monitoring and facilitating early detection and correction of anomalies. In addition, the project develops an innovative ICT platform for IT asset management, improving energy efficiency, security and environmental sustainability.
The project focuses on smart networks and microgrids, using advanced technologies for management and control. It includes innovative devices and measurement methodologies for smart grid applications, ensuring more efficient and sustainable energy management.
BI-MADE aligns with several trajectories of priority interest in the Lazio region’s Smart Specialization Strategy, including the development of technologies to foster energy system flexibility and end-user participation. The data-driven approach and the use of AI are key to improving energy efficiency and reducing costs.
BI-MADE contributes to the circular economy by optimizing maintenance processes and extending the useful life of plants. Continuous monitoring of energy data enables detection of maintenance problems or failures before they become serious, enabling timely intervention and reducing the need for new purchases. This approach promotes environmental sustainability through repair and reuse of existing equipment.
The BI-MADE project aims to leverage AI and BIM modeling to improve monitoring and energy efficiency in data centers. The BI-MADE platform will offer a comprehensive solution for monitoring and managing IT assets, analyzing energy data in detail to identify inefficiencies in heating, lighting, ventilation and air conditioning systems.
EU member states have pledged to reduce average emissions by 40 percent by 2030 compared to 1990 values. In this context, data centers, being highly energy-consuming infrastructures, need significant improvements to reduce their environmental impact. BI-MADE addresses these issues through an anomaly detection system based on IoT data and BIM modeling, optimizing energy use and improving energy efficiency.
The BI-MADE project aims to foster sustainable European economic growth by improving the energy efficiency of strategic energy-intensive assets such as data centers through the integration of innovative AI-based technologies and BIM modeling. The main technological goals are:
OT1 – AI model development
Develop an AI model for data center energy monitoring and efficiency, using advanced algorithms such as neural networks, data mining, decision tree and deviation detection.
OT2 – Framework for Data Center BIM Modeling.
Create a framework for data center BIM modeling, integrating existing ontologies and standards such as SAREF, ASHRAE Standard 90.4, IFC, gbXML, BEMSchema, EnergyPlus Data Dictionary, and OBEP.
OT3 – ICT platform development
Develop an innovative ICT platform for energy asset monitoring and energy efficiency, integrating AI model and BIM modeling framework, ensuring scalability and resilience through full cloud microservices architecture and containerization.
OT4 – Validation on a Case Study.
Validate the BI-MADE platform on a real-world case study by monitoring and analyzing energy data from an existing data center to verify the effectiveness of the proposed solution.
The added value of BI-MADE lies in the integration of BIM, IoT and AI into a single platform for data center energy monitoring and efficiency. This innovative approach improves energy efficiency, environmental sustainability, operational resilience and safety, with a positive impact on economic, social and environmental aspects.
The BI-MADE project has several competitive advantages for participating companies, including:
– Development of company know-how: through participation in the project, LASIA aspires to acquire innovative skills and knowledge in the field of digital technologies and Artificial Intelligence applied to energy efficiency, which can be a competitive advantage over other companies in the sector by being able to have both historical skills related to design technologies and data processing through AI models.
– Enhancement of intellectual property by protection through industrial property rights: the results obtained from the BI-MADE project, such as the artificial intelligence models developed or the new ICT platforms for data center management, can be the subject of patents and other intellectual property rights that enable companies to protect their innovation and create a competitive advantage while increasing the value of capitalizations.
– Increased profitability: the results of the BI-MADE project, if properly leveraged, can lead to increased profitability for participating companies primarily through increased service levels as a magnitude inversely proportional to the reduction of extraordinary maintenance work
– Employment and environmental spin-offs: the BI-MADE project can also have important employment and environmental spin-offs, creating new specialized and sustainable jobs in the field of digital technologies for energy efficiency, and contributing to the reduction of CO2 emissions and the consequent improvement of environmental conditions also considering the strong growth trend of the data center sector in Europe for the coming years.
The BI-MADE project aims to develop new technologies and methodologies for energy efficiency through the use of advanced digital technologies such as artificial intelligence and big data analytics. One of the most important challenges the project wants to address is to ensure that the knowledge developed and results achieved are replicable, so that they are accessible and usable to a wide range of energy stakeholders beyond the data center.
To this end, the project envisages the definition of open, interoperable technology models and standards that promote interoperability between systems and applications, thus ensuring greater dissemination and adoption of the solutions developed. In addition, the project includes the organization of technical workshops and seminars, as well as the publication of documents and guides, in order to promote the dissemination and adoption of the technologies and methodologies developed.
