Software architecture knowledge for intelligent light maintenance

The maintenance management plays an important role in the monitoring of business activities. It ensures a certain level of services in industrial systems by improving the ability to function in accordance with prescribed procedures. This has a decisive impact on the performance of these systems in terms of operational efficiency, reliability and associated intervention costs. To support the maintenance processes of a wide range of industrial services, a knowledge-based component is useful to perform the intelligent monitoring. In this context we propose a generic model for supporting and generating industrial lights maintenance processes. The modeled intelligent approach involves information structuring and knowledge sharing in the industrial setting and the implementation of specialized maintenance management software in the target information system. As a first step we defined computerized procedures from the conceptual structure of industrial data to ensure their interoperability and effective use of information and communication technologies in the software dedicated to the management of maintenance (E-candela). The second step is the implementation of this software architecture with specification of business rules, especially by organizing taxonomical information of the lighting systems, and applying intelligencebased operations and analysis to capitalize knowledge from maintenance experiences. Finally, the third step is the deployment of the software with contextual adaptation of the user interface to allow the management of operations, editions of the balance sheets and real-time location obtained through geolocation data. In practice, these computational intelligence-based modes of reasoning involve an engineering framework that facilitates the continuous improvement of a comprehensive maintenance regime

Urban flood impact assessment: A state-of-the-art review

Copyright © 2013 Taylor & Francis. This is an Author's Accepted Manuscript of an article published in Urban Water Journal (2013), available online at: http://www.tandfonline.com/10.1080/1573062X.2013.857421There is another ORE record for this publication: http://hdl.handle.net/10871/31595Flooding can cause major disruptions in cities, and lead to significant impacts on people, the economy and on the environment. These impacts may be exacerbated by climate and socio-economic changes. Resilience thinking has become an important way for city planners and decision makers to manage flood risks. Despite different definitions of resilience, a consistent theme is that flood resilient cities are impacted less by extreme flood events. Therefore, flood risk professionals and planners need to understand flood impacts to build flood resilient cities. This paper presents a state-of-the-art literature review on flood impact assessment in urban areas, detailing their application, and their limitations. It describes both techniques for dealing with individual categories of impacts, as well as methodologies for integrating them. The paper will also identify future avenues for progress in improving the techniques.Research on the CORFU (Collaborative research on flood resilience in urban areas) project was funded by the European Commission through Framework Programme

Urban vulnerability assessment: Advances from the strategic planning outlook

[EN] Urban strategic planning and urban vulnerability assessment have increasingly become important issues in both policy agenda and academia. However, a comprehensive review of the advances made in urban vulnerability, emphasizing their shared aspects, has yet to be performed. The aiming of this paper is to addresses the latter by conducting an evaluation on assessment methods disclosed in this decade. Once their common evolutive pathway is traced, the review follows an analytical framework, based on the above, evaluating the research requirements from both a quantitative and qualitative point of view. Our findings indicate that the robustness, cognitive and participatory research lines are those in which most advancement has been made, while those of urban dynamics and multi-scale progressed the least. Our analysis also demonstrates that methods integrating more lines of research, as well as the employment of comprehensive approaches, promotes advancing the developmental stage. We conclude that the focusing of research lines should be shifted, in order to bridge the qualitative gap identified without demanding an improbable, quantitative increase.The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R).Salas, J.; Yepes, V. (2018). Urban vulnerability assessment: Advances from the strategic planning outlook. Journal of Cleaner Production. 179:544-558. https://doi.org/10.1016/j.jclepro.2018.01.088S54455817

Critical Infrastructure Protection Approaches: Analytical Outlook on Capacity Responsiveness to Dynamic Trends

