Indoor Air Research Articles

Data Augmentation Method Using Room Transfer Function for Monitoring of Domestic Activities

Monitoring domestic activities helps us to understand user behaviors in indoor environments, which has garnered interest as it aids in understanding human activities in context-aware computing. In the field of acoustics, this goal has been achieved through studies employing machine learning techniques, which are widely used for classification tasks involving sound recognition and other objectives. Machine learning typically achieves better performance with large amounts of high-quality training data. Given the high cost of data collection, development datasets often suffer from imbalanced data or lack high-quality samples, leading to performance degradations in machine learning models. The present study aims to address this data issue through data augmentation techniques. Specifically, since the proposed method targets indoor activities in domestic activity detection, room transfer functions were used for data augmentation. The results show that the proposed method achieves a 0.59% improvement in the F1-Score (micro) from that of the baseline system for the development dataset. Additionally, test data including microphones that were not used during training achieved an F1-Score improvement of 0.78% over that of the baseline system. This demonstrates the enhanced model generalization performance of the proposed method on samples having different room transfer functions to those of the trained dataset.

Air quality disparities and respiratory health risks in critically polluted and relatively non-polluted areas: a prospective child health study.

Air pollution, a significant global health concern, notably impacts human well-being. Children, owing to their distinctive physiology and behavior, are particularly susceptible to its adverse effects. This prospective study examines air quality variations and respiratory risks in children residing in critically polluted areas (CPA) compared to relatively non-polluted areas (NPA), utilizing a prospective design to understand the impacts of air pollution on children's respiratory health, including measures like relative risk (RR) and attributable risk (AR). This prospective study tracked 739 students of 5th- 7th grade residing in CPA and NPA for one year, and measured the ambient and indoor air quality levels in both these areas. Throughout the study, based on the observed respiratory symptoms new episodes of upper and lower respiratory tract illnesses were recorded for each child on a weekly basis. Incidence rate, RR and AR for both the illnesses were compared. Statistical analysis was performed with SPSS 26.0. The study observes higher concentration for particulate matter and gaseous pollutants at CPA in comparison to NPA. Children living in CPA exhibited a notably greater weekly occurrence of both upper and lower respiratory tract illnesses compared to those in NPA, with RR of 1.26 (95% CI: 1.16-1.37) and 1.74 (95% CI: 1.34-2.27), respectively. The AR associated with air pollution for upper and lower respiratory tract illnesses among CPA students was found to be 20.7% and 42.7%, respectively. This research underscores the pressing need to address air pollution in critically polluted areas and its profound effects on children's respiratory health. Public health interventions, such as reducing emissions from industries and creating green spaces, should be prioritized. Furthermore, early respiratory health screening in schools within polluted areas could aid in the timely diagnosis and management of respiratory issues in children.

A Framework for Industry 4.0 Related Green Concept Integration of Services Component in Commercial Buildings

The effects of global warming are far-reaching and can affect and threaten every aspect of human existence. Human activities such as burning fossil fuels and deforestation have mainly contributed to the emission of these greenhouse gases into the atmosphere. Construction activities and practices are one such human activity. Building services are the aspects of a building that ensure the occupants are comfortable and secure within the building. However, building services use resources such as energy and water to create such comfort. The 4.0 era of industry has introduced dimensions to Green Building Concepts and practices of creating structures and processes that are environmentally friendly, responsible and resource efficient. This research, therefore, seeks to develop a framework for the integration of Industry 4.0-related green concepts into services in commercial buildings. A cross-sectional survey design was adopted in this research to provide information concerning integrating green concepts into building services in commercial buildings in Nigeria. Data were collected with questionnaires from 106 built environment professionals who also use commercial buildings in the study area of Abuja. Statistical tools for frequency, percentage, mean score, relative important index (RII), independent samples t test, Mann–Whitney U test and the factor reduction method based on eigen values were used to analyze the data. The results indicated that quality indoor air conditioning is the most critical satisfaction parameter for users within commercial buildings, with an average mean score of 3.81. The aesthetic effect of installed services on the building façade and high-quality building services components was ranked high, with an average mean score of 3.33 for each. The results also indicated that the lack of relevant technology and inadequate training of service personnel hindered the growth of green building concepts in Nigeria. These factors had a mean score of 4.35 each. Professionals ranked energy efficient/saving bulbs, e.g., CFLs, remote controlled, sensored lights, natural daylight, solar photovoltaic panels and building management systems, as the most effective green components that can be incorporated into commercial buildings. These factors and others were combined to create a framework for integrating green concepts for services into commercial buildings. When the construction industry and government in Nigeria adopt this framework, it can promote more integration of green concepts into commercial building services.

A fingerprint dictionary processing approach in indoor localization system based on wi-fi

Indoor localization using Wi-Fi fingerprinting based on Received Signal Strength (RSS) has gained widespread attention due to its immunity to external factors and ability to penetrate obstacles. The localization process involves an offline phase for building a radio map and an online phase for matching location queries. Existing matching algorithms often prioritize enhancing online phase accuracy, overlooking the importance of offline data preprocessing, which can negatively impact overall performance. This study introduces a novel approach called Fingerprint Dictionary Preprocessing (FDP) that employs Convolutional Dictionary Learning (CDL) to process radio map data. CDL learns a set of kernels capturing site characteristics, representing RSS values from Access Points (APs) in a sparse manner. The proposed FDP system compresses data through feature learning, reducing storage requirements for data transmission. In the online phase, CDL is utilized for assisting matching fingerprints against the learned dictionary, accurately locating users. The contributions of the FDP system presenting a cost-effective and practical solution for indoor localization, addressing the challenges associated with large data collection and multi-dimensional data requirements, making it a promising approach for real-world applications. We conducted experiments in two real indoor environments, and the results indicated that the proposed FDP system, whether applied to the original radio map or the preprocessed fingerprint database, led to improved localization accuracy and reduced localization time.

Impacts of Indoor Air Quality on Working‐Age Populations' Subjective Well‐Being: Evidence From China Labor Dynamics Survey

ABSTRACTOutdoor air pollution can affect physical labor productivity and mental health, but it remains to be studied how indoor air quality (IAQ) exposure affects working‐age populations' subjective well‐being and physical health. Here, the first evidence of a link between IAQ and the subjective well‐being of working‐age populations has been provided using the dataset from a longitudinal survey in China. Using household ventilation as an instrument variable (IV) of IAQ revealed that IAQ improvements increased working‐age populations' subjective well‐being and life satisfaction by significantly affecting their physical health. Our analysis shows that an increase in IAQ by one standard deviation improves working‐age populations' subjective well‐being by 0.041 standard deviations. The marginal willingness to pay for IAQ is approximately 98.09 CNY. Compared with outdoor air quality, the impact of IAQ on well‐being and life satisfaction is more conspicuous. The results are robust to a variety of alternative specifications. For developing countries, improving IAQ is a new channel toward enhancing life quality, with lower economic and social costs.

The impact of residential winter HVAC usage behavior on arthritis in older adults: A PLS-SEM analysis

Environmental factors like temperature and humidity have been shown to influence arthritis symptoms in older adults, and HVAC equipment can regulate indoor environmental parameters. This study aimed to explore the pathways and effectiveness of residential HVAC usage behavior during winter on arthritis conditions. Conducted across four major climate zones in China, this cross-sectional study involved 3579 older adults aged 60–74 years and collected data on demographics, residential environments, lifestyles, and health outcomes. Utilizing Partial Least Squares - Structural Equation Modeling (PLS-SEM), a complex structural equation model (SEM) and an HVAC-Health mediation model was developed to analyze the relationships among influencing factors and health outcomes. Results revealed that socio-economic status, building characteristics, lifestyles, HVAC usage behavior, and indoor environmental exposure significantly affect the frequency of arthritis flare-ups (p < 0.05). Specifically, lifestyles, indoor wet and cold exposures have strong direct effects on health outcomes, with path coefficients of 0.178, 0.155 and 0.143, respectively. Moreover, HVAC usage indirectly influences health through mediators, with cold exposure (β = 0.045, p < 0.001), air pollution (β = 0.025, p < 0.001), and wet exposure (β = 0.012, p = 0.001) ranked in terms of their mediating effects. This research underscores the crucial role of HVAC systems in mitigating arthritis symptoms in older adults, advocating for enhanced implementation of HVAC technologies in senior housing to promote health and well-being. The originality of this study lies in employing the PLS-SEM method to elucidate how the indoor environment—particularly under the premise of HVAC usage—affect arthritis symptoms in older adults.

Aldehydes: What We Should Know About Them

From Egyptian mummies to the Chanel N° 5 perfume, aldehydes have been used for a long time and continue to impact our senses in a wide range of perfumes, foods, and beverages. Aldehydes represent one of the categories of volatile organic compounds (VOCs), which are categorized as chemicals with boiling points up to 260 °C and can be found in indoor environments in the gaseous phase. Because of their potential or known hazardous properties for humans, the World Health Organization (WHO)-Europe provided some guidelines that may prevent several health risks. Indeed, some aldehydes, reported to be risky for humans, have been retired from the market, such as butylphenyl methylpropional (BMHCA). The purpose of this review is to summarize the most important aldehydes found indoors and outdoors and analyse in depth the toxicological aspects of these compounds, whose presence in perfumes is often underestimated. In addition, the ingredients’ synonyms that are reported in the literature for the same compound were unified in order to simplify their identification.

Differentiated Impacts of Indoor and Outdoor Fitness Environments on Residents’ Activity Intensity: A Perspective on Homo Urbanicus

This study develops a framework for the impact mechanism based on the “homo urbanicus” theoretical perspective, linking indoor and outdoor fitness environmental elements to residents’ subjective perceptions and their activity intensity. An empirical investigation is conducted using structural equation modeling (SEM) with data from 286 valid questionnaires (N = 421). The results demonstrate that both indoor and outdoor fitness environmental elements—specifically spatial, facility, and environmental factors—significantly positively influence residents’ fitness activity intensity, with this relationship mediated by perceptions of safety, convenience, comfort, and aesthetics. Furthermore, the study uncovers variations in the types and degrees of influence across indoor and outdoor settings. Based on these findings, the author proposes several planning and design strategies: “In indoor environments, it is essential to ensure that fitness spaces feature bright lighting and thoughtful design to enhance aesthetic appeal; additionally, optimizing spatial layouts and integrating information services can foster greater social interaction. For outdoor environments, prioritizing locations near aesthetically pleasing architecture, adjacent to blue landscapes, and within open areas, as well as sites that are close to community amenities and abundant surrounding facilities, will enhance residents’ fitness activity intensity”.

Optimal Determining Air Supply Humidity for Multi-Location Demands Under Different Objectives in an Indoor Moisture Environment: A Comprehensive Method and Case Study

Within high-precision indoor environments, such as semiconductor fabrication or textile plants, humidity control is paramount for preserving product integrity and reducing energy expenditure. The non-uniform indoor air environment poses a significant challenge in achieving humidity regulation that meets the distinct requirements of various locations. Traditional feedback control mechanisms may lead to instability, overshooting, and oscillation in indoor parameters. This paper proposes a comprehensive method to address humidity assurance issues in high-precision indoor environments by establishing analytical expressions that link the demand parameters at different locations with air supply parameters. Using a case study, this paper examines several typical operational scenarios with diverse control objectives, including minimizing dehumidification energy consumption, minimizing air supply humidity adjustment values, and constraints on adjustable air supply inlets. This method enables rapid calculation of air supply humidity and regulation of humidity parameters at multiple locations within the indoor environment. It considers various locations, requirements, optimization targets, and precision, demonstrating that it can quickly determine the optimal air supply parameters based on the objective function. This method facilitates rapid adjustment and high-precision assurance of different humidity requirements at multiple locations, making it suitable for high-precision design and control of indoor humidity environments.

Localization in MR-based Indoor Navigation System using point cloud registration

Abstract. This paper addresses the pervasive challenge of localization within indoor navigation systems. Many existing systems grapple with this issue, relying on marker-based methods, Bluetooth beacon localization, and image processing. However, these solutions often necessitate the placement of predetermined markers within the environment, presenting limitations such as marker deterioration over time, spatial constraints, and associated costs. In response, we propose a novel point cloud registration-based approach. This method involves the creation of a comprehensive global point cloud representing the entire indoor environment, effectively serving as a three-dimensional virtual map. Concurrently, a mixed-reality device is utilized to generate a local point cloud specific to the device’s current location within the building. By aligning and registering the local cloud with the global counterpart, the device’s precise location within the virtual map can be determined. This approach enables seamless navigation within indoor environments without the reliance on physical markers, offering a versatile and cost-effective solution to the challenge of localization in indoor navigation systems. Finally, an error analysis was also done to test localization accuracy for different illumination conditions, demonstrating the effectiveness of this method.

Low-Cost Thermal Point Clouds of Indoor Environments

Abstract. The integration of low-cost thermal sensors with Apple Smart Devices supports the generation of 3D point clouds that include temperature indicators. This generates a new perspective for the study of buildings, allowing for fast and reliable examination of physical building structures. To the best of our knowledge, this study is the first to demonstrate the use of affordable sensors for 3D thermal point cloud generation. The study involved capturing data from the LiDAR and thermal sensors, followed by an extrinsic calibration process to align the datasets. Subsequently, the point cloud was segmented based on different acquisition poses of the device and finally, the thermal data was projected onto the 3D model, integrating temperature information with spatial coordinates. Our results demonstrate the effectiveness of the approach for three-dimensional point cloud generation in indoor environments, highlighting significant thermal variations and enabling thermal mapping of building structures. Furthermore, our findings underscore the feasibility of employing low-cost sensors for generating detailed thermal models, opening possibilities for widespread adoption in various building analysis applications. This approach provides a comprehensive and cost-effective solution for building monitoring, democratizing access to advanced evaluation tools.

Integration of a Paper‐Based Supercapacitor and Flexible Perovskite Mini‐Module: Toward Self‐Powered Portable and Wearable Electronics

AbstractAn all‐flexible self‐powering unit, combining a flexible perovskite solar mini‐module for energy conversion and ultra‐flexible screen‐printed interdigitated carbon supercapacitors on paper for energy storage, is designed and developed. Through a hybrid bifurcated structure, the supercapacitors are connected in series and neatly layered on a paper substrate with the perovskite solar mini‐module strategically placed on top for seamless integration. The photosupercapacitor quickly reaches saturated voltage under various light intensities (1 sun, 1000 lx, 500 lx, and 200 lx) and displays a self‐discharge time of over 2 minutes. It delivers peak overall and storage efficiencies of 2.8% and 23%, respectively, and exhibits an extensive potential window of 3.8 V, making it a prominent choice for real time applications in electronic systems. In a nutshell, the inherent flexibility of both the solar module and the storage system, coupled with the space‐saving design, and the extensive potential window of the hybrid photosupercapacitor paves the way for implementation in portable and wearable electronics operating in indoor environments, ushering a new era of more versatile and adaptable energy solutions.

Indoor Localization in Commercial 5G Environment with Single BS

Abstract. As commercial 5G systems rapidly expand, indoor positioning using 5G signals holds great potential for serving a large number of users. In this paper, an effective fingerprint solution is proposed for indoor positioning with 5G signal base station by exploring the multi-beam property. Multi-beam channel state information (CSI) and multi-beam reference signal received power (RSRP) are used as the observations for fingerprinting. To assess the effectiveness of the proposed scheme, field tests were conducted across various indoor environments. The results showed that the positioning accuracy is improved by more than 45% compared with the single beam by using the multi-beam characteristics of the 5G signal. Based on the multi-beam RSRP, the proposed scheme can achieve a positioning error of 67% below 1 meter. In the awareness of the two typical indoor deployments of 5G systems, i.e., the digital indoor distribution (DID) and the distributed antenna system (DAS), the paper also compared the 5G positioning performance in these two scenarios. The field tests showed that, the multi-beam in DID has more features than in DAS, which lead to a better positioning performance than that in DAS.

Features, reasons, and significance of radon and thoron attributable radiological dose in the indoor environment

Humans receive around 50% of natural radiation dose due to 222Rn (radon), 220Rn (thoron) and their decay products. Several field campaigns measuring these gases and the decay products in different regions of India have been conducted in the recent past. Some of these studies measured indoor activity concentration and/or dose due to these gases and the associated decay products. This work compares the fraction of 222Rn and decay products and 220Rn and decay products in inhalation dose for 10 studies conducted in Uttarakhand state. It is seen that AEDT (annual effective dose due to 220Rn and decay products) for these regions varies between 21 and 48% and it is significantly higher than the averaged worldwide reference value of 6%. Based on elaborative measurements performed in the Bageshwar district (present work), Almora and Nainital districts (our previous campaigns); the reasons for this high value have been explored. It was observed that a higher source term for mud houses could be the main reason for the high AEDT range. Interestingly, preliminary analysis revealed that the fraction is higher for the dwellings situated at higher altitudes thus indicating the role of the unavailability of modern building construction materials at remote locations. The study highlights the significant contribution of thoron in the Indian Himalayas.

Voxel Size Performance in 3D Indoor Model Creation for 3D Evacuation Simulations

Abstract. 3D voxel models facilitate simulating 3D pedestrian motions within indoor environments with diverse furniture, equipment, and complex room layouts featuring stairs and ramps. Reasonable voxel sizes enable the effective identifications of indoor spaces, navigable surfaces, and vertical links from voxel models for the simulations. However, the performance of different voxel sizes on these identifications has yet to be thoroughly investigated. The choice of appropriate voxel sizes for various 3D evacuation scenarios has to be clarified to avoid unreliable simulation outcomes. Therefore, this paper aims to assess the performance of different voxel sizes on the identifications of the spaces, surfaces, and links. Firstly, we introduce three key metrics for the assessment: accuracy, robustness, and efficiency. Then, three IFC models are selected based on predefined criteria for the tests. Experimental procedures are elaborated to include data preparation, collection, and analysis. The primary findings of this investigation are: 1) with increasing voxel sizes, accuracy decreases, robustness changes, and efficiency increases; 2) larger indoor spaces exhibit smaller changes in accuracy across different voxel sizes, while smaller indoor spaces show more significant changes in accuracy. 3) when the voxel size is tiny, it becomes challenging to complete identifications. Conversely, with relatively larger voxel sizes, some indoor spaces and vertical links cannot be identified. 4) Indoor spaces with complex and non-orthogonal geometries require more identification time. This work is expected to advance the creation of 3D indoor model to facilitate 3D evacuation simulations.

Relationship between indoor environmental quality and guests’ comfort and satisfaction at green hotels: A comprehensive review

Abstract Recent studies have focused on different aspects of green management, practices, and green consumption in the hotel industry. However, there is a need to explore and better understand the association between indoor environmental quality (IEQ) and green hotel guest’s comfort. Therefore, it is essential to explore the effects of IEQ on the comfort and satisfaction of green hotel guests. This study conducts a comprehensive review of the effects of various IEQ parameters, including indoor air quality, thermal comfort, lighting, visual/view, acoustic comfort, building characteristics, decoration, and indoor greenery, on guest’s comfort and satisfaction in green hotels. Based on previous literature, it was also revealed that most current green building schemes lack of comprehensive evaluation of the performance of IEQ dimensions in green hotels. It was also observed that these IEQ parameters show a significant influence on the hotel guest’s comfort and satisfaction. Based on the findings of the literature review, a conceptual model was developed to represent the relationship between the IEQ parameters and guest’s comfort and satisfaction. The proposed conceptual model can be implemented by the hotel management for a comprehensive assessment of guests’ perceptions toward the IEQ in green hotels. The novelty of this study is based on its findings that establish a more effective IEQ evaluation method and serve as the reference scenario of IEQ, which can be a useful tool for both academician and practitioners and contribute to improving the indoor environmental performance of green hotels through highlighting the key IEQ parameters, which affect the comfort and satisfaction of hotel guests.

Evaluation of a Kirigami-inspired double-skin adaptive façade for natural ventilation and solar harvesting to enhance indoor environment and energy performance

A novel kirigami-inspired design concept for an environmentally responsive adaptive façade is presented and evaluated for the objectives of solar energy harvesting and adaptive ventilation through controllable surface orientation and opening. The concept is a double-skin façade where the outer skin includes a straight cut kirigami-inspired adaptive component. Controllable actuation of the kirigami-inspired section opens the outer skin for ventilation while also changing the orientation of the outer surface for solar tracking. The primary objective of this study is to evaluate the potential benefits for this concept integrated within a building façade for solar energy harvesting, air changes, and indoor temperature control. As such, a computational study is used to estimate the proposed facade concept's performance within various generalized building-environment scenarios. The methodology is detailed to computationally estimate the potential environmental performance of this concept with respect to solar harvesting with adhered solar panels, as well as air changes and HVAC cost for associated interior spaces. The example scenarios include various building components, from a single room to multiple building stories, and two geographic locations with significantly different environmental conditions, and both daily and yearly performance estimates are shown. The component is most effective when the outdoor temperature is near to the desired indoor temperature and wind speeds are mild, but can still reduce HVAC usage for more disparate temperatures. For example, in the scenarios shown the component can eliminate HVAC use for a 5°C difference between outdoor and indoor temperature and reduces HVAC usage for temperature differences up to 15°C. Moreover, the component has the potential to significantly increase net energy generation, with yearly performance estimated for the scenarios to be as much as 25% greater than that of a flat closed façade. However, the component cut parameters can have a significant impact on environmental performance, and thus require careful design consideration.

