4.7 Article

Deployment of crowdsourced occupant data to support fault detection and diagnosis in buildings

Related references

Note: Only part of the references are listed.
Article Construction & Building Technology

Cohort comfort models - Using occupant's similarity to predict personal thermal preference with less data

Matias Quintana et al.

Summary: Cohort Comfort Models (CCM) are a technique that predicts personalized thermal comfort for new building occupants by leveraging historical data from similar individuals. It combines background information and one-time surveys with physiological and environmental sensor measurements. The results demonstrate that CCM performs as well as or better than conventional models and achieves increased prediction accuracy when incorporating historical preference data points.

BUILDING AND ENVIRONMENT (2023)

Article Construction & Building Technology

Digital twin enabled fault detection and diagnosis process for building HVAC systems

Xiang Xie et al.

Summary: The emerging concept of digital twins allows for intelligent buildings. This paper presents a digital twin-based approach using symbolic artificial intelligence to automatically identify informative sensory dimensions for building-specific faults and develop a digital twin data platform. A machine-readable fault tag system is implemented to annotate real-time data and produce filtered low-latency data streams for dynamic asset management.

AUTOMATION IN CONSTRUCTION (2023)

Review Construction & Building Technology

Digital Twin for Fault Detection and Diagnosis of Building Operations: A Systematic Review

Faeze Hodavand et al.

Summary: Intelligence in Industry 4.0 has led to the development of smart buildings with various control systems for data collection, optimization, and fault detection. Digital Twin (DT) technology offers a sustainable solution for facility management. This research comprehensively reviews DT performance evaluation in building life cycle and predictive maintenance. The study emphasizes the advantages of data-driven methods and highlights the importance of unsupervised and semi-supervised learning for building operations with HVAC systems. Future research should focus on developing interpretable models and exploring the potential of deep learning methods.

BUILDINGS (2023)

Article Environmental Studies

It's not just technical-Socio-technical challenges to the efficient operation of commercial office buildings

Connor Brackley et al.

Summary: This study conducted individual interviews with professionals in two facility management companies to investigate the socio-technical aspects of energy management. Through the interviews and existing challenges identified in the literature, nine primary challenges faced by these organizations were identified, along with nine recommendations for the industry.

ENERGY RESEARCH & SOCIAL SCIENCE (2023)

Article Construction & Building Technology

A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics

Haidar Hosamo Hosamo et al.

Summary: This research proposes a Digital Twin predictive maintenance framework for Air Handling Units (AHU) in buildings. The framework overcomes limitations of current facility maintenance management systems and utilizes Digital Twin technology along with Building Information Modeling, Internet of Things, and semantic technologies to create a better maintenance strategy. The results demonstrate the effectiveness of the framework in detecting faults and predicting the future state of AHU components, leading to energy savings.

ENERGY AND BUILDINGS (2022)

Article Construction & Building Technology

Personal comfort models based on a 6-month experiment using environmental parameters and data from wearables

Federico Tartarini et al.

Summary: Personal thermal comfort models are an important paradigm for predicting building occupants' perception of their thermal environment. This study conducted a longitudinal field study with 20 participants, collecting over 1080 surveys per participant using smartwatches for 180 days. Machine learning models were trained and tested using environmental and physiological data to predict participants' thermal preferences. The results showed that skin temperature, indoor temperature, near body temperature, and heart rate were the most valuable variables for accurate prediction, and approximately 250-300 data points per participant were needed for accurate prediction.

INDOOR AIR (2022)

Review Construction & Building Technology

A review of the Digital Twin technology for fault detection in buildings

Haidar Hosamo Hosamo et al.

Summary: This study evaluates the utilization of Digital Twin technology for fault detection in buildings. The research finds that further development is needed in areas such as scanner hardware and software, detection and prediction algorithms, modeling, and twinning programs. Additionally, financial incentives are required for building owners, architects, and engineers to invest in condition monitoring. Future research should focus on integrating machine learning with other Digital Twin components to develop new fault detection methods.

FRONTIERS IN BUILT ENVIRONMENT (2022)

Review Energy & Fuels

A review on buildings energy information: Trends, end-uses, fuels and drivers

M. Gonzalez-Torres et al.

Summary: Buildings contribute significantly to climate change, but there is a lack of reliable and consistent data for the development and evaluation of mitigation policies. Residential buildings have the highest energy consumption, with HVAC systems being the main source. Electrification has the potential to mitigate climate change if renewable power is promoted, but global cooperation is needed to break the link between economic growth, urbanization, and energy consumption in developing nations.

