Well-being Of Occupants Research Articles

Dynamic Indoor Environmental Quality Assessment in Residential Buildings: Real-Time Monitoring of Comfort Parameters Using LoRaWAN

This study addresses an identified literature gap regarding indoor environmental quality in residential buildings, where the primary focus has traditionally been on energy performance rather than comfort optimization. Leveraging the low-cost and easy-to-implement LoRaWAN protocol, this research collects and analyses real-time data on comfort parameters, including temperature, CO2 levels, humidity, lighting, atmospheric pressure, and total volatile organic compounds (TVOC) across various buildings within the INCUBE EU project. The results highlight the dynamic nature of the parameters and emphasize the importance of continuous monitoring to enhance comfort and energy efficiency in smart residential buildings. The findings advocate for integrating technologies like LoRaWAN to optimize indoor environmental quality, ultimately improving residential comfort and occupant well-being.

Exploring Asymmetric Lens–Total Internal Reflection (AL–TIR) Optics for Uniform Ceiling Illumination in Interior Lighting

This study presents a significant advancement in LED interior lighting through the development and application of Asymmetric Lens–Total Internal Reflection (AL–TIR) optics, with a focus on enhancing lighting uniformity and indoor comfort by simulating sky-like lighting distribution. AL–TIR technology employs asymmetric lenses combined with total internal reflection to efficiently redirect and spread light, achieving a controlled and even ceiling illumination suitable for various interior applications. This research explored the establishment of ideal luminous intensity curves, devised practical AL–TIR optical designs through numerical calculations, and conducted extensive simulations to assess performance in typical indoor environments. Our findings demonstrated substantial improvements in lighting uniformity, with the AL and AL–TIR systems achieving direct illuminance uniformities of 0.78 and 0.83, respectively, compared to traditional tube LEDs at 0.25. These results, validated in several office rooms, highlight the efficacy of AL–TIR optics in revolutionizing indoor lighting design by balancing optimal lighting distribution with occupant comfort and well-being.

AI-Based Controls for Thermal Comfort in Adaptable Buildings: A Review

Due to global weather changes and pandemics, people are more likely to spend most of their time in indoor environments. In this regard, indoor environment quality is a very important aspect of occupant well-being, which is often ignored in modern building designs. Based on our research, thermal comfort is one of the essential items in building environments that can improve the mental stability and productivity of the occupants if the building’s indoor environment is created in a way that meets the occupants’ comfort requirements. Buildings nowadays operate on adaptive or stationary models to attain thermal comfort, which is based on Fanger’s model of the Predicted Mean Vote (PMV). Based on the literature review, limited work has been carried out to enhance the quality of the inside environment, and most research work has been devoted to building energy management. Moreover, there have been no definite solutions so far that have the capability to detect the thermal comfort requirements of multiple occupants in real time. Modern buildings tend to operate on predefined set point parameters to control the indoor environment based on the measured room temperature, which can be different from the thermal comfort requirements of the occupants. This paper discusses the limitations and assumptions that are associated with the existing thermal comfort solutions and emphasises the importance of having a real-time solution to address the thermal requirements of occupants.

Integrating Machine Learning and Genetic Algorithms to Optimize Building Energy and Thermal Efficiency Under Historical and Future Climate Scenarios

As the global energy demand rises and climate change creates more challenges, optimizing the performance of non-residential buildings becomes essential. Traditional simulation-based optimization methods often fall short due to computational inefficiency and their time-consuming nature, limiting their practical application. This study introduces a new optimization framework that integrates Bayesian optimization, XGBoost algorithms, and multi-objective genetic algorithms (GA) to enhance building performance metrics—total energy (TE), indoor overheating degree (IOD), and predicted percentage dissatisfied (PPD)—for historical (2020), mid-future (2050), and future (2080) scenarios. The framework employs IOD as a key performance indicator (KPI) to optimize building design and operation. While traditional indices such as the predicted mean vote (PMV) and the thermal sensation vote (TSV) are widely used, they often fail to capture individual comfort variations and the dynamic nature of thermal conditions. IOD addresses these gaps by providing a comprehensive and objective measure of thermal discomfort, quantifying both the frequency and severity of overheating events. Alongside IOD, the energy use intensity (EUI) index is used to assess energy consumption per unit area, providing critical insights into energy efficiency. The integration of IOD with EUI and PPD enhances the overall assessment of building performance, creating a more precise and holistic framework. This combination ensures that energy efficiency, thermal comfort, and occupant well-being are optimized in tandem. By addressing a significant gap in existing methodologies, the current approach combines advanced optimization techniques with modern simulation tools such as EnergyPlus, resulting in a more efficient and accurate model to optimize building performance. This framework reduces computational time and enhances practical application. Utilizing SHAP (SHapley Additive Explanations) analysis, this research identified key design factors that influence performance metrics. Specifically, the window-to-wall ratio (WWR) impacts TE by increasing energy consumption through higher heat gain and cooling demand. Outdoor temperature (Tout) has a complex effect on TE depending on seasonal conditions, while indoor temperature (Tin) has a minor impact on TE. For PPD, Tout is a major negative factor, indicating that improved natural ventilation can reduce thermal discomfort, whereas higher Tin and larger open areas exacerbate it. Regarding IOD, both WWR and Tin significantly affect internal heat gains, with larger windows and higher indoor temperatures contributing to increased heat and reduced thermal comfort. Tout also has a positive impact on IOD, with its effect varying over time. This study demonstrates that as climate conditions evolve, the effects of WWR and open areas on TE become more pronounced, highlighting the need for effective management of building envelopes and HVAC systems.

Evaluating UKCP18-Based weather files for overheating assessment using building simulation: A case study for a flat in london

Global warming and net zero transition are the two biggest challenges currently faced by the building industry in the UK. While the net zero transition primarily focuses on the problems of energy efficiency and heat decarbonization, the rise of global temperature imposes a significant threat to the health and wellbeing of occupants and the industry is obliged to make buildings climate-resilient by testing their designs using future weather files. To improve the quality of the current weather files, a new project has been commissioned by CIBSE to revisit the data and the methodology employed for creating future weather files and produce new CIBSE weather files using the latest UK Climate Projections released in 2018 (UKCP18). In this study, we evaluate the newly produced weather files for overheating risk using building simulation. Two different batches of weather files were curated. The first batch was produced primarily using the existing methodology for creating the UKCP09 based weather files, with an adjustment to accommodate new features of the UKCP18 and an improved procedure for morphing the solar radiation data. The second batch was created through an improved morphing process to better emulate the characteristics of distributions of climatic variables. The differences between the existing UKCP09 and new UCKP18 based weather files are compared by evaluating overheating metrics. The new weather files enable robust building performance assessment against future climate conditions under different scenarios and will play an important role in designing climate-resilient buildings and delivering a net zero built environment. Practical applications As the extreme weather events resulting from climate change become more frequent and intense, they pose significant challenges to the resilience of the built environment and severe threats to the health and wellbeing of the occupants. Climate data, which serves as the foundation for climate risk assessment, plays a critical role in helping the building sector to achieve climate resilience through the means of performance assessment and the channel of regulatory compliance. In this study, the revised future weather files created using the latest UKCP18 climate projections are presented and evaluated using building simulation, as part of the weather file testing programme for quality assurance. The revision of the CIBSE weather files according to the latest climate science, i.e. UKCP18, will enable the building industry to quantify overheating risks with more accurate climate assumptions and better inform decision making about risk mitigation and climate adaptation.

The Impact of Green Building Design on Indoor Air Quality and Occupant Experience

This study examines the impact of green building design on indoor air quality (IAQ) and occupant experience, using Heritage Place in Ikoyi, Lagos, as a case study. Green buildings are known for incorporating sustainable practices such as the use of eco-friendly materials, advanced ventilation systems, and biophilic design elements, all aimed at enhancing environmental sustainability and occupant well-being. A descriptive survey methodology was employed, with data gathered through a questionnaire administered to 50 occupants of the building to assess their perceptions of IAQ, health, comfort, and overall satisfaction. The findings indicate that the majority of respondents reported high levels of satisfaction with IAQ, attributing improvements in their health, productivity, and comfort to the building’s green design features. Specifically, low-emission materials and enhanced ventilation systems were highly praised for reducing pollutants and maintaining a healthy indoor environment. However, a few respondents expressed concerns about inconsistent thermal comfort in certain areas. These results underscore the importance of sustainable design in creating healthier, more productive indoor environments. Recommendations for future green building projects include fine-tuning HVAC systems to improve thermal comfort and enhancing occupant education on the benefits of sustainable features.

