A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Software defined neighborhood area network for smart grid applications

Information gathered from the Smart Grid (SG) devices located in end user premises provides a valuable resource that can be used to modify the behavior of SG applications. Decentralized and distributed deployment of neighborhood area network (NAN) devices makes it a challenge to manage SG efficiently. The NAN communication network architecture should be designed to aggregate and disseminate information among different SG domains. In this paper, we present a communication framework for NAN based on wireless sensor networks using the software defined networking paradigm. The data plane devices, such as smart meters, intelligent electronic devices, sensors, and switches are controlled via an optimized controller hierarchy deployed using a separate control plane. An analytical model is developed to determine the number of switches and controllers required for the NAN and the results of several test scenarios are presented. A Castalia based simulation model was used to analyze the performance of modified NAN performance

Anomaly detection in the dynamics of web and social networks

In this work, we propose a new, fast and scalable method for anomaly detection in large time-evolving graphs. It may be a static graph with dynamic node attributes (e.g. time-series), or a graph evolving in time, such as a temporal network. We define an anomaly as a localized increase in temporal activity in a cluster of nodes. The algorithm is unsupervised. It is able to detect and track anomalous activity in a dynamic network despite the noise from multiple interfering sources. We use the Hopfield network model of memory to combine the graph and time information. We show that anomalies can be spotted with a good precision using a memory network. The presented approach is scalable and we provide a distributed implementation of the algorithm. To demonstrate its efficiency, we apply it to two datasets: Enron Email dataset and Wikipedia page views. We show that the anomalous spikes are triggered by the real-world events that impact the network dynamics. Besides, the structure of the clusters and the analysis of the time evolution associated with the detected events reveals interesting facts on how humans interact, exchange and search for information, opening the door to new quantitative studies on collective and social behavior on large and dynamic datasets.Comment: The Web Conference 2019, 10 pages, 7 figure

Health Participatory Sensing Networks for Mobile Device Public Health Data Collection and Intervention

The pervasive availability and increasingly sophisticated functionalities of smartphones and their connected external sensors or wearable devices can provide new data collection capabilities relevant to public health. Current research and commercial efforts have concentrated on sensor-based collection of health data for personal fitness and personal healthcare feedback purposes. However, to date there has not been a detailed investigation of how such smartphones and sensors can be utilized for public health data collection. Unlike most sensing applications, in the case of public health, capturing comprehensive and detailed data is not a necessity, as aggregate data alone is in many cases sufficient for public health purposes. As such, public health data has the characteristic of being capturable whilst still not infringing privacy, as the detailed data of individuals that may allow re-identification is not needed, but rather only aggregate, de-identified and non-unique data for an individual. These types of public health data collection provide the challenge of the need to be flexible enough to answer a range of public health queries, while ensuring the level of detail returned preserves privacy. Additionally, the distribution of public health data collection request and other information to the participants without identifying the individual is a core requirement. An additional requirement for health participatory sensing networks is the ability to perform public health interventions. As with data collection, this needs to be completed in a non-identifying and privacy preserving manner. This thesis proposes a solution to these challenges, whereby a form of query assurance provides private and secure distribution of data collection requests and public health interventions to participants. While an additional, privacy preserving threshold approach to local processing of data prior to submission is used to provide re-identification protection for the participant. The evaluation finds that with manageable overheads, minimal reduction in the detail of collected data and strict communication privacy; privacy and anonymity can be preserved. This is significant for the field of participatory health sensing as a major concern of participants is most often real or perceived privacy risks of contribution

Algorithmic generation of vascular network models for additive manufacturing

Fabrication of functional vascularised three-dimensional tissue constructs has been a long-standing objective in the field of tissue engineering. Currently, the main limitation in this field is the inability to produce fully vascularised tissue with an internal mass transport system (vascular network) that can provide cells with nutrients and oxygen while removing waste, to imitate the functions of human living tissue. Achieving such a system would allow the development of large-scale tissue constructs and increase the potential for in vivo integration. There are different approaches to attempt vascularisation, which use a diversity of techniques. Among these, one of the most promising is additive manufacturing due to its versatility, reproducibility, and compatibility with suitable materials. With the aim of contributing towards the efforts in this field, the present work presents a method for the automatic generation of physiologically-based vascular network structures as solid 3D models suitable for additive manufacturing technologies. Considering the natural hierarchical branching vasculature as an ideal solution, an algorithm was developed to generate branching tree structures connected at the ends to form vascular networks. The implementation is based on previous work in the field of computational bio-simulation of arterial tree growth. It consists of a space-filling algorithm that connects all given points to a growing tree within a defined three-dimensional volume, while fulfilling constraints associated with the physiological laws of circulation. The networks are generated using a CAD environment and thus can be used in additive manufacturing processes. An investigation was carried out on the effect of three input parameters (namely volumetric flow rate, pressure difference across the tree, and number of terminal points) in order to find a suitable combination of parameters that would produce networks with diameters above the fabrication threshold. In order to demonstrate feasibility and functionality of the networks fabricated using this proposed method, two network models were produced by 3D printing and subsequently used as a sacrificial structure to produce PDMS blocks with the hollow vascular networks embedded in it. Particle tracking was used to measure the flow velocity in the channels at two different inlet flow rates. Comparisons were made with theoretical values obtained from computational fluid dynamics simulations and show a good agreement between experiment and theory. From the measurements of maximum velocity, it was observed that at a lower flow rate, the experimental values were closer to the theoretical values than at a higher flow rate. This might be due to the challenges that higher flow rates represent, such as less accurate particle tracking. Given the overall agreement, it is concluded that computational fluid dynamics simulations are a fast and effective way to analyse flow in vascular network models produced by the method here proposed.The Cambridge Trust, CONACyT (Consejo Nacional de Ciencia y Tecnologia), EPSRC Cambridge & Cranfield Doctoral Training Centre in Ultra Precisio

IoT on Shared Vehicles

Nowadays the need of people to have the power to control everything is increasing. Due to the technological evolution together with the Internet of things, this is already possible. In this context, the shared vehicles are a good example. With just one click people can use a vehicle from a vehicle sharing eet anywhere, anytime. During the realization of this project the uMDC was developed. It is a small device capable of managing and controlling di erent types of vehicles, with the main focus being the electric bicycles. As a nal conclusion of the project, the results obtained with the uMDC have proved very attractive. During its integration in the electric bicycles, the system was capable of controlling the bicycle's di erent components, as required for the rst prototype.Hoje em dia, a necessidade das pessoas terem controlo sobre tudo está a aumentar. Devido á evolução tecnológica juntamente com a Internet das coisas, isso já é possível. Neste contexto, os veículos partilhados são um bom exemplo disso. Com um simples clique, as pessoas podem usufruir e uma viatura de uma frota de veículos partilhados em qualquer lugar, a qualquer hora. Durante a realização deste projeto, foi desenvolvido o uMDC. Um pequeno ispositivo capaz de gerir e controlar diferentes tipos de veículos, sendo o foco principal as bicicletas elétricas. No nal deste projeto, os resultados obtidos com o uMDC foram bastante satisfatórios. Durante a sua integração nas bicicletas elétricas, o sistema foi capaz de controlar diferentes componentes das mesmas, como requerido para primeiro protótipo

NETWORK TRAFFIC CHARACTERIZATION AND INTRUSION DETECTION IN BUILDING AUTOMATION SYSTEMS

The goal of this research was threefold: (1) to learn the operational trends and behaviors of a realworld building automation system (BAS) network for creating building device models to detect anomalous behaviors and attacks, (2) to design a framework for evaluating BA device security from both the device and network perspectives, and (3) to leverage new sources of building automation device documentation for developing robust network security rules for BAS intrusion detection systems (IDSs). These goals were achieved in three phases, first through the detailed longitudinal study and characterization of a real university campus building automation network (BAN) and with the application of machine learning techniques on field level traffic for anomaly detection. Next, through the systematization of literature in the BAS security domain to analyze cross protocol device vulnerabilities, attacks, and defenses for uncovering research gaps as the foundational basis of our proposed BA device security evaluation framework. Then, to evaluate our proposed framework the largest multiprotocol BAS testbed discussed in the literature was built and several side-channel vulnerabilities and software/firmware shortcomings were exposed. Finally, through the development of a semi-automated specification gathering, device documentation extracting, IDS rule generating framework that leveraged PICS files and BIM models.Ph.D

NR-SLAM: Non-Rigid Monocular SLAM

In this paper we present NR-SLAM, a novel non-rigid monocular SLAM system founded on the combination of a Dynamic Deformation Graph with a Visco-Elastic deformation model. The former enables our system to represent the dynamics of the deforming environment as the camera explores, while the later allows us to model general deformations in a simple way. The presented system is able to automatically initialize and extend a map modeled by a sparse point cloud in deforming environments, that is refined with a sliding-window Deformable Bundle Adjustment. This map serves as base for the estimation of the camera motion and deformation and enables us to represent arbitrary surface topologies, overcoming the limitations of previous methods. To assess the performance of our system in challenging deforming scenarios, we evaluate it in several representative medical datasets. In our experiments, NR-SLAM outperforms previous deformable SLAM systems, achieving millimeter reconstruction accuracy and bringing automated medical intervention closer. For the benefit of the community, we make the source code public.Comment: 12 pages, 7 figures, submited to the IEEE Transactions on Robotics (T-RO

Concurrency Controls in Event-Driven Programs

Functional reactive programming (FRP) is a programming paradigm that utilizes the concepts of functional programming and time-varying data types to create event-driven applications. In this paradigm, data types in which values can change over time are primitives and can be applied to functions. These values are composable and can be combined with functions to create values that react to changes in values from multiple sources. Events can be modeled as values that change in discrete time steps. Computation can be encoded as values that produce events, with combination operators, it enables us to write concurrent event-driven programs by combining the concurrent computation as events. Combined with the denotational approach of functional programming, we can write programs in a concise manner. The style of event-driven programming has been widely adopted for developing graphical user interface applications, since they need to process events concurrently to stay responsive. This makes FRP a fitting approach for managing complex state and handling of events concurrently. In recent years, real-time systems such as IoT (internet of things) applications have become an important field of computation. Applying FRP to real-time systems is still an active area of research.For IoT applications, they are commonly tasked to perform data capturing in real time and transmit them to other devices. They need to exchange data with other applications over the internet and respond in a timely manner. The data needs to be processed, for simple analysis or more computation intensive work such as machine learning. Designing applications that perform these tasks and remain efficient and responsive can be challenging. In this thesis, we demonstrate that FRP is a suitable approach for real-time applications. These applications require soft real-time requirements, where systems can tolerate tasks that fail to meet the deadline and the results of these tasks might still be useful.First, we design the concurrency abstractions needed for supporting asynchronous computation and use it as the basis for building the FRP abstraction. Our implementation is in Haskell, a functional programming language with a rich type system that allows us to model abstractions with ease. The concurrency abstraction is based on some of the ideas from the Haskell solution for asynchronous computation, which elegantly supports cancelation in a composable way. Based on the Haskell implementation, we extend our design with operators that are more suitable for building web applications. We translate our implementation to JavaScript as it is more commonly used for web application development, and implementing the RxJS interface. RxJS is a popular JavaScript library for reactive programming in web applications. By implementing the RxJS interface, we argue that our programming model implemented in Haskell is also applicable in mainstream languages such as JavaScript