Application of Smart Technologies in Buildings

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	5.0	6.9	2020	19.2 Days	CHF 1800
Automation automation	2.0	4.1	2020	30.9 Days	CHF 1200
Buildings buildings	3.1	4.4	2011	15.1 Days	CHF 2600
Electronics electronics	2.6	6.1	2012	16.4 Days	CHF 2400
Smart Cities smartcities	5.5	14.7	2018	25.2 Days	CHF 2000
Symmetry symmetry	2.2	5.3	2009	15.8 Days	CHF 2400
Urban Science urbansci	2.9	3.7	2017	21.6 Days	CHF 1800

28 pages, 9705 KB

Open AccessArticle

Enhancing Smart Building Energy Resilience: A Novel Parallel-Series PV Architecture for Urban Partial Shading Mitigation

by Tanveer Abbas, Syed Talha Safeer Gardezi, Noman Khan, Adnan Khan, Shakeel Ahmed and Kambiz Tehrani

Smart Cities 2026, 9(4), 68; https://doi.org/10.3390/smartcities9040068 - 13 Apr 2026

Viewed by 374

Abstract

Building-integrated photovoltaic systems are essential components of smart buildings and sustainable urban infrastructure, contributing to energy efficiency and carbon footprint reduction in smart cities. Mismatch loss, particularly under partial shading, is one of the concerns in photovoltaic (PV) systems, especially in urban environments [...] Read more.

Building-integrated photovoltaic systems are essential components of smart buildings and sustainable urban infrastructure, contributing to energy efficiency and carbon footprint reduction in smart cities. Mismatch loss, particularly under partial shading, is one of the concerns in photovoltaic (PV) systems, especially in urban environments where buildings, trees, and other structures create complex shading patterns. It leads to significant power loss and poor efficiency. Several methods, such as string converters, multi-string converters, central converters, and micro-inverters/power optimizers, have been widely employed to address this issue. These methods suffer from hardware complexity and are good in certain shading patterns only; they remain ineffective otherwise. Power optimizers lead in efficiency under all the shading patterns, whereas string converters lead in hardware simplicity. We propose a novel parallel-series converter to mitigate mismatch losses in smart building applications that is as efficient as power optimizers and as simple as converters. In the proposed parallel-series converter design, multiple PV modules are connected in parallel to a very simple converter, and many such converters are then connected in series to get the final output. The proposed converter is rigorously evaluated for various shading patterns using MATLAB/SIMULINK. A prototype system of

3 \times 2

PV panels is also developed for hardware evaluation. The simulation and hardware results show that the proposed parallel-series converter dominantly competes with power optimizers with much simpler hardware and outperforms the other converters, making it particularly suitable for smart building energy systems where cost-effectiveness and reliability are critical. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

41 pages, 22723 KB

Open AccessArticle

Parameter-Efficient Adaptation of Generative-Foundation (Flux, Qwen) vs. Zero-Shot (Gemini, SAM3) Models for Aerial Image Segmentation

by Dina Shata, Simon Denman, Sara Omrani, Robin Drogemuller, Hend Ali and Ayman Wagdy

Buildings 2026, 16(7), 1369; https://doi.org/10.3390/buildings16071369 - 30 Mar 2026

Viewed by 599

Abstract

Accurate rooftop segmentation from aerial imagery is essential for large-scale urban analysis, including applications such as solar potential assessment and urban monitoring. However, it remains constrained by the high cost of dense annotation and the limited generalisation of supervised models across heterogeneous urban [...] Read more.

Accurate rooftop segmentation from aerial imagery is essential for large-scale urban analysis, including applications such as solar potential assessment and urban monitoring. However, it remains constrained by the high cost of dense annotation and the limited generalisation of supervised models across heterogeneous urban morphologies. This study investigates binary rooftop segmentation for fine-tuning large image-editing foundation models using parameter-efficient Low-Rank Adaptation (LoRA). Using parts of Brisbane metropolitan dataset (split 80/20 into 97 training and 24 testing tiles), three paradigms were evaluated under a unified protocol: zero-shot image-editing models (including Gemini 3 Pro), a segmentation-first baseline (Segment Anything Model 3, SAM3), and LoRA-adapted diffusion models (FLUX.1 Kontext, FLUX.2, and Qwen Image Edit 2509) fine-tuned each 250 steps up to 5000 steps. Evaluated under zero-shot conditions, the generative models demonstrated varying levels of boundary fidelity. The Gemini model achieved a strong zero-shot baseline with [IoU, Dice] scores of [85%, 91%], followed by the SAM3 baseline, which also achieved a stable [84%, 91%] but exhibited increased false negatives in visually complex scenes. The tested diffusion models (FLUX.1 Kontext, FLUX.2, and Qwen) showed more limited initial spatial overlap, scoring [45%, 55%], [67%, 78%], and [33%, 46%], respectively. Following LoRA adaptation, the FLUX and Qwen models showed substantial improvements, with their respective [IoU, Dice] metrics increasing to [89%, 94%], [82%, 90%], and [87%, 93%]. FLUX.1 Kontext achieved the strongest overall performance at step 4250, yielding a mean IoU of 89% (SD = 3.16%) and a pixel accuracy exceeding 96%. These results demonstrate that parameter-efficient fine-tuning, combined with rigorous evaluation under class-imbalanced conditions, can transform general-purpose generative models into competitive, scalable spatial analysis tools that match or exceed both dedicated segmentation baselines and strong zero-shot multimodal models. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

24 pages, 4289 KB

Open AccessArticle

Floor Plan Generation of Existing Buildings Based on Deep Learning and Stereo Vision

by Dejiang Wang and Taoyu Peng

Buildings 2026, 16(7), 1310; https://doi.org/10.3390/buildings16071310 - 26 Mar 2026

Viewed by 547

Abstract

The reinforcement and renovation of existing buildings constitute an important component of the future development of the civil engineering industry. Such projects typically require the original construction drawings of the building. However, for older structures, the original paper-based drawings may be damaged or [...] Read more.

The reinforcement and renovation of existing buildings constitute an important component of the future development of the civil engineering industry. Such projects typically require the original construction drawings of the building. However, for older structures, the original paper-based drawings may be damaged or lost. Moreover, traditional manual surveying and mapping methods are time-consuming, labor-intensive, and limited in accuracy. To address these issues, this paper proposes a floor plan generation method for existing buildings that integrates deep learning and stereo vision based on a fusion of synthetic and real data. First, collaborative modeling and automated rendering between a large language model and Blender are implemented based on the Model Context Protocol (MCP), enabling indoor scene modeling and image acquisition to construct a synthetic dataset containing structural components such as doors, windows, and walls. Meanwhile, manually annotated real indoor images are incorporated. Synthetic and real data are mixed in different proportions to form multiple dataset configurations for model training and validation. Subsequently, the SegFormer model is employed to perform semantic segmentation of indoor components. Combined with stereo camera calibration results, disparity computation is conducted to extract the three-dimensional spatial coordinates of component corner points. On this basis, the architectural floor plan is generated according to the spatial geometric relationships among structural components. Experimental results demonstrate that the proposed method effectively reduces the need for manual annotation and on-site measurement, providing an efficient technical solution for indoor floor plan generation of existing buildings. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

23 pages, 7241 KB

Open AccessArticle

A Hybrid Deep Learning and Rule-Based Method for Architectural Drawing Vectorization and CAD Reconstruction

by Minqi Lin and Dejiang Wang

Buildings 2026, 16(5), 1043; https://doi.org/10.3390/buildings16051043 - 6 Mar 2026

Viewed by 938

Abstract

A large number of architectural drawings have historically existed in paper form or as non-editable raster images, which makes them difficult to directly support information reuse and digital management, while manual CAD reconstruction is time-consuming and inefficient. This paper proposes a hybrid deep [...] Read more.

A large number of architectural drawings have historically existed in paper form or as non-editable raster images, which makes them difficult to directly support information reuse and digital management, while manual CAD reconstruction is time-consuming and inefficient. This paper proposes a hybrid deep learning and rule-based method for architectural drawing vectorization and CAD reconstruction, which automatically converts scanned raster images into editable CAD vector files while preserving geometric structure and scale consistency. The proposed method consists of four modules: axis grid and dimension detection, text recognition and scale recovery, architectural line topology reconstruction, and CAD geometric rectification and reconstruction. The method utilizes object detection and OCR technologies to extract key semantic information from the drawings. By extracting semantic information, the method constructs a line topology structure and applies architectural drawing constraints to parameterize and normalize geometric results, thereby achieving the recognition and vectorization of raster drawings. Experimental results and engineering case studies demonstrate that the proposed method can effectively extract typical architectural elements, and generate directly editable CAD vector drawings. The method achieves favorable geometric accuracy and topological consistency in architectural drawing digitization and automatic CAD reconstruction tasks, providing a technical solution for the automatic vectorization of existing architectural drawings. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

20 pages, 2390 KB

Open AccessArticle

Research on Dynamic Contagion of Banking Risks and Identification of Systemically Important Institutions: Based on the HD-TVP-VAR-DY Model

by Cuicui Liu, Huizi Ma, Xiangrong Wang, Shengnan Zhao and Zhenyan Qin

Symmetry 2026, 18(2), 338; https://doi.org/10.3390/sym18020338 - 12 Feb 2026

Viewed by 467

Abstract

This study focuses on analyzing the dynamic process, strength, and orientation of risk spillovers in the Chinese banking system under the exogenous shock of the COVID-19 pandemic. Using daily closing prices of 25 representative banks, it stratifies the data into three periods: pre-, [...] Read more.

This study focuses on analyzing the dynamic process, strength, and orientation of risk spillovers in the Chinese banking system under the exogenous shock of the COVID-19 pandemic. Using daily closing prices of 25 representative banks, it stratifies the data into three periods: pre-, during-, and post-pandemic. Employing the HD-TVP-VAR-DY model and dynamic topological directed networks, this study captures the time-varying heterogeneity of risk spillovers and identifies systemic core nodes. The findings reveal that abrupt shocks significantly exacerbate systemic fragility. The primary risk transmitters in the pre-, during-, and post-pandemic periods were CCBs, JSCBs, and CCBs, while SOCBs and RCBs were the main net risk recipients. The interbank risk propagation exhibits a structural evolution pattern of “Concentration–Decentralization–Reshaping.” In the pre-pandemic period, the network was highly concentrated, forming a directional connectedness structure from JSCBs to large banks. During the pandemic, the network underwent significant decentralization, with CMBC and SZRCB emerging as pivotal spillover sources; risk flows shifted from directional to systemic diffusion, characterized by passive absorption. Post-pandemic, the network reverted to a hierarchical-driven pattern, with BOC becoming the core risk source, and the propagation dynamics shifted from passive absorption back to active spillover dominance. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

20 pages, 4637 KB

Open AccessArticle

A Lightweight YOLOv13-G Framework for High-Precision Building Instance Segmentation in Complex UAV Scenes

by Yao Qu, Libin Tian, Jijun Miao, Sergei Leonovich, Yanchun Liu, Caiwei Liu and Panfeng Ba

Buildings 2026, 16(3), 559; https://doi.org/10.3390/buildings16030559 - 29 Jan 2026

Viewed by 571

Abstract

Accurate building instance segmentation from UAV imagery remains a challenging task due to significant scale variations, complex backgrounds, and frequent occlusions. To tackle these issues, this paper proposes an improved lightweight YOLOv13-G-based framework for building extraction in UAV imagery. The backbone network is [...] Read more.

Accurate building instance segmentation from UAV imagery remains a challenging task due to significant scale variations, complex backgrounds, and frequent occlusions. To tackle these issues, this paper proposes an improved lightweight YOLOv13-G-based framework for building extraction in UAV imagery. The backbone network is enhanced by incorporating cross-stage lightweight connections and dilated convolutions, which improve multi-scale feature representation and expand the receptive field with minimal computational cost. Furthermore, a coordinate attention mechanism and an adaptive feature fusion module are introduced to enhance spatial awareness and dynamically balance multi-level features. Extensive experiments on a large-scale dataset, which includes both public benchmarks and real UAV images, demonstrate that the proposed method achieves superior segmentation accuracy with a mean intersection over union of 93.12% and real-time inference speed of 38.46 frames per second while maintaining a compact Model size of 5.66 MB. Ablation studies and cross-dataset experiments further validate the effectiveness and generalization capability of the framework, highlighting its strong potential for practical UAV-based urban applications. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

20 pages, 3362 KB

Open AccessArticle

Design and Evaluation of a Mixed Reality System for Facility Inspection and Maintenance

by Abuzar Haroon, Busra Yucel and Salman Azhar

Buildings 2026, 16(2), 425; https://doi.org/10.3390/buildings16020425 - 20 Jan 2026

Viewed by 547

Abstract

Emerging technologies are transforming Facilities Management (FM), enabling more efficient and accurate building inspections and maintenance. Mixed Reality (MR), which integrates virtual content into real-world environments, has shown potential for improving operational performance and technician training. This study presents the development and evaluation [...] Read more.

Emerging technologies are transforming Facilities Management (FM), enabling more efficient and accurate building inspections and maintenance. Mixed Reality (MR), which integrates virtual content into real-world environments, has shown potential for improving operational performance and technician training. This study presents the development and evaluation of an MR-assisted system designed to support facility operations in academic buildings. The system was tested across three case scenarios, namely plumbing, lighting, and fire sprinkler systems, using Microsoft HoloLens^®. A mixed-methods approach combined a post-use questionnaire and semi-structured interviews with twelve FM professionals, including technicians, inspectors, and managers. Results indicated that 66.67% of participants found the MR interface highly effective in visualizing systems and guiding maintenance steps. 83.33% agreed that checklist integration enhanced accuracy and learning. Technical challenges, including model drift, latency, and occasional software crashes, were also observed. Overall, the study confirms the feasibility of MR for FM training and inspection, offering a foundation for broader implementation and future research. The findings provide valuable insights into how MR-based visualization and interaction tools can enhance efficiency, learning, and communication in facility operations. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

25 pages, 3564 KB

Open AccessSystematic Review

IFC and Project Control: A Systematic Literature Review

by Davide Avogaro and Carlo Zanchetta

Buildings 2026, 16(1), 91; https://doi.org/10.3390/buildings16010091 - 25 Dec 2025

Viewed by 975

Abstract

Project control in cost estimation, time scheduling, and resource accounting remains challenging, particularly when using the open-source Industry Foundation Classes (IFCs) format. This study aims to define the state of the art in integrating these three domains. A systematic literature review was conducted, [...] Read more.

Project control in cost estimation, time scheduling, and resource accounting remains challenging, particularly when using the open-source Industry Foundation Classes (IFCs) format. This study aims to define the state of the art in integrating these three domains. A systematic literature review was conducted, using a bibliometric analysis to map and interpret scientific knowledge and research trajectories, and an inductive analysis for a detailed examination of relevant studies. The analysis highlights a lack of clarity in applying the IFC standard across project control domains, as current practices often rely on non-standardized procedures, including incorrect use of classes or properties, creation of unneeded user-defined PropertySets and properties, or reliance on proprietary software. Integration of cost, time, and resource management remains limited, and proposed technological solutions generally require coding skills that typical professionals do not possess. Additional challenges include fragmented data across multiple databases, manual assignment of time, cost, and resource information, and limited collaboration, all of which are time-consuming and error-prone. There is a critical need for clearer guidelines on IFC usage to enable standardized procedures and facilitate the development of IFC-based tools. Automating these labor-intensive tasks could improve efficiency, reduce errors, and support broader adoption of integrated project control practices. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

25 pages, 1241 KB

Open AccessArticle

Structural Equation Model (SEM)-Based Productivity Evaluation for Digitalization of Construction Supervision

by Da Hee Kim, Chan Hyuk Park, Wi Sung Yoo and Seong Mi Kang

Buildings 2025, 15(23), 4380; https://doi.org/10.3390/buildings15234380 - 3 Dec 2025

Cited by 1 | Viewed by 1276

Abstract

The construction industry continues to face declining productivity due to its heavy reliance on labor and the repetitive, non-value-adding nature of supervision tasks. This study provides an exploratory, practitioner-based evaluation of how selected digital technologies, PDF-based documentation systems, object recognition algorithms, and 3D [...] Read more.

