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Development of an Expert System for advanced Podiatric Treatments and Ergonomics

Development of an Expert System for Advanced Podiatric Treat...

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International Symposium on advanced Computing and Communication (ISACC)

作者： P Vigneshwaran V Buvanesh Pandian M Radha B Mohan R Santhana Krishnan J Relin Francis Raj Department of Electronics and Communication Engineering P.S.R. Engineering College Sivakasi India Department of Electrical and Electronics Engineering Kalasalingam Academy of Research and Education Krishnankoil India Department of Electronics and Communication Engineering Francis Xavier Engineering College Tirunelveli India Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

An expert system tailored for foot pressure analysis and imprint detection, with a focus on enhancing podiatric treatments and ergonomics. The system comprises three key components: a foot pressure analyser, an image processing-based foot imprint analyser, and a machine learning-driven data analyser. The foot pressure analyser employs an array of FSR sensors with piezo resistive material Velostat, accommodating various foot types. The collected data is processed using thermal image algorithms to create foot pressure images. The image processing unit of the system utilizes edge detection techniques to extract relevant features from the foot pressure images, forming a dataset for machine learning. A neural network is trained using this dataset to identify lower limb abnormalities accurately. The expert system encompasses an extensive knowledge base, storing foot anatomy, pressure point norms, common foot conditions, footwear information, and also analyses lower limb extremities like arthritis and synovial accumulations etc., especially helps in geriatric care. The system generates comprehensive reports summarizing the analysis results, facilitating treatment planning for specific applications, age groups, genders, and foot shapes and giving real-time feedback and recommendations based on the Expert’s knowledge to aid in treatment planning, ensuring accessibility and data security. Future developments include 3D printing integration, research support, and machine learning enhancements. The system promises to advance foot health diagnostics and treatments significantly, benefiting healthcare professionals and patients.

关键词： Limbs Shape Medical services Machine learning Footwear Three-dimensional printing Planning Expert systems Foot sensor arrays

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A Comparative Study of Various Human Activity Recognition Techniques Using Deep Learning 1st

A Comparative Study of Various Human Activity Recognition Te...

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1st International conference on advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Gupta, Saurabh Mahapatra, Rajendra Prasad Verma, Kamal Kant Department of Computer Science and Engineering Delhi NCR Campus SRM Institute of Science and Technology Ghaziabad India Verma School of Computer Science and Engineering IILM University Greater Noida India

ISBN: (纸本)9783031860683

In the realm of scientific research, the domain of Human Activity Recognition (HAR) stands as a well-established field, tirelessly committed to the task of automating the identification and categorization of human activities. This endeavor relies on an array of sensors as data sources, nurturing a multitude of applications across diverse domains such as healthcare, sports analysis, surveillance, and human-computer interaction. Within the pages of this comprehensive survey paper, our purpose is to embark on a journey through the contemporary landscape of HAR. In this paper, we shall examine on meaningful components, including sensor-based modalities that incorporate different types of sensors being used. The various kind of feature extractors used to find meaningful patterns from the input raw data and the kind of various classification algorithm developed to recognize these human activities along with measuring parameters to measure the efficiency of the HAR system deployed in real time environment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Real time systems

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IoT-Enabled Smart Classrooms for Enhanced Learning Environments

IoT-Enabled Smart Classrooms for Enhanced Learning Environme...

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Computational Intelligence, Communication Technology and Networking (CICTN), International conference on

作者： Prem Kumar Priyanshu Negi Priyanka Sharma Pratham Mittal School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Innovative integration of digital infrastructure with pedagogical practices in rapidly transforming educational environments. The technology is well recognized yet fails to solve issues in traditional classrooms due to poor resource management, less individualized learning experiences, and real-time performance monitoring. The research focuses on these issues and answers them by designing and implementing an IoT-enabled smart classroom ecosystem aiming at changing the learning environment. Developed an end-to-end IoT framework that incorporates sensor networks, machine learning algorithms, and adaptive learning interfaces across multiple educational institutions using a mixed-method approach. This included prototype development, systematic data collection, and iterative performance analysis using advanced analytics and user experience assessments. Significant learning engagement improvements by 23.7%. Resource usage efficiency improves by 35.2%. Excellent Personalized learning results, Real-time environmental monitoring of the IoT system, Adaptive instructional strategy with the complete track record of the student. The precision control in climate through sensors for an optimum lighting effect Smart management of the space using sensors. In sum, our research establishes a transformative model for technology-enhanced educational spaces, providing a scalable blueprint for future smart learning environments where technological innovation is integrated into pedagogical effectiveness.

关键词： Temperature measurement Technological innovation Systematics Space technology Prototypes Educational technology Aerospace electronics Real-time systems User experience Resource management

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A Fully-Integrated Wireless Ingestible Drug Delivery Chip with Electrochemical Energy Harvesting and pH-Based MPPT

A Fully-Integrated Wireless Ingestible Drug Delivery Chip wi...

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Custom Integrated Circuits conference (CICC)

作者： So-Yoon Yang Deniz Umut Yildirim Saransh Sharma Donghyeon Han Rishabh Mittal Husna Ellis Jaehong Jung Eunseok Lee Yubin Cai Giovanni Traverso Anantha P. Chandrakasan Massachusetts Institute of Technology USA Chung-ang University Republic of Korea MediaTek USA

ISBN: (数字)9798331517458

ISBN: (纸本)9798331517465

Advances in personalized medicine are spurring the development of ingestible electronics for controlled, on-demand drug delivery in the gastrointestinal (GI) tract, enhancing therapeutic efficacy further beyond traditional oral pills. These systems rely on electronically controlled drug release actuation mechanisms, like micropumps [1] and reservoir-based designs [2], for precision dosing [3], [4]. However, they often require substantial energy and space [5]. While conventional batteries have powered ingestible electronics, they pose challenges due to their bulkiness, limited energy density, and safety risks associated with toxic materials [6], [7]. Consequently, battery-free energy harvesting solutions and energy-efficient drug delivery actuation mechanisms are crucial for progress in this field. Among other energy-harvesting methods, such as thermal or vibrational energy harvesters, a galvanic cell (GC), which converts chemical energy from acidic GI fluid, is particularly well-suited for high-power applications like drug delivery [6]. However, the maximum power point (MPP) of GC is a nonlinear function of pH and opencircuit voltage [2], necessitating the sampling of real-time pH data of the GI fluid to perform maximum power point tracking (MPPT) for efficient energy harvesting. For drug delivery, a reservoir-based system sealed with an electrochemically dissolvable metal membrane offers a compact design and protection of sensitive payloads such as unstable drugs from the harsh environment of the GI tract [2], [8]. However, the activation voltage for dissolving the metal membrane of the reservoirbased systems also varies with pH, further highlighting the need to sample the GI pH in real-time [9].

关键词： Maximum power point trackers Drugs Wireless communication Wireless sensor networks Fluids Metals Voltage Drug delivery Real-time systems Energy harvesting

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2nd International conference on Agricultural-Centric Computation, ICA 2024

2nd International Conference on Agricultural-Centric Computa...

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2nd International conference on Agricultural-Centric Computation, ICA 2024

ISBN: (纸本)9783031744396

The proceedings contain 26 papers. The special focus in this conference is on Agricultural-Centric Computation. The topics include: Enhancing Horticulture Field Security: Intruder Detection Utilizing Wi-Fi-CSI Technology with ESP32 Modules;Negative Affective State Vocalization Analysis of Dairy Cattle Using 3D MFCC Features with CNN-LSTM Model on an Edge Device;comparative Analysis of Machine Learning Based Soil pH Prediction Using Spectral Bands and Indices;Fruit Detection Using DepthAI and Convolutional Block Attention Module;KrishiAI: Architecture for Harnessing Capabilities of LLMs for Delivery of Accurate Cultivation Information to Farmers;Detection of Potato Leaf Diseases Using PSOK Image Segmentation and CNN Model;application of Industry 4.0 for Enhancing Climate Compliant Irrigation System in Agriculture;ambiTag Blue: Bluetooth Low Energy Based Environment Monitoring and Data Logging Solution;BLE Receiver Antenna Design for Monitoring and Sensing applications;digital Entomology sensor for advanced Biodiversity Monitoring and Precision Agriculture;a Novel Autonomous Bird Deterrent System for Crop Protection Using Drones;blockchain-Powered Smart Agriculture: Harnessing Cyber-Physical systems to Enhance Farmer Profits;design of IoT Enabled Smart sensor System for In-situ Black Pepper Plant Health Monitoring Using Deep Learning Model;Machine Learning Based Approach to Detect Adulteration in Turmeric Using RGB and Thermal Images;modeling and Analysis of Thermal Dynamics of Polyhouses for Precision Agriculture;ioT Enabled Irrigation for Roadside Plantation;UAV-Borne Hyperspectral Imaging Dataset of Pearl Millet Canopy Water Stress;enhancing the Explainability and Interpretability of Crop Yield Prediction Models Through Precision Agriculture;investigating the Segment Anything Model for Crop Head Counting in Cereal Crops;real Time Detection and Classification of Strawberry Developmental Stages Using Deep Learning: A Technological Approach for Precision Agriculture;a

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Real-Time Detection of Road Objects and Lane Markings for Autonomous Vehicles

Real-Time Detection of Road Objects and Lane Markings for Au...

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Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： Kanagamalliga S Latha R Sugitha N Iraianbu E Guru S Renugadevi R Dept. of Electronics and Communication Engineering Saveetha Engineering College Chennai India Dept. of CSE Vignan's Foundation for Science Technology and Research Guntur Andhrapradesh

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

This research focuses on the development of an advanced object and lane recognition system for autonomous vehicles, leveraging the YOLOv8 Deep Learning (DL) model. The primary goal is to ensure accurate, real-time recognition of road objects, lane boundaries, and other critical features to enhance autonomous navigation. The methodology involves preprocessing and augmentation of a diverse dataset, followed by training and testing the YOLOv8 model. This approach ensures robustness under varying environmental and traffic conditions, including occlusions and lighting challenges. The final model is integrated into an intuitive user interface that provides real-time visual feedback, enabling seamless interaction and monitoring. Comprehensive evaluations were conducted to validate the system’s performance. The results demonstrated high accuracy in recognizing objects like vehicles, and pedestrians, as well as stable lane recognition across diverse scenarios. Despite minor limitations in extreme conditions, the system proved to be reliable and efficient for real-world applications. Future work will aim to expand functionality by incorporating additional sensors like LiDAR and optimizing the system for edge devices to reduce computational overhead. Additional features, such as traffic sign recognition and obstacle prediction, will also be explored. The proposed system serves as a robust foundation for enhancing Autonomous Vehicle (AV) technology, contributing significantly to road safety and intelligent transportation systems. Through innovative integration of machine learning techniques, this research addresses key challenges in autonomous navigation and lays the groundwork for further advancements in the field. This research addresses inaccurate object detection and unstable lane recognition in autonomous vehicles. The proposed system improves accuracy and reliability for safer self-driving technology.

关键词： Accuracy Laser radar Lighting User interfaces sensor fusion Real-time systems Robustness Object recognition Autonomous vehicles Testing

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ElephantGuardNet: A Comprehensive Solution for Elephant Conservation and Human-Elephant Conflict Reduction

ElephantGuardNet: A Comprehensive Solution for Elephant Cons...

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Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： S. Naveen R. Dhamotharan S. Sahebzathi R. Santhana Krishnan V. Vinoth Kumar P. Sundaravadivel Department of Mechanical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Information Technology Kalasalingam Academy of Research and Education Krishnankoil India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Artificial Intelligence and Machine Learning Saveetha Engineering College Chennai India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The ElephantGuardNet system is an advanced technological framework designed to monitor and protect elephants while minimizing human-elephant conflict. The system leverages a combination of real-time data collection, AI-driven analysis, and IoT sensors to track elephant movements across vast territories. By integrating wildlife camera traps, drones, satellite imagery, and IoT sensors such as infrared motion detectors and seismic sensors, the system provides continuous monitoring of elephant activity, enabling proactive management of potential risks. A custom dataset, ElephantMovementTracker, compiled from diverse data sources, forms the foundation for the model's training. Preprocessing techniques such as data normalization, augmentation, and noise filtering enhance the dataset's quality and ensure its suitability for deep learning applications. EfficientNet B7 and YOLO are employed for image and real-time detection tasks, respectively, while 3D CNNs are used for video analytics, enabling accurate tracking of dynamic movement patterns. GRU-based models predict future elephant movements, helping assess the likelihood of conflict. XGBoost is utilized for classification tasks, evaluating the risk of human-elephant conflict. The system is deployed on AWS and incorporates NVIDIA Jetson Nano for real-time detection and automated alerting via SMS and email. IoT sensors and automated deterrent systems, including sound emitters and drones, further mitigate conflict risk. The system's effectiveness in reducing human-elephant conflicts and providing a scalable solution for elephant conservation demonstrates the potential of AI and IoT integration in wildlife protection efforts, offering a comprehensive approach to both conservation and human-elephant coexistence.

关键词： Deep learning YOLO Accuracy Tracking Visual analytics Wildlife Predictive models Real-time systems sensor systems Drones

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A Lossless Image, Video and Audio Encryption Method Based Hybrid Chaotic Map and DNA Encryption 3rd

A Lossless Image, Video and Audio Encryption Method Based H...

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3rd International conference on Advancements in Smart Computing and Information Security, ASCIS 2024

作者： Khaladkar, Vrushali Kumar, Manish Maharashtra Pune India Department of Mathematics Birla Institute of Technology and Science Pilani Hyderabad Campus Jawahar Nagar Kapra Mandal Medchal District Telangana Hyderabad500078 India

ISBN: (纸本)9783031863042

The suggested lightweight video encryption strategy offers a promising method for safeguarding multimedia data in cyberspace. The proposed strategy is based on a hybrid chaotic map and DNA encryption. Due to the fewer dimensions of the chaotic map, it can be adapted to secure real-time data generated using closed-circuit television and other Wireless sensors network tools. The strategy provides a strong level of security and resistance against different attacks by utilizing advanced cryptographic techniques including hybrid chaotic systems and DNA encryption. The proposed work is decently compared with other contemporary competing encryption schemes which shows that the proposed one can be adapted for the encryption of videos in lightweight applications. The thorough assessment using simulation results and statistical experiments highlights the practical applicability and efficiency of the proposed encryption technique. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Wireless sensor networks

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Medical respiratory monitoring sensors based on microbend fiber loss 7

Medical respiratory monitoring sensors based on microbend fi...

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conference on advanced sensor systems and applications vii

作者： Zhao, Yong Zhouxiao, Liuting Yang, Jian Li, Xianjing Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781510604698;9781510604704

In this work, a medical respiratory monitoring sensor based on the microbend effect of optical fiber on light transmission is proposed. The microbend effect of multimode optical fiber is analyzed theoretically using optical theory. A respiratory signal modulator with a "sandwich" microbender structure is designed enabling the noninvasive real-time monitoring. In vitro testing showed that the proposed sensor has excellent following characteristics and can automatically discern respiratory condition, the signal-to-noise ratio can be better than 28dB.

关键词： optical fiber sensor microbend loss respiratory signal modulator breathing frequency

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Development of fiber optical temperature sensor based on fluorescence lifetime 7

Development of fiber optical temperature sensor based on flu...

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conference on advanced sensor systems and applications vii

作者： Zhao, Yong Zheng, Hong-kun Li, Gui-lin Yue, Ming-yang Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781510604698;9781510604704

This paper puts forward a kind of optical fiber temperature sensor based on fluorescence lifetime, which can be applied to measurement in strong electromagnetic, strong corrosion and other harsh environment. A small volume, long service life, strong anti-jamming capability of fluorescence temperature sensor was designed by matching rare earth fluorescent material with longer fluorescent lifetime with tee optical coupler. The experimental results show that this method has a high measuring precision within the scope of 0-90 degrees C.

关键词： fluorescence lifetime optical couple optical fiber temperature measurement rare earth fluorescent material

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