Overview: Critical infrastructures (CIs) – any asset with a functionality that is critical to normal societal functions, safety, security, economic or social wellbeing of people, and disruption or destruction of which would have a very significant negative societal impact. CIs are clearly central to the normal functioning of a nation’s economy and require to be protected from both intentional and unintentional sabotages. It is important to correctly discern and aptly manage security risks within CI domains. The protection (security) of CIs and their networks can provide clear benefits to owner organizations and nations including: enabling the attainment of a properly functioning social environment and economic market, improving service security, enabling integration to external markets, and enabling service recipients (consumers, clients, and users) to benefit from new and emerging technological developments. To effectively secure CI system, firstly, it is crucial to understand three things - what can happen, how likely it is to happen, and the consequences of such happenings. One way to achieve this is through modelling and simulations of CI attributes, functionalities, operations, and behaviours to support security analysis perspectives, and especially considering the dynamics in trends and technological adoptions. Despite the availability of several security-related CI modelling approaches (tools and techniques), trends such as inter-networking, internet and IoT integrations raise new issues. Part of the issues relate to how to effectively (more precisely and realistically) model the complex behavior of interconnected CIs and their protection as system of systems (SoS). This report attempts to address the broad goal around this issue by reviewing a sample of critical infrastructure protection approaches; comprising tools, techniques, and frameworks (methodologies). The analysis covers contexts relating to the types of critical infrastructures, applicable modelling techniques, risk management scope covered, considerations for resilience, interdependency, and policy and regulations factors. Key Findings: This research presents the following key findings: 1. There is not a single specific Critical Infrastructure Protection (CIP) approach – tool, technique, methodology or framework – that exists or emerges as a ‘fit-for-all’; to allow the modelling and simulation of cyber security risks, resilience, dependency, and impact attributes in all critical infrastructure set-ups. 2. Typically, two or more modelling techniques can be (need to be) merged to cover a broader scope and context of modelling and simulation applications (areas) to achieve desirable highlevel protection and security for critical infrastructures. 3. Empirical-based, network-based, agent-based, and system dynamics-based modelling techniques are more widely used, and all offer gains for their use. 4. The deciding factors for choosing modelling techniques often rest on; complexity of use, popularity of approach, types and objectives of user Organisation and sector. 5. The scope of modelling functions and operations also help to strike the balance between ‘specificity’ and ‘generality’ of modelling technique and approach for the gains of in-depth analysis and wider coverage respectively. 6. Interdependency and resilience modelling and simulations in critical infrastructure operations, as well as associated security and safety risks; are crucial characteristics that need to be considered and explored in revising existing or developing new CIP modelling approaches. Recommendations: Key recommendations from this research include: 1. Other critical infrastructure sectors such as emergency services, food & agriculture, and dams; need to draw lessons from the energy and transportation sectors for the successive benefits of: i. Amplifying the drive and efforts towards evaluating and understanding security risks to their infrastructure and operations. ii. Support better understanding of any associated dependencies and cascading impacts. iii. Learning how to establish effective security and resilience. iv. Support the decision-making process linked with measuring the effectiveness of preparedness activities and investments. v. Improve the behavioural security-related responses of CI to disturbances or disruptions. 2. Security-related critical infrastructure modelling approaches should be developed or revised to include wider scopes of security risk management – from identification to effectiveness evaluations, to support: i. Appropriate alignment and responsiveness to the dynamic trends introduced by new technologies such as IoT and IIoT. ii. Dynamic security risk management – especially the assessment section needs to be more dynamic than static, to address the recurrent and impactful risks that emerge in critical infrastructures

Soil-related geohazard assessment for climate-resilient UK infrastructure

UK (United Kingdom) infrastructure networks are fundamental for maintaining societal and economic wellbeing. With infrastructure assets predominantly founded in the soil layer (< 1.5m below ground level) they are subject to a range of soil-related geohazards. A literature review identified that geohazards including, clay-related subsidence, sand erosion and soil corrosivity have exerted significant impacts on UK infrastructure to date; often resulting in both long-term degradation and ultimately structural failure of particular assets. Climate change projections suggest that these geohazards, which are themselves driven by antecedent weather conditions, are likely to increase in magnitude and frequency for certain areas of the UK through the 21st century. Despite this, the incorporation of climate data into geohazard models has seldom been undertaken and never on a national scale for the UK. Furthermore, geohazard risk assessment in UK infrastructure planning policy is fragmented and knowledge is often lacking due to the complexity of modelling chronic hazards in comparison to acute phenomenon such as flooding. With HM Government's recent announcement of £50 million planned infrastructure investment and capital projects, the place of climate resilient infrastructure is increasingly pertinent. The aim of this thesis is therefore to establish whether soil-related geohazard assessments have a role in ensuring climate-resilient UK infrastructure. Soil moisture projections were calculated using probabilistic weather variables derived from a high-resolution version of the UKCP09 (UK Climate Projections2009) weather generator. These were then incorporated into a geohazard model to predict Great Britain's (GB) subsidence hazard for the future scenarios of 2030 (2020-2049) and 2050 (2040-2069) as well as the existing climatic baseline (1961-1990). Results suggest that GB is likely to be subject to increased clay-related subsidence in future, particularly in the south east of England. This thesis has added to scientific understanding through the creation of a novel, national-scale assessment of clay subsidence risk, with future assessments undertaken to 2050. This has been used to help create a soil- informed maintenance strategy for improving the climate resilience of UK local roads, based on an extended case study utilising road condition data for the county of Lincolnshire, UK. Finally, a methodological framework has been created, providing a range of infrastructure climate adaptation stakeholders with a method for incorporating geohazard assessments, informed by climate change projections, into asset management planning and design of new infrastructure. This research also highlights how infrastructure networks are becoming increasingly interconnected, particularly geographically, and therefore even minor environmental shocks arising from soil-related geohazards can cause significant cascading failures of multiple infrastructure networks. A local infrastructure hotspot analysis methodology and case-study is provided

