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The Smart Optimization of Security Systems in Wireless Personal Sensor Networks 2

The Smart Optimization of Security Systems in Wireless Perso...

引用

2nd IEEE international conference on distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Das, Sunanda Sindhu Madhuri, G. Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

Wireless personal sensor networks (WPSNs) are an emerging technology that provides a platform for monitoring and collecting data from a variety of sources. These networks are used to monitor environmental, health, and even lifestyle factors. As the use of WPSNs continues to grow, it is important to consider the security implications of using these networks. WPSNs rely on a variety of technologies to ensure secure communication between devices. These include encryption, authentication, secure protocols, and secure key management. Encryption is used to protect data from being intercepted and decoded by an unauthorized user. Authentication is used to verify the personality of the user and the device attempting to access the WPSN. Secure protocols are used to ensure secure communication between the devices and the server. Finally, secure key management is used to manage and store the encryption keys used to protect the data. In addition to encryption, authentication, and secure protocols, WPSNs must also be designed with a robust access control system. Access control systems are used to limit access to the WPSN based on user credentials and other factors. This assist ensure that authorized users alone can access the data stored on the WPSN. © 2023 IEEE.

关键词： Authentication

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Design and Implementation of Remote control intelligent Vehicle in distributed Environment 5

Design and Implementation of Remote Control Intelligent Vehi...

引用

5th international conference on computer Network, Electronic and Automation, ICCNEA 2022

作者： Lu, Hao Xiao, Feng Huang, Shujuan Zhang, Wenjuan Xi'an Technological University School of Armament Science and Technology Xi'an China Xi'an Technological University School of Computer Science and Engineering Xi'an China Xi'an Technological University School of Science Xi'an China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

Driverless vehicles is the main body for urban intelligent transportation system in the future. But as a user, how to use and control driverless vehicles in a complicated distributed environment is more and more becoming an important issue. It is very necessary to carry out remote real-time control of driverless vehicle in complex distributed environment. This paper designs and implements a remote control system for driverless intelligent vehicle under two different operating system vxworks and linux. Users can login the internet of things control center based on linux from the embedded devices based on vxworks real-time operating system which will control the driverless intelligent vehicle by sending the remote commands in real time. The experiments show that in the distributed environment, the internet of things control center can receive the remote commands sent by users and send these commands to the driverless vehicles so as it can do the corresponding actions. This will be realized by the wireless network and then users can control the driverless vehicles in real time. © 2022 IEEE.

关键词： intelligent vehicle highway systems

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Delivering High-Resolution Historical Remote Sensing Image using Integration of SRGAN 10

Delivering High-Resolution Historical Remote Sensing Image u...

引用

10th international conference on computer, control, Informatics and its Applications, IC3INA 2023

作者： Vatresia, Arie Ismanto, Rido Dwi Utama, Ferzha Putra Rais, Rendra Regen Permana, Wijaya Widyastiti, Astri University of Bengkulu Informatics-Engineering Faculty Bengkulu Indonesia Research Center for Computing Cibinong Indonesia University of Bengkulu Information System-Engineering Faculty Bengkulu Indonesia The Ministry of Environmental and Forestry Conservation and Natural Resouce Agency Bengkulu Indonesia

ISBN: (纸本)9798350394870

High-resolution remote sensing images are used in Earth mapping and sensing. With high resolution, we can see clearer details and get more accurate information about topography, vegetation, land use, and environmental changes such as deforestation, climate change, and natural disasters. This data is important for environmental monitoring, urban planning, natural resource management, disaster mitigation, and integrated real time monitoring. However, the data resource for Indonesia are still limited to time and space, especialy for historical data. The importance of high-resolution remote sense imagery lies in its ability to provide detailed and accurate data in various fields in which can be improved by the acceleration of artificial intelligent development. SRGAN is one of the algorithm that promising in way to improve the quality of images. Here we present the improvement of Landsat Image from 2000 to 2020 for P126R62 with the integration of SRGAN algorithm to perform four times improvement of pixels availibility. The data showed that the algorithm worked properly to improve and reduced the cloud with the loss rate of 0.000156 in discriminator loss and 0.549 in generator loss showing the model fitted to be applied over remote sensing images. © 2023 IEEE.

关键词： Remote sensing

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Cloud and IoT based Framework for Air and Noise Pollution monitoring System via Extreme Learning Machine 7

Cloud and IoT based Framework for Air and Noise Pollution Mo...

引用

7th international conference on intelligent Computing and control Systems, ICICCS 2023

作者： Tinnaluri, V S Narayana Sahukar, Latha Chaudhari, Ankur Malathy, G. Kolavennu, Subbarao Leonard, L. Koneru Lakshmaiah Education Foundation Department of Computer Science Green fields Vaddeswaram Andhra Pradesh Guntur India Sreenidhi Institute of Science and Technology Yamnampet ECE Department Telangana Hyderabad India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Paavai Engineering College Pachal Department of Computer Science & Engineering Tamilnadu Namakkal India Sphoorthy Engineering College CSE Cyber Security Department Telangana Hyderabad India ISBR Business School Department of Analytics Karnataka Bangalore India

ISBN: (纸本)9798350397253

Nowadays, air and noise pollution pose the greatest threat to the environment and to public health. Air and noise pollution are rising rapidly. In order to get it under control, close observation of it is strongly advised. This research addresses this problem by unveiling a method of detecting both ambient noise and the presence of potentially dangerous chemicals. Pollution is increasing at an alarming rate, and it's starting to cause problems for living things. Pollutants like loud noises and hazardous gases have a negative impact on people's health and want special attention. In this research, the proposed approach suggests the development of a network of sensors to monitor the environmental noise and air quality. A NodeMCU equipped with an ESP8266 WLAN adaptor is part of an Internet of Things (IoT) based Air and noise pollution monitoring system, together with a DHT11, a MQ9 gas sensor, and a Lm393 sound sensor. This monitoring system was developed with the help of neural network-based algorithms like CNN, SVM, and ELM to accurately forecast the level of pollution in a given area. Root-Mean-Square-Error (RMSE), Mean Square Error (MSE), and Mean-Absolute-Error (MAE) were used as performance indicators. Based on the performance, the Extreme Learning Machine (ELM) based training algorithm for single hidden layer feed forward neural networks (SLFNs) has revolutionized SLFN development. The results showed ELM as the most effective solution. The proposed model can now be used in high-pollution and noisy locations. © 2023 IEEE.

关键词： Errors

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An Approach of monitoring the Vehicle's Condition Based on Blockchain and Smart Contracts 24

An Approach of Monitoring the Vehicle's Condition Based on B...

引用

7th international conference on Blockchain Technology and Applications, ICBTA 2024

作者： Trofimov, Stanislav Ivanovich Voskov, Leonid Sergeevich Komarov, Mikhail Mikhailovich Graduate School of Business Hse University Moscow Russia Department of Computer Engineering Hse University Moscow Russia

ISBN: (纸本)9798400717390

The development of the intelligent Transportation System (ITS) is penetrating many economies around the globe. Various researchers in both industry and academia are looking into more efficient management of both vehicles and related data processing aspects. A vast trend related to the latter part is the distributed data processing of the transmitted data. This article discusses approaches to the use of blockchain technology in ITS. It explores the use of blockchain in modern transport industries. Particularly, the paper proposes a novel approach to the maintenance of public transportation vehicles or buses. The specificity of the proposed approach is the autonomous control of the technical condition using information systems. When using blockchain technology, building a transparent vehicle fleet management system is possible. The specificity of the proposed approach lies in the approach to data processing: in the organization, confidence in data increases, the possibility of manipulating transportation is eliminated, and the decision-making chain is reduced. As a result, the system can manage itself. It also helps to increase the service life of vehicles, makes it possible to predict their malfunctions and improves the quality of data on their technical condition. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Blockchain

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Construction of Green environmental Protection intelligent control and monitoring System Based on Neural Network Algorithm

Construction of Green Environmental Protection Intelligent C...

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distributed Computing and Optimization Techniques (ICDCOT), international conference on

作者： Hao'en Cheng Ziqian Wang Jiayi Qiu Jiahao Zhao North China University of Science and Technology Tangshan Hebei China Hebei University of Science & Technology Shijiazhuang Hebei China

environmental automatic monitoring system has been widely used in iron and steel enterprises, and has achieved certain results, Traditional techniques' imprecise monitoring of environmental contamination and resource use are caused by characteristics such sensor performance, data collecting frequency, and number of monitoring stations, which restrict their accuracy. The accuracy of environmental monitoring data may be increased to more precisely represent environmental conditions by incorporating neural network algorithms and continually learning and optimizing. To lower noise in the data, a significant amount of environmental monitoring data was gathered and preprocessed. While ambient spatiotemporal and temporal data were being recorded, the Inception-Long Short-Term Memory (LSTM) model was built. The outputs of the LSTM and Inception modules were combined via the fusion layer. According to the test set findings, the Inception-LSTM model had an average accuracy of 97.9% in predicting environmental conditions. Therefore, the application of the Inception-LSTM model can accurately predict environmental conditions, It can not only be applied to the environmental monitoring of the existing factory, but also to the monitoring of a certain area.

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Oyster Cold Chain Logistics monitoring System Based on RFID and Cloud Platforms 4

Oyster Cold Chain Logistics Monitoring System Based on RFID ...

引用

4th international conference on Signal Processing and computer Science, SPCS 2023

作者： Liu, Kai Gao, Wen Cong, Chenxuan Faculty of Information and Electronic Engineering Shandong Technology and Business University Yan Tai China

ISBN: (纸本)9781510672505

The cold chain logistics of oysters starts from the moment they are harvested and ends when they reach the consumers' homes. The process includes various stages: pre-processing, packaging, pre-cooling, processing, cold storage, loading, transportation, and sales. Due to inadequate quality control in the logistics process, fresh oysters often experience a significant decline in quality during transportation and storage, resulting in substantial losses. To address this issue, this article presents a real-time, traceable, and visual quality monitoring system for oyster cold chain logistics. It combines RFID technology with the development of a unique binding technique for preservation boxes and utilizes a hybrid technology incorporating "RFID+4G+DTU+MQTT+cloud storage + Web" to enable real-time collection of oyster transportation environmental parameters and distributed, non-volatile, and cost-effective data storage. A supporting B-S mode system management platform was developed and deployed on a cloud server. The system, with the flow of information as its main focus, provides functions including personnel management, oyster identification and traceability, data visualization monitoring, and quality prediction. The online operation of this system has proven to be highly real-time and stable, effectively enhancing the quality monitoring capability throughout the entire oyster transportation process, and it has demonstrated significant economic and social benefits. © 2023 SPIE.

关键词： Cold storage

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A Meta-reinforcement Learning Framework for Adaptive Quadrotor UAV Attitude control 25th

A Meta-reinforcement Learning Framework for Adaptive Quadro...

引用

25th international conference on Parallel and distributed Computing, Applications and Technologies, PDCAT 2024

作者： Zhao, Kaidong Li, Yanjie Liu, Zihan Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China School of Mechanical Engineering and Automation The Harbin Institute of Technology Shenzhen Shenzhen518055 China

ISBN: (纸本)9789819642069

This paper presents a meta-reinforcement learning approach for quadrotor UAV attitude control, addressing the limitations of traditional control methods in complex, dynamic, and uncertain environments. Our method integrates the advantages of context learning, Gaussian sampling, and multi-task training to rapidly adapt to diverse aircraft parameters and environmental conditions. Specifically, we utilize historical information quadruples as contextual data to accurately estimate current task characteristics through real-time observation and learning. In the latent space, we employ Gaussian sampling to effectively handle unknown UAV parameters. To validate the method’s efficacy, we conducted a series of experiments in the Bullet simulator, including single attitude tracking, resultant acceleration control, and continuous trajectory tracking. Experimental results demonstrate that our approach significantly outperforms traditional PID controllers and domain randomization-based SAC methods in terms of stability, rapid response, and trajectory tracking precision. Through multi-task training, our controller has developed the ability to swiftly adapt to novel situations. This research provides a robust and flexible solution for adaptive control of quadrotor UAVs, showing promise for more efficient and stable flight control in complex and dynamically changing environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Reinforcement learning

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Proceedings - 2023 international conference on Mobile Internet, Cloud Computing and Information Security, MICCIS 2023

Proceedings - 2023 International Conference on Mobile Intern...

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2023 international conference on Mobile Internet, Cloud Computing and Information Security, MICCIS 2023

ISBN: (纸本)9798350300932

The proceedings contain 33 papers. The topics discussed include: intelligent data center safety status prediction based on algorithm ensemble;research on solution of group data flow integration based on big data;soft actor-critic-based grid dispatching with distributed training;attribute-based searchable encryption with policy hidden in edge computing;energy-saving combined frequency conversion and ai for cloud and edge enabled data centers;predictive control based on transformer as surrogate model for cooling system optimization in data center;comparison of stability and energy consumption of AGV system based on clouding server and physical servers methods;joint physical-layer attributes-based authentication and authorization mechanism for green cloud data centers;exploiting implicit neural representation for temperature distribution reconstruction in data centers;and system for data center environmental monitoring that uses visible light communication positioning.

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Decision-Making for Remote control of Emergency Mobile Robot 5

Decision-Making for Remote Control of Emergency Mobile Robot

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5th IEEE international conference on Modern Electrical and Energy System, MEES 2023

作者： Tsymbal, Oleksandr Posashkov, Oleh Kharkiv National University of Radio Electronics Automation and Mechatronics Department of Computer-Integrated Technologies Kharkiv Ukraine

ISBN: (纸本)9798350359787

The proposed paper analyses the decision-making for remote control of emergency mobile robotic platforms. There is described a model of robot's decision-making, based on predicate logics, which combines local and remote procedures of goals and actions determination. The developed model uses the description of local emergency workspace added with remote-supplied information, based on distributed computer vision system. In core of decision-making system is problem-solving engine, which includes the set of action procedures, goals, specifications of robot and its sensor system. The procedure of action typically contains the result of action, the set of subgoals to solve, set of added facts and removed facts on workspace. Facts of considered workspace includes the descriptions of objects inside workspace with their coordinates, dimensions, and probable identification. To describe the emergency workspace here is proposed information model, based on set theory descriptions. While emergency robot is mostly considered as autonomous system with independent decision-making, the role of remote control is still essential for fast recognition of unknown or damaged objects, fast generation of movements and actions in emergency workspace, fast solution on actions in dangerous situations, for fast information support from other robots and people. The key role of remote control system can be executed by human operator with help of intelligent tools of other remote control systems, which provide monitoring of emergency workspace, based on computer-vision of acting robot and other information sources. The proposed ideas can be considered as a basis for real emergency robot control system implementation. © 2023 IEEE.

关键词： Decision making

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