Indoor Sites Research Articles

Deep learning-based computer vision in project management: Automating indoor construction progress monitoring

Progress monitoring is crucial for effective project management, particularly in construction projects. The adoption of computer vision with deep learning expedites automation, accuracy, and efficiency in construction progress monitoring by overcoming the challenges of laborious, and error prone manual methods. While there is growing attention on developing computer vision based deep learning models for construction progress monitoring, deployment platforms for project managers are lacking. Using computer vision, this study develops a Mask Recurrent Convolutional Neural Network deep learning model. It utilizes progress images of drywall construction from two indoor construction sites and tests the model on a third indoor site in Sydney, Australia. The model is capable of automated as-built visual detection and work-in-progress measurement. The study also provides an understanding on the deployment process of the deep learning model on a cloud-based platform called Streamlit. By developing a model tailored for automatically quantifying work-in-progress of indoor construction elements and detailing the process of deploying that model on a cloud-based platform, this study significantly advances digitalization of construction project management. Project managers, stand to benefit from these advancements by gaining access to more accurate and automated construction progress monitoring for better decision-making.

A Disaster Response Complex for training of emergency responders in the Northwest United States.

The Disaster Response Complex (DRC) is a year-round training complex that specializes in training emergency responders in realistic indoor and outdoor environments. The outdoor site is comprised of 3 acres of secured customizable space for various exercises. The indoor site is designed to include an indoor facility with a full-size city street, complete with storefronts and motor vehicles that can be configured for emergency response training exercises, and a train or subway station where mockups of derailments can be simulated. The DRC includes large parking areas to accommodate multiple vehicles, allowing trainees the space needed to set up equipment and tactical operations. In addition, a campus office space is also available for an off-site operations center.

Harmful Risk of Bioaerosol Pollution at Major Indoor Sites of a Summer Campus in Guilin City

Bioaerosols are a potential risk of infection in densely populated indoor sites at university campuses. In this study, indoor bioaerosols from the canteen, classroom, and dormitory on campus were sampled and analyzed in the summer of 2021 to investigate the harmful risk. The results showed that bacteria are the predominant microbes, and the total number of bacteria detected in the classroom during no lesson in the morning (33% of samples) and in the canteen during meal times (55% of samples) was greater than the World Health Organization’s recommended value (1000 CFU/m3). The ranges of respirable bioaerosol (<3.3 µm) contributions in the classroom, dormitory, and canteen were 50–75%, 57–70%, and 64–80%, respectively. Bacteroidetes and Firmicutes were the most dominant phyla in all three indoor environments, with a relative abundance of both above 20%. At the family level, Muribaculaceae, Lachnospiraceae, and Bacteroidaceae had high relative abundance in all indoor sites. Some of the microbes carried by bioaerosols were conditionally pathogenic bacteria, such as Micrococcaceae and Enterococcaceae, which may have a harmful risk of causing various inflammatory infections. The results of this study provide basic data to improve indoor environments and control indoor bioaerosol pollution on campus.

Environmental factors and particle size shape the community structure of airborne total and pathogenic bacteria in a university campus.

Given the dense population on university campuses, indoor and outdoor airborne bacterial contamination may lead to the rapid spread of diseases in a university environment. However, there are few studies of the characteristics of airborne and pathogenic bacterial communities in different sites on a university campus. In this study, we collected particulate matter samples from indoor and outdoor locations at a university in Bengbu City, Anhui Province, China, and analyzed the community characteristics of airborne and pathogenic bacteria using a high-throughput sequencing technique. The results showed that the composition of the dominant airborne and pathogenic bacterial communities was consistent among sites at the phylum and genus levels, with differences in their relative abundance. There were significant differences in the structure of the airborne and pathogenic bacterial communities between indoor and outdoor sites (p < 0.05). An analysis of similarities (ANOSIM) indicated that the structure of airborne bacterial communities in indoor sites was influenced by the room occupancy rate, ventilation conditions, and the extent of indoor furnishing (p < 0.05), while the structure of pathogenic bacterial communities was influenced by the number of individuals and spatial dimensions (p < 0.05). The impact of particle size on the structure of airborne and pathogenic bacterial communities was relatively minor. A total of 194 suspected pathogenic bacterial species were identified, accounting for 0.0001-1.3923% of the total airborne bacteria, all of which were conditional pathogens. Among them, Saccharopolyspora rectivirgula, Acinetobacter johnsonii, and Moraxella osloensis exhibited relatively high relative abundance, accounting for 24.40, 16.22, and 8.66% of the total pathogenic bacteria, respectively. Moreover, 18 emerging or re-emerging pathogenic bacterial species with significant implications for human health were identified, although their relative abundance was relatively low (0.5098%). The relative abundance of pathogenic bacteria in indoor environments was significantly higher than outdoors, with the laboratory and dormitory having the highest levels. The findings of this study provide valuable guidance for the prevention and control of airborne bacterial contamination and the associated health risks in both a campus environment and other public spaces with high occupancy rates.

Compact rover surveying and laser scanning for BIM development.

This paper presents a custom made small rover based surveying, mapping and building information modeling solution. Majority of the commercially available mobile surveying systems are larger in size which restricts their maneuverability in the targeted indoor vicinities. Furthermore their functional cost is unaffordable for low budget projects belonging to developing markets. Keeping in view these challenges, an economical indigenous rover based scanning and mapping system has developed using orthogonal integration of two low cost RPLidar A1 laser scanners. All the instrumentation of the rover has been interfaced with Robot Operating System (ROS) for online processing and recording of all sensorial data. The ROS based pose and map estimations of the rover have performed using Simultaneous Localization and Mapping (SLAM) technique. The perceived class 1 laser scans data belonging to distinct vicinities with variable reflective properties have been successfully tested and validated for required structural modeling. Systematically the recorded scans have been used in offline mode to generate the 3D point cloud map of the surveyed environment. Later the structural planes extraction from the point cloud data has been done using Random Sampling and Consensus (RANSAC) technique. Finally the 2D floor plan and 3D building model have been developed using point cloud processing in appropriate software. Multiple interiors of existing buildings and under construction indoor sites have been scanned, mapped and modelled as presented in this paper. In addition, the validation of the as-built models have been performed by comparing with the actual architecture design of the surveyed buildings. In comparison to available surveying solutions present in the local market, the developed system has been found faster, accurate and user friendly to produce more enhanced structural results with minute details.

GPS-Aided Automatic Site Survey Method for WiFi RTT-Based Positioning

The fine timing measurement protocol defined in the IEEE 802.11-2016 standard leads to precise ranging between WiFi devices. However, because the locations of WiFi access points (APs) are required for locating mobile devices, a site survey must be performed prior to the deployment of positioning services, which is extremely time-consuming. This paper studies an automated site survey method that utilize the global positioning system (GPS) and built-in sensors in mobile devices. When a user enters an indoor site from outside, the outside trajectory is obtained using GPS and built-in sensors, and the indoor trajectory can be estimated solely relying on the sensor measurements. Thereafter, the locations of APs can be determined using the ranging results obtained at multiple positions on the estimated indoor trajectory. The experimental results revealed that the difference in average positioning error obtained using the estimated and perfect AP locations was 30 cm different from the error using perfect AP locations

Urban Soundscape: White-vented Myna choruses on Zhongqing road

Urbanization has impacted both humans and birds, and certain bird species, like the white-vented myna choruses on Zhongqing Road, have adapted to human-dominated environments. A study in April 2023 utilized cameras and sound level meters to document this phenomenon. Two phases were conducted: the first phase recorded white-vented mynas' departure and return times at dawn and dusk, along with the sound pressure level of birdsong. The second phase measured indoor sound pressure levels during peak birdsong at nearby buildings. Additionally, a questionnaire assessed people's perception of the bird choruses. Results indicated that birdsong at dawn had a lower sound pressure level (68.8 dBA) compared to dusk (75.4dBA), but it persisted longer. The dominant frequency was around 3150 Hz. Three out of four indoor sites exceeded the regulatory standard of 60 dBA. The questionnaire showed that over 75% of nearby residents disliked the bird choruses, while 18% of passersby found them interesting and potentially attractive for visitation. In conclusion, urban bird choruses can impact indoor acoustic environments and lead to negative perceptions among residents. This study aimed to provide quantitative data and insights into residents' listening impressions of bird choruses on Zhongqing Road, offering valuable reference data for stakeholders.

Measuring the impact of COVID-19 on heritage sites in the UK using social media data

The COVID-19 pandemic has had a profound impact on almost all aspects of society. Cultural heritage sites, which are deeply intertwined with the tourism industry, are no exception. The direct impacts of the virus on the population, as well as indirect impacts, such as government-mandated measures including social distancing, face coverings, and frequent temporary closures of sites, have greatly impacted visitor experiences at heritage sites. To quantitatively evaluate the impact of these measures from the perspective of visitors, we collected 1.4 millions visitor reviews from the Google Maps platform for 775 heritage sites. We analyzed visiting rates using the number of online reviews as a proxy and adopt state-of-the-art natural language processing techniques to more deeply understand visitor perception of preventive measures put in place to control the spread of COVID-19. Our findings reveal that even if visitor focus on COVID-19 has significantly decreased, there may still be notable difference between actual and expected number of reviews, suggesting that visitor involvement (e.g., number of visitors) for cultural heritage sites, especially urban indoor sites, needs more time to recover. Our findings further show that most comments by visitors to sites were associated with negative sentiment toward restricted access, but recognized the necessity of other safeguarding measures (e.g., social distancing and the requirement for face coverings). Moreover, they exhibited negative sentiment towards staff or other visitors who did not adhere to these measures. We make specific recommendations for heritage sites to adapt to the COVID-19 pandemic and a more general observation that the method used to gather information from online reviews in this paper will be effective in measuring visitor perceptions towards specific aspects of heritage sites, particularly in capturing changes in perception before and after unexpected or disruptive events at heritage sites.

Effects of nature on restorative and cognitive benefits in indoor environment

This study investigates the effects of natural exposure in an indoor environment on restorative quality and cognitive ability. Thirty participants were shown nature at three different indoor sites: baseline, indoor (some vegetation), and semi-indoor (a large amount of vegetation and view to sky) for five minutes. After viewing, they completed an assessment of restoration and a cognitive task, and their electroencephalography (EEG) was recorded. Compared to the baseline, the sites with nature resulted in restorative (higher perceived restoration scores) and cognitive (higher working memory performance and lower delta-to-theta ratio (DTR), delta-to-alpha ratio (DAR), theta-to-beta ratio (TBR), and alpha-to-beta ratio (ABR) responses) benefits. These findings further our understanding of the effects of exposure to nature on restorative and cognitive benefits in an indoor environment, and help to build guidance for future research on the effects of nature indoors and designing restorative- and cognitive-enhancing indoor spaces.

Automatic Site Survey for RSS-Based Wi-Fi Positioning Using Unlabeled Data

Preparing a database of Wi-Fi access points (APs) is essential for deploying Wi-Fi-based positioning solutions. This study proposes an automated method to discover APs installed in an indoor site by exploiting unlabeled data provided by mobile users. Furthermore, the positions of these APs are estimated by comparing the shapes of two trajectories, which are obtained using the provided Wi-Fi and sensor data. The effectiveness of the proposed method is verified with excessive experimental campaigns, including an extreme case scenario, where the positions of 60 APs are obtained from only three APs with known positions.

Microplastics in Australian indoor air: Abundance, characteristics, and implications for human exposure

Studies on airborne microplastics (AMPs) have reported higher abundance of AMPs in indoor air compared to outdoors. Most people spend more time indoors compared to outdoors, and it is therefore important to identify and quantify AMPs in indoor air to understand human exposure to AMPs. This exposure can vary among different individuals as they spend their time in different locations and different activity levels, and thus experience different breathing rates. In this study, AMPs ranging from 20–5000 μm were sampled across different indoor sites of Southeast Queensland using an active sampling technique. The highest indoor MP concentration was observed at a childcare site (2.25 ± 0.38 particles/m3), followed by an office (1.20 ± 0.14 particles/m3) and a school (1.03 ± 0.40 particles/m3). The lowest indoor MP concentration was observed inside a vehicle (0.20 ± 0.14 particles/m3), comparable to outdoor concentrations. The only shapes observed were fibers (98%) and fragments. MP fibers ranged from 71 to 4950 μm in length. Polyethylene terephthalate was the prominent polymer type at most sites. Using our measured airborne concentrations as inhaled air concentrations, we calculated the annual human exposure levels to AMPs using scenario-specific activity levels. Males between the ages of 18 to 64 were calculated to have the highest AMP exposure at 3187 ± 594 particles/year, followed by males ≥65 years at 2978 ± 628 particles/year. The lowest exposure of 1928 ± 549 particles/year was calculated for females between the ages of 5 to 17. This study provides the first report on AMPs for various types of indoor locations where individuals spend most of their time. Considering acute, chronic, industrial, and individual susceptibility, more detailed human inhalation exposure levels to AMPs should be estimated for a realistic appraisal of the human health risk, including how much of the inhaled particles are exhaled. SynopsisLimited research exists on the occurrence and the associated human exposure levels to AMPs in indoor locations where people spend most of their time. This study reports on the occurrence of AMPs at indoor locations and associated exposure levels using scenario-specific activity levels.

Perception-Aware Tag Placement Planning for Robust Localization of UAVs in Indoor Construction Environments

Tag-based visual-inertial localization is a lightweight method for enabling autonomous data collection missions of low-cost unmanned aerial vehicles (UAVs) in indoor construction environments. However, finding the optimal tag configuration (i.e., number, size, and location) on dynamic construction sites remains challenging. This work proposes a perception-aware genetic algorithm-based tag placement planner (PGA-TaPP) to determine the optimal tag configuration using four-dimensional (4D) building information models (BIM), considering the project progress, safety requirements, and UAV’s localizability. The proposed method provides a 4D plan for tag placement by maximizing the localizability in user-specified regions of interest (ROIs) while limiting the installation costs. Localizability is quantified using the Fisher information matrix (FIM) and encapsulated in navigable grids. The experimental results show the effectiveness of our method in finding an optimal 4D tag placement plan for the robust localization of UAVs on under-construction indoor sites.

Field Validation of a Public Health Particulate Matter (PHPM) Low‐Cost PM2.5 Monitor and Commercial Sensors with Light Scattering Technology

Low‐cost PM2.5 sensors are the key to creating high‐resolution monitoring networks for localized reporting and increased public awareness. A low‐cost PM2.5 sensor using light‐scattering technology Public Health Particulate Matter (PHPM) was developed and validated against measurements from a commercial device that reports real‐time aerosol concentration and also collects gravimetric samples (DustTrak DRX Aerosol Monitor 8533). Linear regression of measurements from a controlled indoor site and three ambient air sites found that the novel PM2.5 sensor correlated well with the measured PM2.5 concentrations (r ≥ 0.90) at the three ambient air locations with PM2.5 concentrations ranging from 48 to 602 μg/m3 measured at 30‐minute intervals. The correlation was lower (r = 0.71) at the chamber, which used incense as a particulate matter source. The PHPM data of PM2.5 concentrations was using multiply with 2.33. The hope is that the PHPM device can provide an additional tool for participatory in community and increased public awareness about PM2.5 in Thailand. This PHPM device is more suitable for ambient air than the chamber. The PHPM device is inexpensive, portable, and can be charged with a power bank.

A deep learning-based approach to facilitate the as-built state recognition of indoor construction works

PurposeRecognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.Design/methodology/approachThe one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.FindingsThe DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.Originality/valueThis study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

Seasonal occurrence, concentrations, and occupational exposure to VMSs in different environments of a WWTP

In the present study, indoor and outdoor environments of a wastewater treatment plant (WWTP) were monitored by passive air samplers to assess the presence and seasonal trends of three linear (L3-L5) and four cyclic (D3-D6) volatile methylsiloxanes (VMSs). Furthermore, passive sampling rates (PSRs) were estimated from literature values to calculate VMSs air concentrations and occupational exposure to potentially toxic (D4-D6) congeners. Results showed a seasonal pattern of VMSs in outdoor locations (especially in the aeration tank and preliminary treatment), being the highest levels of total VMSs reached in Summer and the lowest in Spring, caused by the confluence of changing weather conditions and VMSs consumption patterns. This seasonality was not found in indoor sites. The congener profiles of VMSs were consistent throughout the year, showing a prevalence of D5 outdoors, and of D3 and D4 in strictly indoor environments. Different sources of VMSs, together with an air filtering system installed in the sampled buildings explain these differences. Estimated PSRs yielded lower values indoors (0.16–0.21 m3/day) than outdoors (0.32–0.49 m3/day), due to different wind speeds. Overall, outdoor locations showed higher VMSs concentrations in air than indoors. However, the values detected in both environments (∑VMSs between 8.00 and 2000 ng/m3) were within the ranges described in the literature for these locations. The occupational exposure to D4-D6 estimated for three different activities in the WWTP showed the highest values for Maintenance Technicians (8010 ± 722 ng/(kg·year)) and the lowest for Laboratory Technicians (5410 ± 874 ng/(kg·year)), in direct correlation with the higher amount of time spent outdoors by the former. In any case, the exposure was below the inhalation threshold of 150 μg/(kg·day) proposed as safe by other authors.

Composite Nano-Calcium-Based Material for Reinforcement and Protection of Earthen Ruins in Humid Environment

China is an ancient civilization. History has left us with a rich cultural heritage, of which ancient cultural sites account for a large proportion. As far as the current scientific research and technology are concerned, due to the particularity and complexity of the humid environment, the protection of ancient cultural sites in the humid environment is still an important topic before us. The research topic involved in this article is about the application of composite nano-calcium-based materials for the reinforcement and protection of soil sites in humid environments. Combined with the development of the research content of this article, the research thinking of the thesis is also adjusted accordingly, making the analysis and solution of the problem clearer. The first is a conceptual study, expounding the relevant concepts in this article. The main purpose is to sort out and study the reinforcement and protection measures and methods of relevant sites and ancient cultural sites, as well as the classification, characteristics, and protection value of ancient cultural sites. Through the analysis and research of these aspects, the composite nano-calcium bases for ancient cultural sites in the subsequent humid environment is proposed based on material basic information. The second is a descriptive research, qualitative and quantitative analysis of humid environment. On the basis of summarizing previous researches, this paper mainly conducts qualitative and quantitative analysis on the judgment of humid environment, the influence mechanism on ancient cultural sites, and the main diseases. Then, it is analytical research, studying the main diseases and causes of the underground palace site in the engineering case, and it is concluded that it is mainly affected by the combined effect of the characteristics of the site’s soil and the environment. Through the collection of data from the site survey, field test, and indoor experiment of the underground palace site, the preservation status of the site is collected, and the disease problems faced by the site were analyzed, making it more difficult to protect. The main problem facing the protection of soil relics in humid environment, that is, the research focus, is the research on the development and applicability of reinforcement protection materials. This article attempts to explore the protective effect of composite nano-calcium-based materials on wet sites. Practical research was conducted to verify the feasibility of composite nano-calcium-based materials in practice through indoor site soil simulation. After the completion of a series of experiments, the applicability and compatibility of the composite nano-calcium-based material to strengthen the wet site soil was verified through data analysis, data collection, and mechanism discussion. The experimental results show that the sample with a solid content of 0.4% composite nano-calcium matrix has better salt and alkali resistance. Moreover, the unconfined compressive strength growth rate of 0.4% of the samples has a qualitative improvement over other solid content samples.

Concrete Urban Refugia forCulex quinquefasciatus, Impact of Summer Stressors, and Strategies Adopted to Oversummer

We carried out vector surveillance to locate adult sites of Culex quinquefasciatus, a filarial vector, during the summer in North Campus, Delhi University, Delhi, India. It revealed that the adults were a rare sight but landed naturally and assembled in indoor sites during the peak summer in 2016 and 2019. New adults repopulated some of these sites, after the removal of the samples. These adults were used to study the impact of summer stressors on their morphological, physiological, and behavioral traits, and strategies followed to oversummer in the urban environment. Adults adopted endophily, vagility, and staying at a lower height as strategies to avoid lethality. Females outnumbered the males, and showed morphological, physiological, and behavioral consequences; the majority were unfed. In females, sublethal effects such as aberrations of body parts including mouthparts; distorted oviposition pattern, reduced fecundity, and precocious tanning of retained eggs; and reduced egg hatch rate contributed to reduced survival and reduced reproductive output, thereby reducing vector load during peak summer. These are novel findings. Source reduction of adults during this period would provide effective eco-friendly control of this established species and should be part of the vector management strategies so that swarms of adults during monsoon could be prevented.