Disaster risk management of interdependent infrastructure systems for community resilience planning

This research focuses on developing methodologies to model the damage and recovery of interdependent infrastructure systems under disruptive events for community resilience planning. The overall research can be broadly divided into two parts: developing a model to simulate the post-disaster performance of interdependent infrastructure systems and developing decision frameworks to support pre-disaster risk mitigation and post-disaster recovery planning of the interdependent infrastructure systems towards higher resilience. The Dynamic Integrated Network (DIN) model is proposed in this study to simulate the performance of interdependent infrastructure systems over time following disruptive events. It can consider three different levels of interdependent relationships between different infrastructure systems: system-to-system level, system-to-facility level and facility-to-facility level. The uncertainties in some of the modeling parameters are modeled. The DIN model first assesses the inoperability of the network nodes and links over time to simulate the damage and recovery of the interdependent infrastructure facilities, and then assesses the recovery and resilience of the individual infrastructure systems and the integrated network utilizing some network performance metrics. The recovery simulation result from the proposed model is compared to two conventional models, one with no interdependency considered, and the other one with only system-level interdependencies considered. The comparison results suggest that ignoring the interdependencies between facilities in different infrastructure systems would lead to poorly informed decision making. The DIN model is validated through simulating the recovery of the interdependent power, water and cellular systems of Galveston City, Texas after Hurricane Ike (2008). Implementing strategic pre-disaster risk mitigation plan to improve the resilience of the interdependent infrastructure systems is essential for enhancing the social security and economic prosperity of a community. Majority of the existing infrastructure risk mitigation studies or projects focus on a single infrastructure system, which may not be the most efficient and effective way to mitigate the loss and enhance the overall community disaster resilience. This research proposes a risk-informed decision framework which could support the pre-disaster risk mitigation planning of several interdependent infrastructure systems. The characteristics of the Interdependent Infrastructure Risk Mitigation (IIRM) decision problem, such as objective, decision makers, constraints, etc., are clearly identified. A four-stage decision framework to solve the IIRM problem is also presented. The application of the proposed IIRM decision framework is illustrated using a case study on pre-disaster risk mitigation planning for the interdependent critical infrastructure systems in Jamaica. The outcome of the IIRM problem is useful for the decision makers to allocate limited risk mitigation budget or resources to the most critical infrastructure facilities in different systems to achieve greater community disaster resilience. Optimizing the post-disaster recovery of damaged infrastructure systems is essential to alleviate the adverse impacts of natural disasters to communities and enhance their disaster resilience. As a result of infrastructure interdependencies, the complete functional restoration of a facility in one infrastructure system relies on not only the physical recovery of itself, but also the recovery of the facilities in other systems that it depends on. This study introduces the Interdependent Infrastructure Recovery Planning (IIRP) problem, which aims at optimizing the assignment and scheduling of the repair teams for an infrastructure system with considering the repair plan of the other infrastructure systems during the post-disaster recovery phase. Key characteristics of the IIRP problem are identified and a game theory-based IIRP decision framework is presented. Two recovery time-based performance metrics are introduced and applied to evaluate the efficiency and effectiveness of the post-disaster recovery plan. The IIRP decision framework is illustrated using the interdependent power and water systems of the Centerville virtual community subjected to seismic hazard