The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe

Gkoumas, Konstantinos; Gkoktsi, Kyriaki; Bono, Flavio; Galassi, Maria Cristina; Tirelli, Daniel

doi:10.3390/infrastructures6030043

Cited by 21 publications

(6 citation statements)

References 71 publications

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“…Nevertheless, smartphone-based and drive-by SHM together with crowdsourcing has huge potential to contribute to bridge damage and deterioration assessments, e.g., detecting scour [ 132 ]. With the MITICA project, there is a significant investment to expand this concept through densely instrumented realistic testbeds [ 133 ]. In realistic environments, it is essential to eliminate the operational effects that can mask damage indicators in modal frequencies [ 134 ] and account for the vehicle properties for the precise removal of vehicular effects distorting indirect bridge data [ 135 ].…”

Section: Drive-by Smartphone Sensing For Bridge Monitoringmentioning

confidence: 99%

Smartphone Prospects in Bridge Structural Health Monitoring, a Literature Review

Ozer,

Kromanis

2024

Sensors

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Bridges are critical components of transportation networks, and their conditions have effects on societal well-being, the economy, and the environment. Automation needs in inspections and maintenance have made structural health monitoring (SHM) systems a key research pillar to assess bridge safety/health. The last decade brought a boom in innovative bridge SHM applications with the rise in next-generation smart and mobile technologies. A key advancement within this direction is smartphones with their sensory usage as SHM devices. This focused review reports recent advances in bridge SHM backed by smartphone sensor technologies and provides case studies on bridge SHM applications. The review includes modelbased and data-driven SHM prospects utilizing smartphones as the sensing and acquisition portal and conveys three distinct messages in terms of the technological domain and level of mobility: (i) vibration-based dynamic identification and damage-detection approaches; (ii) deformation and condition monitoring empowered by computer vision-based measurement capabilities; (iii) drive-by or pedestrianized bridge monitoring approaches, and miscellaneous SHM applications with unconventional/emerging technological features and new research domains. The review is intended to bring together bridge engineering, SHM, and sensor technology audiences with decade-long multidisciplinary experience observed within the smartphone-based SHM theme and presents exemplary cases referring to a variety of levels of mobility.

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Section: Drive-by Smartphone Sensing For Bridge Monitoringmentioning

confidence: 99%

Smartphone Prospects in Bridge Structural Health Monitoring, a Literature Review

Ozer,

Kromanis

2024

Sensors

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“…were the first to suggest using smart vehicles for SHM. Gkoumas et al (2021) replaced the term CAVs for smart-vehicles with the justification that vehicles with autonomy and connectivity could be a better source of data for SHM. However, none of these works introduced a framework for implementing the proposed systems.…”

Section: Drive-by Shmmentioning

confidence: 99%

In‐fleet structural health monitoring of roadway bridges using connected and autonomous vehicles’ data

Shokravi,

Vafaei,

Samali

et al. 2024

Computer aided Civil Eng

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Drive‐by structural health monitoring (SHM) is a cost‐efficient alternative to the direct SHM of short‐ to medium‐size bridges requiring no sensors to be installed on the structure. However, drive‐by SHM is generally known as a short‐term monitoring technique due to the challenges associated with using multiple passages of instrumented vehicles for a long time. This paper proposes combining the potentiality of connected and autonomous vehicles (CAVs) into drive‐by damage detection by introducing In‐Fleet SHM. To the authors’ knowledge, this is the first study that proposes using CAVs for SHM application in civil engineering structures. Each In‐Fleet CAV could automatically collect the vehicle's persistent and temporal data by the embedded sensors and transmit them to edge computing systems for analysis. These persistent data include type and model and temporal parameters encompassing position, speed, heading, and vertical acceleration of CAVs. Knowing the persistent and temporal data of the passing vehicles over the transportation infrastructures enables the identification of the dynamic parameters of the bridge from the vehicles’ vertical acceleration response using drive‐by techniques and, on the other hand, reconstruction of the finite element model of the passing vehicles over the supporting bridges in a near real‐time manner. In contrast to the drive‐by SHM, In‐Fleet monitoring has an expanded spatial and temporal coverage, enabling continuous near real‐time monitoring of highway bridges of the transportation network. The accuracy and resolution of the identified modal components in In‐Fleet SHM are enhanced due to the crowdsensing nature of the collected data. Furthermore, by offering a unique set of characteristics, this method fills the crucial gap in implementing Industry 4.0 technologies and digital twins for SHM of bridges.

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“…According to scientists' conclusions, problems of this kind are solved in the context of the implementation of IT, that is, a self-organizing system and automated logistics, which is provided by intermodal transportation and efficient use of infrastructure in all modes. Road maps of the European Road Transport Research Advisory Council (ERTRAC) emphasize that long-distance and regional freight transport must become even more sustainable, while maintaining transparency and accessibility for users and system participants [21]. However, the real patterns of the development of intercity road freight transportation have not been analyzed.…”

Section: Chaptermentioning

confidence: 99%

Coordination of material and information flows in intercity logistics systems

Oliskevych¹,

Danchuk

Pelo

et al. 2022

Logistics Systems: Technological and Economic Aspects of Efficiency

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The problem of the effectiveness of the use of road transport in logistics systems is considered. Carriers attract additional motor vehicles according to increasing in freight turnover, namely in long-distance routes. The trend of growth in the volume of transportation and the distance of cargo transportation has been maintained in recent years, despite the crisis periods in the economies of the European Union countries. However, the increase in the number of vehicles of fleets is accompanied by an increase in their idle time and delays in the delivery of goods. This phenomenon is explained by the lack of necessary coordination of material flows on the transport network. We considered two types of material flows, namely cargo flows and automobile flows. Both types of flows are discrete in nature. In order to represent the interaction of material flows in the logistics system, the term elementary logistics operation is used, which is the smallest constant element of the logistics chain. Despite the wide variety of processes that occur in logistics systems, the number of typical elementary logistics operations is limited and quite small. For the numerical characterization of material flows, such parameters as a tact, a front, the size of a group of material elements, and the average intensity of the flow are used. Based on the known dependencies between these parameters and taking into account the connections of elementary logistics operations, a structural model of logistics chains is built. It is taken into account that information messages in the logistics system arise when material flows change. The impact of changes in the intensity of cargo flows in logistics chains has been studied and the majority of sources of information messages in space and time have been determined. It has been proven that the use of the objectively necessary amount of information with the necessary advance time makes it possible to reduce dynamic and static delays of cargo flows to a minimum. Due to the fact that changes in the intensity of material flows occur stochastically in logistics chains, the feasibility of assessing the resistance of a given logistics system to external disturbances was developed. The influence of information provision of truck crews performing transport tasks on highway connections is studied. An information support scheme has been developed on the terms of cargo delivery with the need for the truck to arrive at the unloading point on time.

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The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe

Cited by 21 publications

References 71 publications

Smartphone Prospects in Bridge Structural Health Monitoring, a Literature Review

Smartphone Prospects in Bridge Structural Health Monitoring, a Literature Review

In‐fleet structural health monitoring of roadway bridges using connected and autonomous vehicles’ data

Coordination of material and information flows in intercity logistics systems

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