Aslak Johansen

Brick: Towards a Unified Metadata Schema For Buildings

Commercial buildings have long since been a primary target for applications from a number of areas: from cyber-physical systems to building energy use to improved human interactions in built environments. While technological advances have been made in these areas, such solutions rarely experience widespread adoption due to the lack of a common descriptive schema which would reduce the now-prohibitive cost of porting these applications and systems to different buildings. Recent attempts have sought to address this issue through data standards and metadata schemes, but fail to capture the set of relationships and entities required by real applications. Building upon these works, this paper describes Brick, a uniform schema for representing metadata in buildings. Our schema defines a concrete ontology for sensors, subsystems and relationships among them, which enables portable applications. We demonstrate the completeness and effectiveness of Brick by using it to represent the entire vendor-specific sensor metadata of six diverse buildings across different campuses, comprising 17,700 data points, and running eight complex unmodified applications on these buildings.

OccuRE: An Occupancy REasoning Platform for Occupancy-Driven Applications

Occupant behavior determines a large share of the energy consumption of buildings. Software applications driven by information about occupant behavior provide a mean to optimize this share. However, existing systems for sensing occupancy behavior provide technology-specific APIs statically coupled to the type of computed occupancy information. Software platforms for developing applications for buildings do also not provide abstractions for occupancy behavior. Therefore, technology lock in and lack of proper abstractions wreck the development of occupancy-driven applications. In this paper we present the design, implementation and evaluation of OccuRE, a stream-based Occupancy REasoning platform. OccuRE provides a technology agnostic API for accessing occupancy information to significantly improve portability. The platform uses a component-based computation model with dynamic composition to calculate and reason about occupancy behavior. Together these elements avoid that developers need to deal with technology-specific processing of sensor data to ease application development. Through micro-benchmarks we show that OccuRE successfully and efficiently computes occupancy information for technology-heterogeneous building instrumentations. We use the development of three prototype applications to demonstrate that the API of OccuRE (i) enables several types of occupancy-driven applications, (ii) that the applications -- by using the interface -- achieve portability in regards to occupancy information computation and (iii) that the application code avoids handling sensor data processing.

Demand response in commercial buildings with an Assessable impact on occupant comfort

Electricity grids are facing challenges due to peak consumption and renewable electricity generation. In this context, demand response offers a solution to many of the challenges, by enabling the integration of consumer side flexibility in grid management. Commercial buildings are good candidates for providing flexible demand due to their volume and the stability of their loads. However, existing technologies and strategies for demand response in commercial buildings fail to enable services with an assessable impact on load changes and occupant comfort. In this paper we propose the ADRALOC system for Automated Demand Response with an Assessable impact on Loads and Occupant Comfort. This enhances the quality of demand response services from a grid management perspective, as these become predictable and trustworthy. At the same time building managers and owners can participate without worrying about the comfort of occupants. We present results from a case study in a real office building where we illustrate the advantages of the system (i.e., load sheds of 3kW within comfort limits). Presenting a better system for demand response in commercial buildings is a step towards enabling a higher penetration of intelligent smart grid solutions in commercial buildings.

Towards a metadata discovery, maintenance and validation process to support applications that improve the energy performance of buildings

Using pervasive computing at a scale for improving the energy performance of buildings requires that applications are portable among buildings. One problem in enabling portable applications is metadata about building infrastructures. The challenge is that there are multiple ways to annotate sensor data and actuation points, which makes it difficult to have a proper level of abstraction. Another problem is the amount of insufficient or missing metadata. This paper presents an analysis of the leading software platforms for sensor infrastructures with respect to how metadata is handled. Furthermore, the paper also presents an analysis of the leading metadata formats with respect to how they support building applications. Based on the analysis, we conclude that there is a need for a structured way to manage metadata in buildings. Therefore we present our vision of a process view on discovery, maintenance and validation of metadata in buildings.

A Framework for Fully Automated Performance Testing for Smart Buildings

A significant proportion of energy consumption by buildings worldwide, estimated to ca. 40%, has yielded a high importance to studying buildings’ performance. Performance Testing is a mean by which buildings can be continuously commissioned to ensure that they operate as designed. Historically, setup of Performance Tests has been manual and labor-intensive and has required intimate knowledge of buildings’ complexity and systems. The emergence of the concept of smart buildings has provided an opportunity to overcome this restriction. In this paper, we propose a framework for automated Performance Testing of smart buildings that utilizes metadata models. The approach features automatic detection of applicable Performance Tests using metadata queries and their corresponding instantiation, as well as continuous commissioning based on metadata. The presented approach has been implemented and tested on a case study building at a university campus in Denmark.

Room-level occupant counts, airflow and CO2 data from an office building

The area of occupant sensing is lacking public datasets to baseline and foster data-driven research. This abstract describes a dataset covering room-level occupant counts, in-room ventilation airflow and CO2 data from an office building. This dataset can among others be used for developing and evaluating data-driven algorithms for occupant sensing and building analytics.

Portable Queries Using the Brick Schema for Building Applications: Demo Abstract

Sensorized commercial buildings are a rich target for building a new class of applications that improve operational and energy efficiency of building operations that take into account human activities. Such applications, however, rarely experience widespread adoption due to the lack of a common descriptive schema that would enable porting these applications and systems to different buildings. Our demo presents Brick [4], a uniform schema for representing metadata in buildings. Our schema defines a concrete ontology for sensors, subsystems and relationships among them, which enables portable applications. Using a web application, we will demonstrate real buildings that have been mapped to the Brick schema, and show application queries that extracts relevant metadata from these buildings. The attendees would be able to create example buildings and write their own queries.

Demonstrating OccuRE: an Occupancy REasoning Platform for Occupancy-driven Applications: Demo Abstract

Occupant behavior determines a large share of the energy consumption of buildings. Software applications driven by information about occupant behavior provide a mean to optimize this share. However, existing systems for sensing occupancy behavior provide technology-specific APIs statically coupled to the type of computed occupancy information. Software platforms for developing applications for buildings do also not provide abstractions for occupancy behavior. Therefore, technology lock in and lack of proper abstractions wreck the development of occupancy-driven applications. In this paper we present the design, implementation and evaluation of OccuRE, a stream-based Occupancy REasoning platform. OccuRE provides a technology agnostic API for accessing occupancy information to significantly improve portability. The platform uses a component-based computation model with dynamic composition to calculate and reason about occupancy behavior. Together these elements avoid that developers need to deal with technology-specific processing of sensor data to ease application development. Through micro-benchmarks we show that OccuRE successfully and efficiently computes occupancy information for technology-heterogeneous building instrumentations. We use the development of three prototype applications to demonstrate that the API of OccuRE (i) enables several types of occupancy-driven applications, (ii) that the applications -- by using the interface -- achieve portability in regards to occupancy information computation and (iii) that the application code avoids handling sensor data processing.