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检索条件"任意字段=5th IEEE International Conference on Distributed Computing in Sensor Systems"

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Printed Flexible Carbon Black-Based sensor for Nitrite Detection in Medical Applications 5

Printed Flexible Carbon Black-Based Sensor for Nitrite Detec...

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5th ieee international conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Shboul, Ahmad Al Pacheco, Dianne Izquierdo, Ricardo Department of Electrical Engineering 1100 Notre-Dame St W MontrealQCH3C 1K3 Canada

ISBN: (纸本)9781665457330

this work presents a novel printed and flexible sensor for detecting nitrite (NO2-) using a hybrid nanocomposite composed of carbon black (CB), polyvinyl butyral (PVB), and 4-aminophenol (AP). We prepared the NO2- sensor using a combination of simple mixed materials, and a moderate drying temperature of 40°. the sensor has two linear response ranges to NO2- from 25 μM to 1 mM and from 1 to 50 mM, with a detection limit of 25 μM at room temperature. Our results show that the sensor displays appropriate selectivity towards 50 μM of NO2- in the presence of potentially interfering anions and organic compounds that may be present in human urine. We propose that the sensing mechanism is based on the physical electrostatic interaction of NO2- molecules with AP's positively charged amine groups. this interaction results in a reduction of the electrical resistance when the sensor is exposed to NO2- anions. Our work highlights the potential of this printed sensor as a reliable and accurate tool for NO2- detection in medical applications. © 2023 ieee.

关键词： Carbon black

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the Parallelized Cuckoo Filter for Cold Data Representation 23

The Parallelized Cuckoo Filter for Cold Data Representation

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Sun, Bowen Luo, Lailong Li, Shangsen Chen, Yingwen Guo, Deke College of Computer National University of Defense Technology China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China College of Computer National University of Defense Technology National Lab for Parallel and Distributed Processing China

ISBN: (纸本)9781665494571

Cold data contributes a large portion of the big data today and is usually stored in secondary storage. Various sketch data structures are implemented to represent the stored elements and provide constant-time membership queries. Considering the large volume and infrequent access of cold data, we envision three rationales of cold data representation: 1) parallelized insertion, 2) accurate representation, and 3) constant-time query/deletion. the existing sketches, however, fail to achieve these rationales simultaneously. To this end, we propose a novel sketch named Parallelized cuckoo Filter (PCF) in this paper. PCF divides the standard cuckoo filter into multiple homogenous segments. An additional hash function is introduced to assign an element to a segment. the element will be inserted into the selected segment. With such a design, element insertions in PCF can be naturally parallelized. Besides, as a variant of the cuckoo filter, PCF naturally realizes the accurate representation and constant-time query/deletion requirements. Comprehensive experiments further indicate that PCF achieves the three rationales simultaneously. © 2021 ieee.

关键词： Hash functions Smart cities Big Data Data structures Standards

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Optimal Placement and Power Supply of distributed Generation to Minimize Power Losses 14

Optimal Placement and Power Supply of Distributed Generation...

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14th ieee international conference on Communications, Control, and computing Technologies for Smart Grids, SmartGridComm 2023

作者： Pan, Shijie Maleki, Sajjad Lakshminarayana, Subhash Konstantinou, Charalambos Cemse Division Saudi Arabia University of Warwick School of Engineering Coventry United Kingdom

ISBN: (纸本)9781665455541

An increasing number of renewable energy-based distribution generation (DG) units are being deployed in electric distribution systems. therefore, it is of paramount importance to optimize the installation locations as well as the power supply of these DGs. the placement of DGs in the grid can decrease the total distance that power is transmitted and thus reduce power losses. Additionally, the reactive power supply from the DGs can further reduce power losses in the distribution grid and improve power transmission efficiency. this paper presents a two-stage optimization strategy to minimize power losses. In the first stage, the DG locations and active power supply that minimize the power losses are determined. the second optimization stage identifies the optimal reactive power output of the DGs according to different load demands. the proposed approach is tested on the ieee 15-bus and the ieee 33-bus systems using DIgSILENT PowerFactory. the results show that the optimized power losses can be reduced from 58.77 kW to 3.6 kW in the 15 -bus system, and from 179.46 kW to around 5 kW in the 33 -bus system. Moreover, with the proposed optimization strategy, voltage profiles can be maintained at nominal values enabling the distribution grid to support higher load demand. © 2023 ieee.

关键词： distributed power generation

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Curvature and Contact Sensing with Optical Waveguides for Soft Silicone Pneumatic Actuator 5

Curvature and Contact Sensing with Optical Waveguides for So...

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5th international conference on Soft Robotics (RoboSoft)

作者： Aljaber, Faisal Hassan, Ahmed Vitanov, Ivan Althoefer, Kaspar Queen Mary Univ London Sch Engn & Mat Sci London England Queen Mary Univ London Sch Elect Engn & Comp Sci London England

ISBN: (纸本)9781665408288

Optical waveguide sensors exhibit fast response, radically low power consumption, and offer one of the most efficient means of detecting bends in soft actuators. they are, however, sensitive to non-uniform deformations at high curvature and external stimuli and much remains to be done to improve their robustness and resilience. In this study, we present a series of improvements to the design and fabrication of a soft multi-point waveguide sensor. the developed pressure-sensitive sensor measures bending longitudinally along a soft silicone pneumatic actuator (SSPA). SSPAs exhibit uniform bending behaviour as compared to fabric-based actuators, which makes for a more stable medium within which to embed our sensor. Additionally, the sensor can detect bending behaviour at multiple points in a soft actuator. In previous work, we demonstrated the multi-point sensor's ability to accurately measure curvature in a fabric finger. In this paper, we report on various enhancements to the waveguide sensor that optimise its performance in various bending scenarios. the design is optimised in terms of novel material use for the sensor housing, reduction in size and weight, plus, by integrating with an SSPA, we achieve bending beyond 90 degrees. the newly optimised sensor's characteristics and increased sensitivity are investigated by performing reliability tests, ten-cycle cyclic-compression tests, and free bending. In addition, we subject the actuator to bending while grasping various shapes, including a sphere, a hollow cylinder, a cube, and a hexagon, while varying the pressure intake.

关键词： Pneumatic actuators Shape Optical device fabrication Bending sensor phenomena and characterization Soft robotics Robot sensing systems

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Deep Learning based Channel Estimation for Full-Duplex Backscatter Communication systems 5

Deep Learning based Channel Estimation for Full-Duplex Backs...

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5th international conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Jung, Chae Yoon Kang, Jae Mo Kim, Dong In Sungkyunkwan Univ SKKU Dept Elect & Comp Engn Dept Superintelligence Engn Suwon South Korea Kyungpook Natl Univ Dept Artificial Intelligence Daegu South Korea

ISBN: (纸本)9781665456456

A novel deep learning (DL) based channel estimation method is proposed for full-duplex backscatter communication systems to realize the wireless-powered sensor networks (WPSN) for internet of things (IoT). We aim to minimize the power consumption at a sensor node by reflecting the supplied power signal from an access point (AP), which is called backscatter communication. Moreover, by adopting the frequency-shifted modulation technique during backscatter transmission, full-duplex communication is performed between the AP and the sensor node. However, this incurs a problem that the uplink and downlink channels are cascaded, which results in degrading the performance of beamforming. In order to overcome this problem, we propose a novel channel estimation method that extracts separate uplink and downlink channels from the cascaded channels. We formulate the problem for joint channel estimation and pilot optimization, and then design the DL based channel estimator, which is composed of feedforward neural network(FNN) and convolutional neural network(CNN), for compensating non-linearity and non-convexity. Finally, we analyze the performance of the proposed DL based channel estimator compared to the conventional channel estimator.

关键词： Beamforming channel estimation (CE) deep learning (DL) full-duplex backscatter communication internet of things (IoT) wireless-powered sensor networks (WPSN)

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Sensing the Future: Challenges and Trends in IoT sensor Technology 4

Sensing the Future: Challenges and Trends in IoT Sensor Tech...

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4th international conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Rajora, Ricky Rajora, Aarju Sharma, Bhanu Aggarwal, Priyanshi thapliyal, Siddhant Chitkara University Institute of Engineering and Technology Chitkara University Punjab 140401 India Chandigarh Engineering College Department of Computer Science & Engineering Mohali India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350307757

In the ever-evolving world of the Internet of things (IoT), sensors play a crucial role as essential parts, linking and merging different elements to create a smart worldwide network. this study examines the crucial function of sensors in the Internet of things (IoT) ecosystem, where they serve as sensory organs that translate the intricacies of the physical world into a uniform language for networked systems. the main emphasis is on their ability to gather and evaluate factual data from the surroundings, which impacts the performance and effectiveness of IoT applications in many industries. this research explores the uses and relevance of many sensor types, including temperature, humidity, proximity, motion, gas, biometric, vibration, image, infrared (IR), occupancy, water quality, pressure, light, and sound sensors. Although sensors contribute to the improvement of automation, control systems, and predictive analysis, they also give rise to issues in terms of security, interoperability, and power efficiency. the convergence of edge computing, artificial intelligence (AI), quantum sensors, 5G connection, and improved sensor integration has the potential to bring about significant changes in the Internet of things (IoT) environment. the study provides a thorough survey of sensor applications in several domain including healthcare, agriculture, smart cities, and automotive sectors. Lastly, it examines the difficulties and potential opportunities, highlighting the vital significance of sensors in influencing the future of interconnection and data-driven decision-making. © 2024 ieee.

关键词： Internet of things

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Privacy-Preserving Collaborative AI for distributed Deep Learning with Cross-sectional Data 5

Privacy-Preserving Collaborative AI for Distributed Deep Lea...

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5th international conference on Bio-engineering for Smart Technologies, BioSMART 2023

作者： Iqbal, Saeed Qureshi, Adnan N. Aurangzeb, Khursheed Javeed, Khalid University of Central Punjab Faculty of Information Technology & Computer Science Department of Computer Science Lahore Pakistan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia University of Sharjah College of Computing and Informatics Department of Computer Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350338492

the article discusses the challenges of using deep learning in healthcare due to the lack of extensive medical datasets and concerns about confidentiality and privacy. the article then focuses on the analysis of skin lesion images, which are complex and difficult to classify. the article presents a unique CNN model (skin-net) using a progressively private federated learning architecture to potentially address these issues. Recent advancements in medical image analysis using convolutional neural networks and federated learning techniques have shown promising results (96.19 accuracy, 96.37 sensitivity and 96.53 specificity) in accurately classifying skin diseases while maintaining data privacy. Using these methods offers a potentially effective way to examine human skin while improving the model's generalization performance through image augmentation. © 2023 ieee.

关键词： Deep learning

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Machine Learning Based Characterization of a Waterproofed Soft Multi-Directional Force sensor 5

Machine Learning Based Characterization of a Waterproofed So...

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5th ieee international conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Hasan Saikot, Md Mahmud Shafatul Islam Subad, Rafsan Al Park, Kihan Bangladesh University of Eng. and Tech. Department of Mechanical Engineering Dhaka1000 Bangladesh University of Massachusetts Dartmouth Department of Mechanical Engineering North DartmouthMA02747 United States

ISBN: (纸本)9781665457330

A cost-effective soft multi-directional force sensor can enable next-generation robots to recognize object features by touch, similar to humans. this paper presents a novel approach for force region classification on a soft hemispherical sensor made up of four flex sensors placed 90° apart. By considering a quarter of the hemisphere due to its symmetry, we effectively divided the sensor into three distinct regions where force can be applied. We used the K-means clustering algorithm to classify the region of the applied force, which successfully categorized all 60 test trials into the correct force regions. the effective range for detection was about 1.5 - 5 N of force. Our experimental results also showed that the sensor responded well to being kept submerged in salt water for 7 days, indicating its suitability for operation in underwater environments. this study opens up possibilities for 3D multi-directional force recognition using the soft sensor, which has potential usage in diverse fields, such as robotics and healthcare, even in challenging underwater environments. © 2023 ieee.

关键词： Cost effectiveness

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Towards Ambiently Powered Inference on Wireless sensor Networks: Asynchrony is the Key! 17

Towards Ambiently Powered Inference on Wireless Sensor Netwo...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Papageorgiou, Vasileios Nichoritis, Athanasios Vasilakopoulos, Panagiotis Vougioukas, Georgios Bletsas, Aggelos Tech Univ Crete Sch Elect & Comp Engn Khania 73100 Greece

ISBN: (纸本)9781665439299

Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication principles and make autonomous, in-network decisions, solely powered by the environment? While edge and cloud computing emerge, this work points towards the opposite direction, inspired by the fact that ambient energy, either from radio frequency (RF), sun, motion, temperature or even living organisms, has fixed (on average) density per surface (or volume). It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, message passing problem. Examples from Gaussian Belief Propagation and Average Consensus are offered;ambient energy harvesting and availability are quantified, controling the probability of successful (or not) message passing. Such interrupted communication requires distributed algorithms robust to asynchrony, at the expense of increased overall delay. Simulation and experimental validation are offered in a WSN testbed with solar energy harvesting. Future work will focus on overall delay minimization.

关键词： Wireless communication Wireless sensor networks Message passing Solar energy sensor systems Delays Low-power electronics

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Wireless sensor Network Using IOT Security: Architecture, Challenges and Proposed Model 5

Wireless Sensor Network Using IOT Security: Architecture, Ch...

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5th international conference on Contemporary computing and Informatics, IC3I 2022

作者： Verma, Abhishek Singh, Akhilesh Chauhan, Anurag Rana, Arun Kumar Galgotias College of Engineering and Technology Dept. of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350398267

Cloud computing, near-field communication, wireless cellular networks, etc. are only a few of the associated technological advancements that have gained widespread market adoption in relation to the Internet of things. therefore, from an IoT viewpoint, it is crucial to pay attention to its applicability and feasibility features in connection to pertinent security concerns. this paper's goal is to analyse and illustrate how security issues with wireless sensor networks affect the Internet of things and its applications. As a result, this publication offers an overview of the major and secondary security requirements for wireless sensor networks together with a taxonomy of potential threats and attacks against these requirements. Despite recent advancements in WSN technology, the application still confronts major difficulties because these sensors are often put in remote places. the main issues here include risks to network security, network architecture, data collecting and deployment, and network coverage. these five subjects have so been extensively researched in the literature. this paper's major goal is to thoroughly discuss these challenges and proposed model with solution (Contiki Cooja) also discussed in details © 2022 ieee.

关键词： Wireless sensor networks

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