Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification

Detecting faults in electrical power grids is of paramount importance, either from the electricity operator and consumer viewpoints. Modern electric power grids (smart grids) are equipped with smart sensors that allow to gather real-time information regarding the physical status of all the component elements belonging to the whole infrastructure (e.g., cables and related insulation, transformers, breakers and so on). In real-world smart grid systems, usually, additional information that are related to the operational status of the grid itself are collected such as meteorological information. Designing a suitable recognition (discrimination) model of faults in a real-world smart grid system is hence a challenging task. This follows from the heterogeneity of the information that actually determine a typical fault condition. The second point is that, for synthesizing a recognition model, in practice only the conditions of observed faults are usually meaningful. Therefore, a suitable recognition model should be synthesized by making use of the observed fault conditions only. In this paper, we deal with the problem of modeling and recognizing faults in a real-world smart grid system, which supplies the entire city of Rome, Italy. Recognition of faults is addressed by following a combined approach of multiple dissimilarity measures customization and one-class classification techniques. We provide here an in-depth study related to the available data and to the models synthesized by the proposed one-class classifier. We offer also a comprehensive analysis of the fault recognition results by exploiting a fuzzy set based reliability decision rule

A smart driving smartphone application : real-world effects on driving performance and glance behaviours

A smart driving Smartphone application – which offers real-time fuel efficiency and safety feedback to the driver in the vehicle – was evaluated in a real-world driving study. Forty participants drove an instrumented vehicle over a 50 minute mixed route driving scenario, with 15 being selected for video data analysis. Two conditions were adopted, one a control, the other with smart driving advice being presented to the driver. Key findings from the study showed a 4.1% improvement in fuel efficiency when using the smart driving system, and an almost 3-fold reduction in time spent travelling closer than 1.5 seconds to the vehicle in front. Glance behavior results showed that drivers spent an average of 4.3% of their time looking at the system, at an average of 0.43 seconds per glance, with no glances of greater than two seconds. In conclusion this study has shown that a smart driving system specifically developed and designed with the drivers’ information requirements in mind can lead to significant improvements in real-world driving behaviours, whilst limiting visual distraction, with the task being integrated into normal driving

‘Smart Cities’ – Dynamic Sustainability Issues and Challenges for ‘Old World’ Economies: A Case from the United Kingdom

The rapid and dynamic rate of urbanization, particularly in emerging world economies, has resulted in a need to find sustainable ways of dealing with the excessive strains and pressures that come to bear on existing infrastructures and relationships. Increasingly during the twenty-first century policy makers have turned to technological solutions to deal with this challenge and the dynamics inherent within it. This move towards the utilization of technology to underpin infrastructure has led to the emergence of the term ‘Smart City’. Smart cities incorporate technology based solutions in their planning development and operation. This paper explores the organizational issues and challenges facing a post-industrial agglomeration in the North West of England as it attempted to become a ‘Smart City’. In particular the paper identifies and discusses the factors that posed significant challenges for the dynamic relationships residents, policymakers and public and private sector organizations and as a result aims to use these micro-level issues to inform the macro-debate and context of wider Smart City discussions. In order to achieve this, the paper develops a range of recommendations that are designed to inform Smart City design, planning and implementation strategies