A novel autonomous exploration algorithm via LiDAR/IMU SLAM and hierarchical subsystem for mobile robot in unknown indoor environments

Abstract Autonomous exploration in unknown environments is an essential capability for mobile robots. The complexity of autonomous exploration, however, means that existing algorithms struggle to balance efficiency and comprehensiveness, causing low mapping accuracy and redundant path planning. To perform accurate and efficient exploration tasks, we have proposed a novel autonomous exploration algorithm via LiDAR/IMU (Inertial Measurement Unit) Simultaneous Localization and Mapping (SLAM) and hierarchical subsystem for mobile robot in unknown environments. Firstly, to enhance mapping accuracy for mobile robot exploration, LiDAR/IMU SLAM is improved with the assistance of backward propagation and iterated Kalman filter, and Bidirectional Rapidly–Exploring Random Trees* (BI–RRT*) is applied for efficient frontier point detection. Secondly, we optimize local path planning by leveraging information theory through perceptual quality evaluation, which is then integrated with global path planning utilizing an enhanced Travelling Salesman Problem solver and a sparse grid map to amplify exploration efficiency. Thirdly, an enhanced hierarchical autonomous exploration method for mobile robots is proposed, which incorporates local path planning for seamless navigation around highly promising exploration spots, coupled with global path planning to effectively interconnect various sub–regions. Finally, simulations and field tests have demonstrated that the proposed method explores an unknown indoor environment with a 30.8% reduction in exploration time and a 29.9% reduction in exploration path in comparison with Dynamic Stage Viewpoint Planner. The map constructed in this paper has more accurate details and exploration paths have been shortened to ensure effective exploration.

Pedestrian Path Choice in Crowded Indoor Environments

Abstract. Indoor crowds can be regarded as dynamic obstacles and they could impede the movement of pedestrians. For instance, the scope of crowds could significantly impact accurate path choices. There are few discussions from an individual’s perspective to reveal the decision-making process of reasonable path choices. In this paper, we aim to address how an indoor pedestrian would walk in a crowded indoor environment. We propose a method to simulate a pedestrian’s path choices during wayfinding process. It is wrapped in a workflow that can capture near-real-time crowd uncertainty. First, the measurement errors of crowds are alleviated with a Bayesian filter. According to crowd locations at each moment, the method of Kernel Density Estimation (KDE) is applied to a grid model of the building to obtain the uncertainty map of the crowds. Based on a two-level spatial model, the logical path represented by a room sequence can be derived from a ’room-door’ network, while detailed path choices on the ’operational’ level are refined in each room. By considering both crowd uncertainty and time cost, path choices for a user are determined by using the A* algorithm at each time slot. By iterating the optimal path to the next door/the target in the current room, the user location of the next moment can be inferred. Our test initially validated the feasibility of the method on the path choices of a pedestrian. In the future, we plan to further conduct field tests with different users in crowded indoor environments.

Efficient Multi-floor Indoor Mapping with A Versatile Rotating LiDAR System

Abstract. Light Detection And Ranging (LiDAR) technology has provided an impactful way to capture 3D environmental map. However, consistent mapping in sensing-degenerated and perceptually-limited scenes (e.g. multi-story buildings) or under high dynamic sensor motion (e.g. rotating platform) remains a significant challenge. To this end, an efficient multi-floor indoor mapping system is proposed in this paper utilizing a versatile rotating LiDAR platform. In the front end, measurements from motor, IMU and LiDAR are tightly integrated to track the fast motion state of system, based on iterative Error State Kalman Filter (ESKF). Then linear and planar features are extracted from the point cloud map voxelized with adaptive resolutions. A sliding-window-based batch optimization is performed to simultaneously optimize the states of local frames with reference to the map consistency. In the experiments, we investigated the influence of rotating speed on the mapping performance as well as the superiority of rotating mechanism when compared to standard LiDAR setup. Moreover, comparative studies with one of the SOTA work, FAST-LIO2, have shown the competitive mapping results in multi-floor indoor environments.