Review and Measure Winter Thermal Performance in CLT Building: A Case Study on Meldia Research Institute for Advanced Wood

Abstract CLT (Cross Laminated Timber) as a building material could help lower the carbon footprint of construction projects. Thermal performance and comfort in CLT buildings as a place to work are very important for optimizing comfort and work quality using CLT buildings. In winter conditions, measure and review is very necessary to optimize the desired building according to the standard level of comfort when working. The aims of this research is to measure and review indoor thermal comfort of CLT building during winter, with the case study Meldia Research Institute for Advanced Wood, Fukuoka, Kitakyushu. This research method involves measuring indoor temperature intensity in winter to understand how CLT buildings can achieve an optimal balance of thermal comfort. The results of measurements using PMV analysis of both rooms with the HVAC on at a temperature of 22 degrees Celsius are that the PMV value tends from a Slightly warm condition (+1) to a Neutral (0) at each measurement time and at all points. Room 1 has the highest PMV value between slightly cool (-0.5) to Slightly warm (+1), while room 2 has the lowest value between Cool (-2) to Slightly warm (+1). These findings can guide building designers in developing architectural solutions that are sustainable and focus on occupant well-being.

An architectural design framework to promote healthy indoor-outdoor connections in Arctic housing

This research proposes biophilic intermediate spaces as a promising architectural solution to improve indoor-outdoor connections, occupant well-being, and energy efficiency in Arctic housing. Basic examples of intermediate spaces in Arctic housing models include porches and vestibules. However, the architecture of these spaces has not yet been optimized to adress extreme climatic conditions and occupants’ needs. Therefore, this research develops an architectural design framework to optimize the architecture of intermediate spaces for Arctic housing to meet occupants’ well-being needs and improve housing energy efficiency. The research methodology combines an archetypal approach, exploratory case study analysis, and scoping literature review. The archetypal study examines the historical development of Canadian Arctic housing models in Nunavut, revealing the typological evolution, features, potentials, and deficiencies of intermediate spaces in the Arctic. The study identifies of the main design variables and performance indicators of intermediate spaces corresponding to healthy and positive indoor-outdoor connections, thermal and visual comfort, and energy efficiency. A conceptual model of an intermediate space is then simulated as an exploratory case study for a public Canadian Arctic residential building. The architectural design framework is established based on findings from the literature, archetypal studies of Arctic housing, and simulation results of an integrated model for an intermediate space and a public Arctic housing model in Nunavut. The proposed framework includes main architectural variables such as physical adjacency, material, orientation, space depth, and transparency ratio which impact thermal, lighting, and energy performance. This design framework can serve as a reference for creating policies and decision-making processes that integrate biophilic intermediate spaces with Arctic building practices, contributing to Canada's strategic plan for energy efficiency and vegetable production in the Arctic.

Efficient Daylighting: The Importance of Glazing Transmittance and Room Surface Reflectance

This study quantitatively analyzes the influence of the spectral characteristics, reflectance or transmittance, of different materials on the lighting of an interior space with natural and artificial light. For this purpose, a three-dimensional simulated classroom is used, where each of the components is assigned specific materials with an associated reflectance or transmittance. Additionally, two types of lighting are available: 6500 K daylight and light from six continuous spectrum LED luminaires. The lighting is evaluated on two planes: the work plane and the corneal plane (80 cm and 120 cm from the floor, respectively). Three versions of the same classroom were analyzed by varying the walls (white, blue, and red), each with a different neutral-colored floor. Furthermore, calculations were performed in each situation considering two different types of glazing in the windows, with 20% and 88% transmittance. The photopic and melanopic lighting analysis was carried out with the ALFA calculation program to verify the necessary requirements for adequate lighting. The results show that the white classroom is the best lit, followed by the blue and finally the red, due to the reflectance characteristics of the walls and floor although slight differences among them are found. It was found that in some cases, additional auxiliary luminaires would be required for proper lighting depending on the transmittance of the glazing. This study highlights the critical role of material selection in optimizing both photopic and melanopic lighting, with practical implications for energy efficiency and occupant well-being in educational spaces.

