scholarly journals An Optimized Propagation Model based on Measurement Data for Indoor Environments

2018 ◽  
Vol 2 ◽  
pp. 69-75 ◽  
Author(s):  
Marco Morocho-Yaguana ◽  
Patricia Ludeña-González ◽  
Francisco Sandoval ◽  
Betty Poma-Vélez ◽  
Alexandra Erreyes-Dota
Keyword(s):  
Measurement Data ◽  
Propagation Model ◽  
Average Error ◽  
Indoor Environments ◽  
University Campus ◽  
Campus Environment ◽  
Loss Parameter ◽  
Indoor Scenarios ◽  
Wireless Communications Systems ◽  
Parameter Values

Propagation is an essential factor ensuring good coverage of wireless communications systems. Propagation models are used to predict losses in the path between transmitter and receiver nodes. They are usually defined for general conditions. Therefore, their results are not always adapted to the behavior of real signals in a specific environment. The main goal of this work is to propose a new model adjusting the loss coefficients based on empirical data, which can be applied in an indoor university campus environment. The Oneslope, Log-distance and ITU models are described to provide a mathematical base. An extensive measurement campaign is performed based on a strict methodology considering different cases in typical indoor scenarios. New loss parameter values are defined to adjust the mathematical model to the behavior of real signals in the campus environment. The experimental results show that the model proposed offers an attenuation average error of 2.5% with respect to the losses measured. In addition, comparison of the proposed model with existing solutions shows that it decreases the average error significantly for all scenarios under evaluation.

scholarly journals An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model

2021 ◽  
Author(s):  
Stefanos Sotirios Bakirtzis ◽  
Jiming Chen ◽  
Kehai Qiu ◽  
Jie Zhang ◽  
Ian Wassell
Keyword(s):  
Measurement Data ◽  
Wireless Channel ◽  
Propagation Model ◽  
Radio Propagation ◽  
Data Driven ◽  
Indoor Environments ◽  
Real World Data ◽  
Propagation Models ◽  
Frequency Bands ◽  
Propagation Modelling

Efficient and realistic indoor radio propagation modelling tools are inextricably intertwined with the design and operation of next generation wireless networks. Machine learning (ML)-based radio propagation models can be trained with simulated or real-world data to provide accurate estimates of the wireless channel characteristics in a computationally efficient way. However, most of the existing research on ML-based propagation models focuses on outdoor propagation modelling, while indoor data-driven propagation models remain site-specific with limited scalability. In this paper we present an efficient and credible ML-based radio propagation modelling framework for indoor environments. Specifically, we demonstrate how a convolutional encoder-decoder can be trained to replicate the results of a ray-tracer, by encoding physics-based information of an indoor environment, such as the permittivity of the walls, and decode it as the path-loss (PL) heatmap for an environment of interest. Our model is trained over multiple indoor geometries and frequency bands, and it can eventually predict the PL for unknown indoor geometries and frequency bands within a few milliseconds. Additionally, we illustrate how the concept of transfer learning can be leveraged to calibrate our model by adjusting its pre-estimate weights, allowing it to make predictions that are consistent with measurement data. <br>

scholarly journals An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model

2021 ◽  
Author(s):  
Stefanos Sotirios Bakirtzis ◽  
Jiming Chen ◽  
Kehai Qiu ◽  
Jie Zhang ◽  
Ian Wassell
Keyword(s):  
Measurement Data ◽  
Wireless Channel ◽  
Propagation Model ◽  
Radio Propagation ◽  
Data Driven ◽  
Indoor Environments ◽  
Real World Data ◽  
Propagation Models ◽  
Frequency Bands ◽  
Propagation Modelling

Efficient and realistic indoor radio propagation modelling tools are inextricably intertwined with the design and operation of next generation wireless networks. Machine learning (ML)-based radio propagation models can be trained with simulated or real-world data to provide accurate estimates of the wireless channel characteristics in a computationally efficient way. However, most of the existing research on ML-based propagation models focuses on outdoor propagation modelling, while indoor data-driven propagation models remain site-specific with limited scalability. In this paper we present an efficient and credible ML-based radio propagation modelling framework for indoor environments. Specifically, we demonstrate how a convolutional encoder-decoder can be trained to replicate the results of a ray-tracer, by encoding physics-based information of an indoor environment, such as the permittivity of the walls, and decode it as the path-loss (PL) heatmap for an environment of interest. Our model is trained over multiple indoor geometries and frequency bands, and it can eventually predict the PL for unknown indoor geometries and frequency bands within a few milliseconds. Additionally, we illustrate how the concept of transfer learning can be leveraged to calibrate our model by adjusting its pre-estimate weights, allowing it to make predictions that are consistent with measurement data. <br>

scholarly journals Performance Evaluation of Particulate Matter and Indoor Microclimate Monitors in University Classrooms under COVID-19 Restrictions

2021 ◽  
Vol 18 (14) ◽  
pp. 7363
Author(s):  
Laurentiu Predescu ◽  
Daniel Dunea
Keyword(s):  
Performance Evaluation ◽  
Particulate Matter ◽  
Air Quality ◽  
Indoor Environment ◽  
Indoor Environments ◽  
University Campus ◽  
Particle Counter ◽  
Thermal Environments ◽  
University Classrooms ◽  
Academic Personnel

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m−3 and PM10 ranged between 30 and 42 μg m−3. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10−4 mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.

Constructing Floor Plan through Smoke Using Ultra Wideband Radar

2021 ◽  
Vol 5 (4) ◽  
pp. 1-29
Author(s):  
Weiyan Chen ◽  
Fusang Zhang ◽  
Tao Gu ◽  
Kexing Zhou ◽  
Zixuan Huo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Low Cost ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Floor Plan ◽  
Construction Methods ◽  
Median Error ◽  
Indoor Scenarios

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

Optimization Model for Parking in the Campus Environment

1996 ◽  
Vol 1564 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Orikaye G. Brown-West
Keyword(s):  
Optimization Model ◽  
Central Business District ◽  
University Campus ◽  
University Administrators ◽  
Campus Planning ◽  
Campus Environment ◽  
Planning And Design ◽  
Site Characteristics ◽  
Business District ◽  
The University

Parking has long been recognized as a major land use problem in campus planning. Anyone who drives an automobile appreciates the difficulties of finding a parking space in areas of intense academic, administrative, student residential, and recreational activities. This shortage of parking spaces near activity centers has worsened as automobile ownership and registration on campus have increased. The problem is more pronounced and the solution more critical on large urban campuses located in or at the periphery of the central business district. An approach to solving the chronic and prevalent parking problem in the campus environment is addressed. An institution-based and evaluative model is introduced as a tool to determine how best to use existing land in the competitive and oftentimes policy-driven university campus environment. Practical solutions that will assist in the proper planning and design of campus parking spaces and facilities are also developed. The optimization model design takes into account the major operational and site characteristics, as well as parameters that traffic engineers and planners consider conducive to optimal parking. The model will help traffic engineers, campus planners, and university administrators maximize land on the university campus. It will also answer the question of what principles should be adopted in the proper planning of facilities for the vehicle at rest within the context of a diminishing campus environment in general and inadequate funding for facilities renewal and maintenance in particular.

scholarly journals INVESTIGATION ON NEED FOR SPECIFIC PROPAGATION MODEL FOR SPECIFIC ENVIRONMENT BASED ON DIFFERENT TERRAIN CHARACTERISTICS

2018 ◽  
Vol 19 (2) ◽  
pp. 90-104
Author(s):  
Jide Julius Popoola ◽  
Akinlolu Adediran Ponnle ◽  
Yekeen Olajide Olasoji ◽  
Samson Adenle Oyetunji
Keyword(s):  
Performance Evaluation ◽  
Field Strength ◽  
Measurement Data ◽  
Propagation Model ◽  
Propagation Loss ◽  
Detailed Knowledge ◽  
Propagation Models ◽  
Radio Stations ◽  
Service Environments ◽  
Terrain Characteristics

