Enabling Hardware Green Internet of Things: A review of Substantial Issues

Between now and the near future, the Internet of Things (IoT) will redesign the socio-ecological morphology of the human terrain. The IoT ecosystem deploys diverse sensor platforms connecting millions of heterogeneous objects through the Internet. Irrespective of sensor functionality, most sensors are low energy consumption devices and are designed to transmit sporadically or continuously. However, when we consider the millions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology, as well as the development of EE solutions for sustainable IoT technology, cannot be overemphasised. Propelled by this need, EE proposals are expected to address the EE issues in the IoT context. Consequently, many developments continue to emerge, and the need to highlight them to provide clear insights to researchers on eco-sustainable and green IoT technologies becomes a crucial task. To pursue a clear vision of green IoT, this study aims to present the current state-of-the art insights into energy saving practices and strategies on green IoT. The major contribution of this study includes reviews and discussions of substantial issues in the enabling of hardware green IoT, such as green machine to machine, green wireless sensor networks, green radio frequency identification, green microcontroller units, integrated circuits and processors. This review will contribute significantly towards the future implementation of green and eco-sustainable IoT

On thermal sensor calibration and software techniques for many-core thermal management

The high power density of a many-core processor results in increased temperature which negatively impacts system reliability and performance. Dynamic thermal management applies thermal-aware techniques at run time to avoid overheating using temperature information collected from on-chip thermal sensors. Temperature sensing and thermal control schemes are two critical technologies for successfully maintaining thermal safety. In this dissertation, on-line thermal sensor calibration schemes are developed to provide accurate temperature information. Software-based dynamic thermal management techniques are proposed using calibrated thermal sensors. Due to process variation and silicon aging, on-chip thermal sensors require periodic calibration before use in DTM. However, the calibration cost for thermal sensors can be prohibitively high as the number of on-chip sensors increases. Linear models which are suitable for on-line calculation are employed to estimate temperatures at multiple sensor locations using performance counters. The estimated temperature and the actual sensor thermal profile show a very high similarity with correlation coefficient ~0.9 for SPLASH2 and SPEC2000 benchmarks. A calibration approach is proposed to combine potentially inaccurate temperature values obtained from two sources: thermal sensor readings and temperature estimations. A data fusion strategy based on Bayesian inference, which combines information from these two sources, is demonstrated. The result shows the strategy can effectively recalibrate sensor readings in response to inaccuracies caused by process variation and environmental noise. The average absolute error of the corrected sensor temperature readings is A dynamic task allocation strategy is proposed to address localized overheating in many-core systems. Our approach employs reinforcement learning, a dynamic machine learning algorithm that performs task allocation based on current temperatures and a prediction regarding which assignment will minimize the peak temperature. Our results show that the proposed technique is fast (scheduling performed in \u3c1 \u3ems) and can efficiently reduce peak temperature by up to 8 degree C in a 49-core processor (6% on average) versus a leading competing task allocation approach for a series of SPLASH-2 benchmarks. Reinforcement learning has also been applied to 3D integrated circuits to allocate tasks with thermal awareness

Stabilization of halide perovskites with silicon compounds for optoelectronic, catalytic, and bioimaging applications

Silicon belongs to group 14 elements along with carbon, germanium, tin, and lead in the periodic table. Similar to carbon, silicon is capable of forming a wide range of stable compounds, including silicon hydrides, organosilicons, silicic acids, silicon oxides, and silicone polymers. These materials have been used extensively in optoelectronic devices, sensing, catalysis, and biomedical applications. In recent years, silicon compounds have also been shown to be suitable for stabilizing delicate halide perovskite structures. These composite materials are now receiving a lot of interest for their potential use in various real‐world applications. Despite exhibiting outstanding performance in various optoelectronic devices, halide perovskites are susceptible to breakdown in the presence of moisture, oxygen, heat, and UV light. Silicon compounds are thought to be excellent materials for improving both halide perovskite stability and the performance of perovskite‐based optoelectronic devices. In this work, a wide range of silicon compounds that have been used in halide perovskite research and their applications in various fields are discussed. The interfacial stability, structure–property correlations, and various application aspects of perovskite and silicon compounds are also analyzed at the molecular level. This study also explores the developments, difficulties, and potential future directions associated with the synthesis and application of perovskite‐silicon compounds. imag

Applications in Electronics Pervading Industry, Environment and Society

This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs

Silicon Photonics for All-Optical Processing and High-Bandwidth-Density Interconnects

Silicon photonics has emerged in recent years as one of the leading technologies poised to enable penetration of optical communications deeper and more intimately into computing systems than ever before. The integration potential of power efficient WDM links at the first level package or even deeper has been a strong driver for the rapid development this field has seen in recent years. The integration of photonic communication modules with very high bandwidth densities and virtually no bandwidth-distance limitations at the short reach regime of high performance computers and data centers has the potential to alleviate many of the bandwidth bottlenecks currently faced by board, rack, and facility levels. While networks on chip for chip multiprocessors (CMP) were initially deemed the target application of silicon photonic components, it has become evident in recent years that the initial lower hanging fruit is the CMP's I/O links to memory as well as other CMPs. The first chapter of the thesis provides more detailed motivation for the integration of silicon photonic modules into compute systems and surveys some of the recent developments in the field. The second chapter then proceeds to detail a technical case study of silicon photonic microring-based WDM links' scalability and power efficiency for these chip I/O applications which could be developed in the intermediate future. The analysis, initiated originally for a workshop on optical and electrical board and rack level interconnects, looks into a detailed model of the optical power budget for such a link capturing both single-channel aspects as well as WDM-operation-related considerations which are unique for a microring physical characteristics. The holistic analysis for the full link captures the wavelength-channel-spacing dependent characteristics, provides some methodologies for device design in the WDM-operation context, and provides performance predictions based on current best-of-class silicon photonic devices. The key results of the analysis are the determination of upper bounds on the aggregate achievable communication bandwidth per link, identifying design trade-offs for bandwidth versus power efficiency, and highlighting the need for continued technological improvements in both laser as well as photodetector technologies to allow acceptable power efficiency operation of such systems.The third chapter, while continuing on the theme silicon photonic high bandwidth density links, proceeds to detail the first experimental demonstration and characterization of an on-chip spatial division multiplexing (SDM) scheme based on microrings for the multiplexing and demultiplexing functionalities. In the context of more forward looking optical network-on-chip environments, SDM-enabled WDM photonic interconnects can potentially achieve superior bandwidth densities per waveguide compared to WDM-only photonic interconnects. The microring-based implementation allows dynamic tuning of the multiplexing and demultiplexing characteristic of the system which allows operation on WDM grid as well device tuning to combat intra-channel crosstalk. The characterization focuses on the first reported power penalty measurements for on-chip silicon photonic SDM link showing minimal penalties achievable with 3 spatial modes concurrently operating on a single waveguide with 10-Gb/s data carried by each mode. The chapter also details the first demonstration of WDM combined with SDM operation with six separate wavelength-and-spatial 10-Gb/s channels with error free operation and low power penalties. The fourth, fifth, and sixth chapters shift in topic from the application of silicon photonics to communication links to the evolving use of silicon waveguides for nonlinear all-optical processing. The unique tight mode confinement in sub-micron cross-sections combined with the high response of silicon have motivated the development of four-wave mixing (FWM)-based processing silicon devices. The key feature of the silicon platform for these nonlinear processing platforms is the ability to finely and uniformly control the dispersive properties of the optical structures in a way that enables completely offsetting the material dispersion and achieve dispersion profiles required for effective parametric interaction of waves in the optical structures. Chapter four primarily introduces and motivates nonlinear processing in communication applications and focuses on recent achievements in non-silicon and silicon FWM platforms. Chapter five describes some of the author's contributions on parametric processing of high speed data in silicon nonlinear devices, with first of a kind demonstrations of wavelength conversion of 160-Gb/s optically time division multiplexed (OTDM) data as well as the wavelength-multicasting of a 320-Gb/s OTDM stream. The chapter then details a methodical characterization and demonstration of several record wavelength conversion experiments of data in silicon with 40-Gb/s data wavelength-converted across more than 100 nm with only 1.4-dB of power penalties as well as the wavelength and format conversion of 10-Gb/s data across up to 168 nm with sensitivity gains stemming from the format conversion of about 2 dB and a residual conversion penalty of only 0.1 dB, achieved by implementing an improved experimental setup. Both experiments highlight the performance uniformity of the conversion process for a wide range of probe-idler detuning settings, showcasing the silicon platform's unique broadband phase matching properties. The sixth chapter presents a slight shift in motivation for parametric processing from traditional telecom-wavelength applications to functionalities developed targeting mid-IR operation. Parametric-processing in the silicon platform at long wavelengths holds large potential for performance improvements due to the elimination of two-photon absorption in silicon at long wavelengths as well as silicon's dispersion engineering capabilities which uniquely position the silicon platform for effective phase matching of significantly wavelength detuned waves. Four-wave mixing signal generation and reception at mid-IR wavelengths are attractive candidates for tunable flexible operation with modulation and detection speeds which are currently only available at telecom wavelengths. With this vision in mind, several contributions detailing extension of FWM functionalities in silicon to operate at wavelengths close to 2 μm with performance equivalent to much smaller detuning setting measurements. The contributions detail the experimental demonstration of the first silicon optical processing functionalities achieved at such long wavelengths including the wavelength conversion and unicast of 10-Gb/s signals with up to 700 nm of probe-idler detuning, the combined two-stage 10-Gb/s FWM-link in which both data generation and detection at 1900 nm is facilitated by parametric processing in silicon with only 2.1-dB overall penalty, the first ever 40-Gb/s receiver at 1900 nm based on a FWM stage for simultaneous temporal demultiplexing and wavelength conversion, and lastly, the demonstration of a 40-Gb/s FWM-link operation with only 3.6 dB of penalty. The chapter concludes with a short discussion on possible extensions to enable silicon parametric processing at even longer wavelengths targeting the mid-IR spectral transmission window of 3-5 μm

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Degradation Science: Mesoscopic Evolution and Temporal Analytics of Photovoltaic Energy Materials

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. We delineate paths forward for degradation science

Artificial Intelligence Technology

This open access book aims to give our readers a basic outline of today’s research and technology developments on artificial intelligence (AI), help them to have a general understanding of this trend, and familiarize them with the current research hotspots, as well as part of the fundamental and common theories and methodologies that are widely accepted in AI research and application. This book is written in comprehensible and plain language, featuring clearly explained theories and concepts and extensive analysis and examples. Some of the traditional findings are skipped in narration on the premise of a relatively comprehensive introduction to the evolution of artificial intelligence technology. The book provides a detailed elaboration of the basic concepts of AI, machine learning, as well as other relevant topics, including deep learning, deep learning framework, Huawei MindSpore AI development framework, Huawei Atlas computing platform, Huawei AI open platform for smart terminals, and Huawei CLOUD Enterprise Intelligence application platform. As the world’s leading provider of ICT (information and communication technology) infrastructure and smart terminals, Huawei’s products range from digital data communication, cyber security, wireless technology, data storage, cloud computing, and smart computing to artificial intelligence

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc