Visual Analytics for Energy Monitoring in the Context of Building Management (original) (raw)

Building Energy Simulation and Monitoring: A Review of Graphical Data Representation

Energies, 2022

Data visualization has become relevant in the framework of the evolution of big data analysis. Being able to understand data collected in a dynamic, interactive, and personalized way allows for better decisions to be made when optimizing and improving performance. Although its importance is known, there is a gap in the research regarding its design, choice criteria, and uses in the field of building energy consumption. Therefore, this review discusses the state-of-the-art of visualization techniques used in the field of energy performance, in particular by considering two types of building analysis: simulation and monitoring. Likewise, data visualizations are categorized according to goals, level of detail and target users. Visualization tools published in the scientific literature, as well as those currently used in the IoT platforms and visualization software, were analyzed. This overview can be used as a starting point when choosing the most efficient data visualization for a specific type of building energy analysis.

From Building Information Model to Digital Twin: A Framework for Building Thermal Comfort Monitoring, Visualizing, and Assessment

Buildings

The existing building stock is globally responsible for 17.5% of greenhouse gas emissions due to their operation to achieve occupant satisfaction, thus requiring a vast intervention. However, reducing building stock emissions and optimizing building energy performance cannot be considered independently by the users’ well-being. The thermal comfort conditions and their monitoring represent a central issue that could optimize building energy usage while achieving good indoor environmental conditions. This document describes the first findings of ongoing research focused on the development of a building monitoring system, based on the integration of Building Information Modeling tools and sensor technology through Dynamo Visual Programming. Starting from the development of an Asset Information Model, which represents the virtual replica of a building that currently hosts the administrative offices of the municipality of Cagliari, the first step presented in this contribution shows a th...

Building energy management and data analytics

2015 International Symposium on Smart Electric Distribution Systems and Technologies (EDST), 2015

Energy efficiency in buildings depends on the way the building is operated. Therefore energy management is the key component for efficient operation. Data analysis of operation data helps to better understand the systems and detect faults and inefficiencies. The facility manager benefits from smart analysis that makes use of machine learning algorithms and innovative visualizations. This analysis is part of a bigger review of the current structure of building automation as it is used in today's buildings. The operation targets in energy efficiency are complex, ambiguous and contradictory: indoor comfort, energy efficiency, high availability and low costs cannot be met at the same time. In order to improve building operation, a novel model of automation is discussed. The foundation of this model is in cognitive automation, since each building is unique in its selection of energy sources, architecture, usage and location, which implies that the building's control system has to be adapted individually. This paper connects the data-driven analysis of operation data with a cognitive concept to be used for operating the energy systems in a building and regarding goals on how to optimally operate while considering constraints about the limits of operation, using the complex, dynamic data from building automation.

Large-Scale Assessment and Visualization of the Energy Performance of Buildings with Ecomaps - Project SUNSHINE: Smart Urban Services for Higher Energy Efficiency

Proceedings of 3rd International Conference on Data Management Technologies and Applications, 2014

This paper illustrates the preliminary results of a research project focused on the development of a Web 2.0 system designed to compute and visualize large-scale building energy performance maps, so called "ecomaps", using: emerging platform-independent technologies such as WebGL for data presentation, an extended version of the EU-Founded project TABULA/EPISCOPE for automatic calculation of building energy parameters and CityGML OGC standard as data container. The proposed architecture will allow citizens, public administrations and government agencies to perform city-wide analyses on the energy performance of building stocks.

BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings

Sustainability, 2021

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors ...

Developing User Interfaces For Monitoring Systems In Buildings

This paper explores the main requirements and design guidelines of user interfaces for monitoring systems in office buildings. We first discuss five information streams in the monitoring system (energy use, indoor environment, external environment, occupants' states, and environmental control systems states). We then present the results of a user survey (134 participants) and three focus group sessions (24 participants) conducted in Vienna and Taiwan. The objective of this survey was to capture the views of the potential receivers of building monitoring information regarding the relative importance of different kinds of information and the modes and means of presenting and visualizing such information. The outcome of these studies is expected to advance the state of art in connecting occupants and buildings.

IoT-based architecture for efficient energy monitoring in existing building structures

IOP conference series, 2022

Considering the definition of Environmental, Social and Governance (ESG) criteria, historical buildings in Europe need solutions to be able to be more energy efficient. One approach to identify high energy consumers is data analysis. To enable this approach, the following research questions have to be answered: 1. How can data be captured in a valid and efficient way? 2. How can data be standardized and merged within dashboards? 3. How can data be analysed within these common dashboards? To answer these questions, results of a mixed-methods-research project [1] were used, to give a view on the impact and use of emerging technologies and to allow the definition of the best suited technology. Based on the results of this step and previous research [2], the relevant tools and the IT architecture was defined. Thirdly, a case study was enrolled, which is based on the previously defined IT architecture, using IoT measuring devices from European production, two different databases and two analytic tools. To cover the ESG-reporting demands, data structure and relevant building structures were defined. The paper also presents the final decision on the database and the analytics tool, both capable to analyse large amount of data and operated as open solutions (enables enlargement at any time and works without license cost).

Enhancing energy awareness through the analysis of thermal energy consumption

Energy efficiency by means of reduction in wasteful energy consumption is a growing policy priority for many countries. Innovative systems should be designed to continuously monitor a smart city environment and provide all stakeholders the tools to improve energy efficiency. This paper presents the EDEN platform, designed to collect and analyze thermal energy consumption of residential and public building heating systems. EDEN is being deployed in a major Italian city and collects energy consumption measurements through an extensive smart metering grid involving thousands of buildings. EDEN also collects and analyzes indoor climate conditions, and user feedbacks, such as their thermal comfort perception, by means of an ad-hoc social network. Collected data are further enriched with temporal and spatial information at different abstraction levels and meteorological data available as an open source data set. Several technical Key Performance Indicators (KPIs) have been defined to inform users on their building thermal energy consumption, while user-friendly KPIs present energy savings or over-consumptions in an informative fashion