Indoor environment and user perceptions in offices in Greenland compared to Denmark

Most of the Greenlandic building stock comprises residential houses and apartments. Consequently, the indoor environment in Greenlandic office buildings has not been subject to wide-ranging investigations. The purpose of this study was to investigate the indoor environment in office buildings in Greenland and to characterise the buildings, their indoor environment, and occupant well-being, health and self-assessed performance. This was done through a post occupancy evaluation (POE), where 22 office buildings, including 70 offices in Nuuk and Sisimiut, were evaluated based on indoor environment measurements and questionnaires of occupants' perceived indoor environment. This was compared with data and results from a related study in office buildings in Denmark (26 office buildings, including 83 offices) collected in the same period. The Danish office buildings performed slightly better than the Greenlandic office buildings regarding the perceived indoor environment. The measured indoor environment differed in performance between the countries when benchmarking towards the requirements and guidelines of the Danish Working Environment Authority (DWEA). It was concluded that the office buildings in Greenland did not differ much from the office buildings in Denmark regarding the measured and perceived indoor environment.

Personalized low-cost thermal comfort monitoring using IoT technologies

Thermal comfort plays an essential role in the well-being and productivity of occupants. Typically, thermal comfort is assessed either through surveys completed by building occupants or through sensor data that is analyzed using thermal comfort models. Automating comfort surveys and data collection processes reduce the risk of information loss, providing more accurate and personalized thermal comfort assessments over longer periods of time. To this end, this paper presents the design and implementation of a thermal comfort monitoring system consisting of low-cost hardware components and using IoT technologies. The system consists of intelligent wireless sensor nodes that collect and process environmental data, a portable main station that integrates and stores data, and a digital survey that provides feedback from building occupants. To ensure accuracy, the low-cost hardware components of the intelligent sensor nodes are calibrated in a climate chamber, using high-precision sensors for reference. After calibration, the system is deployed in a field test where several intelligent sensor nodes collect environmental data in an office, while occupants complete the digital thermal comfort survey. In addition, thermal comfort indexes are computed by the intelligent sensor nodes and compared with the feedback of each building occupant. The results indicate that the low-cost thermal comfort monitoring system successfully collects and integrates thermal comfort data from the intelligent sensor nodes and the digital survey, being able to create personalized thermal comfort profiles. In future work, the system can be used in large-scale thermal comfort surveys, to develop personalized thermal comfort models and to control personalized comfort systems.

Investigating daylighting quality in educational spaces following building renovation

Abstract Daylighting is essential to the well-being of occupants in educational spaces. It increases students’ performance and provides an opportunity for achieving energy efficiency, as well as indoor visual and thermal comfort. However, daylight performance is rarely accounted for when taking decisions attributed to building renovation. This results in increased or decreased daylighting lighting levels and glare which jeopardizes the functional requirements of the space. Hence, this study adopted a mixed qualitative/quantitative approach to compare two recently renovated educational spaces (architectural design studio drawing halls) in terms of the effect of renovation activities on daylighting and visual comfort, noting that both spaces were located in the same building and subject to similar prevailing climatic conditions. This included a sequence of site measurements, surveys and simulations. The results showed great variation between both studied spaces in terms of daylight efficiency and visual comfort. Some design proposals were tested in order to deduct learnt lessons for proper accounting of daylight during building renovation plans.

Maintaining Optimal Indoor Air Quality

In the study of indoor air quality in mixed-use complexes, the focus lies on understanding the intricate balance required to maintain optimal Indoor Air Quality (IAQ). Mixed-use environments present a unique challenge due to the diverse sources of indoor pollutants they encompass. By employing a survey research design that integrates both qualitative and quantitative data analysis, the study aims to shed light on the effectiveness of various strategies in controlling pollutant sources and ensuring well-maintained HVAC systems to improve IAQ. The findings of this research underscore the need to adopt a holistic approach to achieve and sustain optimal levels of IAQ levels within mixed-use complexes. Recommendations such as implementing high-efficiency filtration systems and enhancing ventilation mechanisms emerge as crucial steps towards improving air quality and ultimately enhancing the comfort and well-being of occupants in these multifaceted environments. This comprehensive approach not only addresses the immediate concerns related to IAQ but also contributes to the overall sustainability and liveability of mixed-use complexes, aligning with the growing emphasis on green technologies and practices in modern architectural design.

A personal thermal comfort model based on causal artificial intelligence: a physiological sensor-enabled causal identifiability.

Personal thermal comfort affects occupants' health, well-being, and productivity. Its satisfaction is subjective, based on individual characteristics and dynamic environments, and challenging to understand, requiring predicted outcomes and explanations of how and why the outcomes happen. This research fulfills this concern using a personal thermal comfort model based on causal artificial intelligence. It encodes personal thermal comfort satisfaction based on a new causal-and-effect framework to connect the human mind and environmental factors. Random variables encode relevant factors, and the structural causal model performs cause-and-effect relationships. The do-calculus (e.g., d-separated and d-connected) draws the common sense of the model based on causal structure representation, contributing to a human-intelligent understanding. A directed acyclic graph and exact-inference-based variable elimination quantify the model parameters based on real-world observational data. The strength of causal relationships is verified based on causal odd ratio, causal sensitivity, and causal impact. The results highlight that our proposed model can encode physiological and physical factors to predict and explain personal thermal comfort satisfaction. It can predict and explain such satisfaction reasonably and robustly, converging to human-like interpretation. It can be applied to intelligent systems to understand personal thermal comfort.

A physics-informed deep learning-based urban building thermal comfort modeling and prediction framework for identifying thermally vulnerable building stock

PurposeDue to the increasing frequency of extreme weather and densifying urban landscapes, residences are susceptible to heat-related discomfort, especially those in a naturally ventilated built environment in tropical climates. Indoor thermal comfort is thus paramount to building sustainability and improving occupants' health and well-being. However, to assess indoor thermal comfort considering the urban context, it is conventional to use questionnaire surveys and monitoring units, which are both case-centric and time-intensive. This study presents a dynamic computational thermal comfort modeling framework that can determine indoor thermal comfort at an urban scale to bridge this gap.Design/methodology/approachThe framework culminates in developing a deep learning model for predicting the accurate hourly indoor temperature of urban building stock by the coupling urban scale capabilities of environment modeling with single-building dynamic thermal simulations.FindingsUsing the framework, a surrogate model is created and verified for Dharavi, India's informal urban settlement. The results indicated that the developed surrogate model could predict the building's indoor temperature in several complex new urban scenarios with different building orientations, layouts, building-to-building distances and surrounding building heights, using five different random urban representative scenarios as the training set. The prediction accuracy was reliable, as evidenced by the mean bias error (MBE) and coefficient of (CV) root mean squared error (MSE) falling between 0 and 5%. The findings also showed that if the urban context is ignored, estimates of annual discomfort hours may be inaccurate by as much as 70%.Social implicationsThe developed computational framework could help regulators and policymakers engage in more informed and quantitative decision-making and direct efforts to enhance the thermal comfort of low-income dwellings and informal settlements.Originality/valueUp to this point, majority of literature that has been presented has concentrated on building a body of knowledge about urban-based modeling from an energy management standpoint. In contrast, this study suggests a dynamic computational thermal comfort modeling framework that takes into account the urban context of the neighborhood while examining the indoor thermal comfort of the residential building stock.

Digital occupancy assessment for lighting evaluation: a pilot study to prepare for real-time research results

The relationship between lighting and human well-being is pivotal in architecture and environmental design. Adequate lighting enhances visual appeal and significantly influences occupant comfort, productivity, and satisfaction. This pilot study aimed to integrate digital occupancy assessment methods to understand indoor lighting conditions' impact on occupant well-being. Hypotheses explored the potential link between lighting conditions and occupant well-being, as assessed through physiological indicators and the influence of interior attributes on occupants' perceptions and physiological responses. The identified main components were satisfaction with artificial and daylighting, ambiance, and stimulation. The study explored the relationship between lighting conditions, physiological responses, and subjective assessments, revealing potential influences on occupant perceptions. A real-time data visualization could be valuable for data-intensive projects, enhancing comprehension and decision-making for facility management. While limited by the small sample size, trends, and moderate correlations were observed, indicating the need for larger, more diverse samples in future research.

Influence analysis of environmental factors on the subjective well-being of office workers in Japan: A structural equation modeling approach

The built environment is believed to have a considerable influence on the well-being of individuals. However, very few studies have been conducted to clarify the influence structure on the well-being of occupants in office spaces. There is a need to assess the influence of environmental factors at work and quality of life on well-being. We conducted an online survey in three metropolitan areas of Japan to investigate the influence structure on the subjective well-being (SWB). The survey items included questions on SWB, employment, office environment, private life, and community, personal attributes, and spatial attributes of the offices where they work. It was hypothesized that the influence structure can be explained using a higher-order factor analysis model, wherein “quality of work,” " quality of private life,” and " quality of community” serve as the top factors. Consequently, a structural equation model with a high level of goodness of fit was developed (CFI = 0.908 and RMSEA = 0.044). Improving “quality of work” had a significant impact as a key factor in promoting SWB in this model. The importance of “job satisfaction,” “fulfillment of office environment,” and “work engagement” in the assessment of work quality was further clarified. The multi-group analysis demonstrated the impact of variations in personal and spatial attributes on the influence structure. For example, office environments with basic quality and adjustability were found to be more critical for enhancing SWB of environmentally sensitive workers. Future surveys with diverse sample groups are required to validate the model in this study.

Exploring the Benefits of Mass Timber Construction in the Workplace: A Novel Primer for Research

Mass timber construction has recently gained popularity due to its outstanding environmental benefits and building performance, which hold revolutionary potential for the construction industry. However, its impacts from the perspective of occupants have not been thoroughly explored. This study introduces an innovative empirical approach that explores the potential benefits of mass timber construction for individuals and organizations, with an emphasis on the workplace. We review the conceptual framework regarding how visual and physical exposure to timber construction materials and finishes have a positive effect on individuals and organizations at a broad level. We propose a more holistic mixed-method behavioral approach to studying occupant behavior and well-being by integrating self-reported questionnaires, objective biomarkers (heart rate variability and hair cortisol), and indoor environmental quality (IEQ) measures. Our study offers a novel research primer on the exploration of mass timber construction impacts and benefits for both office workers and construction workers. Participants from different office settings completed pre- and post-occupancy evaluation surveys to assess their experiences, including IEQ satisfaction, productivity, and health. Office workers were located in three different offices: a controlled laboratory environment, an open-plan office, and an open-plan space with a timber interior. The construction workers worked in a timber space for three months and then moved to work in a building with a concrete structure. The analysis included descriptive statistics, t-tests, ANOVA, and linear regression to compare differences between office settings and assess the relationship between environmental variables and overall satisfaction in IEQ, comfort, productivity, and health. In office workers, in terms of building image, thermal comfort, and artificial lighting, the data analysis revealed significant differences in occupants’ satisfaction levels between office settings. However, the low number of participants affected the results, and some factors were not found significant in relation to the office setting. Among tradespeople, there was no relationship between the building environment and productivity, health, or comfort. However, the results of hair cortisol testing indicated that working in a timber space can decrease the level of cortisol (stress) and have an impact on the productivity of workers. Such occupant’s perspective research is pivotal to informing policy makers, developers, business owners, construction professionals, timber industry stakeholders, environmentalists, and researchers in their decision-making processes. Fostering the future widespread adoption and advancement of mass timber construction.

Towards Sustainable Living through Thermoneutral Temperature Management in Subtropical Steppe Climates

This study addresses the critical interplay between sustainable living and thermal comfort within residential buildings in subtropical steppe (BSh) climates, particularly in Northern Iraq. With the global imperative to enhance energy efficiency and occupant well-being, this research emphasizes the identification of thermoneutral indoor air temperature ranges that both support sustainable energy use and ensure the occupants’ thermal comfort. By analyzing the acceptable temperature limits across different building orientations during summer and winter, the study utilizes the predicted mean vote–predicted percentage dissatisfied (PMV-PPD) index approach to establish thermal comfort thresholds. The findings reveal that the optimal summer and winter indoor air temperatures are 29.2 °C and 19.4 °C, respectively, with variations across orientations highlighting the significant influence of building directionality on achieving thermoneutral conditions. A wider range of accepted temperatures exists in the eastward orientation in summer (between 26.6 °C and 29.2 °C). The study advances our understanding of sustainable thermal comfort practices, proposing orientation-specific temperature ranges as a cornerstone for reducing energy consumption without compromising occupant comfort in subtropical steppe climates.

The Role of Internet of Things (IoT) in Transforming Facilities Management in Smart Cities

The shift in urban foundation and administrations inside keen cities requests a comprehensive, innovative, and user-centric strategy that continues coordinating cutting-edge advances. This paper presents a spearheading approach that leverages the control of the Web of Things (IoT), Counterfeit Insights (AI), and Machine Learning (ML) to revolutionize the way shrewd city offices are overseen. At the centre of this strategy is the improvement of a centralized, cloud-based Offices Administration Stage (FMP) that serves as the spine for keen city operations. The FMP acts as an integrated hub, drawing together information from numerous IoT sensors, building automation systems, and other urban infrastructure. The policy also encourages user-centred design in light of improving occupant comfort, productivity, and well-being. Backed by IoT sensors and AI-driven building computerization frameworks, robust natural condition control and vitality utilization streamlining of the FMP can assist in conveying a predominant client involvement inside savvy city office.