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Improving Energy Efficiency using Colliding Bodies Optimization based Routing Protocol for Wireless sensor Networks

Improving Energy Efficiency using Colliding Bodies Optimizat...

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Electronics and Renewable systems (ICEARS), International conference on

作者： P. Prabakaran R. Shalini N Hariharan S. Marieswari Kallakunta Ravi Kumar Maturi Gayatri Lakshmi Apoorva Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Chennai Department of BCA & IT School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Chennai Science and Humanities – EEE R.M.K. College of Engineering and Technology Thiruvallur India Biomedical Engineering P. S. R. Engineering College Department of ECE Koneru Lakshmaiah Education Foundation Vaddeswaram ECE Department Amrita School of Engineering

Wireless sensor network (WSN) contains millions of small, low-power gadgets with a lack of resources are memory and battery power. Such gadgets were deployed in a dispersed manner and were often utilized to monitor and sense applications. Owing to constraints and limited resources of WSNs, routing can be a great difficulty. Routing in WSN was the process of choosing the optimal path for data to travel from a source node to a destination node. The goal of routing in WSN offer dependable and effective transmission while minimizing network overhead and energy consumption. This study designs an Energy Efficient Colliding Bodies Optimization based Routing Protocol (EECBO-RP) for WSN. The end goal of the EECBO-RP algorithm lies in the optimal election of routes to a destination. For achieving reasonable results for the minimization of energy exploitation, the EECBO-RP system derives the fitness function using the following variables: residual energy, distance to BS, and node degree. The EECBO-RP technique chooses the relay nodes so that a way that the overall efficiency of the WSN gets maximized. The simulation values of the EECBO-RP system are tested under several dimensions and the outcomes pointed out the betterment of the EECBO-RP technique.

关键词： Wireless sensor networks Renewable energy sources Voting Routing Minimization Routing protocols Energy efficiency

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ML Enhanced Autonomous Night Patrol Robot for Intelligent Security

ML Enhanced Autonomous Night Patrol Robot for Intelligent Se...

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Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： L.Raja Ganeshkumar.A Abinesh.K Aswin.V Hariharan.S Department of ECE Sri Eshwar College of Engineering Coimbatore India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

The ML-Enhanced Autonomous Night Patrol Robot discussed here is designed to enhance security in any environment when carrying out operations during the night. Using advanced sensor technologies such as LiDAR, ultrasonic sensors, and night vision cameras combined with machine learning algorithms, the robot can navigate complex terrain independently and correctly detect and classify any danger in real-time. Through the utilization of deep learning models, the surveillance of the robot is enhanced as it can recognize objects and adapt to dynamic security conditions. Edge computing also facilitates easy management of data in real-time and interaction with security personnel, which ensures timely incident responses. Overall, the proposed robot provides an extensible solution for smart security applications, significantly enhances security efficiency, and reduces reliance on human patrols.

关键词： Night vision Materials science and technology Navigation Microcontrollers Surveillance Robot vision systems Cameras Real-time systems Security Personnel

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Stiffness Assessment in tissue grasping using surgical tool integrated with Fiber Bragg Grating sensor

Stiffness Assessment in tissue grasping using surgical tool ...

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IEEE International conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Padmanaban S Srijith Kanakambaran Pravin Kumar Subbaraj Department of Biomedical Engineering Sri Sivasubramaniya Nadar College of Engineering Chennai India Department of Electronics and Communication Engineering Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

This paper presents an investigation into tissue grasping dynamics utilizing a novel approach with a polydimethylsiloxane (PDMS) embedded fiber Bragg grating (FBG) sensor. The study aims to characterize the mechanical behavior of tissues during grasping maneuvers, comparing the effects of finger and palm grasping techniques. Four distinct tissue sample models, including PVC, foam, silicone rubber, and plexiglass, were employed to replicate tissue properties. The PDMS embedded FBG sensor facilitated real-time monitoring of wavelength shifts, enabling the calculation of strain during grasping. From the resultant force and strain data, tissue stiffness was quantified. Notably, the results revealed significant differences in tissue stiffness between finger and palm grasping, with higher forces observed during palm grasping. This investigation sheds light on the mechanical interactions between tissues and grasping instruments, providing valuable insights for the development of advanced surgical tools and robotics applications.

关键词： Minimally invasive surgery Wavelength measurement Force Fingers Grasping Robot sensing systems Fiber gratings

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A Cost-Effective Real-Time Water Quality Monitoring System

A Cost-Effective Real-Time Water Quality Monitoring System

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Power, Electrical, and Electronics and Industrial applications (PEEIACON), IEEE International conference on

作者： Anik Ghosh Md Manirul Islam Bishowjit Paul Saydul Mursalin Peash Nazmul Islam Multazimul Islam Mohammad Fahim Hossain Md Hasibul Islam Hasib Sarafat Hussain Abhi Mechatronics Engineering RUET Rajshahi Bangladesh

ISBN: (数字)9798331517984

ISBN: (纸本)9798331517991

Ensuring access to safe drinking water is critically important, particularly in regions facing scarcity and contamination challenges. This paper presents a cost-effective, IoT-based water quality monitoring system specifically designed for rural areas. The system measures key water parameters, including pH, turbidity, temperature, electrical conductivity, and TDS. It integrates an ESP8266 for data acquisition, filtering, and transmission to RTWQMS, a real-time web-based application for data visualization, which utilizes an inference engine for binary decision-making. The system's architecture is structured into three layers: the Physical Layer (sensors), the Network Layer (ESP8266), and the Application Layer (RTWQMS). This project aims to provide an affordable solution for continuous water quality assessment, thereby ensuring safe drinking water in underserved communities. Future developments will include the integration of an expert system for decision-making using advanced machine learning algorithms for multi-class classification of water quality.

关键词： Temperature measurement Temperature sensors Decision making Turbidity sensor systems and applications Physical layer Water pollution Real-time systems Pollution measurement Monitoring

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Enhancing Reliability in Wireless sensor Networks through Cluster Based Optimization

Enhancing Reliability in Wireless Sensor Networks through Cl...

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Science and Information Technology in Smart Administration (ICSINTESA), International conference of

作者： Yaqin Jasim Abd Hashim Saad Talib Hasson University of Babylon Iraq

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

This study delves into enhancing the reliability of Wireless sensor Networks (WSNs) through the implementation of the Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm. WSNs play a vital role in various domains, including environmental monitoring and industrial automation, necessitating dependable data transmission. Initially, the research evaluates the reliability of WSNs without clustering, serving as a baseline. Subsequently, LEACH is applied to organize sensors into clusters, optimizing energy usage and network efficiency. The focus lies on improving reliability metrics, such as packet delivery ratio (PDR), which quantifies the proportion of successfully transmitted data packets. Through simulation and analysis, the effectiveness of LEACH in enhancing reliability is thoroughly examined. The results demonstrate a significant enhancement in reliability, indicating a substantial reduction in packet loss and data inconsistency. This reliability enhancement is attributed to the intelligent clustering of sensors, which minimizes energy consumption and optimizes data routing. The findings underscore the importance of employing advanced algorithms like LEACH to bolster the reliability of WSNs, ensuring accurate and timely data delivery in critical applications.

关键词： Wireless sensor networks Adaptive systems Scalability Clustering algorithms Packet loss Routing Energy efficiency Delays Reliability Intelligent sensors

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A 32×32 SPAD LiDAR sensor with In-pixel Spatial-temporal Coincidence and Per-SPAD Pulse Delay for Resolution-lossless Imaging

A 32×32 SPAD LiDAR Sensor with In-pixel Spatial-temporal Co...

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IEEE Asian conference on Solid-State Circuits (ASSCC)

作者： Bu Chen Zhangcheng Huang Jingyi Wang Hongyang Shang Hankun Lv Qi Liu Ming Liu State Key Lab of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University

ISBN: (数字)9798350376326

ISBN: (纸本)9798350376333

Single-photon Avalanche Diode (SPAD)-based LiDAR technology finds significant applications in advanced driver assistance systems, etc. Extracting distance information necessitates creating a histogram from enormous frames to filter out the overwhelming background light (BGL) data. As the formats of SPAD pixel arrays scaling up [1], the processing, storage, and transmission of extensive data result in ultra-high power consumption and increased layout area. In order to reduce BGL, previous studies [2][3] [4] have leveraged spatial coincidence and histograms in pixels, and [5] utilized external double pulses to enhance the signal-to-noise ratio. However, a significant amount of data still needs to be processed within the sensor. To address these challenges, this paper presents a $32 \times 32$ SPAD LiDAR sensor that incorporates in-pixel spatial-temporal coincidence to effectively compress random background light and a per-SPAD pulse delay method to realize resolution-lossless imaging. This approach achieves an impressive 98.3% compression rate of background light under 100 klux illumination while maintaining a low power consumption of $14.6 \mu \mathrm{~W}$ per pixel.

关键词： Histograms Laser radar Power demand Imaging Delays Solid state circuits Spatial resolution Signal resolution Single-photon avalanche diodes Signal to noise ratio

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A Numerical Investigation of Potential Ion Current sensor applications in Premixed Charge Compression Ignition Engine 3

A Numerical Investigation of Potential Ion Current Sensor Ap...

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SAE 2022 3rd conference on Sustainable Mobility, CSM 2022

作者： Golc, Dominik Esposito, Stefania Loffredo, Francesca Pitsch, Heinz Beeckmann, Joachim RWTH Aachen University Germany

Simultaneous reduction of engine pollutants (e.g., CO, THC, NOx, and soot) is one of the main challenges in the development of new combustion systems. Low-temperature combustion (LTC) concepts in compression ignition (CI) engines like premixed charged compression ignition (PCCI) make use of pre-injections to create a partly homogenous mixture. In the PCCI combustion regime, a direct correlation between injection and pollutant formation is no longer present because of long ignition delay times. In LTC combustion systems, the in-cylinder pressure sensor is normally used to help the combustion control. However, to allow the control of PCCI engines, new sensor concepts are investigated to obtain additional information about the PCCI combustion for advanced controller structures. In LTC combustion systems like gasoline-controlled autoignition (GCAI) concepts, the application of ion current sensors enables additional monitoring of the combustion process with real-time capability. In analogy to GCAI, the use of an ion current sensor for the control of PCCI combustion in diesel engines could allow effective pollutant and combustion control. To investigate the potential of the application of an ion current sensor for controlling a PCCI engine, numerical engine investigations have been performed and are presented in this work. Experimental data of a single cylinder engine (SCE) are used to validate a RANS 3D-CFD simulation framework focusing on the prediction of engine-out emissions. The assembled chemical kinetic model accounts for ion and NOx formation inside the combustion chamber. After model validation, operating conditions with varying pre-injection patterns were analyzed to find correlations between pollutant and ion formation. The simulation results show a correlation between NOx and ion formation, suggesting that engine controls relying on ion current measurements potentially allow for a reduction of NOx emissions. Applying ion current sensors to control PCCI combust

关键词： Temperature

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A Simple Piezoelectric Structural Health Monitoring System for use in concrete applications in Real-Time

A Simple Piezoelectric Structural Health Monitoring System f...

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Modeling, Simulation & Intelligent Computing (MoSICom), International conference on

作者： Vijai Meyyappan Moorthy Deevi Radha Rani M Karthikeyan Challagulla Teja Amrutha Sai Department of Advanced Computer Science and Engineering Vignan’s Foundation for Science Technology and Research Guntur Andhra Pradesh India Department of Civil Engineering Vignan’s Foundation for Science Technology and Research Guntur Andhra Pradesh India

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

This study outlines the creation of a piezoelectric sensor-based system for real-time building monitoring. The sensors convert mechanical vibrations and stresses in the building structure into electrical impulses using the piezoelectric effect. Signal processing is used to discover abnormalities and structural defects in these signals. Their noise floor should be almost zero and their sensitivity high. The proposed technology monitors the building structure instantly, allowing early detection of problems and prompt repairs. Laboratory and outdoor studies prove the approach can effectively detect and pinpoint construction faults. This project aims to create a piezoelectric sensor-based structural health monitoring (SHM) system. Empirical testing showed that these sensors had great sensitivity, low noise, and good sensor resolution. Indeed, they outperform commercial equipment.

关键词： Vibrations Sensitivity Buildings Noise Piezoelectric effect Real-time systems Monitoring Intelligent sensors Stress Testing

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Smart Water-Powered Renewable Energy System with IoT Integration

Smart Water-Powered Renewable Energy System with IoT Integra...

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Decision Aid Sciences and Application (DASA), International conference on

作者： Amjed Abbas Ahmed Ali Hamza Najim Ahmed Salman Ibraheem Khattab M. Ali Alheeti Nurhizam Safie Mohd Satar Aisha Hassan Abdallah Hashim Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Imam AlKadhum College (IKC) Baghdad Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Al-Diwaniyah Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Baghdad Iraq Computer Networking Systems Department College of Computer and Information Technology University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Malaysia Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

An advanced hybrid renewable energy collecting and storage system prototype that utilizes water flow as its primary power source. Additionally, the system incorporates an energy monitoring system based on the Internet of Things (IoT) technology. The device effectively harnesses energy from the movement of water, storing it for future use in low-voltage applications. It demonstrates a maximum daily energy capture capacity of about 100Wh. The energy monitoring system, based on the Internet of Things (IoT), enables the real-time and remote monitoring of energy harvesting and usage. We thoroughly assessed the energy harvesting component across different situations to identify the crucial parameters that impact energy output. The results of our study demonstrate that several elements, including the spatial separation “between the energy harvester and the water source, Water flow” speed, sensor orientation, and sensor density, all play significant roles in determining the quantity of energy collected. This research shows that it is possible to integrate IoT technology with hydropower renewable energy systems. It provides significant perspectives on enhancing energy extraction efficiency in practical scenarios.

关键词： Renewable energy sources Low voltage Prototypes Real-time systems Internet of Things Energy harvesting Water resources Remote monitoring sensor arrays Pragmatics

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advanced Gas sensor Design: A Machine Learning Perspective on Photonic Crystals

Advanced Gas Sensor Design: A Machine Learning Perspective o...

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IEEE Electron Devices Kolkata conference (EDKCON)

作者： Debjyoti Karmakar Joydip Saw Debashis Modak Subhajit Pramanick Suman Pal Kanishka Majumder Electronics and Communication Engineering Academy of Technology (MAKAUT) Hooghly West Bengal India

ISBN: (数字)9798350374643

ISBN: (纸本)9798350374650

A novel machine learning (ML) based approach is introduced for designing photonic crystal (PhC) gas sensors to detect SF6, CH4, and CO 2 . In this work, we have implemented both the algorithm Support Vector Machine (SVM) and Random Forest (RF) then comparing both algorithms, achieved the highest accuracy of 97.01% for SVM in case of gas classification. We have designed the sensor integrating machine learning models for real-time classification. We have run extensive simulations that provide dataset over a wide range of temperatures and pressures. Using this dataset, we have trained and optimized SVM and RF classifiers. The accuracies of gas detection get improved with machine learning along with simple sensor designs, which then presents an effective tool for density prediction. This work has opened pathways toward developing efficient, compact, and highly accurate gas sensors for environmental applications.

关键词： Support vector machines Radio frequency Accuracy Machine learning algorithms Photonic crystals Real-time systems Classification algorithms Random forests Gas detectors Tuning

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