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Battery Monitoring System Design Based on NB-IoT 1

Battery Monitoring System Design Based on NB-IoT

引用

1st international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2022

作者： Wang, Xiaoping Yi, Xianjun Ding, Han Wuhan Institute of Technology Dept. School of Electrical Information Wuhan China

ISBN: (纸本)9781665452151

Aiming at problems such as limited computing power, insufficient local data storage capacity and short data transmission distance of traditional battery monitoring systems, this paper designed a lithium battery monitoring system based on Narrow Band Internet of Things (NB-IoT). System is designed with STM32F103 as the main control chip, and the BQ76930 chip collects relevant information such as voltage, current and temperature. The battery information is transmitted to the Alibaba Cloud server through the NB-IoT module, and state of charge (SOC) estimation and information storage are performed on the server. Finally, the battery information is displayed through the PC and mobile terminal. According to the results of the test, the system meets the design requirements and has practical engineering significance. © 2023 ieee.

关键词： Internet of things

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Speech Detection and Comparison using Different Feature Extraction Method for Correct Verification 3

Speech Detection and Comparison using Different Feature Extr...

引用

3rd international conference on Communication, control, and intelligent systems, CCIS 2024

作者： Upadhyay, Shrikant Kumar, Binod Singh, Rajan Alam, Md. Irfan Kumari, Barkha Hinz, Binita Roshima Mlr Insitute of Technology Department of Electronics and Communication Engineeing Hyderabad India Jharkhand Rai University Facultyt of Cse & It Ranchi India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India Jharkhand Rai University Faculty of Cse & It Ranchi India Pune India Rtc Institute of Technology Department of Computer Science and Engineering-Cyber Security Ranchi India

ISBN: (纸本)9798331528201

Mental status through physical appearance identification is not possible as it does not give complete status of any human. Using voice and considering quality extraction of talked it is quite easy to predict the mental behavior and internal variation that will help the doctor related with medical treatment that support them to give proper treatment to person. Hindi is the natural language of India and large community of population talk and speaks this language to exchange and communicate. Various inputs like specific feature, images and vital report of serious person and it is one of the important facts sources for deep training or gaining systems. In this research paper we try to identify the speech signal under different scenario like gun noise, car noise etc. following different feature extraction approaches and compare it for its proper verification. This verification may help to enhance the quality of speech in different adverse scenario and make the speech detection easy. Here, the comparison has been done with various feature extraction method and the results reflects that MFCC has good efficiency of 95% and with a low error rate of 2% compared to other approach. For analysis Hindi voice sample were used for the experimental analysis for 50 samples. © 2024 ieee.

关键词： Speech enhancement

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OCDE: Adaptive Differential Evolution Algorithm in Distributed intelligent systems 16

OCDE: Adaptive Differential Evolution Algorithm in Distribut...

引用

16th international conference on cyber-Enabled Distributed Computing and Knowledge Discover, cyberC 2024

作者： Wang, Minghao Du, Shaoyi Xi'an Jiaotong University Institute of Artificial Intelligence and Robotics Xi'an China

ISBN: (纸本)9798331506896

In autonomous driving, the optimization theory and algorithms for distributed intelligent systems are essential for enhancing vehicle decision-making capabilities, path planning, and environmental perception. Evolutionary algorithms, as a global optimization method inspired by biological evolution, is widely used in these scenarios. Unfortunately, the performance of evolutionary algorithms relies on the properties of the solution space, the optimization strategy, and parameter settings, and their efficiency also requires more rigorous evaluation. This study focuses on differential evolution algorithm, examining the properties of the solution space for optimization problems, the preferences of strategies and parameters in different optimization scenarios, and setting new standards for efficiency evaluation. Based on the experimental conclusions, modifications are made to our algorithm to further verify the correctness of our findings. All experimental results are deduced based on the CEC2017 benchmark problem suite from the ieee Congress on Evolutionary Computation (CEC). © 2024 ieee.

关键词： Anthropogenic

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FUZZY AHP and TOPSIS Approach to Evaluate the Criteria of HVAC control System

FUZZY AHP and TOPSIS Approach to Evaluate the Criteria of HV...

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2024 ieee international conference on Information technology, Electronics and intelligent Communication systems, ICITEICS 2024

作者： Gowda, S. Mayur Urf Hosamani, Manjunath Madar Kodipalli, Ashwini Rohini, B.R. Soma, Bhavani Gargi, N. Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798350382693

Effective control of Heating, Ventilation, and Air Conditioning (HVAC) systems is necessary to optimize indoor comfort, energy efficiency, and environmental impact. This study presents a novel method that combines the Technique for Order of Preferences by Similar to Ideal Solution (TOPSIS) with the Fuzzy Analytic Hierarchy Process (AHP) to improve decision-making in HVAC control systems. Conventional HVAC control systems may not be well-suited to dynamic and uncertain situations since they frequently rely on deterministic algorithms and preset rules. On the other hand, the suggested method makes use of fuzzy logic to address the innate ambiguity and imprecision in HVAC control choices. reducing the impact on the environment and energy use. © 2024 ieee.

关键词： Fuzzy logic

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Edge Multi-agent Intrusion Detection System Architecture for IoT Devices with Cloud Continuum 7

Edge Multi-agent Intrusion Detection System Architecture for...

引用

ieee 7th international conference on Industrial cyber-Physical systems (ICPS)

作者： Funchal, Gustavo Pedrosa, Tiago de la Prieta, Fernando Leitao, Paulo Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI Campus Santa ApolOnia P-5300253 Braganca Portugal Inst Politecn Braganca Lab Sustentabilidade & Tecnol Regioes Montanha Su Campus Santa ApolOnia P-5300253 Braganca Portugal Univ Salamanca BISI Digital Innovat Hub Edificio I D IC Espejos S-N Salamanca 37007 Spain

ISBN: (纸本)9798350363029;9798350363012

The Industry 4.0 has brought significant changes in production processes and business models worldwide. Advanced technologies, e.g., Collaborative Robotics, Artificial Intelligence, Cloud Computing, and Internet of Things (IoT) are playing a crucial role in improving efficiency and productivity. However, the adoption of these technologies, particularly IoT, introduces security vulnerabilities and potential attacks due to inadequate security measures. This paper addresses the need for dedicated cybersecurity mechanisms and secure device design in IoT networks, particularly emphasizing the challenges faced in implementing Intrusion Detection systems (IDS) on resource-constrained IoT edge devices, limiting the use of traditional machine learning based detection methods. Moreover, the limited computational resources of IoT devices require lightweight techniques that have low power requirements but can accurately detect anomalies in the network. To tackle these challenges, a novel multi-agent based architecture is proposed, considering the distribution of nodes along the edge-cloud continuum, and enabling the collaboration among different processes to detect anomalies during attacks. The proposed architecture is evaluated at the edge level using the CICIoT2023 dataset. The results demonstrate the feasibility of using multi-agent systems for a collaborative detection of IoT attacks, contributing to enhance the security of IoT-based systems against cyber threats in Industry 4.0 environments by leveraging lightweight techniques.

关键词： Intrusion Detection systems Multi-agent systems Internet of Things Machine Learning

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SEDSpec: Securing Emulated Devices by Enforcing Execution Specification 54

SEDSpec: Securing Emulated Devices by Enforcing Execution Sp...

引用

54th Annual ieee/IFIP international conference on Dependable systems and Networks (DSN)

作者： Chen, Yang Zhang, Shengzhi Jia, Xiaoqi Zhou, Qihang Huang, Heqing Xu, Shaowen Du, Haochao Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Boston Univ Metropolitan Coll Boston MA 02215 USA

ISBN: (纸本)9798350341065;9798350341058

Device emulation is a vital aspect of virtualization, yet remains vulnerable to security threats. Prior research has focused on monitoring I/O data flow or identifying internal device anomalies but often falls short in precision and automation. In this paper, we propose a novel method that leverages the normal operations of an emulated device to formulate an execution specification. The specification acts as a criterion to evaluate the device's behavior and state transitions. We implement SEDSpec, a prototype system that automatically generates the execution specification for an emulated device and devises three check strategies for identifying any deviations from this specification, thereby ensuring normal operations and enhancing the security of the emulated device. We evaluate SEDSpec with five different execution specifications. The results show that SEDSpec can detect anomalies caused by vulnerability exploitation while maintaining the devices' regular functioning with minimal performance overhead.

关键词： device emulation anomaly detection execution specification program analysis

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Energy-Efficient Safety-Aware Scheduling of Real-Time control systems with Burst Tasks 22

Energy-Efficient Safety-Aware Scheduling of Real-Time Contro...

引用

22nd ieee international conference on Industrial Informatics, INDIN 2024

作者： Cheng, Ting Liang, Yonghui Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798331527471

In industrial sites, multiple real-time control systems often share computing resources. However, burst computing tasks may lead to the random dropping of control computing subtasks, resulting in control failures and potential hazards. To address this issue, we propose an energy-efficient safety-aware task scheduling scheme based on mixed-integer programming. When burst computing tasks are triggered, this scheduling scheme adaptively releases resources from low-criticality control computing subtasks and adjusts the processor speed based on the dynamic voltage and frequency scaling technology (DVFS), ensuring the timely completion of burst computing tasks and keeping the control system state deviation within a safe threshold. To achieve the scheduling scheme, we propose an efficient algorithm called EESASA. Simulation results show that EESASA can minimize the overall cost of control and processor energy while ensuring the safety of the control system and the timely completion of burst computing tasks. © 2024 ieee.

关键词： Dynamic frequency scaling

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Multi-Level Features Fusion for Zero-Shot Object Pose Estimation 26

Multi-Level Features Fusion for Zero-Shot Object Pose Estima...

引用

26th international conference on Industrial technology, ICIT 2025

作者： Huang, Nanxin Xu, Chi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Driven by advancements in industrial production and artificial intelligence, the need for pose estimation of new ob-jects in areas like robotic manipulation and virtual reality is increasing. We introduce a zero-shot object pose estimation approach that identifies the poses of objects excluded from the training dataset, removing the requirement for re-modeling. The method is built around a multi-level features fusion framework de-signed to enhance generalization. First, a trainable feature extraction module filters and selects multi-level features extracted by the backbone network. Unlike traditional convolutional ker-nels, we incorporate a dynamic convolution kernel to enhance the feature extraction capability. Second, in the feature fusion module, we adopt a dynamic weight generation strategy to perform weighted fusion of multi-level features. This method enhances template matching by effectively describing similarities between unseen objects (those absent from the training set) and templates, leveraging robust and adaptive feature representations to narrow the gap with seen objects. Experimental results demonstrate that our approach achieves state-of-the-art performance on two popu-lar benchmark datasets, LineMod and LineMod-Occlusion, proves that our method has better generalization than previous models. © 2025 ieee.

关键词： Industrial robots

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Analysis and Calculation of Strength and Rigidity for Industrial Grinding Robot 12

Analysis and Calculation of Strength and Rigidity for Indust...

引用

12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Xu, Manman Zhang, Zhitao Shao, Long Zhang, Zhen Cao, Chuqing Anhui Polytechnic University School of Mechanical Engineering Wuhu241000 China Hit Robot Technology Research Institute Co. Ltd Department of Wuhu Wuhu241000 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The rigidity of the grinding robot will greatly affect the tool path and the actual grinding effect. In this paper, the structural model of grinding robot is preliminarily designed and statically analyzed. The maximum stress value is 22.13 MPa and the maximum deformation is 0.17 mm, which meets the strength design standard of grinding robot. The static stiffness model of the grinding robot has been built, analyzing the transmission relationship of each joint, deducing the stiffness conversion formula, converting the stiffness of each part to the joint, and calculating the theoretical stiffness of each joint. The stiffness of joint 4 and joint 5 is better, which are 6.46e6 and 6.13e6 respectively. It provides the data foundation for improving the robot rigidity, so as to promote the development of higher precision grinding robot. © 2022 ieee.

关键词： Stiffness

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AI-Based Detection and Analysis of Phishing Domains: Leveraging Machine Learning for Enhanced cybersecurity

AI-Based Detection and Analysis of Phishing Domains: Leverag...

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2024 international conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Dhanalakshmi, R. Vijayaraghavan, N. Kumar, Akhil Beni Prathiba, B. Sahaya School of Computer Science and Engineering Vellore Institute of Technology - Chennai Center for Cyber Physical Systems Chennai India Kcg College of Technology Department of Mathematics Chennai India Scset Bennett University Greater Noida India School of Computer Science and Engineering Vellore Institute of Technology Center for Cyber Physical Systems Chennai India

ISBN: (纸本)9798331510022

In the ever-evolving landscape of cyber security, the prevalence of phishing attacks poses a formidable threat to information security systems worldwide, compromising data integrity and eroding user trust. This paper introduces an innovative solution harnessing artificial intelligence to identify and analyze phishing domains, particularly focusing on newly registered domains from public databases like WHOIS. This approach is crucial as traditional security measures often prove insufficient against the sophistication of phishing tactics. Our proposed AI-driven system employs an analysis strategy. It utilizes machine learning to conduct an in-depth backend code and content analysis. This involves comparing suspect and legitimate sites for structural and syntactical disparities, utilizing deep learning models trained on extensive datasets of known phishing and authentic domains. These methodologies offer a nuanced evaluation, crucial for distinguishing sophisticated phishing attempts from genuine domains. Additionally, the system excels at identifying malicious links within these domains, enhancing its overall protective capabilities. The efficiency of our solution lies in its capacity for real-time, accurate threat detection. We introduce a probabilistic scoring mechanism that assesses the likelihood of a domain being a phishing site, facilitating informed decision-making for cyber security personnel. Furthermore, our system is designed for seamless integration into existing cyber security frameworks, providing versatility and ease of use. © 2024 ieee.

关键词： Phishing

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