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Machine Learning and Wireless sensor Network based Library Automation System 3

Machine Learning and Wireless Sensor Network based Library A...

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3rd international conference on Power, Energy, Control and Transmission systems, ICPECTS 2022

作者： Manikandan, J. Sivanesan, T.M. Gunasekaran Ramapraba, P.S. Sri Sairam Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India R&D Institute of Science and Technology Vel Tech Rangarajan Dr. Sagunthala Department of Computer Science and Engineering Tamil Nadu Chennai India Sidhartha Institute of Science and Technology Department of Electronics and Communication Engineering Andhra Pradesh Puttur India Panimalar Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665462754

Remote sensor network and radio frequency identification innovation are on the world's outskirts. In this age of data innovation, the library as a repository for information gathering and distribution is critical. Innovations such as the personal computer, the Internet, and universal identification have sped the shift to the digital age. New improvements were integrated to configure Radio Frequency Identification remote organization with Wireless sensor network comprising hubs to work on the intelligent administration of the library, relying on manual and data the board. The three modules that were basically researched were writing seek positioning framework, book full casing framework, and programmed getting and returning entry monitor warning framework. The intelligent library framework based on Wireless sensor organization and Radio Frequency Identification incorporated sophisticated RFID and ZigBee technologies for the simplification and inclusion of writing assets, administration interface, and the library's administrative procedure. The significance of library computerization and smart collaboration was recognized, and the notion of individuals situated was fully explored. According to the findings, the smart library framework, which is based on wireless sensor organization and radio frequency identification, was able to fundamentally understand the smart library executives. To summarize, the framework creates an unpredictable library administration and board framework at any time and in any location. © 2022 ieee.

关键词： Automation

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Routing Protocol Attack Detection Using Machine Learning Through Parallel computing in Wireless sensor Network

Routing Protocol Attack Detection Using Machine Learning Thr...

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computing and Machine Intelligence (ICMI), international conference on

作者： Mithun Kumar PK Al Amin Hossain Sufian Al Majmaie Fathi Amsaad Department of Computer Science and Engineering Wright State University Dayton Ohio USA

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

The wireless sensor network is a hot and significant research area nowadays and it can be addressed in almost every sector and environment. A few major challenges are countered in the wireless sensor network such as energy consumption, battery lifetime, Attacks, Data Transmission, etc. Generally wireless sensor network produces non-Euclidian sensing data and metadata structures and it is very complex to deal with the structure, especially in order to measure anomalies and disruption in a network. In this paper, we have introduced parallel computing to resolve the heterogeneity of the sensing data and metadata as well. Parallel computing has been applied implicitly for extracting only paramount data from the large scale of data to detect routing layer attacks. The convolution neural network (CNN) has been considered as a machine-learning model and we have enhanced the kernel to optimize the performance of the conventional CNN model to detect network layer attacks in terms of wireless sensor networks. Our investigated method demonstrates better results in detecting anomalies and attacks than the existing methods or techniques.

关键词： Wireless sensor networks Energy consumption Computational modeling Machine learning Parallel processing Metadata Routing

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Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study 17

Large Scale Global Optimization Algorithms for IoT Networks:...

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

作者： Goudos, Sotirios K. Boursianis, Achilles D. Mohamed, Ali Wagdy Wan, Shaohua Sarigiannidis, Panagiotis Karagiannidis, George K. Suganthan, Ponnuthurai N. Aristotle Univ Thessaloniki Sch Phys ELEDIA AUTH Thessaloniki Greece Cairo Univ Fac Grad Studies Stat Res Operat Res Dept Giza Egypt Nile Univ Wireless Intelligent Networks Ctr WINC Sch Engn & Appl Sci Giza Egypt Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan Peoples R China Univ Western Macedonia Dept Informat & Telecommun Engn Kozani Greece Aristotle Univ Thessaloniki Sch Elect & Comp Engn Thessaloniki Greece Nanyang Technol Univ Sch Elect Elect Engn Singapore Singapore

ISBN: (纸本)9781665439299

The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-rdG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.

关键词： Internet of Things optimal power allocation wireless sensor network large scale global optimization

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Multi-sensor Scheduling Method for Cooperative Target Tracking Based on ADP 3

Multi-sensor Scheduling Method for Cooperative Target Tracki...

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3rd international conference on Wireless Communications and Smart Grid, ICWCSG 2021

作者： Zhang, Shanshan Xin, Haihui Dalian Maritime University Dalian China Dalian University of Science and Technology Dalian China

ISBN: (纸本)9781665425988

In order to solve the limitations of limited sensing, communication, computing resources and energy supply in wireless sensor networks, a lot of basic research and development work have been carried out to study the optimal containment control problem of multi-agent systems with unknown disturbances. In this paper, through problem conversion, the robust containment control problem of the multi-agent system under unknown disturbances is first transformed into the optimal containment control problem of an auxiliary system, and a control method based on adaptive dynamic programming is proposed to solve the optimal containment control problem of multi-agent systems. Meanwhile, a VI algorithm for solving the optimal solution of the coupled DTHJB equation is proposed too. Then an actorcritic network is used to calculate the iterative solution by way of online learning with only data input and output. Finally, the simulation results verify the effectiveness of the proposed distributed control design. © 2021 ieee.

关键词： Multi agent systems

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Reliability Assessment of Medium and Low Voltage Distribution Networks Considering distributed Energy Sources

Reliability Assessment of Medium and Low Voltage Distributio...

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Energy Engineering and Power systems (EEPS), international conference on

作者： Wei Zhang Liwen Qin Yangjun Zhou Chenying Yi Shan Li Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China

In order to truly evaluate the reliability of low-voltage distribution network, considering the influence of distributed energy uncertainty on the reliability evaluation of low-voltage distribution network, a reliability evaluation method of low-voltage distribution network considering distributed energy is proposed. Firstly, considering the load recovery capability of distributed energy after failure, and then combining with distributed energy, a collaborative assessment method based on sequential Monte Carlo for medium-low voltage distribution network reliability is proposed. Finally, taking ieee RBTS BUS-2 system as an example, the system reliability levels in different scenarios are compared and analyzed, and the effectiveness of the proposed method is verified.

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A WSN (Wireless sensor Network) Approach for Controlling the Actuator Wirelessly through Database Interaction 7

A WSN (Wireless Sensor Network) Approach for Controlling the...

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7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Bin Karim, Md. Asif Rahman, Md. Mukidur Shahriar, Saquib Islam, Md. Manirul Department of Mechatronics Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350341485

This research study explores the wireless sensor networking, where sensor data is transmitted to a local database via a nearby server. The primary focus of this research study is real-time environment monitoring systems and wireless control and actuation systems. This research study incorporates the DHT 11 (Temperature and Humidity) and MQ-6 (LPG Gas) sensors. Selecting an appropriate controller is crucial to attaining desired system attributes like high-speed precision and meeting requirements for precise motion control at high speeds. That is why the ESP-8266-based NodeMCU is adopted for this ***, both feedback and feedforward closed-loop control mechanisms are implemented. As a result, the system can either control the actuator itself or by user demand. Leveraging sensor-derived data, the controller can automatically trigger the actuation system precisely within estimated time. Further, this study also depicts a clear differentiation between conventional methods and the proposed novel approach. Moreover, an IP (Internet Protocol) based monitoring system allows to monitor the sensor-derived data instantly, even without internet connectivity. Notably, the entire system operates on solar power, ensuring uninterrupted functionality even during power outages. © 2023 ieee.

关键词： Internet protocols

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Advanced Feature Extraction Techniques for Machine Learning-Based Fault Analysis in Power Grids

Advanced Feature Extraction Techniques for Machine Learning-...

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Electrical Power Engineering, Communication and computing Technology(ODICON), Odisha international conference on

作者： Pratham Tatraiya Himanshu Priyadarshi Manipal University Jaipur Jaipur India

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

As the infrastructure develops and more elements are added in the daily livelihood of humankind, dependable electrical power distribution is critical for keeping society and economies running smoothly. Modern power grids are complex, with wide networks and diverse components, requiring advanced problem detection and management systems for its upkeep. The growing demand of reliable power supply, as well as the necessity for long-term power infrastructure, emphasize the importance of reliable fault detection systems. This work aims to improve the resilience and reliability of electricity grids by using machine learning (ML) techniques to detect and analyze faults in power grids, using extensive feature extraction. The original base dataset, generated on an ieee 6-bus grid system for consistent benchmarking, of three phase voltages and currents will be transformed into a dataset inclusive of time and other derivations, namely, voltage and current unbalance factor, volt-age and current harmonic distortion and the root-mean-square current and voltages. The results show a massive improvement in accuracy and related metrics between the base dataset, hovering between 34%-45% for various ML techniques to the improved dataset, yielding accuracy in the range of 87% -92% for respective techniques.

关键词： Analytical models Accuracy Computational modeling sensor phenomena and characterization Feature extraction Power grids sensor systems Reliability Data mining Load modeling

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Intelligent sensor and IoT Based Vehicle Pollution Monitoring System with Alert 3

Intelligent Sensor and IoT Based Vehicle Pollution Monitorin...

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3rd international conference on Power, Energy, Control and Transmission systems, ICPECTS 2022

作者： Shakunthala Sangeetha, S.V. Tresa Krishnammal, Muthu Padmavathy, T.V. R.M.D Engineering College Department of Electronics and Communication Engineering Tamil Nadu Kavaraipettai India University of Technology and Applied Science-Al Mudabah Department of Electrical and Electronics Engineering Al-Mussanah Oman School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati India R.M.K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Kavaraipettai India

ISBN: (纸本)9781665462754

Natural disasters are a growing issue these days. Vehicle, rail, and truck air pollution can cause respiratory diseases and asthma episodes. Transportation accounts for more than half of all carbon monoxide emissions in the atmosphere. Currently, when the RTO office issues the wellness certification, the vehicle's emissions are validated using pollution control stations located in particular urban areas. The health declarations for private autos are valid for a long time and must be updated at regular intervals after that. In the case of transportation vehicles, the health certification is granted for a long time and then expanded every year. We cannot distinguish outflows caused by this interaction since we presume the vehicle is static until FC. This project will be able to monitor and warn about air pollution on city streets by linking the Global System of Mobile Communications Network to the cloud, as well as track automobiles that emit discharges above a set edge. This also focuses on avoiding accidents caused by carbon monoxide gas produced by vehicles by installing a Gas sensor. © 2022 ieee.

关键词： Vehicles

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Reliable Wireless sensor Network using Ant Colony Optimization (ACO) 3

Reliable Wireless Sensor Network using Ant Colony Optimizati...

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3rd international conference on Electronics and Sustainable Communication systems, ICESC 2022

作者： Kruthi, B. Anand, Santosh Mysore Amrita Vishwa Vidyapeetham Amrita School of Arts and Sciences Department of Computer Science India

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

Wireless sensor network is deployed in an unreachable place for humans. There are significant problems in WSN to transfer data from source node to destination node. Reliable data transfer is one of the most important aspects. Nodes that having low energy signal while transmitting the data to the neighbor node and if it does not reach the destination because of low energy then these nodes will consider as faulty nodes. There is a need for protocol or algorithm which can help to solve faulty node issues and provides high reliability. End to End reliability is essential to recognize the reliable,effective shortest path from source to destination nodes. Since nodes will not recognize the shortest paths time taken is more to transfer data from source node to destination node. The proposed research work utilizes Ant Colony Optimization(ACO) to check and identify the shortest path. The Shortest path will be identified by sending dummy data by using ACO. It will also help to check the effect of failed link and how it retrieves when there is a failure of link. With the help of ACO Fault tolerance can also be presented. With the help of this process data loss can be reduced and provide reliable transfer of data packets. To improve the lifetime of the network and to avoid data loss whole data will be converted into multiple packets. The parameters in the proposed work are transmission rate,data loss efficiency,energy level. © 2022 ieee.

关键词： Ant colony optimization

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An AI AUV Enabling Vision-based Diver-following and Obstacle Avoidance with 3D-modeling Dataset 3

An AI AUV Enabling Vision-based Diver-following and Obstacle...

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ieee 3rd international conference on Artificial Intelligence Circuits and systems (AICAS)

作者： Chou, Yu-Cheng Chen, Hsin-Hung Wang, Chau-Chang Chou, Hui-Min Wang, Chua-Chin Natl Sun Yat Sen Univ Inst Undersea Technol Kaohsiung Taiwan Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung Taiwan

ISBN: (纸本)9781665419130

This paper presents an AUV with AI (artificial intelligence), which is able to perform real-time optical vision-based diver-following and forward looking altimeter-based obstacle avoidance. The AI AUV is equipped with thrusters and a standard navigation-related sensor suite. A diver detection convolutional neural network, a suite of motion controllers, and a diver detection payload device are developed to enable diver-following functionality of the AUV. An obstacle avoidance algorithm based on forward looking altimeters is developed to enhance the waypoint navigation security of the AUV with obstacle avoidance functionality. The diver-following and the obstacle avoidance capabilities of the Taiwan Moonshot AUV under different scenarios are evaluated through hardware-in-the-loop simulations. In addition, the designated single diver following capability of the Taiwan Moonshot AUV is also verified through closed water experiments conducted in a towing tank.

关键词： Artificial Intelligence Autonomous Underwater Vehicle Diver-following Obstacle Avoidance

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