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advanced sensor for Arsenic and Fluoride Detection 26th

Advanced Sensor for Arsenic and Fluoride Detection

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26th International conference on Hydraulics, Water Resources and Coastal Engineering, HYDRO 2021

作者： Pandey, Shivani Mishra, Satanand Dwivedi, Vijay Kumar Sardar, Tanmay Singh, Archana Bhargav, Hari Narayan Department of CARS & GM AcSIR—CSIR-Advanced Materials and Processes Research Institute Madhya Pradesh Bhopal462026 India Department of Civil Engineering National Institute of Technology Durgapur Durgapur India Mechanical Engineering Department Motilal Nehru National Institute of Technology Allahabad211004 India Department of Intelligent Materials and Advanced Processes AcSIR—CSIR-Advanced Materials and Processes Research Institute Madhya Pradesh Bhopal462026 India

ISBN: (纸本)9789811991509

Arsenic and Fluoride on the top of hazardous contaminants in water that has been exposed to root substantial effects in individuals through drinking water. It affects more than 200 million individuals spread over 50 countries and could enter the human body through the absorption of nutrient, drinking water system, inhalation, and dermic interaction. To ensure safety, it is critical not only to detect but also precisely quantify aqueous Arsenic and Fluoride. The urgent need is to develop a smart water quality testing systems that are capable of collecting real-time geolocated water quality data without the requirement for professional experience using. Synthesized nanoparticles and carbon quantum dots materials for a fluorometric detection and quick quantification of Arsenic and Fluoride in drinking water. The quantum dots mechanism has been completely defined, and the sensing mechanism has been systematically implemented. FTIR and XPS techniques are used for specific functional group determination and TEM for morphological and structural detection. Developed materials are extremely selective for Arsenic and Fluoride both, based on functional group selectivity. Synthetic Arsenic and Fluoride standards and water samples from impacted regions were used to test the sensing material’s consistency in performance. The proposed sensor detects Arsenic and Fluoride in common applications for non-expert users, especially in rural locations. The Artificial Intelligence is used for water quality monitoring. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Potable water

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A Smart Robotic Device for Automated Environmental Monitoring: An Integrated Approach for Real-Time Data Collection and Analysis

A Smart Robotic Device for Automated Environmental Monitorin...

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Computational Intelligence Approaches and applications (ICCIAA), International conference on

作者： Amjad Aldweesh College of Computing and IT Shaqra University Shaqra Saudi Arabia

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Smart robotic devices have emerged as a promising solution for automated environmental monitoring that addresses the limitations of traditional monitoring methods. We present a novel smart robotic device that integrates advanced mobility, energy management, data processing, and sensor modularity. The device features a robust chassis structure that supports a terrain-adaptive mobility assembly, a 360-degree rotational modular sensor arm, an onboard data processing unit, and a power management system with a rechargeable battery and a solar panel assembly. This integrated approach enables continuous, real-time data collection and analysis in diverse and challenging environments. The modular design of the device facilitates rapid customization and upgrades to meet specific monitoring needs, ensuring versatility and extended service life. We discuss the key components of the device, their interactions, and the advantages of this integrated approach for environmental monitoring applications.

关键词： Smart cities Power system management Data collection Robot sensing systems Smart systems Real-time systems Environmental monitoring Solar panels Resource management Assembly

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

16th International Joint Conference on Biomedical Engineerin...

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

The proceedings contain 196 papers. The special focus in this conference is on Biomedical Engineering systems and Technologies. The topics include: Monitoring of Vital Signs in the Home Environment: A Review of Current Technologies and Solutions;Analysis of a Simple Method to Change the Wettability of the PDMS Surface for Biomicrofluidic applications;in Vitro Flow Study in an Intracranial Aneurysm Biomodel Manufactured by Additive Manufacturing;a Novel Multi-Modal Sensing System Prototype for Cardiovascular and Cardiopulmonary Monitoring;A Novel Microfluidic Pressure sensor for Traditional Chinese Medicine (TCM) Pulse Data Collection and Analysis;design and Manufacturing of Microtextured Patient-Specific Coronary Stent;ultra-Low Power Electronic Circuits Inspired by Biological Genetic Processes;in silico Tissue Engineering and Cancer Treatment Using Cellular Automata and Hybrid Cellular Automata-Finite Element Models;4D Printed Surgical Devices: Current Capabilities and Challenges;bioimpedance Simulations for the Monitoring of Fluid Overload in Heart Failure Patients;towards an Intelligent Triage Bracelet: A Conceptual Study of a Semi-Automated Prehospital Triage Algorithm and the Integration of Blood Pressure Measurement;simulating the Effects of Melanin and Air Gap Depth on the Accuracy of Reflectance Pulse Oximeters;a Portable System for Screening of Cervical Cancer;A Modular BLE-Based Body Area Network Embedded into a Smart Garment for Rescuers Real-Time Monitoring in Emergency Scenarios;enhancing Men’s Health Management at Home with an Easy-to-Use, App-Connected Prostate Self-Testing Device;towards a Synthetic Tissue Model of the Lower Urinary Tract;biomechanical System Prototype with advanced Biofeedback for Rehabilitation of Bedridden Patients;smartphone sensors to Measure Individual Sleeping Pattern: Experimental Study.

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QHSL image encryption scheme based on a logistic chaotic system 23

QHSL image encryption scheme based on a logistic chaotic sys...

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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： Yan, Fei Li, Mao Li, Nianqiao Iliyasu, Abdullah M. School of Computer Science and Technology Changchun University of Science and Technology Changchun130022 China College of Engineering Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

ISBN: (纸本)9781665494571

On digital computers, the hue, saturation, and lightness (HSL) image model is especially useful in feature detection, image segmentation, and other operations in robot vision, object recognition, etc. On the quantum computing paradigm, such a model was only recently formulated and many new inroads with it are just beginning. Our study proposes a scheme to secure quantum images encoded using the quantum HSL (QHSL) image model. The proposed QHSL encryption scheme (or simply QHES) utilises logistic mapping to induce the chaotic system at the heart of the QHES strategy. The scheme consists of a quantum logistic chaos unit composed of quantum arithmetic modules to generate chaotic sequences. This is followed by a quantum logistic key generation that is subsequently used to encrypt the HSL components of QHSL images. The proposed scheme exploits quantum parallelism to execute its encryption procedure which leads to significant reduction in computational resources. Results of simulation-based experiments reported suggest potentials of the proposed QHES as an efficient cryptosystem on quantum computers. © 2021 IEEE.

关键词： Heart Image segmentation Quantum computing Computational modeling Feature detection Robot vision systems Parallel processing

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

16th International Joint Conference on Biomedical Engineerin...

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

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Raspberry Pi-based cluster network for the emulation of sensor networks in remote teaching 15

Raspberry Pi-based cluster network for the emulation of sens...

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15th International conference of Technology, Learning and Teaching of Electronics (TAEE)

作者： Parejo, Antonio Garcia, Sebastian Francisco Larios, Diego Gallardo, Alejandro Luque, Joaquin Leon, Carlos Univ Seville Dept Tecnol Elect Seville Spain

ISBN: (纸本)9781665421614

Due to their versatility, sensor networks and Internet of Things (IoT) have become technologies of a great importance in many modern applications in so-diverse ambits such as environmental monitoring and smart cities. Therefore, these are included in the contents of the subject "advanced sensor Network Infrastructure" of the Master on Intelligent systems on Energy and Transport of the University of Seville. This subject serves as an introduction to sensor networks, their applications, and their operating principles. Its schedule includes laboratory lessons in which the students use various sensor devices for learning about the existing communication and processing methods. The health crisis caused by the COVID-19 has made difficult that all the students have physical access to the laboratory at the same time, which forced to adapt the existing materials and facilities. In this sense, to solve this problem, a Raspberry Pi-based computer network has been deployed to allow the emulation of a sensor network while providing external remote access to the students for them to perform their laboratory tasks. At the same time, this proposal has expanded the subject contents to cover several data processing layers and architectures.

关键词： remote teaching Raspberry Pi emulation sensor network online

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

16th International Joint Conference on Biomedical Engineerin...

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

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Machine Learning-Based sensor Synchronization for Enhanced Spatial Awareness in Assistive Technologies

Machine Learning-Based Sensor Synchronization for Enhanced S...

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Intelligent systems and advanced applications (ICISAA), International conference on

作者： Iftekar Patel Makarand Kulkarni Ninad Mehendale K. J. Somaiya College of Engineering Somaiya Vidyavihar University Mumbai India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

Enhancing spatial awareness for the visually impaired is crucial for autonomy and mobility. Our research addresses this by proposing a novel approach to sensor data synchronization for assistive technologies, re-framing the challenge as a forecasting task suitable for machine learning solutions. We developed a hard hat assembly equipped with 2D LiDAR, dual 1D LiDARs, and a depth camera to create comprehensive spatial awareness for navigation. By applying various machine learning algorithms to predict 2D LiDAR readings from higher frequency 1D LiDAR data, we aimed to overcome conventional synchronization limitations. Our investigation revealed that while linear models and some non-linear approaches were inadequate, the Generalized Auto-regressive Conditional Heteroskedasticity (GARCH) model showed promise in capturing short-term volatility. Our findings contribute to assistive technologies by introducing a machine learning paradigm for sensor synchronization, potentially improving spatial awareness systems’ accuracy and reliability. This system has the potential to significantly enhance navigation for the visually impaired, fostering greater independence and safety.

关键词： Laser radar Accuracy Navigation Machine learning Assistive technologies Predictive models Robot sensing systems Synchronization Reliability Frequency synchronization

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

16th International Joint Conference on Biomedical Engineerin...

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16th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

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Quality and Trust Indicators of Digital Road Infrastructure Data Are Essential to Improve Its Usability: An Intelligent Speed Assist (ISA) Study 11

Quality and Trust Indicators of Digital Road Infrastructure ...

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11th International conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2025

作者： van de Sluis, Jacco Altgassen, Daniel Schackmann, Peter-Paul Networks Department TNO - ICT The Hague Netherlands Integrated Vehicle Safety Department TNO - Mobility & Build Environment Helmond Netherlands

ISBN: (纸本)9789897587450

The promise of a Digital Road Infrastructure (DRI) is to improve both road and vehicle safety. ADAS/ADS with DRI support, can help vehicles in overcoming certain sensor limitations, handle more complex operational situations and offer additional situational awareness. An effective DRI must be trusted and must offer the required data quality, both are currently lacking. Intelligent Speed Assist (ISA) is an interesting show case for the added value of DRI. In our approach camera-based traffic sign detections and map-based speed limit information, both occasionally wrong, are augmented with actual speed limit and road layout information coming from DRI. A Misbehaviour Detection and Reporting (MBD&R) concept tailored to the ISA sources is deployed in the vehicle to detect and report ISA related misbehaviour. Trust and quality indicators are calculated for data coming from camera, map and DRI, which are used to verify and compare theses sources and make improved ISA speed limit decisions. The vehicle implementation is tested under real-life traffic conditions. Our work is a first step in realizing a trusted DRI. The long-term goal is collaboration among all stakeholders to implement mechanisms that improve trust and the quality of shared data sources for use in traffic safety applications. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： advanced driver assistance systems

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