scholarly journals Real-time Distributed In-Situ Benchmarking of Energy Harvesting IoT Devices

2018 ◽  
Author(s):  
Ashok Samraj Thangarajan ◽  
Fan Yang ◽  
Wouter Joosen ◽  
Danny Hughes
Keyword(s):  
Energy Harvesting ◽  
Real Time ◽  
Iot Devices

scholarly journals The Wireless Solution to Realize Green IoT: Cellular Networks with Energy Efficient and Energy Harvesting Schemes

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5875
Author(s):  
Yuan Ren ◽  
Xuewei Zhang ◽  
Guangyue Lu
Keyword(s):  
Energy Harvesting ◽  
Power Consumption ◽  
Real Time ◽  
Energy Efficient ◽  
Fog Computing ◽  
Random Access ◽  
Reducing Power ◽  
Effective Strategies ◽  
Iot Devices

With the tremendous increase of heterogeneous Internet of Things (IoT) devices and the different service requirements of these IoT applications, machine-type communication (MTC) has attracted considerable attention from both industry and academia. Owing to the prominent advantages of supporting pervasive connectivity and wide area coverage, the cellular network is advocated as the potential wireless solution to realize IoT deployment for MTC, and this creative network paradigm is called the cellular IoT (C-IoT). In this paper, we propose the three-layer structured C-IoT architecture for MTC and review the challenges for deploying green C-IoT. Then, effective strategies for realizing green C-IoT are presented, including the energy efficient and energy harvesting schemes. We put forward several strategies to make the C-IoT run in an energy-saving manner, such as efficient random access and barring mechanisms, self-adapting machine learning predictions, scheduling optimization, resource allocation, fog computing, and group-oriented transmission. As for the energy harvesting schemes, the ambient and dedicated energy harvesting strategies are investigated. Afterwards, we give a detailed case study, which shows the effectiveness of reducing power consumption for the proposed layered C-IoT architecture. Additionally, for real-time and non-real-time applications, the power consumption of different on-off states for MTC devices is discussed.

Probing the Dynamic Self-Assembly Behaviour of Photoswitchable Wormlike Micelles in Real Time

2018 ◽  
Author(s):  
Elaine A. Kelly ◽  
Judith E. Houston ◽  
Rachel Evans
Keyword(s):  
Real Time ◽  
Absorption Spectroscopy ◽  
Self Assembly ◽  
Uv Light ◽  
Wormlike Micelles ◽  
Tetraethylene Glycol ◽  
Light Illumination ◽  
First Time ◽  
Dependent Processes

Understanding the dynamic self-assembly behaviour of azobenzene photosurfactants (AzoPS) is crucial to advance their use in controlled release applications such as<i></i>drug delivery and micellar catalysis. Currently, their behaviour in the equilibrium <i>cis-</i>and <i>trans</i>-photostationary states is more widely understood than during the photoisomerisation process itself. Here, we investigate the time-dependent self-assembly of the different photoisomers of a model neutral AzoPS, <a>tetraethylene glycol mono(4′,4-octyloxy,octyl-azobenzene) </a>(C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>) using small-angle neutron scattering (SANS). We show that the incorporation of <i>in-situ</i>UV-Vis absorption spectroscopy with SANS allows the scattering profile, and hence micelle shape, to be correlated with the extent of photoisomerisation in real-time. It was observed that C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>could switch between wormlike micelles (<i>trans</i>native state) and fractal aggregates (under UV light), with changes in the self-assembled structure arising concurrently with changes in the absorption spectrum. Wormlike micelles could be recovered within 60 seconds of blue light illumination. To the best of our knowledge, this is the first time the degree of AzoPS photoisomerisation has been tracked <i>in</i><i>-situ</i>through combined UV-Vis absorption spectroscopy-SANS measurements. This technique could be widely used to gain mechanistic and kinetic insights into light-dependent processes that are reliant on self-assembly.

Flat Flexible Thin Milli-electrode Array for Real-time in situ Water Quality Monitoring in Distribution Systems

2017 ◽  
Vol 2017 (4) ◽  
pp. 5598-5617
Author(s):  
Zhiheng Xu ◽  
Wangchi Zhou ◽  
Qiuchen Dong ◽  
Yan Li ◽  
Dingyi Cai ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Distribution Systems ◽  
Electrode Array ◽  
Water Quality Monitoring ◽  
Quality Monitoring

scholarly journals Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Original Data ◽  
Local Analysis ◽  
Civil Infrastructure ◽  
Time Requirements ◽  
Iot Devices ◽  
Learning Reinforcement ◽  
The Times ◽  
Acquisition Processes

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.

scholarly journals Underground Microseismic Event Monitoring and Localization within Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Information Needs ◽  
Localization Algorithm ◽  
Distributed Sensors ◽  
Distributed Sensor ◽  
Microseismic Events ◽  
The Stability ◽  
Stability And Accuracy

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.

In-situ liquid cell transmission electron microscopy guiding the design of large-sized cocatalysts coupled with ultra-small photocatalysts for highly efficient energy harvesting

2021 ◽  
Author(s):  
Chunlang Gao ◽  
Chunqiang Zhuang ◽  
Yuanli Li ◽  
Heyang Qi ◽  
Ge Chen ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Energy Harvesting ◽  
Design Strategy ◽  
Efficient Energy ◽  
Highly Efficient ◽  
Transmission Electron ◽  
Cell Transmission ◽  
Liquid Cell

In this study, we employed in-situ liquid cell transmission electron microscopy (LC-TEM) to carry out the new design strategy of precisely regulating the microstructure of large-sized cocatalysts for highly efficient...

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