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The PLURAL project aims to design, validate and demonstrate a palette of versatile, adaptable, scalable, off-site prefabricated plug-n-play facades accounting for user needs; these facades are collectively called “Plug-and-Use” kits (PnU kits for short). Three different core systems are assessed, coupling heating/cooling, ventilation, heat harvesting systems with smart windows, 3D printing, low carbon footprint and nano-enabled coating materials to reduce the building's total primary energy consumption to less than 60 kWh/m2 per year and ensure on-site renewable energy generation to more than 50 kWh/m2 reaching NZEB status for different European climates and different residential building typologies.

Digital Tools in PLURAL

In addition to the main technological pillars of the project, PLURAL has developed a set of advanced distributed IT tools to enable the design, simulation, assessment and monitoring of real live data coming from real building sites. There are two main repositories in PLURAL, that together comprise the LYSIS infrastructure of the project:

A distributed message bus (implemented via a Kafka cluster) that obeys the Publish/Subscribe model: clients wishing to send some data for others to use, publish their data as messages on a specific “topic” in the cluster; other clients wishing to use data that appear on specific topics subscribe to these topics and are notified whenever new messages arrive there. Special provisions have been made for topics hosting large-size messages, such as messages containing the Building Information Model (BIM) of an entire building, in IFC or other formats. The message bus also has several other topics set up for the storing and management of the results of simulations of buildings after their possible deep renovation using one of the PnU kits; further, to support an advanced decision support system (called MODEST) the message bus has several topics (one per building site supported) that accept messages containing the simulated values of several Key Performance Indicators (KPIs) of the corresponding buildings after a deep renovation using a particular PnU kit configuration has been applied. This makes it possible for the decision support system to fetch all simulated configurations, and select the best one for a building, based on a set of KPIs.

A time-series database (Influx DB v.2) that receives and stores time-series data, such as those coming from weather stations as well as from building gateways that transmit data read from multi-sensor instruments reading variables such as electricity consumption, ambient temperature, CO2 concentration, ambient luminosity etc.

Based on the data infrastructure of the project, an advanced Decision Support System called MODEST has been built that provides the following capabilities to its users:

1. Selecting and sorting simulated PnU kit configurations according to an arbitrary number of KPIs, including NZEB status.

2. Rendering time-series diagrams of all quantities stored in LYSIS that vary in time and displaying them in user-specified resolution.

3. Automatic alerts are emailed to specified administrators when a data source stops transmitting data for more than 3 hours.

All the above functionality is natively hosted on the cloud, allowing anyone with the appropriate credentials to access the system anytime from anywhere in the world and allowing full collaboration between accessing partners.

Training Course

In this video, our partners from Netcompany-Intrasoft presented a training course that helped participants explore the platform's functionalities and capabilities. The course emphasized the demonstration of MODEST-LYSIS, as it offers advanced analytics to extract valuable insights from complex data sets. The demonstration highlighted its potential to revolutionize data analysis and decision-making processes in the project.