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Smart Medical Box using Arduino

Smart Medical Box using Arduino

引用

International conference on ent Computing and control systems (ICICCS)

作者： Sweadha. M M. Selvi Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The Smart Medical Box is a sophisticated IoT-driven solution designed to enhance medication adherence by utilizing computer vision and machine learning. The system automates the identification and extraction of essential information from medication labels, ensuring precision in dosage reminders and reducing human error. It incorporates a high-resolution camera, an OCR engine, and an Arduino-based microcontroller to enable seamless image processing and real-time analysis. With an intuitive interface and GPS-enabled location services, users can efficiently manage their medication schedules while accessing nearby pharmacies when needed. This research focuses on designing and implementing a scalable and cost-effective system that improves medication compliance and minimizes health risks associated with missed or incorrect dosages. By integrating advanced image processing techniques and AI-driven recognition algorithms, the Smart Medical Box ensures high accuracy in identifying medications. Additionally, features such as automated alerts, real-time monitoring, and pharmacy locator tools enhance the system's usability and accessibility. This innovation is particularly beneficial for elderly individuals and patients with chronic conditions, offering a simplified and automated approach to medication tracking. Performance evaluations of the system indicate a significant improvement in medication adherence, a high recognition accuracy rate, and positive user feedback. future enhancements, including AI-based OCR, voice assistance, and mobile application connectivity, are expected to further improve functionality and ease of use. This paper presents the conceptualization, development, and testing of the Smart Medical Box, highlighting its potential to revolutionize personal healthcare management by providing an intelligent, efficient, and user-friendly solution.

关键词： Accuracy Image recognition Microcontrollers Optical character recognition Medical services Real-time systems Usability Older adults Biomedical imaging Global Positioning System

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Thai Beef Cattle Recognition for Fattening Farms: An Empirical Study of Cattle Cooperative Practices in Chiang Rai

Thai Beef Cattle Recognition for Fattening Farms: An Empiric...

引用

International ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Ant Maw Khon Myint Myat Pradorn Sureephong Qing Fan Santichai Wicha School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand College of Arts Media and Technology Chiang Mai University Chiang Mai Thailand Key Laboratory of China(Guangxi)-ASEAN CrossBorder Animal Disease Prevention and Control Ministry of Agriculture and Rural Affairs of China Guangxi Veterinary Research Institute Guangxi China Computer and Communication Engineering for Capacity Building (CCC) School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This research focuses on developing an automated system to identify the breed and sex of Thai beef cattle using advanced computer vision technology. By using the YOLOv11 (You Only Look Once) model, a state-of-the-art object detection tool, this system can quickly and accurately identify cattle breeds and determine their sex. High-resolution image datasets were collected and augmented, yielding 81.2% accuracy for breed detection and 95.0% for sex classification, with mAP@50 scores of 85.1% and 99.3%, respectively. However, limited data for certain breeds, like Thai Native and Japanese cattle, reduced the model’s performance for those categories. To overcome this, we aim to expand the dataset from CCTV footage in future studies. The system will include user-friendly features, such as real-time alerts and dashboards, making it practical for farmers to use. This project demonstrates how AI can improve cattle farming by saving time, reducing errors, and supporting better decisions. future improvements will explore applications in disease detection and behavior monitoring.

关键词： YOLO Deep learning computer vision Cows Real-time systems Data models Object recognition Monitoring Farming Diseases

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Improvement and Performance of Data Transmission Algorithms in computer Communications

Improvement and Performance of Data Transmission Algorithms ...

引用

International conference on Communication systems and Network Technologies (CSNT)

作者： Yi Liu Hao Liu Yun Cheng Siqiang Cheng Information School Hunan University of Humanities Science and Technology Loudi China

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

In response to the current problems of low data transmission efficiency, high latency, and insufficient stability in computer communications, this paper studies a comprehensive optimized data transmission algorithm, which aims to improve network resource utilization efficiency and transmission performance and reduce the frequency of congestion by dynamically adjusting the transmission rate, adaptive congestion control and queue management optimization. Firstly, a dynamic rate adjustment mechanism based on real-time network status detection is designed to monitor the network bandwidth, latency, and packet loss rate in real time to dynamically adjust the data packet transmission rate. Secondly, an adaptive congestion control strategy is applied to reduce the impact of congestion on data transmission by monitoring the network congestion status in real time and adjusting it according to the changing trend. Finally, queue management and priority scheduling algorithms are used to reasonably arrange the transmission order of data packets, reduce queuing delays, and improve the transmission efficiency of high-priority data packets. In terms of latency and throughput, as latency increases, throughput gradually decreases. Taking the bandwidth of 100Mbps as an example, when the network latency is 20ms, the throughput is 92.15Mbps, and when the latency is 100ms, the throughput drops to 74.11Mbps. The optimized data transmission algorithm proposed in this paper significantly improves the efficiency and stability of network transmission by dynamically adapting to network conditions. In future research, the application of this algorithm can be further expanded, and its adaptability and robustness in more complex network environments and high-load applications can be enhanced to improve the reliability of data transmission.

关键词： Adaptive systems Heuristic algorithms Packet loss Complex networks Bandwidth Throughput Real-time systems Stability analysis Data communication Thermal stability

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Deployment of Large Language Models to control Mobile Robots at the Edge

Deployment of Large Language Models to Control Mobile Robots...

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Mechatronics, control and Robotics (ICMCR), International conference on

作者： Pascal Sikorski Leendert Schrader Kaleb Yu Lucy Billadeau Jinka Meenakshi Naveena Mutharasan Flavio Esposito Hadi AliAkbarpour Madi Babaias Computer Science Department Saint Louis University Saint Louis USA Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This paper investigates the possibility of intuitive human-robot interaction through the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in mobile robotics. This work aims to explore the feasibility of using these technologies for edge-based deployment, where traditional cloud dependencies are eliminated. The study specifically contrasts the performance of GPT-4-Turbo, which requires cloud connectivity, with an offline-capable, quantized version of LLaMA 2 (LLaMA 2-7B.Q5 K M). These results show that GPT-4-Turbo delivers superior performance in interpreting and executing complex commands accurately, whereas LLaMA 2 exhibits significant limitations in consistency and reliability of command execution. Communication between the control computer and the mobile robot is established via a Raspberry Pi Pico W, which wirelessly receives commands from the computer without internet dependency and transmits them through a wired connection to the robot's Arduino controller. This study highlights the potential and challenges of implementing LLMs and NLP at the edge, providing groundwork for future research into fully autonomous and network-independent robotic systems. For video demonstrations and source code, please refer to: https://***/MobileRobotGPT4LLaMA2024.

关键词： Cloud computing Mechatronics Large language models Source coding Human-robot interaction Natural language processing Software reliability Mobile robots Edge computing

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Tawna Yachaq an Intelligent System for the safe movement of people with visual disabilities

Tawna Yachaq an Intelligent System for the safe movement of ...

引用

IEEE Students' conference on Electrical, Electronics and computer Science (SCEECS)

作者： Víctor Díaz Carrasco Bryan Barzola Melgar Luis Quispe Sayán Ricardo Palomares School of Electronic Engineering and Telecommunications National Technological University of Lima South Lima Peru Research Group of Computing and Cognitive Neuroscience National Technological University of Lima South Lima Peru

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

The development of the intelligent system "Tawna Yachaq" is presented for the safe movement of a volunteer with visual disabilities. This system includes a cane with an obstacle detection system, an artificial vision system for the identification of objects and people, with an alert and position warning system in a controlled environment. The mechanical system consists of an intelligent system protection box developed in Fusion 360 software. The electronic-electrical design of the intelligent system, based on the Raspberry Pi 4B microprocessor. Includes a Neo 6M GPS module to provide real-time user location. Using HC-SR04 ultrasonic sensors and a buzzer module, it emits an alert sound to the user. In addition, an ESP32-Cam camera that uses computer vision algorithms detects predefined objects in the university campus environment. The system is powered by 7.4V Lion rechargeable batteries, with an LM2596 voltage regulator ensuring stable operation. A patent is proposed as future work.

关键词： Visualization Renewable energy sources Regulators Software Real-time systems Wind turbines Intelligent systems Voltage control Sustainable development Protection

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Integrating AI into Software Engineering: A Critical Review and future Directions

Integrating AI into Software Engineering: A Critical Review ...

引用

Intelligent control, Computing and Communications (IC3), International conference on

作者： Aditya Pai H Sharath K R Kavita Babalad Guru Prasad M S Chandrappa S Pratik Kumar MIT School of Computing MIT Art Design and Technology University Pune India Department of Computer Science and Engineering Graphic Era (Deemed-to-be University) Dehradun India School of Computing and Information Technology REVA University Bangalore India School of Computer Science and Engineering JAIN (Deemed-to-be University) Bengaluru India Department of Computer Applications Graphic Era (Deemed-to-be University) Dehradun India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The field of Artificial Intelligence (AI) has been witnessing a huge demand in the field of research, tools development, and applications of deployment. There are multiple software companies which are shifting their focus to developing AI systems, many are also deploying the AI paradigms to their current system. Correspondingly, the academic research community has also used AI paradigms to solve the traditional software engineering problems. AI has become very useful to the software engineering community. The paper also uses a survey of the most commonplace methods of using AI into the Software Engineering, that covers the methods for SE phases such as Requirements, Design, Development, Testing, Release, and Maintenance. The paper also aims in answering to the sufficient intelligence in the SE lifecycle, this evaluates the overlapping of the SE and AI domains, and challenge the current conventional wisdom of the state-of-the-art.

关键词： Software testing Surveys Software maintenance Reviews Software algorithms Prediction algorithms Requirements engineering Artificial intelligence Software engineering Software development management

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Integration of Chemometric Analysis and Machine Learning for Predictive Classification of Raisin Quality

Integration of Chemometric Analysis and Machine Learning for...

引用

2025 International conference on Visual Analytics and Data Visualization, ICVADV 2025

作者： Padmanaban, Gokul Princy Suganthi Bai, S. Hindustan Institute of Technology & Science Department of Computer Application Chennai India Hindustan Institute of Technology & Science Department of Computer Science Chennai India

ISBN: (纸本)9798331521394

The integration of chemometric analysis and machine learning techniques to enhance the predictive classification of raisin quality, a vital task for agricultural and food processing industries. The study employs chemometrics to analyze physical and chemical characteristics, selecting critical features such as color, texture, and chemical composition to reduce data redundancy and optimize model accuracy. Various machine learning algorithms, including Support Vector Machines (SVM), and Artificial Neural Networks (ANN), are applied and compared to predict raisin quality. By merging chemometric approaches with advanced machine learning methods, the proposed framework demonstrates improved classification accuracy over traditional techniques, showcasing its potential for real-world applications in quality control and automated sorting systems. future efforts will aim to expand the dataset, refine model performance, and explore new feature selection techniques to further boost classification accuracy. © 2025 IEEE.

关键词： Support vector machines

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Using Fitts' Law to Benchmark Assisted Human-Robot Performance 25

Using Fitts' Law to Benchmark Assisted Human-Robot Performan...

引用

ACM/IEEE International conference on Human-Robot Interaction (HRI)

作者： Jiahe Pan Jonathan Eden Denny Oetomo Wafa Johal Department of Mechanical Engineering The University of Melbourne Melbourne Australia School of Computing and Information Systems The University of Melbourne Melbourne Australia

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Shared control systems aim to combine human and robot abilities to improve task performance. However, achieving optimal performance requires that the robot's level of assistance adjusts the operator's cognitive workload in response to the task difficulty. Understanding and dynamically adjusting this balance is crucial to maximizing efficiency and user satisfaction. In this paper, we propose a novel benchmarking method for shared control systems based on Fitts' Law to formally parameterize the difficulty level of a target-reaching task. With this we systematically quantify and model the effect of task difficulty (i.e. size and distance of target) and robot autonomy on task performance and operators' cognitive load and trust levels. Our empirical results (N=24) not only show that both task difficulty and robot autonomy influence task performance, but also that the performance can be modelled using these parameters, which may allow for the generalization of this relationship across more diverse setups. We also found that the users' perceived cognitive load and trust were influenced by these factors. Given the challenges in directly measuring cognitive load in real-time, our adapted Fitts' model presents a potential alternative approach to estimate cognitive load through determining the difficulty level of the task, with the assumption that greater task difficulty results in higher cognitive load levels. We hope that these insights and our proposed framework inspire future works to further investigate the generalizability of the method, ultimately enabling the benchmarking and systematic assessment of shared control quality and user impact, which will aid in the development of more effective and adaptable systems.

关键词： Adaptation models Teleoperators Systematics Human-robot interaction Benchmark testing Cognitive load control systems Real-time systems Robots Load modeling

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Design of Automatic Print Defect Detection System Based on Machine Vision Detection Algorithm

Design of Automatic Print Defect Detection System Based on M...

引用

Power Electronics, computer Applications (ICPECA), IEEE International conference on

作者： Chao Wang Feiyan Li Zijuan Xu Yunnan Xinhua Printing Factory No. 5 Co. Ltd Kunming China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

In the context of today's digital production, the quality inspection of printed materials has become a key technology to improve printing efficiency and quality of finished products. Especially with the rapid development of the printing industry, the traditional manual inspection method has been difficult to meet the needs of large-scale, high-efficiency production. In order to solve this problem, the automatic inspection system of print defects based on machine vision comes into being, which can not only greatly improve the detection speed and accuracy, but also effectively reduce the labor cost. This paper proposes an efficient defect detection method for printed materials, combining key technologies such as image differencing, binarization, mathematical morphology algorithms, Blob analysis and connectivity analysis to realize automatic identification and classification of minor defects in printed materials. The design and experimental results of the system show that the method has significant advantages in real-time and detection accuracy, and is expected to play an important role in future printing quality control.

关键词： Printing Industries Accuracy Machine vision Morphology Production Quality control Inspection Real-time systems Defect detection

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Probabilistic Modeling and Uncertainty Quantification of Harmonic Distortions in Grid-Integrated Inverters Through Bayesian Neural Networks

Probabilistic Modeling and Uncertainty Quantification of Har...

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Intelligent control, Computing and Communications (IC3), International conference on

作者： Srinivasa Rao Neeta Awasthy V. Asha Ginni Nijhawan Gurmeet Singh Ali Albawi E. Annapoorna Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Department of Computer Science and Engineering GL Bajaj Group of Institutions Mathura U.P. India Master of Computer Application New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of AIMLE GRIET Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Harmonic distortion in grid connected inverters Thus, impacts on power quality and system stability are high, and more especially for systems that use renewable energy sources. This research presents a new stochastic predictive modelling approach based on Bayesian Neural Networks for forecasting of harmonic distortions with prediction uncertainty. The proposed methodology uses data from the National Renewable Energy Laboratory (NREL) database that consists of detailed grid voltage, current under various REMs. Harmonics components derived via sophisticated signal processing algorithms then yields the desired data base for training and testing. The uncertainty of grid conditions can be modelled by means of probabilities due to the utilization of BNNs for improving the reliability of predictions. The combination of stochastic modelling and harmonic analysis in this work creates a complex approach to enhancing grid stability and power quality. As applied to renewable energy challenges, the common method enhances the proposed approach as a scalable and adaptive solution for the mitigation of harmonic impacts for future power systems.

关键词： Renewable energy sources Adaptation models Uncertainty Stochastic processes Power system harmonics Predictive models Power system stability Harmonic analysis Inverters Harmonic distortion

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