The construction industry continues to face declining productivity due to its heavy reliance on labor and the repetitive, non-value-adding nature of supervision tasks. This study provides an exploratory, practitioner-based evaluation of how selected digital technologies, PDF-based documentation systems, object recognition algorithms, and 3D vision technology may contribute to productivity improvements in construction supervision. A total of 82 valid responses from field engineers were collected to examine perceived task substitution effects across major construction work types and management functions. The findings indicate that higher work-adoption rates of digital technologies are generally associated with improved supervisory productivity, with the strongest perceived benefits observed for PDF-based documentation in reinforced concrete and formwork tasks. However, other expected relationships, particularly those involving work responsibility, did not appear consistently in the practitioner data, suggesting that such perceptions may be influenced by task context and adaptation burden. This study offers a practical and context-specific framework for understanding how digital tools may support productivity enhancement in supervision work. While the results reflect tendencies based on a limited sample, they provide field-grounded insights that can inform the phased and targeted application of digital technologies in construction supervision and guide future empirical model development. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

19 pages, 2441 KB

Open AccessArticle

Simulation and Statistical Validation Method for Evaluating Daylighting Performance in Hot Climates

by Nivin Sherif, Ahmed Yehia and Walaa S. E. Ismaeel

Urban Sci. 2025, 9(8), 303; https://doi.org/10.3390/urbansci9080303 - 4 Aug 2025

Cited by 3 | Viewed by 2036

Abstract

This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simulated using Autodesk Revit and Insight 360, varying three [...] Read more.

This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simulated using Autodesk Revit and Insight 360, varying three critical variables: glazing type (clear, blue, and dark), Window-to-Wall Ratio (WWR) of 15%, 50%, 75%, and indoor wall finish (light, moderate, dark) colors. These were compared to the Leadership in Energy and Environmental Design (LEED) daylighting quality thresholds. The results revealed that clear glazing paired with high WWR (75%) achieved the highest Spatial Daylight Autonomy (sDA), reaching up to 92% in living spaces. However, this also led to elevated Annual Sunlight Exposure (ASE), with peak values of 53%, exceeding the LEED discomfort threshold of 10%. Blue and dark glazing types successfully reduced ASE to as low as 0–13%, yet often resulted in underlit spaces, especially in private rooms such as bedrooms and bathrooms, with sDA values falling below 20%. A 50% WWR emerged as the optimal balance, providing consistent daylight distribution while maintaining ASE within acceptable limits (≤33%). Similarly, moderate color wall finishes delivered the most balanced lighting performance, enhancing sDA by up to 30% while controlling reflective glare. Statistical analysis using Pearson correlation revealed a strong positive relationship between sDA and ASE (r = 0.84) in highly glazed, clear glass scenarios. Sensitivity analysis further indicated that low WWR configurations of 15% were highly influenced by glazing and finishing types, leading to variability in daylight metrics reaching ±40%. The study concludes that moderate glazing (blue), medium WWR (50%), and moderate color indoor finishes provide the most robust daylighting performance across diverse room types. These findings support an evidence-based approach to façade design, promoting visual comfort, daylight quality, and sustainable building practices. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

24 pages, 3803 KB

Open AccessArticle

Symmetry-Aware Hybrid Verification for Complex Building Information Systems

by Linlin Kong, Qiliang Yang, Yaoqin Zhang, Xuewei Zhang and Qizhen Zhou

Symmetry 2025, 17(5), 726; https://doi.org/10.3390/sym17050726 - 9 May 2025

Viewed by 873

Abstract

As building information model technologies become more complex and interconnected, the validation of building information models remains critical to ensure their reliability and effectiveness in practical applications. However, most of the existing research focuses on the application of building information modeling in a [...] Read more.