Sensor-Aided Learning for Wi-Fi Positioning With Beacon Channel State Information

Because each indoor site has its own radio propagation characteristics, a site survey process is essential to optimize a Wi-Fi ranging strategy for range-based positioning solutions. This study examines an unsupervised learning technique that autonomously learns an optimal ranging strategy for each site using Wi-Fi and sensor data accumulated while users access a positioning application. Using the collected sensor data, the device trajectory is regenerated, and a Wi-Fi ranging module is optimized to generate the shape of the estimated trajectory using Wi-Fi, similar to that obtained from sensors. In this process, the ranging module learns the way to identify the channel conditions from each Wi-Fi access point (AP) and produces ranging results accordingly. Furthermore, we collect the channel state information (CSI) from beacon frames to investigate the benefit of using CSI in addition to received signal strength measurements. With the CSI, the ranging module can identify diverse channel conditions from each AP and more accurately generate the reliability of each distance estimate to achieve accurate positioning results. The effectiveness of the proposed learning technique is verified using a real-time positioning application implemented on a PC platform.

Validation of a Model for Estimating Individual External Dose Based on Ambient Dose Equivalent and Life Patterns

Background: After the Fukushima Daiichi Nuclear Power Station (FDNPS) accident, a model was developed to estimate the external exposure doses for residents who were expected to return to their homes after evacuation orders were lifted. However, the model’s accuracy and uncertainties in parameters used to estimate external doses have not been evaluated.Materials and Methods: The model estimates effective doses based on the integrated ambient dose equivalent (H*(10)) and life patterns, considering a dose reduction factor to estimate the indoor H*(10) and a conversion factor from H*(10) to the effective dose. Because personal dose equivalent (Hp(10)) has been reported to agree well with the effective dose after the FDNPS accident, this study validates the model’s accuracy by comparing the estimated effective doses with Hp(10). The Hp(10) and life pattern data were collected for 36 adult participants who lived or worked near the FDNPS in 2019.Results and Discussion: The estimated effective doses correlated significantly with Hp(10); however, the estimated effective doses were lower than Hp(10) for indoor sites. A comparison with the measured indoor H*(10) showed that the estimated indoor H*(10) was not underestimated. However, the Hp(10) to H*(10) ratio indoors, which corresponds to the practical conversion factor from H*(10) to the effective dose, was significantly larger than the same ratio outdoors, meaning that the conversion factor of 0.6 is not appropriate for indoors due to the changes in irradiation geometry and gamma spectra. This could have led to a lower effective dose than Hp(10).Conclusion: The estimated effective doses correlated significantly with Hp(10), demonstrating the model’s applicability for effective dose estimation. However, the lower value of the effective dose indoors could be because the conversion factor did not reflect the actual environment.

Performance of a Live Multi-Gateway LoRaWAN and Interference Measurement across Indoor and Outdoor Localities

Little work has been reported on the magnitude and impact of interference with the performance of Internet of Things (IoT) applications operated by Long-Range Wide-Area Network (LoRaWAN) in the unlicensed 868 MHz Industrial, Scientific, and Medical (ISM) band. The propagation performance and signal activity measurement of such technologies can give many insights to effectively build long-range wireless communications in a Non-Line of Sight (NLOS) environment. In this paper, the performance of a live multi-gateway in indoor office site in Glasgow city was analysed in 26 days of traffic measurement. The indoor network performances were compared to similar performance measurements from outdoor LoRaWAN test traffic generated across Glasgow Central Business District (CBD) and elsewhere on the same LoRaWAN. The results revealed 99.95% packet transfer success on the first attempt in the indoor site compared to 95.7% at the external site. The analysis shows that interference is attributed to nearly 50 X greater LoRaWAN outdoor packet loss than indoor. The interference measurement results showed a 13.2–97.3% and 4.8–54% probability of interfering signals, respectively, in the mandatory Long-Range (LoRa) uplink and downlink channels, capable of limiting LoRa coverage in some areas.