Event-based information-theoretic privacy: A case study of smart meters

Author(s):  
Shuo Han ◽  
Ufuk Topcu ◽  
George J. Pappas
2015 ◽  
Vol 3 (2) ◽  
pp. 55
Author(s):  
Norol Hamiza Zamzuri ◽  
Khairil Wahidin Awang ◽  
Yuhanis Abdul Aziz ◽  
Zaiton Samdin

The growth of the event sector is underpinned by the demand of organizing a business event.  Thus, it leads to an increase in economic and social impact. However, the problems from the growth of this sector potentially results from the use of several event materials, transportation and infrastructure development.  Organizing a green event is seen as one of the strategies to reduce the environmental impact.  Therefore, the aim of this paper is to explore the issues involved throughout the process of greening an event by applying Mair and Jago Model.  Semi-structured interviews were conducted with event managers from six Malaysia business event companies that encourage green practices during their event.  Findings suggest that impact, initiative, support and performance motivates event organizers in organizing a green event.  It has also been found that knowledge, resources and behaviour are the barriers faced by event organizers throughout the process of organizing a green event.  Based on the findings it appears that two important factors have emerged from the data collection and analysis that showed a deviation from the Mair and Jago Model, namely “impact” for the motivation element and “support” for the barrier element.  The main limitation of this study was the scope of the study; as it only focuses on business events.  However, as the main purpose of this study is to explore the issues of organizing a green event, it has been found that there are other issues need to be explored in other contexts and geographical area.  Apart from this, as this is a case study, it can only replicate according to the circumstances of this case study. However, this study can be generalized in terms of the theory that has emerged from it.  It is suggested that further research should explore more issues in other contexts and geographical areas. 


2021 ◽  
Vol 18 (2) ◽  
pp. 172988142199958
Author(s):  
Larkin Folsom ◽  
Masahiro Ono ◽  
Kyohei Otsu ◽  
Hyoshin Park

Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different bimodal probability distributions or introduce bias toward one mode of a bimodal probability distribution. The use of a standard deviation (SD) metric reduces bias while retaining the ability to distinguish between higher and lower risk distributions. Areas of high SD can be safely explored through observation with an autonomous Mars Helicopter allowing safer and faster path plans for ground-based rovers. First, this study presents a single-agent information-theoretic utility-based path planning method for a highly correlated uncertain environment. Then, an information-theoretic two-stage multiagent rapidly exploring random tree framework is presented, which guides Mars helicopter through regions of high SD to reduce uncertainty for the rover. In a Monte Carlo simulation, we compare our information-theoretic framework with a rover-only approach and a naive approach, in which the helicopter scouts ahead of the rover along its planned path. Finally, the model is demonstrated in a case study on the Jezero region of Mars. Results show that the information-theoretic helicopter improves the travel time for the rover on average when compared with the rover alone or with the helicopter scouting ahead along the rover’s initially planned route.


2021 ◽  
Vol 13 (2) ◽  
pp. 693
Author(s):  
Elnaz Azizi ◽  
Mohammad T. H. Beheshti ◽  
Sadegh Bolouki

Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The proposed algorithm (i) filters power signals and accurately detects all events; (ii) extracts specific features of appliances, such as operation modes and their respective power intervals, from their power signals in the training dataset; and (iii) labels with high accuracy each detected event of the aggregated signal with an appliance mode transition. The algorithm is validated using REDD with the results showing its effectiveness to accurately disaggregate low-frequency measured data by existing smart meters.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.


Entropy ◽  
2018 ◽  
Vol 20 (7) ◽  
pp. 534 ◽  
Author(s):  
Hector Zenil ◽  
Narsis Kiani ◽  
Jesper Tegnér

We introduce a definition of algorithmic symmetry in the context of geometric and spatial complexity able to capture mathematical aspects of different objects using as a case study polyominoes and polyhedral graphs. We review, study and apply a method for approximating the algorithmic complexity (also known as Kolmogorov–Chaitin complexity) of graphs and networks based on the concept of Algorithmic Probability (AP). AP is a concept (and method) capable of recursively enumerate all properties of computable (causal) nature beyond statistical regularities. We explore the connections of algorithmic complexity—both theoretical and numerical—with geometric properties mainly symmetry and topology from an (algorithmic) information-theoretic perspective. We show that approximations to algorithmic complexity by lossless compression and an Algorithmic Probability-based method can characterize spatial, geometric, symmetric and topological properties of mathematical objects and graphs.


Geosciences ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 437 ◽  
Author(s):  
Meena ◽  
Tavakkoli Piralilou

Despite landslide inventories being compiled throughout the world every year at different scales, limited efforts have been made to critically compare them using various techniques or by different investigators. Event-based landslide inventories indicate the location, distribution, and detected boundaries of landslides caused by a single event, such as an earthquake or a rainstorm. Event-based landslide inventories are essential for landslide susceptibility mapping, hazard modeling, and further management of risk mitigation. In Nepal, there were several attempts to map landslides in detail after the Gorkha earthquake. Particularly after the main event on 25 April 2015, researchers around the world mapped the landslides induced by this earthquake. In this research, we compared four of these published inventories qualitatively and quantitatively using different techniques. Two principal methodologies, namely the cartographical degree of matching and frequency area distribution (FAD), were optimized and applied to evaluate inventory maps. We also showed the impact of using satellite imagery with different spatial resolutions on the landslide inventory generation by analyzing matches and mismatches between the inventories. The results of our work give an overview of the impact of methodology selection and outline the limitations and advantages of different remote sensing and mapping techniques for landslide inventorying.


Author(s):  
Éric Piel ◽  
Alberto González ◽  
Hans-Gerhard Gross

Publish/subscribe systems are event-based systems separated into several components which publish and subscribe events that correspond to data types. Testing each component individually is not sufficient for testing the whole system; it also requires testing the integration of those components together. In this chapter, first we identify the specificities and difficulties of integration testing of publish/subscribe systems. Afterwards, two different and complementary techniques to test the integration are presented. One is based on the random generation of a high number of event sequences and on generic oracles, in order to find a malfunctioning state of the system. The second one uses a limited number of predefined data-flows which must respect a precise behaviour, implementable with the same mechanism as unit-testing. As event-based systems are well fitted for runtime modification, the particularities of runtime testing are also introduced, and the usage in the context of integration testing is detailed. A case study presents an example of integration testing on a small system inspired by the systems used in the maritime safety and security domain.


Author(s):  
Federico Cabitza ◽  
Carla Simone

In this article, we present WOAD, a framework that was inspired and partly validated within a 2-year observational case study at a major teaching hospital. We present the WOAD framework by stating its main and motivating rationales, outlining its high-level architecture and then introducing its denotational language, LWOAD. We propose LWOAD to support users of an electronic document system in declaratively expressing, specifying and implementing content- and event-based mechanisms that fulfill coordinative requirements and make users aware of relevant conditions. Our focus addresses (a) the user-friendly and yet formal expression of local coordinative practices based on the work context; (b) the promotion of awareness of both these conventions and the context to enable actors to quickly respond; (c) the full deployment of coordination-oriented and context-aware functionalities into legacy electronic document systems. We give examples of LWOAD mechanisms taken from the case study and discuss their impact from the EUD perspective.


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