Mitigating the Event and Effect of Energy Holes in Multi-hop Wireless Sensor Networks Using an Ultra-Low Power Wake-up Receiver and an Energy Scheduling Technique

This research work presents an algorithm for extending network lifetime in multi-hop wireless sensor networks (WSN). WSNs face energy gap issues around sink nodes due to the transmission of large amounts of data through nearby sensor nodes. The limited power supply to the nodes limits the lifetime of the network, which makes energy efficiency crucial. Multi-hop communication has been proposed as an efficient strategy, but its power consumption remains a research challenge. In this study, an algorithm is developed to mitigate energy holes around the sink nodes by using a modified ultra-low-power wake-up receiver and an energy scheduling technique. Efficient power scheduling reduces the power consumption of the relay node, and when the residual power of the sensor node falls below a defined threshold, the power emitters charge the nodes to eliminate energy-hole problems. The modified wake-up receiver improves sensor sensitivity while staying within the micro-power budget. This study's simulations showed that the developed RF energy harvesting algorithm outperformed previous work, achieving a 30% improvement in average charged energy (AEC), a 0.41% improvement in average energy (AEH), an 8.39% improvement in the number of energy transmitters, an 8.59% improvement in throughput, and a 0.19 decrease in outage probability compared to the existing network lifetime enhancement of multi-hop wireless sensor networks by RF Energy Harvesting algorithm. Overall, the enhanced power efficiency technique significantly improves the performance of WSNs

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

The Machine that Lives Forever

Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a transient environment. Example harvesting includes induced and background radiation. Intelligent, biologically-inspired strategies are adopted in forward-scheduling strategies given temporal energy relative to the machine’s function (the Walton)

Analysis of relevant technical issues and deficiencies of the existing sensors and related initiatives currently set and working in marine environment. New generation technologies for cost-effective sensors

The last decade has seen significant growth in the field of sensor networks, which are currently collecting large amounts of environmental data. This data needs to be collected, processed, stored and made available for analysis and interpretation in a manner which is meaningful and accessible to end users and stakeholders with a range of requirements, including government agencies, environmental agencies, the research community, industry users and the public. The COMMONSENSE project aims to develop and provide cost-effective, multi-functional innovative sensors to perform reliable in-situ measurements in the marine environment. The sensors will be easily usable across several platforms, and will focus on key parameters including eutrophication, heavy metal contaminants, marine litter (microplastics) and underwater noise descriptors of the MSFD. The aims of Tasks 2.1 and 2.2 which comprise the work of this deliverable are: • To obtain a comprehensive understanding and an up-to-date state of the art of existing sensors. • To provide a working basis on “new generation” technologies in order to develop cost-effective sensors suitable for large-scale production. This deliverable will consist of an analysis of state-of-the-art solutions for the different sensors and data platforms related with COMMONSENSE project. An analysis of relevant technical issues and deficiencies of existing sensors and related initiatives currently set and working in marine environment will be performed. Existing solutions will be studied to determine the main limitations to be considered during novel sensor developments in further WP’s. Objectives & Rationale The objectives of deliverable 2.1 are: • To create a solid and robust basis for finding cheaper and innovative ways of gathering data. This is preparatory for the activities in other WPs: for WP4 (Transversal Sensor development and Sensor Integration), for WP(5-8) (Novel Sensors) to develop cost-effective sensors suitable for large-scale production, reducing costs of data collection (compared to commercially available sensors), increasing data access availability for WP9 (Field testing) when the deployment of new sensors will be drawn and then realized

UTILIZING AUTOMATIC IDENTIFICATION TRACKING SYSTEMS TO COMPILE OPERATIONAL FIELD AND STRUCTURE DATA

The Maryland State Highway Administration (SHA) and its Office of Materials Technology (OMT) is responsible for ensuring the materials used on its roadway system are properly designed, produced, and built to the approved standards. Each technology subdivision is responsible for the quality assurance of the materials used in transportation facility construction. The management of these materials relies on a series of intensive human processes involving sample collection and delivery. As the materials travel throughout the OMT, associated material information is manually recorded into a localized network database and the Material Management System (MMS) separately. The current large amount of human involvement necessary in the material clearance process can be streamlined with the integration of automatic identification technology (AIT). This study utilizes past implementations of AIT into civil engineering and construction applications to provide the SHA with AIT system hardware recommendations, software development considerations, estimated investment costs, and return on investment