ENERGY REPORTS (2022)

Article Construction & Building Technology

The Information Gap in Occupant-Centric Building Operations: Lessons Learned from Interviews with Building Operators in Germany

Jakob Hahn et al.

Summary: Effective communication between building operators and occupants is crucial for meeting occupant needs. Current practices in building operation can be improved to achieve higher energy-efficiency and better occupant comfort.

FRONTIERS IN BUILT ENVIRONMENT (2022)

Review Construction & Building Technology

A Review of the Use of Wearables in Indoor Environmental Quality Studies and an Evaluation of Data Accessibility from a Wearable Device

Belal Abboushi et al.

Summary: Understanding indoor environmental quality and its impact on occupant well-being is crucial for building design and operation. Using wearables in field studies to collect subjective and objective health performance indicators from occupants can lead to important improvements in indoor environmental quality. However, it is necessary to determine which indicators should be collected and evaluate the data accessibility from these devices.

FRONTIERS IN BUILT ENVIRONMENT (2022)

Article Health Care Sciences & Services

Measuring Criterion Validity of Microinteraction Ecological Momentary Assessment (Micro-EMA): Exploratory Pilot Study With Physical Activity Measurement

Aditya Ponnada et al.

Summary: The study found that mu EMA self-reports using a custom-built smartwatch app were valid for measuring sedentary, light, and moderate to vigorous physical activities. Participants accurately responded to prompts on the smartwatch, indicating criterion validity. Further research is needed to assess the validity of mu EMA in measuring vigorous activities.

JMIR MHEALTH AND UHEALTH (2021)

Article Construction & Building Technology

Data driven indoor air quality prediction in educational facilities based on IoT network

Lavinia Chiara Tagliabue et al.

Summary: The concept of the built environment as a container for human activities has shifted towards focusing on the user's well-being and experience, especially in educational facilities, where indoor air quality significantly impacts learning performance.

ENERGY AND BUILDINGS (2021)

Review Energy & Fuels

Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review

Liang Zhang et al.

Summary: A comprehensive literature review of over 100 FDD-sensor-related papers revealed a focus on FDD algorithms rather than sensors, with less attention on sensor hardware topics compared to software topics. Sensor engineering aspects are often neglected, and important sensor topics such as cost-effectiveness and sensor schema/layout/location are under-studied in the current research landscape.

ADVANCES IN APPLIED ENERGY (2021)

Article Construction & Building Technology

TrojanSense, a participatory sensing framework for occupant-aware management of thermal comfort in campus buildings

Kyle Konis et al.

BUILDING AND ENVIRONMENT (2020)

Review Construction & Building Technology

Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review

Maryam Sadat Mirnaghi et al.

ENERGY AND BUILDINGS (2020)

Article Construction & Building Technology

Case study results: fault detection in air-handling units in buildings

Suhrid Deshmukh et al.

ADVANCES IN BUILDING ENERGY RESEARCH (2020)

Article Construction & Building Technology

Humans-as-a-Sensor for Buildings-Intensive Longitudinal Indoor Comfort Models

Prageeth Jayathissa et al.

BUILDINGS (2020)

Article Construction & Building Technology

A performance evaluation framework for building fault detection and diagnosis algorithms

Stephen Frank et al.

ENERGY AND BUILDINGS (2019)

Review Green & Sustainable Science & Technology

Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future

Yang Zhao et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)

Article Construction & Building Technology

Occupant thermal feedback for improved efficiency in university buildings

Marco Pritoni et al.

ENERGY AND BUILDINGS (2017)

Article Computer Science, Information Systems

Mobile Crowdsourcing of Occupant Feedback in Smart Buildings

Sanja Lazarova-Molnar et al.

APPLIED COMPUTING REVIEW (2017)

Article Construction & Building Technology

A review on buildings energy consumption information

Luis Perez-Lombard et al.

ENERGY AND BUILDINGS (2008)

Article Construction & Building Technology

A rule-based fault detection method for air handling units

Jeffrey Schein et al.

ENERGY AND BUILDINGS (2006)