Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Earth-observation-based estimation and forecasting of particulate matter impact on solar energy in Egypt

This study estimates the impact of dust aerosols on surface solar radiation and solar energy in Egypt based on Earth Observation (EO) related techniques. For this purpose, we exploited the synergy of monthly mean and daily post processed satellite remote sensing observations from the MODerate resolution Imaging Spectroradiometer (MODIS), radiative transfer model (RTM) simulations utilizing machine learning, in conjunction with 1-day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). As cloudy conditions in this region are rare, aerosols in particular dust, are the most common sources of solar irradiance attenuation, causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The proposed EO-based methodology is based on the solar energy nowcasting system (SENSE) that quantifies the impact of aerosol and dust on solar energy potential by using the aerosol optical depth (AOD) in terms of climatological values and day-to-day monitoring and forecasting variability from MODIS and CAMS, respectively. The forecast accuracy was evaluated at various locations in Egypt with substantial PV and CSP capacity installed and found to be within 5–12% of that obtained from the satellite observations, highlighting the ability to use such modelling approaches for solar energy management and planning (M&P). Particulate matter resulted in attenuation by up to 64–107 kWh/m2 for global horizontal irradiance (GHI) and 192–329 kWh/m2 for direct normal irradiance (DNI) annually. This energy reduction is climatologically distributed between 0.7% and 12.9% in GHI and 2.9% to 41% in DNI with the maximum values observed in spring following the frequent dust activity of Khamaseen. Under extreme dust conditions the AOD is able to exceed 3.5 resulting in daily energy losses of more than 4 kWh/m2 for a 10 MW system. Such reductions are able to cause financial losses that exceed the daily revenue values. This work aims to show EO capabilities and techniques to be incorporated and utilized in solar energy studies and applications in sun-privileged locations with permanent aerosol sources such as Egypt

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Acoustic and X-ray Chacterisation of Lithium-Ion Battery Failure

Lithium-ion batteries have become synonymous with modern consumer electronics and potentially, are the cornerstone to development of integrated electrified infrastructure that can support a clean and renewable national energy grid. Despite the widespread applications due to the favourable performance parameters, recent events have elevated the safety concerns associated with lithium-ion batteries. However, there is great difficulty in rapid diagnostic analysis outside specialised laboratories which can hinder the review of functional safety- and novel energy dense- materials for lithium-ion energy storage. The dynamic evolution of internal architectures and novel active materials across multiple length scales are investigated in this thesis; with in-situ and operando acoustic spectroscopy (AS) via ultrasonic time of flight (ToF) probing, high speed synchrotron X-ray imaging, computed tomography and fractional thermal runaway calorimetry. The identification of characteristic precursor events such as gas-induced delamination in degradation mechanisms before eventual failure by AS; is correlated with X-ray imaging and post-mortem computed tomography (CT), highlighting the potential for battery management systems. Mitigation and prevention of failure with plasticized current collectors and thermally stable cellulose separators was also investigated at multiple length scales, with the transient mechanical structure compared with their commercial counterparts in cylindrical cells. Further work investigating the robustness of acoustic spectroscopy and polymer current collectors were applied to pure silicon nanowire negative electrodes. The studies reported in this thesis assess novel materials in lithium-ion batteries, and the potential impact of the work is highlighted. Development of AS via ToF probing offers another unique and field deployable insight allowing more complete and comprehensive understanding of batteries as they continue to evolve in complexity. Lithium-ion failure characterisation techniques and literature have evolved and provided insights into the function of polymer current collectors in different cell formats and chemistries. Findings presented in this thesis are anticipated to augment future inherently safer battery design and characterisation of lithium-ion energy storage thermal runaway

Markov decision processes with applications in wireless sensor networks: A survey

Ministry of Education, Singapore under its Academic Research Funding Tier

TRA of DigiMon components

The DigiMon project aims to develop an affordable, flexible, societally embedded and smart monitoring system for industrial scale subsurface CO2 storage. For this purpose, the DigiMon system is to combine various types of measurements in integrated workflows. In this report, we describe the process of conducting the Technology Readiness Assessment (TRA) of various measurement techniques. We report on the identification, description and assessment of these measurement techniques as Critical Technology Elements (CTEs) being part of the DigiMon system