A smart ink for the assessment of low activity photocatalytic surfaces

The azo dye, basic blue 66 (BB66) is used in a photocatalyst activity indicator ink (paii) to assess the activity of low activity photocatalytic surfaces, such as commercial photocatalytic tiles and silicone contaminated self-cleaning glass. The BB66 paii is shown to respond much faster than a previously reported, resazurin (Rz) based paii, i.e. the use of a BB66 paii on low activity self-cleaning tiles was found to be >6 times faster than the Rz paii. The BB66 paii is also shown to be effective at assessing the activity of piece of commercial self-cleaning glass contaminated with a coating of silicone, on which the Rz ink, in contrast, failed to show any significant change in colour over the same time period.

Smart, Reusable labels for assessing self-cleaning films

Novel, reversible (reusable) photocatalyst activity indicator labels, which undergo a rapid colour change when in contact with a photocatalytic film via the photoreduction of methylene blue contained within the label’s adhesive, are explored as a method for assessing the activity of self-cleaning glass in situ and the laboratory, using digital photography.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

Towards a Cyber-physical Resilience Framework for Smart Grids

As modern power grids move towards becoming a smart grid, there is an increasing reliance on the data that is transmitted and processed by ICT systems. This reliance introduces new digital attack vectors. Many of the proposed approaches that aim to address this problem largely focus on applying well-known ICT security solutions. However, what is needed are approaches that meet the complex concerns of the smart grid as a cyber-physical system. Furthermore, to support the automatic control loops that exist in a power grid, similarly automatic security and resilience mechanisms are needed that rely on minimal operator intervention. The research proposed in this paper aims to develop a framework that ensures resilient smart grid operation in light of successful cyber-attacks.

Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

Cybersecurity Test-Bed for IEC 61850 based Smart Substations

With the development and deployment of IEC 61850 based smart substations, cybersecurity vulnerabilities of supervisory control and data acquisition (SCADA) systems are increasingly emerging. In response to the emergence of cybersecurity vulnerabilities in smart substations, a test-bed is indispensable to enable cybersecurity experimentation. In this paper, a comprehensive and realistic cyber-physical test-bed has been built to investigate potential cybersecurity vulnerabilities and the impact of cyber-attacks on IEC 61850 based smart substations. This test-bed is close to a real production type environment, and has the ability to carry out end-to-end testing of cyber-attacks and physical consequences. A fuzz testing approach is proposed for detecting IEC 61850 based intelligent electronic devices (IEDs) and validated in the proposed test-bed.

Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

Smart inks as photocatalytic activity indicators of self-cleaning paints

Smart inks as a redox indicators of photocatalytic activity were applied on several paints with acrylic and silicate binder exposed to accelerated weathering test. The results show, that self-cleaning paints need some weathering to develop full photocatalytic activity. On the other side weathering may negatively influence the durability of the paint as shown for a silicate based exterior paint, which was significantly degraded after 350 h of weathering test. Smart inks proved to be suitable and rapid indicators of paint photoactivity. Resazurin ink is convenient only for unexposed paint with low photocatalytic activity while an Acid Violet 7 ink was appropriate for most of the paints, especially those that were weathered

Intrinsically flexible electronic materials for smart device applications

A novel method to fabricate chemically linked conducting polymer–biopolymer composites that are intrinsically flexible and conducting for functional electrode applications is presented. Polypyrrole was synthesised in situ during the cellulose regeneration process using the 1-butyl-3-methylimidazolium chloride ionic liquid as a solvent medium. The obtained polypyrrole–cellulose composite was chemically blended and showed flexible polymer properties while retaining the electronic properties of a conducting polymer. Addition of an ionic liquid such as trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, enhanced the flexibility of the composite. The functional application of these materials in the electrochemically controlled release of a model drug has been demonstrated. This strategy opens up a new design for a wide spectrum of materials for smart electronic device applications wherein the functionality of doping and de-doping of conducting polymers is retained and their processability issue is addressed by exploiting an ionic liquid route.

Threat Analysis of BlackEnergy Malware for Synchrophasor based Real-time Control and Monitoring in Smart Grid

The BlackEnergy malware targeting critical infrastructures has a long history. It evolved over time from a simple DDoS platform to a quite sophisticated plug-in based malware. The plug-in architecture has a persistent malware core with easily installable attack specific modules for DDoS, spamming, info-stealing, remote access, boot-sector formatting etc. BlackEnergy has been involved in several high profile cyber physical attacks including the recent Ukraine power grid attack in December 2015. This paper investigates the evolution of BlackEnergy and its cyber attack capabilities. It presents a basic cyber attack model used by BlackEnergy for targeting industrial control systems. In particular, the paper analyzes cyber threats of BlackEnergy for synchrophasor based systems which are used for real-time control and monitoring functionalities in smart grid. Several BlackEnergy based attack scenarios have been investigated by exploiting the vulnerabilities in two widely used synchrophasor communication standards: (i) IEEE C37.118 and (ii) IEC 61850-90-5. Specifically, the paper addresses reconnaissance, DDoS, man-in-the-middle and replay/reflection attacks on IEEE C37.118 and IEC 61850-90-5. Further, the paper also investigates protection strategies for detection and prevention of BlackEnergy based cyber physical attacks.