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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Architectural design of the interplanetary internet is now underway and prototype flight testing of some of the candidate protocols is anticipated within a year. This talk will describe the current status of the project.
This paper summarizes the technology status, highlights current NDT Internet activities and suggests action items for international collaboration.
This paper is to explore a new space flight operations concept of using the off-the-shelf internet tools, combined with gateway servers, space link standards and on-board file system.
The Web Interface for Telescience (WITS) is an Internet-based tool that the Mars Pathfinder mission used for both mission operations at JPL and public outreach.
By the year 2020 it is estimated that there will be more than 50 billion devices connected to the Internet. These devices not only include traditional electronics such as smartphones and other mobile compute devices, but also eEnabled technologies such as cars, airplanes and smartgrids. The IoT brings with it the promise of efficiency, greater remote management of industrial processes and further opens the doors to world of vehicle autonomy. However, IoT enabled technology will have to operate and contend in the contested domain of cyberspace. This discussion will touch on the impact that cybersecurity has on IoT and the people, processes and technology required to mitigate cyber risks.
Using a network of 15 global GPS receivers, GPS data is returning to JPL via the open Internet to determine the orbits and clocks of the GPS constellation in real-time.
On-line access to complete texts of scholarly journal articles, conference papers, and books is facilitated by rapidly developing World-wide Web Internet access and capabilities.
Future long duration exploration missions will require astronauts to work and behave more autonomously. Over the last several years, we have been investigating how integrating sensors into an astronaut’s environment enables crew autonomy. This paper describes the prototypes we have deployed in Earth analogs investigating the concept of the Internet of “Space” Things.
Abstract Since their debut in 2012, triboelectric nanogenerators (TENGs) have attained high performance in terms of both energy density and instantaneous conversion, reaching up to 500 W m −2 and 85%, respectively, synchronous with multiple energy sources and hybridized designs. Here, a comprehensive review of the design guidelines of TENGs, their performance, and their designs in the context of Internet of Things (IoT) applications is presented. The development stages of TENGs in large‐scale self‐powered systems and technological applications enabled by harvesting energy from water waves or wind energy sources are also reviewed. This self‐powered capability is essential considering that IoT applications should be capable of operation anywhere and anytime, supported by a network of energy harvesting systems in arbitrary environments. In addition, this review paper investigates the development of self‐charging power units (SCPUs), which can be realized by pairing TENGs with energy storage devices, such as batteries and capacitors. Consequently, different designs of power management circuits, supercapacitors, and batteries that can be integrated with TENG devices are also reviewed. Finally, the significant factors that need to be addressed when designing and optimizing TENG‐based systems for energy harvesting and self‐powered sensing applications are discussed.
Abstract Soft thermoelectric materials, including conjugated polymers and organic–inorganic hybrids, now demonstrate figures of merit approaching those of inorganic materials. These materials development breakthroughs enable the design of thermoelectric devices that exhibit appropriate efficiencies for commercial use, while simultaneously leveraging the unique processing and mechanical advantages of soft materials. Such a technology opens the door to a suite of new thermoelectric applications, including power generation for biomedical implants and the Internet of Things, or wearable heating and cooling devices. In order to realize deployment of such technologies, there is a fundamental need for deeper understanding of the complex transport physics underlying thermoelectric transport in soft materials. Here, the current state of the art in soft thermoelectrics materials is discussed, and outstanding challenges specific to organic and organic–inorganic hybrid systems are highlighted.
This record provides a numerical investigation of a MAGeI₃-based perovskite solar cell with the structure FTO/TiO₂/MAGeI₃/Spiro-OMeTAD, evaluated for both outdoor and indoor light-harvesting applications using the SCAPS-1D simulator. Device performance is analyzed under AM 1.5G sunlight and several artificial light sources, including LED, incandescent, compact fluorescent lamp (CFL), flashlight, and xenon illumination. The study reports initial and optimized power conversion efficiencies and examines the influence of absorber layer thickness and bandgap on device performance under different lighting conditions. The results highlight the potential of MAGeI₃-based perovskite solar cells for indoor energy harvesting and low-power Internet of Things (IoT) applications.
The ultimate realization of a global quantum internet will require advances in scalable technologies capable of generating, storing, and manipulating quantum information. The essential devices that will perform these tasks in a quantum network are quantum repeaters, which will enable the long-range distribution of entanglement between distant network nodes. Here, in this review, we provide an overview of the primary functions of a quantum repeater and discuss progress that has been made toward the development of repeaters with rare-earth ion doped materials while noting challenges that are being faced as the technologies mature. We give particular attention to erbium, which is well suited for networking applications. Finally, we provide a discussion of near-term benchmarks that can further guide rare-earth ion platforms for impact in near-term quantum networks.
Although the number of smart Internet of Things (IoT) devices has grown in recent years, the public's perception of how effectively these devices secure IoT data has been questioned. Many IoT users do not have a good level of confidence in the security or privacy procedures implemented within IoT smart devices for protecting personal IoT data. Moreover, determining the level of confidence end users have in their smart devices is becoming a major challenge. In this paper, we present a study that focuses on identifying privacy concerns IoT end users have when using IoT smart devices. We investigated multiple smart devices and conducted a survey to identify users’ privacy concerns. Furthermore, we identify five IoT privacy-preserving (IoTPP) control policies that we define and employ in comparing the privacy measures implemented by various popular smart devices. Results from our study show that the over 86% of participants are very or extremely concerned about the security and privacy of their personal data when using smart IoT devices such as Google Nest Hub or Amazon Alexa. In addition, our study shows that a significant number of IoT users may not be aware that their personal data is collected, stored or shared by IoT devices.
Coherent microwave-optical photon conversion is a key enabling technology for the Quantum Internet, since it allows entanglement distribution among superconducting-based network nodes. A high-efficiency electro-optic transducer based on three-dimensional superconducting radio-frequency (SRF) technology has recently been proposed at Fermilab. In this paper, we evaluate the impact of Fermilab's transduction hardware on the entanglement generation probability and the entanglement rate, which are two critical metrics from a communication engineering perspective. Furthermore, we provide some guidelines to increase the direct entanglement rate, i.e., the rate before any entanglement purification process. Our analysis shows that, through high-efficiency transduction, it is possible to reduce the network overhead. This preliminary work paves the way toward distantly interconnected superconducting quantum processors.
Following recent advances in network infrastructure, cloud computing, and embedded systems, fascinating work is underway exploring the utility of demand response in increasing grid stability while permitting high penetration of intermittent renewable distributed generation resources. Although works have demonstrated diverse theoretical advantages of demand response programs, little real-world data are available and utilities generally remain reticent in moving forward with large-scale implementation due to risks inherent to any modification of the power system. Deciding that the next pertinent step in bringing demand response from theory to technology is developing an Internet-of-things hardware-in-the-loop simulation power system integrated device capable of empirically testing the theoretical mechanisms, this work presents an architecture testbed for providing demand response (telemetric monitoring and actuation of loads), which is real node in a power system simulation where virtual node's parameters derive real node data. Finally, we test a demand response algorithm, which provides frequency regulation services.
Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.
Sensor nodes play a crucial role in the promotion of development of Internet of Things (IoT). Through this transaction, RO defines access control policies in script form based on ABAC's access control model to grant access right. The identity of all users in the model is identified by address. This paper builds a more flexible right transfer access control model by means of combining the Attribute-Based Access Control model (ABAC) and blockchain technology. Owing to the characteristics of ABAC’s attributes and right association, the massive problems of some sensor nodes can be solved. At the same time, for the sake of addressing the dynamic problems such as node access and right transfer, right transfer contract (TS) and access control contract (CS) are employed on the chain to ensure efficient and safe transmission of rights. To solve on-chain storage problems and ensure transparency of the operation, the idea of Rollup in Ethereum expansion is used to upload the final state of protocol policy and right exchange to the chain. Any user can know the policy and current right transfer status at any time. Finally, comparative and security analysis show that the model presented here can solve IoT devices’ massive and dynamic problems more effectively and it is more secure than the traditional models.
Data analytics applied to nuclear power operations and nuclear safeguards is in a nascent state, yet some significant initial efforts are being undertaken by industry and academia. This report highlights our findings as to the current state-of-the-art of such efforts, in particular considering the Industrial Internet-of-Things aspect of this work, as well as an investigation into the utility of machine learning tools being developed for other industries. Blockchain applications were also studied. A consideration was undertaken into how to apply data analytics and machine learning to nuclear power and safeguards within the realm of Probabilistic Risk Assessments (PRAs), predictive maintenance & edge analytics, and proprietary data sharing.