A learning-based model predictive control method for unlocking the potential of building energy flexibility

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115299 - 115299

Published: Jan. 1, 2025

Language: Английский

---

Digital twin (DT) and extended reality (XR) for building energy management

Energy and Buildings, Journal Year: 2024, Volume and Issue: 323, P. 114746 - 114746

Published: Aug. 31, 2024

Language: Английский

---

Occupancy Prediction in IoT-Enabled Smart Buildings: Technologies, Methods, and Future Directions

Sensors, Journal Year: 2024, Volume and Issue: 24(11), P. 3276 - 3276

Published: May 21, 2024

In today's world, a significant amount of global energy is used in buildings. Unfortunately, lot this wasted, because electrical appliances are not properly or efficiently. One way to reduce waste by detecting, learning, and predicting when people present To do this, buildings need become "smart" "cognitive" use modern technologies sense how occupying the By leveraging information, can make smart decisions based on recently developed methods. paper, we provide comprehensive overview recent advancements Internet Things (IoT) that have been designed for monitoring indoor environmental conditions within Using these crucial gathering data about environment determining number presence occupants. Furthermore, paper critically examines both strengths limitations each technology occupant behavior. addition, it explores different methods processing making future occupancy predictions. Moreover, highlight some challenges, such as optimal location sensors radars, detailed explanation insights into challenges. possible directions, including security occupants' promotion energy-efficient practices localizing occupants their activities building. With respect other survey works similar topics, our work aims cover sensory approaches review literature estimating occupancy.

Language: Английский

---

A review of current research on occupant-centric control for improving comfort and energy efficiency

Building Simulation, Journal Year: 2024, Volume and Issue: 17(10), P. 1675 - 1692

Published: Aug. 29, 2024

Language: Английский

---

A conceptual framework for designing human-centered building-occupant interactions to enhance user experience in specific-purpose buildings

Design Science, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 1, 2025

Abstract This research proposes a novel conceptual framework that combines the concepts of Human-Computer Interaction (HCI) and Ambient Intelligence (AmI). The proposed aims to shed light on importance considering needs social interactions various building occupants in different types buildings designing HBI strategies accordingly. Specifically, we take educational as case is less explored apply framework, investigating how should be designed address students, primary occupants. Focus groups semi-structured interviews were conducted among students flagship smart engineering at Virginia Tech. Qualitative coding concept mapping used analyze qualitative data determine impact occupant-specific learning experience students. “Finding study space” was found have highest direct “Indoor Environment Quality (IEQ)” indirect impact. results show clear need integrate occupant buildings. Finally, discuss new ideas for potential Intelligent User Interfaces (IUI) identified needs.

Language: Английский

---

Machine learning-enhanced lightweight rule-based control strategy for building energy demand response

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Language: Английский

---

Predicting Spatial Sound Attenuation in Buildings with Machine Learning: Implications for Fire Alarm Placement

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 107314 - 107314

Published: May 1, 2025

Language: Английский

---

Enhancing Office Comfort with Personal Comfort Systems: A Data-Driven Machine Learning Approach

Buildings, Journal Year: 2025, Volume and Issue: 15(10), P. 1676 - 1676

Published: May 15, 2025

Personal Comfort Systems (PCS) have emerged as a flexible alternative to address the diversity of environmental perceptions in office environments. Unlike conventional HVAC systems, PCSs allow users improve their satisfaction and comfort by exercising individualized control over immediate environment without interfering with others around them. This study evaluated use machine learning models generated H2O AutoML predict three four buildings effective occupancy. These were thermal wristband, desk fan, an adjustable lamp. Data collected through sensors, perception surveys, spatial personal attributes used. Synthetic data augmentation automated variable selection also used optimize models’ performance. The predictive had robust performance, R2 values test set 0.86 for 0.84 0.52 most influential variables included BMI, CO2 level, satisfaction, highlighting importance physiological subjective factors. results confirm that anticipating PCS high precision cases, laying foundations future implementation user-oriented adaptive systems. preliminary approach contributes design healthier, more personalized, energy-efficient work

Language: Английский

---

From theory to practice: A critical review of model predictive control field implementations in the built environment

Applied Energy, Journal Year: 2025, Volume and Issue: 393, P. 126091 - 126091

Published: May 20, 2025

Language: Английский

---

The Effectiveness of UWB-Based Indoor Positioning Systems for the Navigation of Visually Impaired Individuals

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(13), P. 5646 - 5646

Published: June 28, 2024

UWB has been in existence for several years, but it was only a few years ago that transitioned from specialized niche to more mainstream applications. Recent market data indicate rapid increase the popularity of consumer products, such as smartphones and smart home devices, well automotive industrial real-time location systems. The challenge achieving accurate positioning indoor environments arises various factors distance, location, beacon density, dynamic surroundings, density type obstacles. This research used MFi-certified chipsets integrated them with mobile application dedicated iOS by implementing near interaction accessory protocol. analysis covers both static cases. Thanks acquisition measurements, two main candidates localization infrastructure were analyzed compared terms accuracy, namely LIDAR, latter reference system. problem applications analyzed, future solutions proposed. results show achieved accuracy is sufficient tracking individuals may serve guidelines achievable or provide basis further into complex sensor fusion-based navigation provides findings. Firstly, conditions, LIDAR measurements showed higher than beacons. Secondly, integrating multiple sensors could enhance non-line-of-sight scenarios. Lastly, advancements technology expand availability competitive hardware, facilitating thorough evaluation its effectiveness practical These insights be particularly useful designing systems blind buildings.

Language: Английский

---