Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

The significance of passive acoustic array-configurations on sperm whale range estimation when using the hyperbolic algorithm

In cetacean monitoring for population estimation, behavioural studies or mitigation, traditional visual observations are being augmented by the use of Passive Acoustic Monitoring (PAM) techniques that use the creature’s vocalisations for localisation. The design of hydrophone configurations is evaluated for sperm whale (Physeter macrocephalus) range estimation to meet the requirements of the current mitigation regulations for a safety zone and behaviour research. This thesis uses the Time Difference of Arrival (TDOA) of cetacean vocalisations with a three-dimensional hyperbolic localisation algorithm. A MATLAB simulator has been developed to model array-configurations and to assess their performance in source range estimation for both homogeneous and non-homogeneous sound speed profiles (SSP). The non-homogeneous medium is modelled on a Bellhop ray trace model, using data collected from the Gulf of Mexico. The sperm whale clicks are chosen as an exemplar of a distinctive underwater sound. The simulator is tested with a separate synthetic source generator which produced a set of TDOAs from a known source location. The performance in source range estimation for Square, Trapezium, Triangular, Shifted-pair and Y-shape geometries is tested. The Y-shape geometry, with four elements and aperture-length of 120m, is the most accurate, giving an error of ±10m over slant ranges of 500m in a homogeneous medium, and 300m in a non-homogeneous medium. However, for towed array deployments, the Y-shape array is sensitive to angle-positioning-error when the geometry is seriously distorted. The Shifted-pair geometry overcomes these limits, performing an initial accuracy of ±30m when the vessel either moves in a straight line or turns to port or starboard. It constitutes a recommendable array-configuration for towed array deployments. The thesis demonstrates that the number of receivers, the array-geometry and the arrayaperture are important parameters to consider when designing and deploying a hydrophone array. It is shown that certain array-configurations can significantly improve the accuracy of source range estimation. Recommendations are made concerning preferred array-configurations for use with PAM systems

HOME ENERGY MANAGEMENT SYSTEM FOR DEMAND RESPONSE PURPOSES

The growing demand for electricity has led to increasing efforts to generate and satisfy the rising demand. This led to suppliers attempting to reduce consumption with the help of the users. Requests to shift unnecessary loads off the peak hours, using other sources of generators to supply the grid while offering incentives to the users have made a significant effect. Furthermore, automated solutions were implemented with the help of Home Energy Management Systems (HEMS) where the user can remotely manage household loads to reduce consumption or cost. Demand Response (DR) is the process of reducing power consumption in a response to demand signals generated by the utility based on many factors such as the Time of Use (ToU) prices. Automated HEMS use load scheduling techniques to control house appliances in response to DR signals. Scheduling can be purely user-dependent or fully automated with minimum effort from the user. This thesis presents a HEMS which automatically schedules appliances around the house to reduce the cost to the minimum. The main contributions in this thesis are the house controller model which models a variety of thermal loads in addition to two shiftable loads, and the optimizer which schedules the loads to reduce the cost depending on the DR signals. The controllers focus on the thermal loads since they have the biggest effect on the electricity bill, they also consider many factors ignored in similar models such as the physical properties of the room/medium, the outer temperatures, the comfort levels of the users, and the occupancy of the house during scheduling. The DR signal was the hourly electricity price; normally higher during the peak hours. Another main part of the thesis was studying multiple optimization algorithms and utilizing them to get the optimum scheduling. Results showed a maximum of 44% cost reduction using different metaheuristic optimization algorithms and different price and occupancy schemes

Geoinformatics in Citizen Science

The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science

SUTMS - Unified Threat Management Framework for Home Networks

Home networks were initially designed for web browsing and non-business critical applications. As infrastructure improved, internet broadband costs decreased, and home internet usage transferred to e-commerce and business-critical applications. Today’s home computers host personnel identifiable information and financial data and act as a bridge to corporate networks via remote access technologies like VPN. The expansion of remote work and the transition to cloud computing have broadened the attack surface for potential threats. Home networks have become the extension of critical networks and services, hackers can get access to corporate data by compromising devices attacked to broad- band routers. All these challenges depict the importance of home-based Unified Threat Management (UTM) systems. There is a need of unified threat management framework that is developed specifically for home and small networks to address emerging security challenges. In this research, the proposed Smart Unified Threat Management (SUTMS) framework serves as a comprehensive solution for implementing home network security, incorporating firewall, anti-bot, intrusion detection, and anomaly detection engines into a unified system. SUTMS is able to provide 99.99% accuracy with 56.83% memory improvements. IPS stands out as the most resource-intensive UTM service, SUTMS successfully reduces the performance overhead of IDS by integrating it with the flow detection mod- ule. The artifact employs flow analysis to identify network anomalies and categorizes encrypted traffic according to its abnormalities. SUTMS can be scaled by introducing optional functions, i.e., routing and smart logging (utilizing Apriori algorithms). The research also tackles one of the limitations identified by SUTMS through the introduction of a second artifact called Secure Centralized Management System (SCMS). SCMS is a lightweight asset management platform with built-in security intelligence that can seamlessly integrate with a cloud for real-time updates

Technology and Management Applied in Construction Engineering Projects

This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC