Detailed Case Studies

Wireless body area networks (WBANs) are one of the key technologies that support the development of pervasive health monitoring (remote patient monitoring systems), which has attracted more attention in recent years. These WBAN applications requires stringent security requirements as they are concerned with human lives. In the recent scenario of the corona pandemic, where most of the healthcare providers are giving online services for treatment, DDoS attacks become the major threats over the internet. This chapter particularly focusses on detection of DDoS attack using machine learning algorithms over the healthcare environment. In the process of attack detection, the dataset is preprocessed. After preprocessing the dataset, the cleaned dataset is given to the popular classification algorithms in the area of machine learning namely, AdaBoost, J48, k-NN, JRip, Random Committee and Random Forest classifiers. Those algorithms are evaluated independently and the results are recorded. Results concluded that J48 outperform with accuracy of 99.98% with CICIDS dataset and random forest outperform with accuracy of 99.917, but it takes the longest model building time. Depending on the evaluation performance the appropriate classifier is selected for further DDoS detection at real-time

Decentralized data management privacy-aware framework for positive energy districts

Energy Transition (ET) needs actors to perform independent actions on multiple levels of governance. These actors may need to write and read their data, and at the same time they want to protect their data from unauthorized access. This is particularly the case for positive energy districts (PED), a growing trend in the EU that requires actors to perform, write and read operations on a neighborhood scale where governance competences are typically absent. This paper presents a decentralized privacy-aware data management framework that enables actors to store, read, and modify data in PEDs. Our framework design integrates blockchain with a Distributed Hash Table (DHT), role-based access control, ring signature, and different encryption techniques. The proposed framework stores encrypted data on the DHT, and metadata and hash key are sent to the blockchain, which allows the data owner to keep track of their data. The proposed framework components handle multi-level data access in PEDs and enable data security at run-time. Moreover, we show security and privacy analysis and performance evaluation in time overhead. The results show that the proposed solution is effective, secure, and scalable

Energy Modelling as a Trigger for Energy Communities: A Joint Socio-Technical Perspective

Mainstreaming energy communities has been one of the main challenges in the low-carbon transition of cities. In this sense, urban building energy modelling (UBEM) has an untapped role in enabling energy communities, as simulations on urban models provide evidence-based decision support to reduce risks, engage, motivate and guide actors, assert wider policy goals and regulatory requirements. This accelerating role and the potential of UBEM is not sufficiently understood, as research into energy community focuses on its barriers and impacts, while the research of UBEM is mainly technologically oriented. This review takes a sociotechnical approach to explore whether UBEM is a technological trigger for energy communities, furthering the conceptual framework of transition management. factors influencing energy community progression in different use-cases and stages of their lifecycle are compiled to assess the affordances of distinct capabilities of prevalent UBEM tools. The study provides a guide for energy community planners to UBEM. It matches different tool capabilities to the various stages of the project lifecycle for the different use-cases, equipping them with the means to accelerate the low-carbon transition of cities from the bottom-up. Finally, the study defines a development trajectory oriented towards application in urban sustainability to a rather new UBEM field

Correction: Salom et al. An Evaluation Framework for Sustainable Plus Energy Neighbourhoods: Moving beyond the Traditional Building Energy Assessment. Energies 2021, 14, 4314

One contributor’s name was missing in the original version of the authorship of the paper [...

Correction: Salom et al. An Evaluation Framework for Sustainable Plus Energy Neighbourhoods: Moving beyond the Traditional Building Energy Assessment. <em>Energies </em>2021, <em>14</em>, 4314

One contributor’s name was missing in the original version of the authorship of the paper [...

An Evaluation Framework for Sustainable Plus Energy Neighbourhoods: Moving Beyond the Traditional Building Energy Assessment

There are international activities and on-going initiatives, particularly at the European level, to define what Positive Energy Districts should be, as the driving concept for the urban transition to a sustainable future. The first objective of the paper is to contribute to the on-going and lively debate about the definition of the notion of Sustainable Plus Energy Neighbourhood (SPEN), which highlights the multiple dimensions when talking about sustainability in districts moving beyond the traditional and strict building energy assessment. Based on a holistic methodology which ensures the consideration of the multidimensional nature and goals of SPEN, the paper outlines an evaluation framework. The evaluation framework defines the key performance indicators distributed in five categories that consider energy and power performance, GHG emissions, indoor environmental quality, smartness, flexibility, life cycle costs and social sustainability. This framework is designed to be implemented during integrated design processes aiming to select design options for a neighbourhood as well within during the operational phase for monitoring its performance. Further work will include the implementation and validation of the framework in four real-life positive energy neighbourhoods in different climate zones of Europe as part of syn.ikia H2020 project