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Item type:Publication, Access status: with files , Personalized low-cost thermal comfort monitoring using IoT technologiesThermal comfort plays an essential role in the well-being and productivity of occupants. Typically, thermal comfort is assessed either through surveys completed by building occupants or through sensor data that is analyzed using thermal comfort models. Automating comfort surveys and data collection processes reduce the risk of information loss, providing more accurate and personalized thermal comfort assessments over longer periods of time. To this end, this paper presents the design and implementation of a thermal comfort monitoring system consisting of low-cost hardware components and using IoT technologies. The system consists of intelligent wireless sensor nodes that collect and process environmental data, a portable main station that integrates and stores data, and a digital survey that provides feedback from building occupants. To ensure accuracy, the low-cost hardware components of the intelligent sensor nodes are calibrated in a climate chamber, using high-precision sensors for reference. After calibration, the system is deployed in a field test where several intelligent sensor nodes collect environmental data in an office, while occupants complete the digital thermal comfort survey. In addition, thermal comfort indexes are computed by the intelligent sensor nodes and compared with the feedback of each building occupant. The results indicate that the low-cost thermal comfort monitoring system successfully collects and integrates thermal comfort data from the intelligent sensor nodes and the digital survey, being able to create personalized thermal comfort profiles. In future work, the system can be used in large-scale thermal comfort surveys, to develop personalized thermal comfort models and to control personalized comfort systems.Publicationtype: Journal Article10 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A systematic survey of Internet of Things frameworks for smart city applicationsRecent developments in smart sensing technologies have fostered the wide-spread utilization of smart city applications, which rely on Internet of Things (IoT) frameworks to work efficiently. The terms “smart city” and “IoT framework”, however, have been given several definitions, without consensus. Consequently, definitions of the terms “smart city” and “IoT framework” need to be condensed, consolidating concepts and guidelines of smart cities and IoT frameworks, as will be shown in this study. In addition, a systematic survey of IoT frameworks for smart city applications is presented, summarizing and comparing the technologies and architectures of IoT frameworks for smart city applications. As a result of this study, trends in IoT frameworks for smart city applications and a definition of the term “smart city” are provided. Materializing the findings achieved in this study, an abstract IoT framework concept for smart city applications is proposed. It is expected that the definition of the term “smart city” may be used as a basis for a generally accepted formal definition and that the proposed IoT framework concept may provide a strong foundation for successful IoT framework implementations in the context of smart city applications.Publicationtype: Journal Article98 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A metamodel for cyber-physical systems(2019-08); ; With the advent of the Internet of Things and Industry 4.0 concepts, cyber-physical systems in civil engineering experience an increasing impact on structural health monitoring (SHM)and control applications. Designing, optimizing, and documenting cyber-physical system on a formal basis require platform-independent and technology-independent metamodels. This study, with emphasis on communication in cyber-physical systems, presents a metamodel for describing cyber-physical systems. First, metamodeling concepts commonly used in computing in civil engineering are reviewed and possibilities and limitations of describing communication-related information are discussed. Next, communication-related properties and behavior of distributed cyber-physical systems applied for SHM and control are explained, and system components relevant to communication are specified. Then, the metamodel to formally describe cyber-physical systems is proposed and mapped into the Industry Foundation Classes (IFC), an open international standard for building information modeling (BIM). Finally, the IFC-based approach is verified using software of the official IFC certification program, and it is validated by BIM-based example modeling of a prototype cyber-physical system, which is physically implemented in the laboratory. As a result, cyber-physical systems applied for SHM and control are described and the information is stored, documented, and exchanged on the formal basis of IFC, facilitating design, optimization, and documentation of cyber-physical systems.Publicationtype: Journal Article76 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automated wireless structural health monitoring and control using tuned liquid column dampers(2019-06); ; Current trends in structural design and retrofit frequently dictate artificially modifying the structural behavior in an attempt to target unfavorable loading scenarios expected to compromise the fulfilment of stability and serviceability criteria. Particularly in structures where operational requirements result in adopting unconventional structural systems, usually falling outside the scope of codified regulations and guidelines, adapting the structural behavior by means of structural subsystems has been widespread. Referred to as “structural control”, enhancing the ability of structures to adapt to unfavorable loading conditions encompasses attaching structural subsystems, such as dampers, to the main structure. Moreover, the increasing application of structural health monitoring (SHM) for structural assessment and maintenance has fueled research in coupling SHM with structural control, thus paving the way for developing structural systems capable of autonomously adapting structural properties. In this context, this paper describes a preliminary approach to automated structural health monitoring and control by coupling a wireless SHM system with a tuned liquid column damper (TLCD). The wireless SHM system is equipped with embedded algorithms managing SHM tasks, such as data sampling and data processing, and with actuators able to modify the properties of the TLCD based on any user-defined control algorithm. The proposed approach serves as a first step towards fully automated structural health monitoring and control and is validated through laboratory tests on a four-story shear frame structure equipped with a wireless SHM system and a TLCD on the top story.Publicationtype: Conference Paper54 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , IFC Monitor – An IFC schema extension for modeling structural health monitoring systems(2018-08); The pervasive emergence of sensing technologies for structural health monitoring (SHM) and the digitalization ubiquitous in engineering (“Industry 4.0”) pose increasing demands on information modeling concepts in civil engineering. While in building information modeling (BIM) conventional building information (such as geometry, material, or cost) can precisely be described using current modeling standards, information about SHM systems, referred to as “monitoring-related information” cannot be fully described on a well-defined, formal basis. In