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IoT based Pet Health Monitoring System for Sick Pets 3

IoT based Pet Health Monitoring System for Sick Pets

引用

3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Nithin Wilfred Reyu, S. Pearly Princess, J. Karunya Institute of Technology and Sciences Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

An inventive way to monitor a pet's health is the utilization of a pet health monitoring system. The proposed system's objective is to provide pet owners with current health information so they may take preventative actions. The wearable device that is part of the pet health monitoring system collects data from pets, including heart rate, temperature, and activity levels, and sends it to a central platform. It is programmed to examine this data in order to look for any irregularities or possible health problems. The system uses Blynk application that makes it easy for pet owners to view and understand the health information about their animals. Pet owners can seek veterinarian care by contacting them if the application notify them to any alarming shifts in their pet's health. By using it, pet owners can take an active role in promoting the health and wellbeing of their animals. Among the primary benefits of the pet health monitoring system are early detection of health issues, improved preventative treatment, remote monitoring capabilities, and more veterinarian-to-veterinarian communication. To sum up, the pet health monitoring system is a revolutionary instrument that helps pet owners effectively keep an eye on and control the health of their animals, ensuring that their beloved companions enjoy longer, healthier lives. © 2024 IEEE.

关键词： Animals

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Research on an aerial object detection algorithm based on improved YOLOv5 3

Research on an aerial object detection algorithm based on im...

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Huang, YiChuan Cui, HuiMing Ma, JiJun Hao, YueHan Beijing Research Institute of Telemetry Control Technology and Systems Laboratory Beijing China

ISBN: (纸本)9781665459112

Aerial target detection is an important direction in target detection. Due to the limitations of UAV's volume and computing power, it is necessary to balance the time complexity and accuracy of the algorithm. This paper selects YOLOv5s as the benchmark method of the article. By introducing the feature extraction structure of shufflenetv2, the backbone of YOLOv5s is improved to reduce the amount of calculation of the network, and then the attention mechanism CBMA module is added to the network. Finally, the detection comparison experiment is carried out on visdrone data set. Experimental results show that flops is reduced from 15.7G to 3.7G. After accelerated by tensorRT framework, the improved algorithm can run 53fps on Jetson nano, which can meet the needs of real-time UAV aerial target detection. © 2022 IEEE.

关键词： Antennas

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The Liquid Level control of a Three-Tank Water Tank is Based On Beetle-Particle Swarm Algorithm 3

The Liquid Level Control of a Three-Tank Water Tank is Based...

引用

3rd international conference on Artificial Intelligence and computer Information Technology, AICIT 2024

作者： Chen, Jian Li, Zicheng Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China

ISBN: (纸本)9798350365443

Aiming at the uncertainty factors such as large inertia, large delay and nonlinearity in the three-tank water level control system, an intelligent control algorithm of Beetle antennae-particle swarm optimization was proposed. Firstly, on the basis of establishing the mathematical model of the three-capacity water tank, the BAS-PSO algorithm is designed, which increases the ability of individual to learn the surrounding information independently on the basis of maintaining the group optimization search and learning the global optimal, and continuously iterates the optimization until the optimal solution is found. Secondly, 5 examples of benchmark test functions are selected for performance testing to evaluate the local search ability and global development ability of the algorithm. Finally, the simulation results show that compared with the traditional intelligent control algorithm, the BAS-PSO algorithm can effectively improve the speed and robustness of the system. © 2024 IEEE.

关键词： Water tanks

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A Hybrid Slime Mould Meta Heuristic Algorithm and Machine Learning Technique for Intrusion Detection System 3

A Hybrid Slime Mould Meta Heuristic Algorithm and Machine Le...

引用

3rd IEEE international conference on Intelligent Techniques in control, Optimization and Signal Processing, INCOS 2024

作者： Umarani, V. Swetha, K. Computer Science and Engineering Saveetha Engineering College Thandalam TamilNadu Chennai India

ISBN: (纸本)9798350361186

Network anomaly prediction is a crucial aspect of network security, as it helps identify unusual or potentially malicious activities within a computer network. There are several approaches and techniques used for network anomaly prediction, and Machine Learning (ML) is often employed due to its ability to detect patterns and anomalies in large datasets. In this research, network anomaly detection is carried out by three stages. In first stage, data set from IEEE data port is collected and LRC, RFC models are trained for prediction. In second stage, dimension reduction algorithm PCA is used for preprocessing and ML models are trained for prediction. In third stage, the hybrid PCA +SMA is proposed along with ML models for prediction. From this analysis, the hybrid PCA+SMA+ML provide better performance (accuracy 96) compared with previous three stages. Finally, the hybrid PCA+SMA+RFC is selected for final deployment. © 2024 IEEE.

关键词： Machine learning

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AI-Driven IoT Framework for Optimal Energy Management in Consumer Devices 3

AI-Driven IoT Framework for Optimal Energy Management in Con...

引用

3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Liyon Raj, S. Malleeshwaran, T. Prasanna, T. Daniel, J. Alfred Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350396157

The explosion of Internet of Things (IoT) devices in consumer applications has led to an unprecedented demand for efficient energy management strategies. However, the existing approaches lack intelligence and responsiveness to varying user needs and grid conditions. This research study introduces an innovative AI-driven IoT framework to optimize energy consumption in consumer devices. The proposed framework dynamically adapts energy usage based on a device context, user behavior, and environmental conditions. The proposed framework integrates cutting-edge AI models and algorithms to analyze real-Time data streams from IoT devices. In addition to that, the framework integrates real-Time energy consumption data from connected devices with AI algorithms for demand forecasting, anomaly detection, and dynamic control. Further, the components and technologies employed illustrate how machine learning enhances decision-making processes for optimal energy efficiency. Experiments in simulated and real-world environments demonstrate significant energy savings of up to 20% compared to conventional methods. The proposed framework offers a scalable and adaptable solution for promoting sustainable energy utilization in the field of consumer electronics. © 2024 IEEE.

关键词： Energy utilization

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Assessment of Depression Level Based on Multi-Scale 3D Convolution and Expression Videos 3

Assessment of Depression Level Based on Multi-Scale 3D Convo...

引用

3rd international conference on computer vision and Pattern Analysis, ICCPA 2023

作者： Cao, Qishuang Gao, Junlong Lv, Zeying Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

The automatic diagnosis of depression using deep learning has recently shown significant progress, and 3DCNN has been applied to assessing depression levels from videos. There are two problems to be encountered applying 3DCNN, including insufficient data to train the model and an insufficient diversity of features extracted on a single scale. An approach is presented in this paper to address these issues. Firstly, we augmented the raw data by adding noise and applying rotations to increase the amount of the training set. Secondly, we constructed a 3DCNN to extract more diverse features from multiscales. We evaluated our proposed method on the AVEC 2014. Our approach achieved MAE=7.13 and RMSE=9.16, demonstrating its effectiveness in improving the accuracy of depression assessment compared to existing approaches. © 2023 SPIE.

关键词： Deep learning

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Securing the Cloud through the Implementation of Encryption Algorithms- A Comprehensive Study 3

Securing the Cloud through the Implementation of Encryption ...

引用

3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Manikanta, Maturi Lohith Naga Venkata Sai Poojith, Chandu Sai Prakash, Modem Bhanu Sathwik, Vagu Bharadwaj Mothukuri, Radha Bulla, Suneetha Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350375190

Cloud computing has become an integral part of modern technology, offering scalable resources and services. However, the security of data and services in the cloud is a paramount concern. To address this, research explores a comprehensive study of various security algorithms employed in cloud computing environments. This research study reviews the mathematical foundations, working principles, and practical applications of these algorithms, focusing on their strengths and weaknesses. This research aims to provide valuable insights into the landscape of cloud security, assisting cloud service providers and users in making informed decisions to protect their data and operations in the cloud. The main goal of this research is to assess the effectiveness of different data encryption techniques in relation to cloud security. This study evaluates the effectiveness of four popular encryption techniques to see which one works best in cloud contexts and for possible industry uses. Those four techniques are AES, DES, SHA-256, ElGamal Numerous advantages come with data encryption, including improved management control, economic effectiveness, and data and communication security for distant workers. By advancing the knowledge of cloud data security, this study helps businesses to make wise decisions about data protection. © 2024 IEEE.

关键词： Cloud security

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Highly Efficient Switched Capacitor Converters for Rechargeable Hearing Aids 3

Highly Efficient Switched Capacitor Converters for Rechargea...

引用

3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Anandi, V. Muthuswamy, Ramesh Pranav, A. Ramaiah Institute of Technology Dept. of Electronics and Communication Bengaluru India School of Management Presidency University Bengaluru India Vit Dept. of Computer Science Engineering Chennai Campus Chennai India

ISBN: (纸本)9798331528201

The paper deals with switched capacitor-based designs for power-efficient rechargeable hearing aids. Switched-capacitor DC-DC power converters are a subset of DC-DC power converters that use only switches and capacitors to convert one voltage to another efficiently. By using switched-capacitor circuits, the aim is to increase the efficiency of hearing aids. To achieve long battery life, a high conversion efficiency is required. At the same time, the physical size should be low as it is desirable for the end-user to have small hearing aids. The voltage levels thus have to be stepped down from the voltage provided by a Li-ion (rechargeable) to levels closer to that of Zn-Air (non-rechargeable). © 2024 IEEE.

关键词： Capacitor bank

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Generation and Adversarial Testing for Assessing Autonomous Vehicles in Complex Environments 3

Generation and Adversarial Testing for Assessing Autonomous ...

引用

3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Lohan, Vishal Kumar Agnihotri, Shantanu Upes School of Computer Science Dehradun India

ISBN: (纸本)9798331528201

Autonomous cars are the new future of the world so they must be reliable and trusted before handing them over to the general public. In order to ensure their reliability, it is important to realize that when naturalistic data is used for training, the idea of safety does not change. This is because, in natural settings, the likelihood of an automobile being involved in an accident is relatively low, making training for such situations challenging. This work proposes an efficient technique by which an adversarial environment is created to train the autonomous vehicle for difficult scenarios. This technique facilitates the evaluation of autonomous vehicles in a multi-agent setting, where adversarial car policies are taught and compared. The experiments are carried out in a simulated urban driving environment that relies on the difficulty of scenarios and provides a high level of accuracy. The findings and training are used to enhance the effectiveness of deep reinforcement learning-based autonomous driving rules. © 2024 IEEE.

关键词： Adversarial machine learning

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An Identification of Guava Fruit Disease Using ML 3

An Identification of Guava Fruit Disease Using ML

引用

3rd international conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

作者： Ahmed, Khandakar Rabbi Salam, Towfika Nandi, Subarna Hasan, Nazmul Rashid, Omor Faruk Al Miraz, Shafiun Reza, Md. Shafi Rahman, Farjana International University of Business Agriculture and Technology Uttara Model Town Miyan Research Institute Dhaka Bangladesh Kazla Dept. of Mechatronics Engineering Rajshahi6204 Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh London South Bank University Dept. of Data Science 103 Borough Rd LondonSE1 0AA United Kingdom Varendra University Dept. of Computer Science and Engineering Rajshahi Bangladesh International University of Business Agriculture and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Jeonbuk National University Graduate School of Integrated Energy of AI North Jeolla Jeonju Korea Republic of

ISBN: (纸本)9798350388282

Fruits contain a lot of fiber. Fruits contain biologically active substances that improve our health. This study focuses on identifying and classifying guava fruit diseases. Guava disease has become a significant issue for guava production, threatening farmers' socioeconomic growth. As a result of this phenomenon, an automated computer vision-based guava disease diagnosis system was developed that can detect malicious guava and direct it to early cure approaches, reducing relative economic loss. In light of this, we present in this study a guava illness detection and categorization recommendation approach based on convolutional neural networks (CNN). This paper employs transfer learning to classify images using our customized convolutional neural network (CNN) model architecture. The photographs in the data set were obtained from the Mendeley Data website. The data set includes 306 images of healthy and unhealthy guava fruits and leaves. The four disease classes targeted by the data sets are dot, Canker, mummification, and Rust. We obtained an average accuracy of 74.72% for training and 34.74% for testing from the data set used. © 2024 IEEE.

关键词： Fruits

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