ABSTRACT: Owing to their speed of excution as well as their limited reliance on detailed knowledge of the terrain characteristics of the service environments, empirical propagation models have enjoyed general acceptability in the wireless communication research community. However, recent industrial observations show that no single propagation model can best fit all the radio service environments, which led to the hypothesis of specific models for specific environments. In order to scientifically verify this hypothesis, the study presented in this paper investigated the performance of the free space propagation loss (FSPL) model in two different radio environments characterised with different types of obstructions. The investigation was conducted through field strength distribution measurement of two broadcasting radio stations transmitting at 96.5 MHz and 102.3 MHz. The field strength measurement data obtained were analysed. The result of the analysis shows gross disparity between the measured path losses and calculated path losses using FSPL model. The disparity thus necessitates the modification of the FSPL model in order to develop each propagation model for each of the two radio stations employed and their environment. The developed models were then evaluated to ascertain their performances relative to the FSPL model. The performance evaluation results show that the predictions of the developed propagation models vary for each of the two environments. Furthermore, the comparative performance evaluation result of the developed models with similar studies in the literature shows that the developed models perform favourably. The overall result from the developed models confirms the hypothesis that each location requires a specific propagation model for proper radio wave design and quality of signal transmission and reception. ABSTRAK: Kelebihan yang ada pada kelajuan perlaksanaannya dan juga kurang pergantungannya pada butiran terperinci ciri-ciri khusus bentuk rupa bumi di persekitaran servisnya, model penyebaran empirik telah diterima umum dalam komuniti kajian komunikasi tanpa wayar. Walau bagaimanapun, pemerhatian industri terkini menunjukkan tidak ada sebarang model penyebaran yang sesuai bagi semua keadaan servis radio, ini menghala kepada hipotesis keperluan model tertentu pada keadaan servis tertentu. Bagi menentusahkan secara saintifik hipotesis ini, kajian yang dibentangkan dalam kertas ini mengkaji tentang prestasi model kehilangan penyebaran pada ruang bebas (FSPL) dalam dua persekitaran radio berlainan melalui beberapa jenis halangan berbeza. Kajian telah dijalankan ke atas dua stesen radio penyiaran pada frekuensi 96.5 MHz dan 102.3 MHz melalui ukuran sebaran ruang keupayaan. Data ukuran ruang keupayaan telah diperoleh dan dianalisa. Keputusan analisis menunjukkan keputusan tidak seragam yang melampau antara ukuran kehilangan laluan dan pada kiraan model FSPL. Ketidaksamaan ini memungkinkan keperluan mengubah model FSPL bagi membangunkan model penyebaran pada setiap dua radio stesen yang digunakan dan persekitarannya. Model yang dibangunkan ini kemudiannya dinilai bagi mengesahkan prestasinya dengan model FSPL. Keputusan penilaian menunjukkan perbezaan pada jangkaan model penyebaran bagi setiap dua keadaan. Tambahan, keputusan perbandingan model yang dibangunkan dalam karya ini adalah serupa seperti kajian lain yang berkaitan. Secara keseluruhannya model yang dibangunkan ini mengesahkan hipotesis bahawa setiap lokasi memerlukan model penyebaran bagi rekaan gelombang radio yang sesuai dan juga kualiti signal penyebaran dan penerimaan.

scholarly journals Molecular corridors and parameterizations of volatility in the evolution of organic aerosols

2015 ◽  
Vol 15 (19) ◽  
pp. 27877-27915
Author(s):  
Y. Li ◽  
U. Pöschl ◽  
M. Shiraiwa
Keyword(s):  
Organic Compounds ◽  
Molar Mass ◽  
High Resolution Mass Spectrometry ◽  
Measurement Data ◽  
Organic Aerosols ◽  
Indoor Environments ◽  
High Molar Mass ◽  
High Volatility ◽  
Sulfur Containing ◽  
Sulfur Containing Compounds

Abstract. The formation and aging of organic aerosols (OA) proceed through multiple steps of chemical reaction and mass transport in the gas and particle phases, which is challenging for the interpretation of field measurements and laboratory experiments as well as accurate representation of OA evolution in atmospheric aerosol models. Based on data from over 30 000 compounds, we show that organic compounds with a wide variety of functional groups fall into molecular corridors, characterized by a tight inverse correlation between molar mass and volatility. We developed parameterizations to predict the volatility of organic compounds containing oxygen, nitrogen and sulfur from the elemental composition that can be measured by soft-ionization high-resolution mass spectrometry. Field measurement data from new particle formation events, biomass burning, cloud/fog processing, and indoor environments were mapped into molecular corridors to characterize the chemical nature of the observed OA components. We found that less oxidized indoor OA are constrained to a corridor of low molar mass and high volatility, whereas highly oxygenated compounds in atmospheric water extend to high molar mass and low volatility. Among the nitrogen- and sulfur-containing compounds identified in atmospheric aerosols, amines tend to exhibit low molar mass and high volatility, whereas organonitrates and organosulfates follow high O : C corridors extending to high molar mass and low volatility. We suggest that the consideration of molar mass and molecular corridors can help to constrain volatility and particle phase state in the modeling of OA particularly for nitrogen- and sulfur-containing compounds.

Integration of Wireless Technologies in Smart University Campus Environment

2017 ◽  
pp. 405-416 ◽  
Author(s):  
Yaser Khamayseh ◽  
Wail Mardini ◽  
Shadi Aljawarneh ◽  
Muneer Bani Yassein
Keyword(s):  
Online Communication ◽  
Cellular Phone ◽  
University Campus ◽  
Wireless Technologies ◽  
Campus Environment ◽  
Social Collaboration ◽  
System Usability ◽  
Smart Technologies ◽  
Future Work ◽  
Education Process

In this paper, the authors are particularly interested in enhancing the education process by integrating new tools to the teaching environments. This enhancement is part of an emerging concept, called smart campus. Smart University Campus will come up with a new ubiquitous computing and communication field and change people's lives radically by providing systems and devices supported with smart technologies that have the capabilities of rapid respond to changes and circumstances without human interference, and it will be able to learn from these circumstances. This paper presents framework architecture for integrating various types of wireless networks into a smart university campus to enhance communication among students, instructors, and administration. Moreover, the authors study two possible applications to utilize the proposed networking framework: smart identification and social collaboration applications. An essential part to achieve the main principles of smart university campus is the deployment and usage of smart card technologies for identification and payment. Nowadays, there are several types of smart identification cards that support wireless technologies such as RFIDs and NFC. In both types, a card reader can read the card information from a distance. Moreover, in NFC cards, the card is integrated with the user's cellular phone. Social networking services (such as Facebook) facilitate online communication and provide a suitable environment for collaboration among students. As a part of future work, the proposed framework is deployed in the authors' university campus to find out the end-end performance and system usability.

scholarly journals Leveraging Visual Place Recognition to Improve Indoor Positioning with Limited Availability of WiFi Scans

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3657 ◽  
Author(s):  
Michał R. Nowicki ◽  
Piotr Skrzypczyński
Keyword(s):  
Indoor Localization ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Positioning System ◽  
Indoor Environments ◽  
University Campus ◽  
Sources Of Information ◽  
Visual Place Recognition ◽  
Indoor Positioning System

WiFi-based fingerprinting is promising for practical indoor localization with smartphones because this technique provides absolute estimates of the current position, while the WiFi infrastructure is ubiquitous in the majority of indoor environments. However, the application of WiFi fingerprinting for positioning requires pre-surveyed signal maps and is getting more restricted in the recent generation of smartphones due to changes in security policies. Therefore, we sought new sources of information that can be fused into the existing indoor positioning framework, helping users to pinpoint their position, even with a relatively low-quality, sparse WiFi signal map. In this paper, we demonstrate that such information can be derived from the recognition of camera images. We present a way of transforming qualitative information of image similarity into quantitative constraints that are then fused into the graph-based optimization framework for positioning together with typical pedestrian dead reckoning (PDR) and WiFi fingerprinting constraints. Performance of the improved indoor positioning system is evaluated on different user trajectories logged inside an office building at our University campus. The results demonstrate that introducing additional sensing modality into the positioning system makes it possible to increase accuracy and simultaneously reduce the dependence on the quality of the pre-surveyed WiFi map and the WiFi measurements at run-time.

scholarly journals Identification on Formalin Content in Swamp Wastewater: Abdurrab University Campus Environment Case

2018 ◽  
Vol 175 ◽  
pp. 012098
Author(s):  
Wahyu Margi Sidoretno ◽  
Rz Ira oktaviani ◽  
Annisa Fauzana ◽  
Isna Wardaniati
Keyword(s):  
University Campus ◽  
Campus Environment
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