As building information model technologies become more complex and interconnected, the validation of building information models remains critical to ensure their reliability and effectiveness in practical applications. However, most of the existing research focuses on the application of building information modeling in a single domain and lacks the collaborative validation of the overall behavior of complex dynamic systems. Therefore, how to ensure the correctness and reliability of complex building systems has become a challenging issue. To solve this problem, this paper proposes a symmetry-aware hybrid validation framework that combines Timed Automata (TA), Unified Modeling Language (UML), and AnyLogic simulation to enhance the logical correctness and practical reliability of complex building information systems; the framework inherently preserves structural and temporal symmetry between formal models and dynamic simulations, ensuring consistent validation across virtual–physical interactions. Taking the Building Information Physical Model (BIPM) as an example, the method first solves the defects of traditional methods in logical consistency and reliability validation by firstly modeling the structural model and behavioral logic of the BIPM through UML normalization, transforming the behavioral logic of the BIPM into a network of TA, and realizing the formal validation of its dynamic interaction mechanism to enhance the logical correctness and practical reliability of the complex building information system. Secondly, AnyLogic is used to map the BIPM structural model into a visual simulation model, which supports the real-time dynamic display of building system behavior and performance analysis, enhances the interpretability of the model, and provides an intuitive decision-making platform for stakeholders. Finally, an empirical study of an air conditioning system as a case study shows that the method can effectively integrate formal verification and dynamic visualization techniques, providing a scalable solution for the collaborative verification of complex building systems. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

29 pages, 1532 KB

Open AccessArticle

The Design of Human-in-the-Loop Cyber-Physical Systems for Monitoring the Ecosystem of Historic Villages

by Giancarlo Nota and Gennaro Petraglia

Smart Cities 2024, 7(5), 2966-2994; https://doi.org/10.3390/smartcities7050116 - 14 Oct 2024

Cited by 3 | Viewed by 3075

Abstract

Today, historic villages represent a widespread and relevant reality of the Italian administrative structure. To preserve their value for future generations, smart city applications can contribute to implement effective monitoring and decision-making processes devoted to safeguarding their fragile ecosystem. Starting from a situational [...] Read more.

Today, historic villages represent a widespread and relevant reality of the Italian administrative structure. To preserve their value for future generations, smart city applications can contribute to implement effective monitoring and decision-making processes devoted to safeguarding their fragile ecosystem. Starting from a situational awareness model, this study proposes a method for designing human-in-the-loop cyber-physical systems that allow the design of monitoring and decision-making applications for historic villages. Both the model and the design method can be used as a reference for the realization of human-in-the-loop cyber-physical systems that consist of human beings, smart objects, edge devices, and cloud components in edge-cloud architectures. The output of the research, consisting of the graphical models for the definition of monitoring architectures and the method for the design of human-in-the-loop cyber-physical systems, was validated in the context of the village of Sant’Agata dei Goti through the implementation of a human-in-the-loop cyber-physical system for monitoring sites aiming at their management, conservation, protection, and fruition. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

25 pages, 6230 KB

Open AccessSystematic Review

A Review of Comprehensive Post-Occupancy Evaluation Feedback on Occupant-Centric Thermal Comfort and Building Energy Efficiency

by Jing Zhao, Faziawati Abdul Aziz, Yiyu Deng, Norsidah Ujang and Yi Xiao

Buildings 2024, 14(9), 2892; https://doi.org/10.3390/buildings14092892 - 13 Sep 2024

Cited by 21 | Viewed by 10427

Abstract

The post-occupancy evaluation process is pivotal for assessing the performance of indoor and outdoor living environments after occupation. This evaluation involves a multifaceted analysis, encompassing energy efficiency, indoor environmental quality, outdoor spaces, and occupant satisfaction. Despite the inherent advantages and potential applicability of [...] Read more.

The post-occupancy evaluation process is pivotal for assessing the performance of indoor and outdoor living environments after occupation. This evaluation involves a multifaceted analysis, encompassing energy efficiency, indoor environmental quality, outdoor spaces, and occupant satisfaction. Despite the inherent advantages and potential applicability of post-occupancy evaluation in residential buildings, the lack of uniformity in research methodologies, data collection techniques, investigative approaches, and result interpretation has impeded cross-comparisons and method replication. In a concerted effort to enhance the understanding of prevailing post-occupancy evaluation methodologies, this study undertook a comprehensive systematic literature review of post-occupancy evaluation practices within the residential domain from 2000 to 2023. The results unequivocally underscored the pervasive lack of consistency in methodological applications, tool deployment, and data reporting across diverse post-occupancy evaluation investigations. The objectives of this review aimed to examine the existing post-occupancy evaluation (POE) methods, assess occupant-centric thermal comfort, evaluate the impact of POE feedback on building design, and develop recommendations for architects, engineers, facility managers, and policymakers on leveraging POE feedback to enhance thermal comfort and energy efficiency in buildings. This study offers critical insights into advocating for a more standardized and cohesive post-occupancy evaluation approach. The findings of this review can direct the establishment of a coherent and consistently implemented post-occupancy evaluation framework within the realm of residential architecture. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

29 pages, 8332 KB

Open AccessArticle

Energy Management in Residential Microgrid Based on Non-Intrusive Load Monitoring and Internet of Things

by Rawda Ramadan, Qi Huang, Amr S. Zalhaf, Olusola Bamisile, Jian Li, Diaa-Eldin A. Mansour, Xiangning Lin and Doaa M. Yehia

Smart Cities 2024, 7(4), 1907-1935; https://doi.org/10.3390/smartcities7040075 - 23 Jul 2024

Cited by 47 | Viewed by 5984

Abstract

Recently, various strategies for energy management have been proposed to improve energy efficiency in smart grids. One key aspect of this is the use of microgrids. To effectively manage energy in a residential microgrid, advanced computational tools are required to maintain the balance [...] Read more.

Recently, various strategies for energy management have been proposed to improve energy efficiency in smart grids. One key aspect of this is the use of microgrids. To effectively manage energy in a residential microgrid, advanced computational tools are required to maintain the balance between supply and demand. The concept of load disaggregation through non-intrusive load monitoring (NILM) is emerging as a cost-effective solution to optimize energy utilization in these systems without the need for extensive sensor infrastructure. This paper presents an energy management system based on NILM and the Internet of Things (IoT) for a residential microgrid, including a photovoltaic (PV) plant and battery storage device. The goal is to develop an efficient load management system to increase the microgrid’s independence from the traditional electrical grid. The microgrid model is developed in the electromagnetic transient program PSCAD/EMTDC to analyze and optimize energy performance. Load disaggregation is obtained by combining artificial neural networks (ANNs) and particle swarm optimization (PSO) to identify appliances for demand-side management. An ANN is applied in NILM as a load identification task, and PSO is used to optimize the ANN algorithm. This combination enhances the NILM technique’s accuracy, which is verified using the mean absolute error method to assess the difference between the predicted and measured power consumption of appliances. The NILM output is then transferred to consumers through the ThingSpeak IoT platform, enabling them to monitor and control their appliances to save energy and costs. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

26 pages, 10488 KB

Open AccessArticle

Development of an AI Model Utilizing Buildings’ Thermal Mass to Optimize Heating Energy and Indoor Temperature in a Historical Building Located in a Cold Climate

by Jan Akander, Hossein Bakhtiari, Ali Ghadirzadeh, Magnus Mattsson and Abolfazl Hayati

Buildings 2024, 14(7), 1985; https://doi.org/10.3390/buildings14071985 - 1 Jul 2024

Cited by 4 | Viewed by 3052

Abstract

Historical buildings account for a significant portion of the energy use of today’s building stock, and there are usually limited energy saving measures that can be applied due to antiquarian and esthetic restrictions. The purpose of this case study is to evaluate the [...] Read more.

Historical buildings account for a significant portion of the energy use of today’s building stock, and there are usually limited energy saving measures that can be applied due to antiquarian and esthetic restrictions. The purpose of this case study is to evaluate the use of the building structure of a historical stone building as a heating battery, i.e., to periodically store thermal energy in the building’s structures without physically changing them. The stored heat is later utilized at times of, e.g., high heat demand, to reduce peaking as well as overall heat supply. With the help of Artificial Intelligence and Convolutional Neural Network Deep Learning Modelling, heat supply to the building is controlled by weather forecasting and a binary calendarization of occupancy for the optimization of energy use and power demand under sustained comfortable indoor temperatures. The study performed indicates substantial savings in total (by approximately 30%) and in peaking energy (by approximately 20% based on daily peak powers) in the studied building and suggests that the method can be applied to other, similar cases. Full article

(This article belongs to the Topic Application of Smart Technologies in Buildings)

► Show Figures

Figure 1

Topic Menu

Topic Editors

Application of Smart Technologies in Buildings

Topic Information

Keywords

Participating Journals

Published Papers (15 papers)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI

Topic Menu

Topic Editors

Application of Smart Technologies in Buildings

Topic Information

Keywords

Participating Journals

Related Topic

Published Papers (15 papers)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI