Monitoring of blood glucose levels, ketones and insulin bolus advice using 4SURE products and app-based technology

With more people being diagnosed with diabetes and requiring insulin therapy as they live longer, an increasing number of individuals are needing access to blood and ketone monitoring that is simple to use and provides accurate results. Having access to a bolus advisor is equally important in order for people with diabetes to calculate accurate insulin doses based on the foods that they are eating. The use of app-based technology for healthcare purposes has increased over recent years and now includes the Diabetes:M application that can be used in conjunction with the 4SURE smart meters with no additional cost to the individual.

Assessing Feature Importance for Short-Term Prediction of Electricity Demand in Medium-Voltage Loads

The design of new monitoring systems for intelligent distribution networks often requires both real-time measurements and pseudomeasurements to be processed. The former are obtained from smart meters, phasor measurement units and smart electronic devices, whereas the latter are predicted using appropriate algorithms—with the typical objective of forecasting the behaviour of power loads and generators. However, depending on the technique used for data encoding, the attempt at making predictions over a period of several days may trigger problems related to the high number of features. To contrast this issue, feature importance analysis becomes a tool of primary importance. This article is aimed at illustrating a technique devised to investigate the importance of features on data deemed relevant for predicting the next hour demand of aggregated, medium-voltage electrical loads. The same technique allows us to inspect the hidden layers of multilayer perceptrons entrusted with making the predictions, since, ultimately, the content of any hidden layer can be seen as an alternative encoding of the input data. The possibility of inspecting hidden layers can give wide support to researchers in a number of relevant tasks, including the appraisal of the generalisation capability reached by a multilayer perceptron and the identification of neurons not relevant for the prediction task.

Determination of Business Intelligence and Analytics-Based Healthcare Facility Management Key Performance Indicators

The use of digital technologies such as Internet of Things (IoT) and smart meters induces a huge data stack in facility management (FM). However, the use of data analysis techniques has remained limited to converting available data into information within activities performed in FM. In this context, business intelligence and analytics (BI&A) techniques can provide a promising opportunity to elaborate facility performance and discover measurable new FM key performance indicators (KPIs) since existing KPIs are too crude to discover actual performance of facilities. Beside this, there is no comprehensive study that covers BI&A activities and their importance level for healthcare FM. Therefore, this study aims to identify healthcare FM KPIs and their importance levels for the Turkish healthcare FM industry with the use of the AHP integrated PROMETHEE method. As a result of the study, ninety-eight healthcare FM KPIs, which are categorized under six categories, were found. The comparison of the findings with the literature review showed that there are some similarities and differences between countries’ FM healthcare ranks. Within this context, differences between countries can be related to the consideration of limited FM KPIs in the existing studies. Therefore, the proposed FM KPIs under this study are very comprehensive and detailed to measure and discover healthcare FM performance. This study can help professionals perform more detailed building performance analyses in FM. Additionally, findings from this study will pave the way for new developments in FM software and effective use of available data to enable lean FM processes in healthcare facilities.

Energy Communities and the Tensions Between Neoliberalism and Communitarianism

The convergent development of (renewable) distributed electricity sources, storage technologies (e.g., batteries), ‘big data’ devices (e.g., sensors, smart meters), and novel ICT infrastructure matching energy supply and demand (smart grids) enables new local and collective forms of energy consumption and production. This socio-technical evolution has been accompanied by the development of citizen energy communities that have been supported by EU energy governance and directives, adopting a political narrative of placing the citizen central in the ongoing energy transition. But to what extent are the ideals that motivate the energy community movement compatible with those of neoliberalism that have guided EU energy policy for the last four decades? Using a framework inspired by Michel Foucault’s idea of governmentality, we analyze the two political forms from three dimensions: ontological, economic and power politics. For the ontological and the economic dimensions, neoliberal governmentality is flexible enough to accommodate the tensions raised by the communitarians. In the dimension of power politics however, the communitarian logic does raise a fundamental challenge to neoliberal governmentality in the sense that it explicitly aims for a redefinition of the ‘common good’ of society’s energy supply based on democratic premises.

Implementation of Load Control for Smart Metering in Smart Grids

The conventional energy meters are not suitable for long operating purposes as they spend much human and material resources. Smart meters, on the other hand, are devices that perform advanced functions including electrical energy consumption recording of residential/industrial users, billing, real-time monitoring, and load balancing. In this chapter, a smart home prototype is designed and implemented. Appliances are powered by the grid during daytime, and a photovoltaic panel stored power during the night or in case of an electricity outage. Second, consumed power from both sources is sensed and further processed for cumulative energy, cost calculations and bill establishment for different proposed scenarios using LABVIEW software. Data are communicated using a USB data acquisition card (DAQ-USB 6008). Finally, a simulation framework using LABVIEW software models four houses each equipped with various appliances. The simulator predicts different power consumption profiles to seek of peak-demand reduction through a load control process.

A METHODOLOGY FOR CYBER HYGIENE IN SMART GRIDS

Although smart grids offer multiple advantages over traditional grids, there are still challenges to overcome to ensure the quality of service and grid security. In particular, cybersecurity plays an essential role in ensuring grid operation reliability and resilience to external threats. The traditional approach to address cybersecurity issues generally does not consider the human factor as the main component. Recently, the concept of cyber hygiene has emerged, where social and human aspects are fundamental to reduce vulnerabilities and the risk of attacks and breaches. In a similar manner to personal hygiene, which greatly influences people’s health, considering the human factor (i.e., human behaviour, awareness, and training) as a critical cybersecurity component, can significantly improve human operator cybersecurity practices that in turn can result in improved cybersecurity performance. In this paper, the authors propose and test a methodology for implementing cyber hygiene practices in the context of Smart Grid systems, focused on smart metering systems. The results suggest that implementing cyber hygiene practices can improve smart meter cybersecurity and be suitable for implementing other sensitive Smart Grid components. Key Words: Cybersecurity, Cyber Hygiene, Internet of Things, Smart Grid, Smart Meters.

IoT Big Data Security, Privacy and Challenges Related to Smart Grid

The highly interconnected network of heterogeneous devices which enables all kinds of communications to take place in an efficient manner is referred to as “IOT.” In the current situation, the data are increasing day by day in size as well as in terms of complexities. These are the big data which are in huge demand in the industrial sectors. Various IT sectors are adopting big data present on IOT for the growth of their companies and fulfilling their requirements. But organizations are facing a lot of security issues and challenges while protecting their confidential data. IOT type systems require security while communications which is required currently by configuration levels of security algorithms, but these algorithms give more priority to functionalities of the applications over security. Smart grids have become one of the major subjects of discussions when the demands for IOT devices increases. The requirements arise related to the generation and transmission of electricity, consumption of electricity being monitored, etc. The system which is responsible to collect heterogeneous data are a complicated structure and some of its major subsystems which they require for smooth communications include log servers, smart meters, appliances which are intelligent, different sensors chosen based on their requirements, actuators with proper and efficient infrastructure. Security measures like collection, storage, manipulations and a massive amount of data retention are required as the system is highly diverse in its architecture and even the heterogeneous IOT devices are interacting with each other. In this article, security challenges and concerns of IOT big data associated with smart grid are discussed along with the new security enhancements for identification and authentications of things in IOT big data environments.

Real-Time Monitoring of Smart Meters Based on Blockchain Technology

In this chapter, the authors primarily discuss how blockchain is being utilized in smarter grids across the globe and how some use cases can be a good fit as a technology. They ensure the reliability and uninterrupted power supply to end users by using smart metering in micro and macro grids, which is possible with novel technology that is transparent and without any cyberattacks/hackers: blockchain technology (BCT). In this chapter, BCT is implemented significantly at micro/macro smart grid network. Such a network would give efficient improvement and be interesting.

Can LTE-A Support Real-Time Smart Meter Traffic in the Smart Grid?

The chapter investigates the scheduling load added on a long-term evolution (LTE) and/or LTE-Advanced (LTEA) network when automatic meter reading (AMR) in advanced metering infrastructures (AMI) is performed using internet of things (IoT) deployments of smart meters in the smart grid. First, radio resource management algorithms to perform dynamic scheduling of the meter transmissions are proposed and shown to allow the accommodation of a large number of smart meters within a limited coverage area. Then, potential techniques for reducing the signaling load between the meters and base stations are proposed and analyzed. Afterwards, advanced concepts from LTE-A, namely carrier aggregation (CA) and relay stations (RSs) are investigated in conjunction with the proposed algorithms in order to accommodate a larger number of smart meters without disturbing cellular communications.