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Special Issue "Sensor Applications on Built Environment"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editor

Prof. Dr. Joan Ramon Casas Rius
E-Mail Website1 Website2
Guest Editor
Civil and Environmental Engineering, Universitat Politecnica de Catalunya (UPC-BarcelonaTECH), 08034 Barcelona, Spain
Interests: bridges; structural safety and reliability; structural health monitoring; dynamic testing; composite materials; inspection and maintenance; fiber optic sensors

Special Issue Information

Dear Colleagues,

The concept of Built Environment refers to those surroundings created by humans and for humans that are to be used for human activity. Therefore, it comprises civil engineering infrastructures ( railways, highways, bridges, dams, pipelines, etc..) to residential and industrials buildings, as well as parks and community gardens. The activities related to built environments range from concept and design to construction and execution and, later , to the maintenance during the expected service life, and, finally, to the demolition and recycling, covering all aspects of the service-life. Monitoring the performance of the built environment encompasses, therefore, three main aspects: monitoring during construction, monitoring during operation, and monitoring at demolition. Performance monitoring, and, more specifically, structural health monitoring (SHM), is based on the real data obtained by sensors deployed in anyone of the three periods of the built asset and compared with a previously defined set of performance goals. Therefore, the proper decisions taken during the construction and the management of the built infrastructure and the accurate life-cycle assessment highly rely on the reliability and the accuracy of the experimental data provided by the sensors. Additionally, the network of sensors should be deployed regarding the optimum location within the asset, aiming to provide the maximum amount of valuable information with the minimum expected cost (Value of Information).   

This Special Issue aims to highlight recent advances in all types of sensors that may be deployed in the built environment and the related techniques that better apply to extracting from them the maximum value of information, which is necessary for a correct life-cycle performance approach. Topics include, but are not limited to, the following:

  • Sensors for the built environment: accuracy, reliability, advantages, and disadvantages
  • Value of Information in the context of Built Environment
  • Case studies of sensors application during construction
  • Case studies of sensors application during service-life
  • Case studies of sensors application during demolition
  • Sensors and life-cycle assessment

Prof. Dr. Joan Ramon Casas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Built Environment
  • Structural Health Monitoring
  • Life-cycle assessment
  • Value of Information
  • Transportation infrastructures
  • Industrial and Residential buildings

Published Papers (7 papers)

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Research

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Article
Modeling Indoor Relative Humidity and Wood Moisture Content as a Proxy for Wooden Home Fire Risk
Sensors 2019, 19(22), 5050; https://0-doi-org.brum.beds.ac.uk/10.3390/s19225050 - 19 Nov 2019
Cited by 6 | Viewed by 972
Abstract
Severe wooden home conflagrations have previously been linked to the combination of very dry indoor climate in inhabited buildings during winter time, resulting in rapid fire development and strong winds spreading the fire to neighboring structures. Knowledge about how ambient conditions increase the [...] Read more.
Severe wooden home conflagrations have previously been linked to the combination of very dry indoor climate in inhabited buildings during winter time, resulting in rapid fire development and strong winds spreading the fire to neighboring structures. Knowledge about how ambient conditions increase the fire risk associated with dry indoor conditions is, however, lacking. In the present work, the moisture content of indoor wooden home wall panels was modeled based on ambient temperature and relative humidity recorded at meteorological stations as the climatic boundary conditions. The model comprises an air change rate based on ambient and indoor (22 °C) temperatures, indoor moisture sources and wood panel moisture sorption processes; it was tested on four selected homes in Norway during the winter of 2015/2016. The results were compared to values recorded by indoor relative humidity sensors in the homes, which ranged from naturally ventilated early 1900s homes to a modern home with balanced ventilation. The modeled indoor relative humidity levels during cold weather agreed well with recorded values to within 3% relative humidity (RH) root mean square deviation, and thus provided reliable information about expected wood panel moisture content. This information was used to assess historic single home fire risk represented by an estimated time to flashover during the studied period. Based on the modelling, it can be concluded that three days in Haugesund, Norway, in January 2016 were associated with very high conflagration risk due to dry indoor wooden materials and strong winds. In the future, the presented methodology may possibly be based on weather forecasts to predict increased conflagration risk a few days ahead. This could then enable proactive emergency responses for improved fire disaster risk management. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Article
A Framework for an Intelligent and Personalized Fire Evacuation Management System
Sensors 2019, 19(14), 3128; https://0-doi-org.brum.beds.ac.uk/10.3390/s19143128 - 16 Jul 2019
Cited by 10 | Viewed by 1409
Abstract
Many research studies have focused on fire evacuation planning. However, because of the uncertainties in fire development, there is no perfect solution. This research proposes a fire evacuation management framework which takes advantage of an information-rich building information modeling (BIM) model and a [...] Read more.
Many research studies have focused on fire evacuation planning. However, because of the uncertainties in fire development, there is no perfect solution. This research proposes a fire evacuation management framework which takes advantage of an information-rich building information modeling (BIM) model and a Bluetooth low energy (BLE)-based indoor real-time location system (RTLS) to dynamically push personalized evacuation route recommendations and turn-by-turn guidance to the smartphone of a building occupant. The risk score (RS) for each possible route is evaluated as a weighted summation of risk level index values of all risk factors for all segments along the route, and the route with the lowest RS is recommended to the evacuee. The system will automatically re-evaluate all routes every 2 s based on the most updated information, and the evacuee will be notified if a new and safer route becomes available. A case study with two testing scenarios was conducted for a commercial office building in Tianjin, China, in order to verify this framework. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Article
A Robust Noise Mitigation Method for the Mobile RFID Location in Built Environment
Sensors 2019, 19(9), 2143; https://0-doi-org.brum.beds.ac.uk/10.3390/s19092143 - 09 May 2019
Cited by 3 | Viewed by 1201
Abstract
The exact location of objects, such as infrastructure, is crucial to the systematic understanding of the built environment. The emergence and development of the Internet of Things (IoT) have attracted growing attention to the low-cost location scheme, which can respond to a dramatic [...] Read more.
The exact location of objects, such as infrastructure, is crucial to the systematic understanding of the built environment. The emergence and development of the Internet of Things (IoT) have attracted growing attention to the low-cost location scheme, which can respond to a dramatic increasing amount of public infrastructure in smart cities. Various Radio Frequency IDentification (RFID)-based locating systems and noise mitigation methods have been developed. However, most of them are impractical for built environments in large areas due to their high cost, computational complexity, and low noise detection capability. In this paper, we proposed a novel noise mitigation solution integrating the low-cost localization scheme with one mobile RFID reader. We designed a filter algorithm to remove the influence of abnormal data. Inspired the sampling concept, a more carefully parameters calibration was carried out for noise data sampling to improve the accuracy and reduce the computational complexity. To achieve robust noise detection results, we employed the powerful noise detection capability of the random sample consensus (RANSAC) algorithm. Our experiments demonstrate the effectiveness and advantages of the proposed method for the localization and noise mitigation in a large area. The proposed scheme has potential applications for location-based services in smart cities. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Article
A Sensing and Monitoring System for Hydrodynamic Flow Based on Imaging and Ultrasound
Sensors 2019, 19(6), 1347; https://0-doi-org.brum.beds.ac.uk/10.3390/s19061347 - 18 Mar 2019
Cited by 7 | Viewed by 1340
Abstract
A built environment, that also includes infrastructures, needs to be taken under control to prevent unexpected modifications, otherwise it could react as a loose cannon. Sensing techniques and technologies can come to the rescue of built environments thanks to their capabilities to monitor [...] Read more.
A built environment, that also includes infrastructures, needs to be taken under control to prevent unexpected modifications, otherwise it could react as a loose cannon. Sensing techniques and technologies can come to the rescue of built environments thanks to their capabilities to monitor appropriately. This article illustrates findings related to monitoring a channel hydrodynamic behavior by means of sensors based on imaging and ultrasound. The ultrasound approach is used here to monitor the height of the water with respect to a maximum limit. Imaging treatment is here proposed to understand the flow velocity under the area to be considered. Since these areas can be covered by trash, an enhanced version of the particle image velocimetry technique has been implemented, allowing the discrimination of trash from water flow. Even in the presence of the total area occupied by trash, it is able to detect the velocity of particles underneath. Rainfall and hydraulic levels have been included and processed to strengthen the study. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Article
Application of a New Geophone and Geometry in Tunnel Seismic Detection
Sensors 2019, 19(5), 1246; https://0-doi-org.brum.beds.ac.uk/10.3390/s19051246 - 12 Mar 2019
Cited by 7 | Viewed by 1889
Abstract
Seismic imaging is the most effective geophysical method and has been extensively implemented to detect potential geological hazards in tunnels during construction. The coupling of geophones and the design of geometry in tunnels are the two major challenges. To ensure successful coupling, a [...] Read more.
Seismic imaging is the most effective geophysical method and has been extensively implemented to detect potential geological hazards in tunnels during construction. The coupling of geophones and the design of geometry in tunnels are the two major challenges. To ensure successful coupling, a high-sensitivity semi-automatic coupling geophone with a broadband was designed. In practice, this geophone is attached with a wheel and two springs. Once inserted into the borehole, an automatic coupling action occurs. This semi-automatic coupling design within the geophone not only guarantees good coupling, but reduces the time and costs usually required to install a traditional geophone. In the use of geophones for tunnel seismic detection, we propose two new two-dimensional (2D) seismic geometries based on the two commonly used geometries. A test to assess the effectiveness of the qualities of imaging from four geometries was completed by comparing the results of the forward modeling of sandwich models. The conclusion is that the larger the horizontal offset of the layout geometry, the higher the resolution of the imaging; the larger the vertical offset, the weaker the mirror image. The vertical offset is limited due to the narrow tunnel condition. Therefore, the mirror effect cannot be entirely eliminated; however, it can be further suppressed by constructing 2D geometry. The two newly proposed 2D geometries caused the imaging arc of the inter-layer, but suppressed the mirror image. The mirror image added a significant number of errors to the data, which could misguide tunnel construction; therefore the new 2D geometries are more reasonable than the two most commonly used. We applied one of the two new 2D geometries that was more practical to an actual project, the Chongqing Jinyunshan Tunnel in China, and acquired high-quality seismic data using two semi-automatic coupling geophones. The detection results were essentially consistent with the excavation conclusions. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Article
Reliability Assessment of Deflection Limit State of a Simply Supported Bridge using vibration data and Dynamic Bayesian Network Inference
Sensors 2019, 19(4), 837; https://0-doi-org.brum.beds.ac.uk/10.3390/s19040837 - 18 Feb 2019
Cited by 3 | Viewed by 1242
Abstract
Structural health monitoring (SHM) has been widely used in all kinds of bridges. It is significant to accurately assess the serviceability and reliability of bridge subjected to severe conditions by SHM technique. Bridge deflection as an essential evaluation index can reflect structural condition [...] Read more.
Structural health monitoring (SHM) has been widely used in all kinds of bridges. It is significant to accurately assess the serviceability and reliability of bridge subjected to severe conditions by SHM technique. Bridge deflection as an essential evaluation index can reflect structural condition perfectly. In this study, an approach for deflection calculation and reliability assessment of simply supported bridge is presented. Firstly, a bridge deflection calculation method is proposed based on modal flexibility and Kriging method improved by artificial bee colony algorithm. Secondly, a dynamic Bayesian network is employed to evaluate the deflection reliability combined with monitoring results which include modal frequency, mode shape, environmental temperature, and humidity. A linear regression model is established to analyze the relationship between modal parameters and environmental factors. Thirdly, a simply supported bridge is constructed and monitored to verify the effectiveness of the proposed method. The results reveal that the proposed method can precisely calculate the bridge deflection. Finally, the time-dependent reliabilities of two cases are computed and the effects of monitoring factors on bridge deflection reliability are analyzed by sensitivity parameter. It indicates that the reliability is negatively correlated with temperature and more sensitive to mode shape than other three factors. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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Review

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Review
A Perspective of Non-Fiber-Optical Metamaterial and Piezoelectric Material Sensing in Automated Structural Health Monitoring
Sensors 2019, 19(7), 1490; https://0-doi-org.brum.beds.ac.uk/10.3390/s19071490 - 27 Mar 2019
Cited by 2 | Viewed by 2115
Abstract
Metamaterials are familiar in life sciences, but are only recently adopted in structural health monitoring (SHM). Even though they have existed for some time, they are only recently classified as smart materials suitable for civil, mechanical, and aerospace (CMA) engineering. There are still [...] Read more.
Metamaterials are familiar in life sciences, but are only recently adopted in structural health monitoring (SHM). Even though they have existed for some time, they are only recently classified as smart materials suitable for civil, mechanical, and aerospace (CMA) engineering. There are still not many commercialized metamaterial designs suitable for CMA sensing applications. On the other hand, piezoelectric materials are one of the popular smart materials in use for about 25 years. Both these materials are non-fiber-optical in nature and are robust to withstand the rugged CMA engineering environment, if proper designs are adopted. However, no single smart material or SHM technique can ever address the complexities of CMA structures and a combination of such sensors along with popular fiber optical sensors should be encouraged. Furthermore, the global demand for miniaturization of SHM equipment, automation and portability is also on the rise as indicated by several global marketing strategists. Recently, Technavio analysts, a well-known market research company estimated the global SHM market to grow from the current US $ 1.48 billion to US $ 3.38 billion by 2023, at a compound annual growth rate (CAGR) of 17.93%. The market for metamaterial is expected to grow rapidly at a CAGR of more than 22% and the market for piezoelectric materials is expected to accelerate at a CAGR of over 13%. At the same time, the global automation and robotics market in the automotive industry is expected to post a CAGR of close to 8%. The fusion of such smart materials along with automation can increase the overall market enormously. Thus, this invited review paper presents a positive perspective of these non-fiber-optic sensors, especially those made of metamaterial designs. Additionally, our recent work related to near field setup, a portable meta setup, and their functionalities along with a novel piezoelectric catchment sensor are discussed. Full article
(This article belongs to the Special Issue Sensor Applications on Built Environment)
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