Acoustic signal-based underwater oil leak detection and localization

Underwater Wireless Sensor Networks (UWSNs) have been becoming popular for exploring offshore, natural resource development, geological oceanography, and monitoring the underwater environment. The acoustic channel characteristics in underwater impose challenges, including limited bandwidth, signal attenuation, and propagation delay that limits UWSN utilization. The marine environment is under threat from pollution, which impacts human life and activities. Compared to other pollution types, the oil leak is a significant threat to the marine ecosystem. When the leaked oil or other petroleum products mix with water in the ocean, significant biological and economic impacts could result. Although much research has focused on improving the reception and processing of acoustic signals, increasing performance, and reducing packet delay, no significant research results have been reported on finding an effective early-stage leak detection method using acoustic signal processing. Accurate information about oil spill location and its characteristics is much needed for oil spill containment and cleanup operations. Developing an efficient under- water oil leak detection and localization algorithm is still challenging in UWSNs because of the impairments of the acoustic channel. In this thesis, we propose a technique that detects the presence of an oil leak in the underwater environment at an early stage. We also propose a localization algorithm that determines the approximate location of the oil leak. Firstly, we review the propagation properties of acoustic signals to understand acoustic communication in the marine environment better. We then discuss the transmission of sound in terms of reflection and refraction. We propose a leak detection technique based on the range estimation method to detect oil leak at an early stage before reaching the ocean sur- face. We perform a two-dimensional analysis for evaluating the performance of the proposed detection technique. To investigate the proposed technique, we perform evaluation with different network sizes and topologies. We discuss the detection ratio, network scalability, power and intensity of the received signal. We then perform a three-dimensional analysis to evaluate the performance of the proposed technique. We conduct theoretical analysis to investigate the proposed technique in terms of detection ratio, network scalability, power and intensity of the received signal. We assess the efficiency of the proposed detection method by considering an oil leak at different ocean levels. Finally, we propose a cooperative localization algorithm for localizing the leak in the UWSN. We then evaluate the proposed localization algorithm for two different topologies. Our results show that our proposed technique works well for an underwater network with concentric hexagonal topology. We can extend the proposed method for other types of targets with different shapes and sizes

Simultaneous wireless information and power transfer in full-duplex communication systems

As wireless devices are mostly constrained by their inability to operate independently infinitely away from centralised power sources, radio frequency (RF) energy harvesting (EH) has been identified as a promising technique for future wireless devices. For this reason, this thesis introduces a novelty in RF EH full-duplex (FD) wireless communication systems. Specifically, this thesis investigate the potentials of simultaneous wireless information and power transfer (SWIPT) in FD communication systems. This thesis firstly focuses on optimal transmit strategies, rate maximization and power minimizing approach for SWIPT in FD systems. Using the rate-split method, difference of convex programming, semi-definite programming technique and one-dimensional search, we reformulate complex optimization problems to yield problem formulations that can be efficiently solved, thus we develop rate maximization algorithm for SWIPT in a point-to-point FD system, SWIPT in FD multiple-input multiple-output (MIMO) two-way relay system and power minimization approach for SWIPT in a multiuser MIMO FD system. This thesis also presents research work carried out with the aim of maximising the secrecy sum-rate for SWIPT in FD systems. In this context, we employ the use of an amplify and forward (AF) relay to inject artificial noise (AN) in order to confuse the eavesdropper. Thus, we address the optimal joint design of the beamforming matrix and AN covariance matrix at the relay, and the transmit power at the sources. Comprehensively, we present extensive theoretical and computer simulations to corroborate the need for joint optimization

Micromobility: Progress, benefits, challenges, policy and regulations, energy sources and storage, and its role in achieving sustainable development goals

Micromobility is dominant in urban areas, enhancing the transportation sustainability and assisting in fulfilling the United Nations Sustainable Development Goals (SDGs). This work provides an overall assessment of micromobility: its role under SDGs, policy options, micromobility regulations, emerging technologies, utilisation determinants, energy source, and energy storage. The analysis shows that micromobility could play a major role in achieving the SDGs, specifically SDG 3 (Good Health and Well-being) by lowering toxic gas emissions and reducing projected traffic accidents. Also, the effect on SDG 8 (Decent Work and Economic Growth) by reducing the transportation footprint, on SDG 11 (Sustainable Cities and Communities) by increasing transposition accessibility, reducing traffic congestion and improving the air quality, and equally on SDG 12 (Responsible Consumption and Production) by reducing transportation footprint and increase the sources efficiency. Moreover, micromobility affects SDG 13 (Climate Action) by reducing the greenhouse gases. Furthermore, the analysis shows a clear gap in literature and publications on micromobility, especially in energy management and energy storage area. This review shows that new technology of renewable energy and energy storage could play a significant role in achieving the sustainability of micromobility therefore achieving the SDGs

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools