Periodic Reporting for period 2 - Auto-DAN (Deploying Augmented intelligence solutions in EU buildings using Data analytics, an interoperable hardware/software Architecture and a Novel self-energy assessment methodology.)
Reporting period: 2022-04-01 to 2023-09-30
The Auto-DAN project aims to enable homes & small businesses across the EU to optimize their energy consumption & provide an assessment of the live energy performance of a building which takes into account the quality of appliances/systems installed, user operational habits & the smart readiness of a building. The solution is rooted in augmented intelligence which will focus on the assistive role automation will have in buildings, emphasizing the fact that cognitive technology is designed to enhance human intelligence rather than replace it & that the occupant is a proactive component of the building. AuI enhances a self-optimisation solution as it is a mix of automated controls with user interaction which will maximise the savings of a building in operation. To enable this step-change, the Auto-DAN project will deliver a trebled-structured project framework that evaluates the actual energy performance of EU buildings & provide building users with the awareness to proactively optimize their energy use.
The following, lists the intended features of the final Auto-DAN platform:
• Smart Hardware Infrastructure - Adaptable hardware strategy that can be applied to all building types and features to ensure maximum replicability of the Auto-DAN solution across the EU building stock.
• Inter-operable Software Architecture - A data analysis platform will be used as a foundation for self-optimizing and self-assessing EU buildings stock complemented by 2 analytical features that provides optimisation actions to the building occupant. Those features are a 1. Digital Occupancy Model and a 2. Digital Twin.
• Self-Energy Assessment Framework - Generates an automated, dynamic and continuous energy performance assessment derived from the monitoring of the energy consumption at building level, dis-aggregated monitoring at an appliance/system level.
The following, lists the intended features of the final Auto-DAN platform:
• Smart Hardware Infrastructure - Adaptable hardware strategy that can be applied to all building types and features to ensure maximum replicability of the Auto-DAN solution across the EU building stock.
• Inter-operable Software Architecture - A data analysis platform will be used as a foundation for self-optimizing and self-assessing EU buildings stock complemented by 2 analytical features that provides optimisation actions to the building occupant. Those features are a 1. Digital Occupancy Model and a 2. Digital Twin.
• Self-Energy Assessment Framework - Generates an automated, dynamic and continuous energy performance assessment derived from the monitoring of the energy consumption at building level, dis-aggregated monitoring at an appliance/system level.
By Month 36, Auto-DAN has significantly advanced in hardware infrastructure, software architecture, augmented intelligence solutions, and energy assessment methodologies. Despite typical pilot project challenges like data availability and integration issues, substantial progress has been made, keeping the project on track to enhance energy efficiency and sustainability across diverse EU building types.
A flexible smart hardware infrastructure has been developed with specifications for integrating various technologies and third-party products. Key components such as smart meters, IoT gateways, and user experience (UX) dashboards have been designed to ensure adaptability across residential and commercial buildings. Feedback from surveys in different demo regions has shaped the hardware strategy to meet diverse needs.
In interoperable software architecture, technologies were integrated into a unified data management platform, achieving interoperability between the iSCAN and SenseIoTy platforms. Advanced digital twin and occupancy models were developed for building performance assessments, though final implementations were delayed due to pilot execution and data availability issues.
For Augmented Intelligence (AuI) solutions, UX dashboards were developed and extensively tested with users to enhance designs based on feedback.
A live self-energy assessment method was also developed, defining and applying key performance indicators (KPIs) across demo sites. Despite challenges like delays in pilot commissioning and data shortages, KPIs were integrated into the Auto-DAN dashboard, improving accessibility and utility.
Lastly, the project aimed to boost sustainable energy investments among EU companies by assessing business models and identifying market opportunities in energy flexibility and demand response. Feedback from building automation experts through surveys and industry events informed strategies on Energy Performance Contractual (EPC) schemes and financing models, focusing on attracting investments and validating Auto-DAN's capability to improve energy efficiency in residential, commercial, and community settings.
A flexible smart hardware infrastructure has been developed with specifications for integrating various technologies and third-party products. Key components such as smart meters, IoT gateways, and user experience (UX) dashboards have been designed to ensure adaptability across residential and commercial buildings. Feedback from surveys in different demo regions has shaped the hardware strategy to meet diverse needs.
In interoperable software architecture, technologies were integrated into a unified data management platform, achieving interoperability between the iSCAN and SenseIoTy platforms. Advanced digital twin and occupancy models were developed for building performance assessments, though final implementations were delayed due to pilot execution and data availability issues.
For Augmented Intelligence (AuI) solutions, UX dashboards were developed and extensively tested with users to enhance designs based on feedback.
A live self-energy assessment method was also developed, defining and applying key performance indicators (KPIs) across demo sites. Despite challenges like delays in pilot commissioning and data shortages, KPIs were integrated into the Auto-DAN dashboard, improving accessibility and utility.
Lastly, the project aimed to boost sustainable energy investments among EU companies by assessing business models and identifying market opportunities in energy flexibility and demand response. Feedback from building automation experts through surveys and industry events informed strategies on Energy Performance Contractual (EPC) schemes and financing models, focusing on attracting investments and validating Auto-DAN's capability to improve energy efficiency in residential, commercial, and community settings.
On the smart hardware infrastructure side, the Auto-DAN solution will provide a flexible approach to deploying smart technologies with a wide spectrum of device choice based on the intended user needs. This flexible approach will be set up specifically to ensure that the user gleans the maximum benefit from their technology installations, providing clarity to the home occupant to develop a, fit-for purpose, all encompassing smart home solution. Furthermore, this simple and non-invasive hardware solution will address the absence of Building Management Systems within these buildings. The creation of this smart hardware infrastructure will provide a new level of smart readiness in small buildings that has been challenging to date.
The existing software market offerings tend to offer a selection of services that can generally be classed under six different headings, namely energy optimization, flexibility optimization, system fault detection, comfort optimization, what-if analysis and certification. Currently, there is currently no individual solution that offers all six of the services above. Furthermore, in many of the cases, significant contributors towards energy performance were omitted from the analytical workflow (for example real-time weather data) , which will have an impact on the accuracy of the computations. The Auto-DAN platform will satisfy all six of the service offerings indicated above, providing the user with a single tool that they can use for all their building performance needs. Also, by exploiting the analytical capabilities of the Digital Twin and Digital Occupancy Model, deep and accurate insights can be shared with the building occupant to significantly improve the performance of their building.
Through Auto-DAN, the implementation of AuI will present energy insights to building users, while enhancing automated controls where they are present. With these newfound or improved insights into operational behaviour, this will also enable citizens to optimise their own energy use and a knock-on effect will take place as occupants can educate alternative occupants to modify their energy patterns to a more conservative approach. Data will be available for use in the Digital Twin to enhance the energy modelling of buildings providing occupants with un-paralleled operational information and scenario generation required to improve energy performance behaviourally before being supplied with an audit detailing optimum energy strategies to implement.
Auto-DAN will unlock the potential of “live” energy audits focusing the whole self-energy performance assessment on it and its structure, thus making these documents accurate in terms of real monitoring data. The Auto-DAN audit will be dynamic and continuous (as the user interacts with their building and make changes the “live” audit, this will be represented). Static existing audits only represent the current status of the building, however the Auto-DAN methodology will provide an ongoing assessment that is reactive to occupational/physical changes & will also have a large impact on EPBD and EU standards for energy efficiency.
The existing software market offerings tend to offer a selection of services that can generally be classed under six different headings, namely energy optimization, flexibility optimization, system fault detection, comfort optimization, what-if analysis and certification. Currently, there is currently no individual solution that offers all six of the services above. Furthermore, in many of the cases, significant contributors towards energy performance were omitted from the analytical workflow (for example real-time weather data) , which will have an impact on the accuracy of the computations. The Auto-DAN platform will satisfy all six of the service offerings indicated above, providing the user with a single tool that they can use for all their building performance needs. Also, by exploiting the analytical capabilities of the Digital Twin and Digital Occupancy Model, deep and accurate insights can be shared with the building occupant to significantly improve the performance of their building.
Through Auto-DAN, the implementation of AuI will present energy insights to building users, while enhancing automated controls where they are present. With these newfound or improved insights into operational behaviour, this will also enable citizens to optimise their own energy use and a knock-on effect will take place as occupants can educate alternative occupants to modify their energy patterns to a more conservative approach. Data will be available for use in the Digital Twin to enhance the energy modelling of buildings providing occupants with un-paralleled operational information and scenario generation required to improve energy performance behaviourally before being supplied with an audit detailing optimum energy strategies to implement.
Auto-DAN will unlock the potential of “live” energy audits focusing the whole self-energy performance assessment on it and its structure, thus making these documents accurate in terms of real monitoring data. The Auto-DAN audit will be dynamic and continuous (as the user interacts with their building and make changes the “live” audit, this will be represented). Static existing audits only represent the current status of the building, however the Auto-DAN methodology will provide an ongoing assessment that is reactive to occupational/physical changes & will also have a large impact on EPBD and EU standards for energy efficiency.