Open data model standards for structural performance monitoring of infrastructure assets

Employing the BIM approach during the operational phase of an infrastructure asset’s life cycle represents the largest opportunity for reducing the total life cycle cost. One aspect of the operation of an infrastructure asset is to monitor its structural performance to ensure safety, for which structural sensors are increasingly being used. Semantically rich as-built BIM models that represent the actual conditions of the constructed assets can improve and quicken the structural performance monitoring of infrastructure assets. Nevertheless, the current open data model standards are not fit for this purpose yet, which greatly reduces the usefulness of the BIM approach during the operational phase of an infrastructure asset. This paper examines the capabilities of existing data model standards and, based on alternative approaches to overcome the lack of current capabilities and a proposed use-case, makes recommendations for possible extensions to the standards. The paper concludes that amendments to current data model standards are needed to enable modelling of complex monitoring systems and appropriate management and visualisation of sensor data.This is the author accepted manuscript. It is currently embargoed pending publication

Design and Data Modelling of Fibre Optic Systems to Monitor Reinforced Concrete Structural Elements

Structural monitoring of built assets, performed to ensure safety, usability, and to better understand the assets’ structural behaviour, is becoming common practice. One method to monitor structural behaviour is to use fibre optic systems to measure temperature and strain in structural elements. Fibre optic systems are relatively inexpensive, easy to install, versatile, and widely applicable. However, all the data acquired by monitoring systems are meaningless if they lack context within the built asset, and they are of little use if they cannot be appropriately exchanged and visualised. This paper presents an extension to the IFC data model standard for structural monitoring systems. The extension allows (1) to model structural monitoring systems, (2) to store and retrieve acquired data, and (3) to visualise the data directly on the BIM model. The James Dyson Building at the University of Cambridge is used as a case study, in which selected reinforced concrete columns, beams, and slabs have been instrumented with two types of fibre optic sensors. The case study demonstrates that the extension is able to fully describe the fibre optic monitoring system and that it can aid in its design, deployment, and further operation.The authors would like to acknowledge funding from the UK Engineering and Physical Sciences Research Council (EPSRC) and Innovate UK. This research was carried out under EPSRC grant no. EP/I019308/1. Acknowledgements also go to several people who contributed to, or facilitated the fibre optic sensor installations in the James Dyson Building: Cedric Kechavarzi, David Rodenas Herráiz, Jason Shardelow, Jules Birks, Pasquale Ponterosso and Peter Knott from CSIC; Greg Smith and Toby Lucas from Morgan Sindall.This is the author accepted manuscript. The final version is available from American Society of Civil Engineers via https://doi.org/10.1061/9780784479827.22

An Architecture for an Infrastructure as a Service for the Internet of Things

Internet of things (IoT) refers to things such as sensors and actuators interacting with each other to reach common goals. It enables multiple applications in sectors ranging from agriculture to health. Nowadays, applications and IoT infrastructure are tightly coupled and this may lead to the deployment of redundant IoT infrastructures, thus, cost inefficiency. Cloud computing can help in tackling the problem. It is a paradigm to quickly provision configured resources (computing, network, memory) on demand for cost efficiency. It has three layers, the infrastructure as a service (IaaS), the platform as a service (PaaS) and the software as a service (SaaS). Through the IaaS, configured hardware resources (CPU, storage, etc.) are provisioned on demand. However, designing and implementing an IoT IaaS architecture for the provisioning of IoT resource on demand remains very challenging. An example of a challenge is using the appropriate publishing and discovery mechanism suitable for IoT devices. Orchestrating a virtualized IoT device over several physical IoT devices is another challenge that needs to be addressed. The main contribution of this thesis is twofold. First, a novel IoT IaaS architecture is proposed where IoT devices can be provisioned as a configured infrastructure resource on demand via node virtualization. Second, the architecture is prototyped and evaluated using real-life sensors that support node virtualization. Node level virtualization achieves resource efficiency in contrast to middleware solutions. The essential architectural features, such as publication, discovery, and orchestration are identified and proposed. Two sets of a high-level interface are also introduced. A low-level uniform interface is suggested to decouple the IoT devices from the applications by allowing the applications to access the heterogeneous devices in a uniform way. In addition, a cloud management interface is proposed to expose the IoT IaaS to the cloud consumers (for example - the PaaS, the application, etc.) and allow them to provision the IoT resources. By allowing the capability sharing of the IoT devices using the node virtualization, the cost efficiency and energy efficiency are achieved in the proposed architecture. Addressing other challenges allowed the proposed architecture to expose the IoT devices to the IaaS in a more abstract manner. Thus allowing the application to provision the IoT resources on demand as well as handling the IoT device heterogeneity in the IaaS

Reference Model for Interoperability of Autonomous Systems

This thesis proposes a reference model to describe the components of an Un-manned Air, Ground, Surface, or Underwater System (UxS), and the use of a single Interoperability Building Block to command, control, and get feedback from such vehicles. The importance and advantages of such a reference model, with a standard nomenclature and taxonomy, is shown. We overview the concepts of interoperability and some efforts to achieve common refer-ence models in other areas. We then present an overview of existing un-manned systems, their history, characteristics, classification, and missions. The concept of Interoperability Building Blocks (IBB) is introduced to describe standards, protocols, data models, and frameworks, and a large set of these are analyzed. A new and powerful reference model for UxS, named RAMP, is proposed, that describes the various components that a UxS may have. It is a hierarchical model with four levels, that describes the vehicle components, the datalink, and the ground segment. The reference model is validated by showing how it can be applied in various projects the author worked on. An example is given on how a single standard was capable of controlling a set of heterogeneous UAVs, USVs, and UGVs

Development of a physical vulnerability model for floods in data-scarce regions: a case study of Nigeria

Knowledge on flood risk, typically originating from data on past hazard, is a key input for developing disaster risk reduction strategies. With the observed increase in frequency and magnitude of flood hazard globally, knowledge on characterizing flood and predicting flood damage is especially important for data-scarce regions, which in many cases are regions with limited capacity to cope with disaster. The objective of this thesis is to develop and test new methods, with reduced data requirement, which can improve characterizing floods and predicting flood damage in data-scarce areas. This overall objective was further divided into three sub-objectives: i) to review existing methods for assessing physical vulnerability to floods and conceptualize a new method for flood damage prediction, ii) to develop and test a hydrodynamic modelling approach to reconstruct a past flood scenario in a data-scare location, and iii) to test the applicability and performance of the new flood damage model and compare its performance to existing methods. Two study regions were selected from Nigeria to test the applicability of the developed methods. Both regions are located in the central part of the country, where small and large rivers are present and fluvial flooding is common. The thesis has contributed to knowledge about the physical vulnerability of buildings to floods in typical data-scarce regions particularly in i) developing a new flood damage prediction method tailored for typical data-scarce areas with a transferable and up-datable framework, and ii) developing a method for increasing sample size of data (flood depth and duration) using hydrodynamic modelling to support physical vulnerability assessments. In addition, the thesis extensively discusses common challenges associated with flood risk assessment in data-scarce areas and suggests recommendations for future studies. The thesis presents one of the first findings for typical buildings in many African countries (sandcrete block and clay buildings) in terms of damage grades classification, identification of main damage drivers, and a model for predicting probable damage. The findings will support decision makers in data-scarce regions to better identify vulnerable buildings and plan for effective risk reduction and mitigation strategies