this paper, a BIM-based approach towards describing monitoring-related information is proposed, using the Industry Foundation Classes (IFC), an open BIM standard facilitating the interoperability of BIM models, as a formal basis. First, possibilities and constraints of describing monitoring-related information with the IFC schema are discussed. Then, information necessary to describe SHM systems is integrated into a semantic model serving as a technology-independent metamodel. Next, the IFC schema is extended to enable BIM-based descriptions of SHM systems in compliance with IFC modeling capabilities, which is referred to as “IFC Monitor” schema. The IFC Monitor schema is verified with test software used in the official IFC certification program. For validation, a prototype SHM system is formally described using the IFC Monitor schema. The validation aims at checking if the IFC Monitor schema is capable of precisely describing monitoring-related information. As will be shown in this paper, the description of the prototype SHM system meets the requirements of a well-defined IFC model as specified in the official IFC certification program. As a result, the IFC Monitor schema proposed in this study advances BIM-based descriptions of SHM systems in association with structural systems being monitored on a well-defined, formal basis.Publicationtype: Journal Article151 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Decentralized infrastructure health monitoring using embedded computing in wireless sensor networksDue to the significant risk posed to public safety by infrastructure ageing and deterioration, infrastructure health monitoring has been drawing increasing research interest in recent years. In the field of infrastructure health monitoring, wireless sensor networks have become particularly popular, because of their cost efficiency, flexibility, and reduced installation time as compared to conventional wired systems. Using embedded computing, it is possible to process the collected data directly on the wireless sensor nodes, thus reducing the wireless communication and the power consumption. In this paper, a methodology to fully decentralize the condition assessment process is presented. The paper showcases the development of embedded algorithms and numerical models to be embedded into the wireless sensor nodes, i.e. the monitored structure is divided into substructures where each sensor node is responsible for monitoring one substructure. The proposed methodology is validated through simulations on a numerical model of a four-story shear frame structure. The objective of the simulations is to test the performance of the algorithms and the quality of the numerical models embedded into the wireless sensor nodes with respect to decentralized condition assessment, taking into consideration the effects of external factors, such as ambient noise, that usually interfere with measured data.Publicationtype: Journal Article27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring(2016-03); System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. The entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.Publicationtype: Conference Paper31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A decentralized approach towards autonomous fault detection in wireless structural health monitoring systems(2014-07); Sensor faults in wireless structural health monitoring (SHM) systems may reduce the monitoring quality and, if remaining undetected, might cause substantial economic loss due to inaccurate or missing sensor data required for structural assessment and lifecycle management of the monitored structure. Usually, fault detection in sensor networks is achieved through a redundant deployment of sensors and further hardware components ("physical redundancy"), which involves considerable penalties in cost and maintainability. Overcoming these drawbacks, in this study the information inherent in the SHM system and the known relationships between the sensors are used for fault detection without the need for additional sensors ("analytical redundancy"). Furthermore, the analytical redundancy approach is implemented in a fully decentralized manner: Partial models of the SHM system, being embedded directly into the wireless sensor nodes, enable each sensor node to autonomously detect sensor faults in real time while efficiently using the limited computing resources.Publicationtype: Conference Paper30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Agricultural ecosystem monitoring based on autonomous sensor systems(2013-12-06)More than two-thirds of freshwater consumed worldwide are used for irrigation, and large quantities of freshwater can be saved by improving the efficiency of irrigation systems. Irrigation control systems deployed in agriculture can substantially be enhanced by implementing intelligent monitoring techniques enabling automated sensing and continuous analyses of actual soil parameters. Automatically scheduling irrigation events based on soil moisture measurements has been proven an effective means to reduce freshwater consumption and irrigation costs, while maximizing the crop yield. Focusing on decentralized autonomous soil moisture monitoring, this paper presents the design, the implementation, and the validation of a low-cost remote monitoring system for agricultural ecosystems. The prototype monitoring system consists of a number of intelligent wireless sensor nodes that are distributed in the observed environment. The sensor nodes are connected to an Internet-enabled computer system, which is installed on site for disseminating relevant soil information and providing remote access to the monitoring system. Autonomous software programs, labeled "mobile software agents", are embedded into the wireless sensor nodes to continuously analyze the soil parameters and to autonomously trigger irrigation events based on the actual soil conditions and on weather data integrated from external sources.Publicationtype: Conference Paper14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A migration-based approach towards resource-efficient wireless structural health monitoringWireless sensor networks have emerged as a complementary technology to conventional, cable-based systems for structural health monitoring. However, the wireless transmission of sensor data and the on-board execution of engineering analyses directly on the sensor nodes can consume a significant amount of the inherently restricted node resources. This paper presents an agent migration approach towards resource-efficient wireless sensor networks. Autonomous software agents, referred to as "on-board agents", are embedded into the wireless sensor nodes employed for structural health monitoring performing simple resource-efficient routines to continuously analyze, aggregate, and communicate the sensor data to a central server. Once potential anomalies are detected in the observed structural system, the on-board agents autonomously request for specialized software programs ("migrating agents") that physically migrate to the sensor nodes to analyze the suspected anomaly on demand. In addition to the localized data analyses, a central information pool available on the central server is accessible by the software agents (and by human users), facilitating a distributed-cooperative assessment of the global condition of the monitored structure. As a result of this study, a 95% reduction of memory utilization and a 96% reduction of power consumption of the wireless sensor nodes have been achieved as compared with traditional approaches.Publicationtype: Journal Article35