This document presents a virtual fitness trainer system that provides real-time feedback on a user's exercise form using the Kinect sensor. The system tracks a user's skeleton joints and uses a random forest classifier to identify the exercise being performed and compare it to a dataset of proper form. If errors are detected, the system provides feedback to the user. The goal is to help users exercise properly at home without an in-person trainer. The system was tested on 5 basic exercises and able to accurately recognize exercises and detect form errors in real-time.
Presentazione human daily activity recognition with sparse representation u...Fabio Greco
Abstract of case study—Human daily activity recognition using mobile personal sensing technology plays a central role in the field of pervasive healthcare. One major challenge lies in the inherent complexity of human body movements and the variety of styles when people perform a certain activity. To tackle this problem, is presented a novel human activity recognition framework based on recently developed compressed sensing and sparse representation theory using wearable inertial sensors. This approach represents human activity signals as a sparse linear combination of activity signals from all activity classes in the training set. The class membership of the activity signal is determined by solving a L^1 minimization problem. Experimentally is validated the effectiveness of the sparse representation-based approach by recognizing nine most common human daily activities performed by 14 subjects.This approach achieves a maximum recognition rate of 96.1%, which beats conventional methods based on nearest neighbor, naive Bayes, and support vector machine by as much as 6.7%. Furthermore ( in the original paper form Mi Zhang, Student Member, IEEE, and Alexander A. Sawchuk, Life Fellow, IEEE) is demonstrated that by using random projection, the task of looking for “optimal features” to achieve the best activity recognition performance is less important within this framework.
human activity recognization using machine learning with data analysisVenkat Projects
Human activity recognition, or HAR for short, is a broad field of study concerned with identifying the specific movement or action of a person based on sensor data.
The sensor data may be remotely recorded, such as video, radar, or other wireless methods. It contains data generated from accelerometer, gyroscope and other sensors of Smart phone to train supervised predictive models using machine learning techniques like SVM , Random forest and decision tree to generate a model. Which can be used to predict the kind of movement being carried out by the person, which is divided into six categories walking, walking upstairs, walking down-stairs, sitting, standing and laying?
MLM and SVM achieved accuracy of more than 99.2% in the original data set and 98.1% using new feature selection method. Results show that the proposed feature selection approach is a promising alternative to activity recognition on smart phones.
This document summarizes a student project on human activity recognition using smartphones. A group of 4 students submitted the project to partially fulfill requirements for a Bachelor of Technology degree in computer science and engineering. The project involved developing a system to recognize human activities using the accelerometer and gyroscope sensors in smartphones. Various machine learning algorithms were tested and evaluated on experimental data collected from smartphone sensors. The goal of the project was to create an accurate and lightweight activity recognition system for smartphones, while also exploring active learning methods to reduce the amount of labeled training data needed.
This document provides an overview of approaches for human activity recognition (HAR). It discusses vision-based approaches including using hand-crafted motion features, depth information methods, and deep learning techniques. Deep learning methods covered include two-stream inflated 3D networks, deep bidirectional LSTM with CNN features, and skeleton-based spatial temporal graph convolutional networks. The document also discusses potential future directions for HAR, which may involve using 3D features, unsupervised learning, skeleton-based methods for privacy, and optimization/quantization. HAR applications in the future could leverage the power of modern AI and embedded abilities while meeting requirements like real-time performance, privacy, and ease of deployment.
IRJET- Convenience Improvement for Graphical Interface using Gesture Dete...IRJET Journal
This document discusses a proposed system for improving graphical user interfaces using hand gesture detection. The system aims to allow users to access information from the internet without using input devices like a mouse or keyboard. It uses a webcam to capture images of hand gestures, which are then processed using techniques like skin color segmentation, principal component analysis, and template matching to recognize the gestures. The recognized gestures can then be linked to retrieving specific data from pre-defined URLs. An evaluation of the system found it had an accuracy rate of 90% in real-time testing for retrieving data from 10 different URLs using 10 unique hand gestures. The proposed system provides a more convenient interface compared to traditional mouse and keyboard methods.
An Efficient VLSI Design of AES Cryptography Based on DNA TRNG DesignIRJET Journal
This document describes an efficient VLSI design for AES cryptography using a true random number generator (TRNG) and DNA encoding. It aims to improve security and reduce area and delay compared to standard AES. The design generates random round keys using a TRNG instead of the standard key expansion process. It further encodes a partial key from the TRNG using DNA encoding to produce the full 128-bit key, strengthening security. Simulation and synthesis results show the TRNG-based AES has lower area and delay than standard AES. Combining the TRNG with DNA encoding further optimizes the design.
An Intelligent Human Computer Communication with Real Time Hand Gesture for M...IJERA Editor
This document presents a system for controlling a wheelchair using finger gestures. A camera is mounted on the wheelchair to capture images of hand gestures. The images are processed using digital image processing techniques like blurring, color space conversion from RGB to HSV, and thresholding to detect and recognize fingers. The finger positions are used to determine gestures for controlling the wheelchair motors and directing its movement forward, backward, left, right, or stopping. An algorithm is provided to map finger positions to specific motor controls. The system was tested with 5 finger gestures and achieved 100% accuracy in controlling the wheelchair movement as intended by each gesture. The goal of the system is to provide an easier way for disabled people to control a wheelchair through simple hand gestures without
MODEL MONITORING PHYSICAL EXERCISE HEART RATE USING INTERNET OF THINGS (MMPEH...ijait
The document describes a proposed model called Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT). The model was designed to monitor heart rate during physical exercise using IoT devices. It consists of six main components: a SmartHeart device to collect heart rate data, a wireless network to transmit data, a SoftAPP to analyze data, a knowledgebase to store data, a server to facilitate user requests, and a user interface. The model aims to prevent health risks from vigorous exercise and promote healthy living by monitoring individuals' heart rates during physical activity.
Presentazione human daily activity recognition with sparse representation u...Fabio Greco
Abstract of case study—Human daily activity recognition using mobile personal sensing technology plays a central role in the field of pervasive healthcare. One major challenge lies in the inherent complexity of human body movements and the variety of styles when people perform a certain activity. To tackle this problem, is presented a novel human activity recognition framework based on recently developed compressed sensing and sparse representation theory using wearable inertial sensors. This approach represents human activity signals as a sparse linear combination of activity signals from all activity classes in the training set. The class membership of the activity signal is determined by solving a L^1 minimization problem. Experimentally is validated the effectiveness of the sparse representation-based approach by recognizing nine most common human daily activities performed by 14 subjects.This approach achieves a maximum recognition rate of 96.1%, which beats conventional methods based on nearest neighbor, naive Bayes, and support vector machine by as much as 6.7%. Furthermore ( in the original paper form Mi Zhang, Student Member, IEEE, and Alexander A. Sawchuk, Life Fellow, IEEE) is demonstrated that by using random projection, the task of looking for “optimal features” to achieve the best activity recognition performance is less important within this framework.
human activity recognization using machine learning with data analysisVenkat Projects
Human activity recognition, or HAR for short, is a broad field of study concerned with identifying the specific movement or action of a person based on sensor data.
The sensor data may be remotely recorded, such as video, radar, or other wireless methods. It contains data generated from accelerometer, gyroscope and other sensors of Smart phone to train supervised predictive models using machine learning techniques like SVM , Random forest and decision tree to generate a model. Which can be used to predict the kind of movement being carried out by the person, which is divided into six categories walking, walking upstairs, walking down-stairs, sitting, standing and laying?
MLM and SVM achieved accuracy of more than 99.2% in the original data set and 98.1% using new feature selection method. Results show that the proposed feature selection approach is a promising alternative to activity recognition on smart phones.
This document summarizes a student project on human activity recognition using smartphones. A group of 4 students submitted the project to partially fulfill requirements for a Bachelor of Technology degree in computer science and engineering. The project involved developing a system to recognize human activities using the accelerometer and gyroscope sensors in smartphones. Various machine learning algorithms were tested and evaluated on experimental data collected from smartphone sensors. The goal of the project was to create an accurate and lightweight activity recognition system for smartphones, while also exploring active learning methods to reduce the amount of labeled training data needed.
This document provides an overview of approaches for human activity recognition (HAR). It discusses vision-based approaches including using hand-crafted motion features, depth information methods, and deep learning techniques. Deep learning methods covered include two-stream inflated 3D networks, deep bidirectional LSTM with CNN features, and skeleton-based spatial temporal graph convolutional networks. The document also discusses potential future directions for HAR, which may involve using 3D features, unsupervised learning, skeleton-based methods for privacy, and optimization/quantization. HAR applications in the future could leverage the power of modern AI and embedded abilities while meeting requirements like real-time performance, privacy, and ease of deployment.
IRJET- Convenience Improvement for Graphical Interface using Gesture Dete...IRJET Journal
This document discusses a proposed system for improving graphical user interfaces using hand gesture detection. The system aims to allow users to access information from the internet without using input devices like a mouse or keyboard. It uses a webcam to capture images of hand gestures, which are then processed using techniques like skin color segmentation, principal component analysis, and template matching to recognize the gestures. The recognized gestures can then be linked to retrieving specific data from pre-defined URLs. An evaluation of the system found it had an accuracy rate of 90% in real-time testing for retrieving data from 10 different URLs using 10 unique hand gestures. The proposed system provides a more convenient interface compared to traditional mouse and keyboard methods.
An Efficient VLSI Design of AES Cryptography Based on DNA TRNG DesignIRJET Journal
This document describes an efficient VLSI design for AES cryptography using a true random number generator (TRNG) and DNA encoding. It aims to improve security and reduce area and delay compared to standard AES. The design generates random round keys using a TRNG instead of the standard key expansion process. It further encodes a partial key from the TRNG using DNA encoding to produce the full 128-bit key, strengthening security. Simulation and synthesis results show the TRNG-based AES has lower area and delay than standard AES. Combining the TRNG with DNA encoding further optimizes the design.
An Intelligent Human Computer Communication with Real Time Hand Gesture for M...IJERA Editor
This document presents a system for controlling a wheelchair using finger gestures. A camera is mounted on the wheelchair to capture images of hand gestures. The images are processed using digital image processing techniques like blurring, color space conversion from RGB to HSV, and thresholding to detect and recognize fingers. The finger positions are used to determine gestures for controlling the wheelchair motors and directing its movement forward, backward, left, right, or stopping. An algorithm is provided to map finger positions to specific motor controls. The system was tested with 5 finger gestures and achieved 100% accuracy in controlling the wheelchair movement as intended by each gesture. The goal of the system is to provide an easier way for disabled people to control a wheelchair through simple hand gestures without
MODEL MONITORING PHYSICAL EXERCISE HEART RATE USING INTERNET OF THINGS (MMPEH...ijait
The document describes a proposed model called Model Monitoring Physical Exercise Heart Rate Using Internet of Things (MMPEH-IOT). The model was designed to monitor heart rate during physical exercise using IoT devices. It consists of six main components: a SmartHeart device to collect heart rate data, a wireless network to transmit data, a SoftAPP to analyze data, a knowledgebase to store data, a server to facilitate user requests, and a user interface. The model aims to prevent health risks from vigorous exercise and promote healthy living by monitoring individuals' heart rates during physical activity.
IRJET- Design an Approach for Prediction of Human Activity Recognition us...IRJET Journal
The document proposes a framework for human activity recognition using smartphones. It involves collecting data from a smartphone's accelerometer and gyroscope sensors worn on the waist during various activities of daily living. The data is preprocessed and classified using machine learning algorithms like Naive Bayes, logistic regression, and SVM. The proposed framework first loads and preprocesses the sensor data, then generates features before splitting the data into training and test sets. Various classifiers are applied and evaluated to select the best performing one for activity recognition. The authors conclude that implementing tri-axial acceleration from sensors provides different accuracy for different algorithms, with SVM achieving maximum accuracy in previous work.
IRJET- Human Activity Recognition using Flex SensorsIRJET Journal
This document discusses a system for human activity recognition using flex sensors. Flex sensors are attached to the body and can detect movements. The flex sensor data is fed into a neural network model to recognize activities. The model is trained using flex sensor data from various human activities. The trained model can then accurately recognize activities based on new flex sensor input data. The system is meant to help elderly people or those with disabilities by allowing them to control devices with body movements detected by flex sensors. It aims to provide a modular system that can adapt to new users and disabilities. Flex sensors make the system customizable while neural networks enable accurate activity recognition.
Comparative Study of the Deep Learning Neural Networks on the basis of the Hu...saurav singla
The comparative study of the three most efficient Deep Learning models LSTM-RNN, GRU-RNN, and CNN has been performed on the most famous dataset ‘Human Activity Recognition using Smartphones Data Set’ present at UCI machine-learning repository.
IRJET- Fish Recognition and Detection Based on Deep LearningIRJET Journal
The document describes a method for fish recognition and detection using deep learning and the R-CNN algorithm. A raspberry pi camera is used to capture underwater images of fish as input datasets. These images are preprocessed using techniques like resizing and background removal. The preprocessed datasets are then trained using the R-CNN deep learning model. This trained model can detect and recognize fish in the images with 85% accuracy. The detected results are stored in an IoT cloud for further use. The proposed method provides high accuracy for fish detection with minimal human intervention.
IRJET- Security in Ad-Hoc Network using Encrypted Data Transmission and S...IRJET Journal
This document discusses security techniques for data transmission in ad-hoc networks, specifically encrypted data transmission and steganography. It proposes a system that enables encrypted data transmission between nodes and uses steganography to hide encrypted data in cover files like images, audio, and video during transmission for additional security. The system architecture includes modules for user interface, embedding secret data in cover files, extracting secret data, sending files between nodes, and receiving files. It aims to securely transmit data in ad-hoc networks using both encryption and steganography to protect confidentiality and integrity of transmitted data.
Recovery Prediction in the Framework of Cloud-Based Rehabilitation Exergametoukaigi
The document proposes a framework for a cloud-based home rehabilitation system using exergames. The framework provides real-time feedback to patients, summarizes feedback after sessions, and predicts rehabilitation progress. It uses a Kinect sensor to track upper limb movement during games. Dynamic Time Warping compares patient and healthy movements. Auto-Regressive Integrated Moving Average is used to forecast rehabilitation based on performance history. Preliminary tests on healthy individuals and one patient show potential for tracking recovery status.
Attendance System using Android Integrated Biometric Fingerprint RecognitionIRJET Journal
This document describes the development of an attendance tracking system using fingerprint recognition and an Android application. Key points:
- The system uses a fingerprint scanner to enroll students' fingerprints and store them in a database along with their IDs. When students place their finger on the scanner, it marks them as present by updating the database.
- An Android app was created to allow students and administrators to check attendance records in real-time by accessing the centralized database.
- The system aims to provide a cheaper and more reliable alternative to traditional paper-based attendance tracking while allowing remote attendance monitoring via the app.
- The system was tested on 5 students and 1 teacher, with fingerprint matching being about 100% accurate though some
IRJET - Creating a Security Alert for the Care Takers Implementing a Vast Dee...IRJET Journal
This document presents a proposed system for creating a security alert for caregivers by implementing a vast deep learning model to recognize human activities and gestures. The system would collect a dataset of skeleton images of human actions and gestures. It would then train models using deep learning algorithms like AlexNet, VGG16, GoogleNet, and ResNet to accurately recognize activities and gestures. This would help monitor senior citizens and detect any health issues or untrustworthy individuals. The proposed system aims to optimize techniques such as stochastic gradient descent and regularizers like ReLU and ELU to increase prediction accuracy and provide low-cost, high-accuracy monitoring to improve senior citizen safety.
this is my final year project based on safe city on roads. This project got second position in DICE project. This project was presented in an international organization.
IRJET- A Survey on Control of Mechanical ARM based on Hand Gesture Recognitio...IRJET Journal
This document summarizes a research paper that proposed a system using wearable IMU sensors and machine learning to recognize hand gestures and control a mechanical arm. The system uses an IMU-based wearable device to collect gesture data from hand movements. A support vector machine classifier is used to classify the gestures in real-time and control the movements of a mechanical arm. The paper reviews several related works that used different sensors and machine learning algorithms for hand gesture recognition, finding that support vector machines provided high accuracy for gesture classification. The proposed system aims to allow remote control of machines through natural hand gestures.
The object of our project is acquisition of Electro cardiogram signal from patient‟s body through wearable system, analyze whether it is normal or abnormal at patient‟s end, then transmit the wireless signal if found that it is abnormal. Transmission is to be done wirelessly through XBEE Technology and then higher level analysis is to be done on computer which is situated at base -station. To achieve our objective we have used microcontroller AT Mega 32 and for its programming we have used dynamic C with AVR Studio base. For higher level analysis we have made software using Java J2EE, Java Script and PHP
This project develops a natural user interface for interacting with 3D environments using the Microsoft Kinect. Two Kinect devices are placed in a virtual reality space to track a user's full body movements and gestures. The Kinect data is used to create a digital avatar that represents the user's position and allows directly interacting with virtual objects by reaching out. Gesture recognition is also implemented to provide additional controls for navigation and selection. The goal is to make interacting with complex 3D data more intuitive by mirroring natural physical interactions.
The blue brain is the first virtual brain in the
world. It is a machine that can work like the human brain. At
present scientists are trying to make a virtual brain that will
be able to make decisions and keep information in the
memory. The idea is to upload the human brain into the
machine. So that man can think without any efforts. The main
advantage of this project is that even after the death of the
person, we can use the knowledge and intelligence of that
person
Games for Health Europe - Federico Semeraro & Luca Marchetti - Relive: a game...Games for Health Europe
Relive is a game designed to teach cardiopulmonary resuscitation (CPR) skills. A study tested Relive on students and found it significantly improved both CPR knowledge and skills. Students who played Relive performed chest compressions with a faster, deeper rhythm closer to guidelines compared to their initial performance without training. The game provides feedback to help players learn compression rate and depth, increasing CPR proficiency in a fun, non-invasive way.
Virtual Yoga System Using Kinect SensorIRJET Journal
The document describes a virtual yoga system using the Microsoft Kinect sensor. The system aims to make yoga exercises more engaging and motivating for patients by tracking their poses in real-time and providing feedback. It recognizes skeleton joints and yoga postures using the Kinect's depth sensing capabilities. Voice instructions guide users through different poses. The system is intended to address issues with traditional physiotherapy being tedious and repetitive. It allows customizing exercises to individual needs and challenges. Recognizing poses accurately in real-time could help patients perform exercises correctly and consistently at home without direct supervision.
IRJET- IoT based Smart Fitness Tracker for GymnasiumsIRJET Journal
This document summarizes a research project that aims to design a smart fitness tracker system for gymnasiums. The system would record users' indoor fitness routines by automatically counting sets and repetitions of weight exercises using sensors, rather than manual counting. It would distinguish members using RFID tags and update individual data on a fitness tracking app and database. The system is intended to provide accurate logging of data and suggestions on progress to help users set goals. It would classify as green IT by using cloud services.
To Design and Develop Intelligent Exercise Systemijtsrd
The document discusses the development of an intelligent exercise system using the Microsoft Kinect sensor. It provides background on the Kinect, including its hardware specifications and capabilities for skeletal tracking and motion recognition. The system is intended to help patients follow rehabilitation exercise plans by tracking their movements and providing guidance. It analyzes exercises based on joint angles, positions and velocities over time to quantify the range of motion, functional envelope, and rate of fatigue. The goal is to help patients improve their exercises while maintaining records for doctors.
IRJET- Recognition of Theft by Gestures using Kinect Sensor in Machine Le...IRJET Journal
This document discusses a system that uses a Kinect sensor to recognize theft gestures using machine learning. The system tracks a person's skeleton and compares their gestures to a dictionary of known theft and normal gestures. If a match for a theft gesture is found, an alarm and SMS notification are generated. The system was implemented using Processing and a logistic regression machine learning algorithm to classify poses as abnormal or normal based on joint angle features extracted from Kinect skeleton data. The system aims to automatically detect theft in environments like banks and stores to improve security.
This document summarizes a research project that uses the Microsoft Kinect sensor to develop a fall detection system for elderly people. It presents two methods for fall detection - the first uses Kinect's core APIs to track skeleton data, while the second extracts the human contour from depth maps and tracks it over time without using Kinect APIs. The researchers believe the second method provides more robust fall detection since Kinect cannot track bodies lying down. The document outlines the motivation for fall detection, related work, and technical details of both proposed approaches.
This document summarizes a research paper that designed a smart waist belt for health monitoring. The belt tracks steps, posture, heart rate and classifies activities using sensors and a random forest machine learning algorithm. It achieved high accuracy rates between 90-95% for classifying activities like sitting, walking and standing. The smart waist belt addresses issues with current fitness trackers and promotes an active lifestyle. It provides real-time health data to a mobile app and cloud for access and analysis. This allows users to conveniently self-monitor health metrics and get notifications about posture.
IRJET- Design an Approach for Prediction of Human Activity Recognition us...IRJET Journal
The document proposes a framework for human activity recognition using smartphones. It involves collecting data from a smartphone's accelerometer and gyroscope sensors worn on the waist during various activities of daily living. The data is preprocessed and classified using machine learning algorithms like Naive Bayes, logistic regression, and SVM. The proposed framework first loads and preprocesses the sensor data, then generates features before splitting the data into training and test sets. Various classifiers are applied and evaluated to select the best performing one for activity recognition. The authors conclude that implementing tri-axial acceleration from sensors provides different accuracy for different algorithms, with SVM achieving maximum accuracy in previous work.
IRJET- Human Activity Recognition using Flex SensorsIRJET Journal
This document discusses a system for human activity recognition using flex sensors. Flex sensors are attached to the body and can detect movements. The flex sensor data is fed into a neural network model to recognize activities. The model is trained using flex sensor data from various human activities. The trained model can then accurately recognize activities based on new flex sensor input data. The system is meant to help elderly people or those with disabilities by allowing them to control devices with body movements detected by flex sensors. It aims to provide a modular system that can adapt to new users and disabilities. Flex sensors make the system customizable while neural networks enable accurate activity recognition.
Comparative Study of the Deep Learning Neural Networks on the basis of the Hu...saurav singla
The comparative study of the three most efficient Deep Learning models LSTM-RNN, GRU-RNN, and CNN has been performed on the most famous dataset ‘Human Activity Recognition using Smartphones Data Set’ present at UCI machine-learning repository.
IRJET- Fish Recognition and Detection Based on Deep LearningIRJET Journal
The document describes a method for fish recognition and detection using deep learning and the R-CNN algorithm. A raspberry pi camera is used to capture underwater images of fish as input datasets. These images are preprocessed using techniques like resizing and background removal. The preprocessed datasets are then trained using the R-CNN deep learning model. This trained model can detect and recognize fish in the images with 85% accuracy. The detected results are stored in an IoT cloud for further use. The proposed method provides high accuracy for fish detection with minimal human intervention.
IRJET- Security in Ad-Hoc Network using Encrypted Data Transmission and S...IRJET Journal
This document discusses security techniques for data transmission in ad-hoc networks, specifically encrypted data transmission and steganography. It proposes a system that enables encrypted data transmission between nodes and uses steganography to hide encrypted data in cover files like images, audio, and video during transmission for additional security. The system architecture includes modules for user interface, embedding secret data in cover files, extracting secret data, sending files between nodes, and receiving files. It aims to securely transmit data in ad-hoc networks using both encryption and steganography to protect confidentiality and integrity of transmitted data.
Recovery Prediction in the Framework of Cloud-Based Rehabilitation Exergametoukaigi
The document proposes a framework for a cloud-based home rehabilitation system using exergames. The framework provides real-time feedback to patients, summarizes feedback after sessions, and predicts rehabilitation progress. It uses a Kinect sensor to track upper limb movement during games. Dynamic Time Warping compares patient and healthy movements. Auto-Regressive Integrated Moving Average is used to forecast rehabilitation based on performance history. Preliminary tests on healthy individuals and one patient show potential for tracking recovery status.
Attendance System using Android Integrated Biometric Fingerprint RecognitionIRJET Journal
This document describes the development of an attendance tracking system using fingerprint recognition and an Android application. Key points:
- The system uses a fingerprint scanner to enroll students' fingerprints and store them in a database along with their IDs. When students place their finger on the scanner, it marks them as present by updating the database.
- An Android app was created to allow students and administrators to check attendance records in real-time by accessing the centralized database.
- The system aims to provide a cheaper and more reliable alternative to traditional paper-based attendance tracking while allowing remote attendance monitoring via the app.
- The system was tested on 5 students and 1 teacher, with fingerprint matching being about 100% accurate though some
IRJET - Creating a Security Alert for the Care Takers Implementing a Vast Dee...IRJET Journal
This document presents a proposed system for creating a security alert for caregivers by implementing a vast deep learning model to recognize human activities and gestures. The system would collect a dataset of skeleton images of human actions and gestures. It would then train models using deep learning algorithms like AlexNet, VGG16, GoogleNet, and ResNet to accurately recognize activities and gestures. This would help monitor senior citizens and detect any health issues or untrustworthy individuals. The proposed system aims to optimize techniques such as stochastic gradient descent and regularizers like ReLU and ELU to increase prediction accuracy and provide low-cost, high-accuracy monitoring to improve senior citizen safety.
this is my final year project based on safe city on roads. This project got second position in DICE project. This project was presented in an international organization.
IRJET- A Survey on Control of Mechanical ARM based on Hand Gesture Recognitio...IRJET Journal
This document summarizes a research paper that proposed a system using wearable IMU sensors and machine learning to recognize hand gestures and control a mechanical arm. The system uses an IMU-based wearable device to collect gesture data from hand movements. A support vector machine classifier is used to classify the gestures in real-time and control the movements of a mechanical arm. The paper reviews several related works that used different sensors and machine learning algorithms for hand gesture recognition, finding that support vector machines provided high accuracy for gesture classification. The proposed system aims to allow remote control of machines through natural hand gestures.
The object of our project is acquisition of Electro cardiogram signal from patient‟s body through wearable system, analyze whether it is normal or abnormal at patient‟s end, then transmit the wireless signal if found that it is abnormal. Transmission is to be done wirelessly through XBEE Technology and then higher level analysis is to be done on computer which is situated at base -station. To achieve our objective we have used microcontroller AT Mega 32 and for its programming we have used dynamic C with AVR Studio base. For higher level analysis we have made software using Java J2EE, Java Script and PHP
This project develops a natural user interface for interacting with 3D environments using the Microsoft Kinect. Two Kinect devices are placed in a virtual reality space to track a user's full body movements and gestures. The Kinect data is used to create a digital avatar that represents the user's position and allows directly interacting with virtual objects by reaching out. Gesture recognition is also implemented to provide additional controls for navigation and selection. The goal is to make interacting with complex 3D data more intuitive by mirroring natural physical interactions.
The blue brain is the first virtual brain in the
world. It is a machine that can work like the human brain. At
present scientists are trying to make a virtual brain that will
be able to make decisions and keep information in the
memory. The idea is to upload the human brain into the
machine. So that man can think without any efforts. The main
advantage of this project is that even after the death of the
person, we can use the knowledge and intelligence of that
person
Games for Health Europe - Federico Semeraro & Luca Marchetti - Relive: a game...Games for Health Europe
Relive is a game designed to teach cardiopulmonary resuscitation (CPR) skills. A study tested Relive on students and found it significantly improved both CPR knowledge and skills. Students who played Relive performed chest compressions with a faster, deeper rhythm closer to guidelines compared to their initial performance without training. The game provides feedback to help players learn compression rate and depth, increasing CPR proficiency in a fun, non-invasive way.
Virtual Yoga System Using Kinect SensorIRJET Journal
The document describes a virtual yoga system using the Microsoft Kinect sensor. The system aims to make yoga exercises more engaging and motivating for patients by tracking their poses in real-time and providing feedback. It recognizes skeleton joints and yoga postures using the Kinect's depth sensing capabilities. Voice instructions guide users through different poses. The system is intended to address issues with traditional physiotherapy being tedious and repetitive. It allows customizing exercises to individual needs and challenges. Recognizing poses accurately in real-time could help patients perform exercises correctly and consistently at home without direct supervision.
IRJET- IoT based Smart Fitness Tracker for GymnasiumsIRJET Journal
This document summarizes a research project that aims to design a smart fitness tracker system for gymnasiums. The system would record users' indoor fitness routines by automatically counting sets and repetitions of weight exercises using sensors, rather than manual counting. It would distinguish members using RFID tags and update individual data on a fitness tracking app and database. The system is intended to provide accurate logging of data and suggestions on progress to help users set goals. It would classify as green IT by using cloud services.
To Design and Develop Intelligent Exercise Systemijtsrd
The document discusses the development of an intelligent exercise system using the Microsoft Kinect sensor. It provides background on the Kinect, including its hardware specifications and capabilities for skeletal tracking and motion recognition. The system is intended to help patients follow rehabilitation exercise plans by tracking their movements and providing guidance. It analyzes exercises based on joint angles, positions and velocities over time to quantify the range of motion, functional envelope, and rate of fatigue. The goal is to help patients improve their exercises while maintaining records for doctors.
IRJET- Recognition of Theft by Gestures using Kinect Sensor in Machine Le...IRJET Journal
This document discusses a system that uses a Kinect sensor to recognize theft gestures using machine learning. The system tracks a person's skeleton and compares their gestures to a dictionary of known theft and normal gestures. If a match for a theft gesture is found, an alarm and SMS notification are generated. The system was implemented using Processing and a logistic regression machine learning algorithm to classify poses as abnormal or normal based on joint angle features extracted from Kinect skeleton data. The system aims to automatically detect theft in environments like banks and stores to improve security.
This document summarizes a research project that uses the Microsoft Kinect sensor to develop a fall detection system for elderly people. It presents two methods for fall detection - the first uses Kinect's core APIs to track skeleton data, while the second extracts the human contour from depth maps and tracks it over time without using Kinect APIs. The researchers believe the second method provides more robust fall detection since Kinect cannot track bodies lying down. The document outlines the motivation for fall detection, related work, and technical details of both proposed approaches.
This document summarizes a research paper that designed a smart waist belt for health monitoring. The belt tracks steps, posture, heart rate and classifies activities using sensors and a random forest machine learning algorithm. It achieved high accuracy rates between 90-95% for classifying activities like sitting, walking and standing. The smart waist belt addresses issues with current fitness trackers and promotes an active lifestyle. It provides real-time health data to a mobile app and cloud for access and analysis. This allows users to conveniently self-monitor health metrics and get notifications about posture.
This document discusses using artificial intelligence and deep learning techniques for yoga pose estimation and classification. Specifically, it proposes training a model using the PoseNet and OpenPose frameworks on a dataset of yoga pose videos to identify key points in the human body and classify the pose. The model would use convolutional neural networks and long short-term memory to process video frames in real-time and provide classification scores for the accuracy of pose identification. This type of system could help improve health and provide feedback to users on yoga pose form without an instructor. However, it is currently limited to a small number of poses and requires internet and webcam access.
This document discusses human activity recognition using deep learning techniques. It describes using a 3D convolutional neural network model to classify human activities in videos. The model is trained on the Kinetics dataset, which contains videos of human actions. The proposed system aims to identify common human activities like reading, writing, and playing instruments through video classification. It evaluates using deep learning for automated activity recognition as a challenging task due to issues like background clutter and pose variations between individuals.
Human Activity Recognition Using SmartphoneIRJET Journal
The document discusses human activity recognition using smartphone sensors. It proposes using a CNN-LSTM model to classify activities like walking, running, and sitting based on accelerometer and gyroscope sensor data from a smartphone. The CNN extracts features from the sensor data, while the LSTM recognizes sequences of activities over time. The model is implemented in an Android application that recognizes activities in real-time and also counts steps, distance, and calories burned. The application uses built-in smartphone sensors like accelerometer, gyroscope, and pedometer to recognize activities affordably and with high availability without external devices. The CNN-LSTM model achieves accurate activity recognition compared to other machine learning techniques.
IRJET - Human Pose Detection using Deep LearningIRJET Journal
This document discusses using deep learning for human pose detection. It begins with an introduction to human pose detection and challenges in the field. It then describes how deep learning can be used for this task by training neural networks on large datasets of images annotated with body joint locations. Specifically, it trained models like COCO and MPII to identify and locate body parts. OpenCV and Flask were used to process video frames and build a graphical interface. The trained models were able to detect poses and provide feedback on proper form for exercises. Graphs and skeletal representations visualized the poses and joint angles. The system was able to perform human pose detection in real-time with low hardware requirements. In conclusion, it achieved an effective low-cost software model for motion
Human pose detection using machine learning by GrandelGrandelDsouza
This document discusses using deep learning for human pose detection. It begins with an introduction to human pose detection and challenges in the field. It then describes how deep learning can be used for this task by training neural networks on large datasets of images annotated with body joint locations. Specifically, it trained models like COCO and MPII to identify and locate body parts. OpenCV and Flask were used to process video frames and build a graphical interface. The trained models were able to detect poses and provide feedback on proper form for exercises. Graphs and skeletal representations visualized the poses and joint angles. The system was able to perform human pose detection in real-time with low hardware requirements. In conclusion, it achieved an effective low-cost software model for motion
AI Personal Trainer Using Open CV and Media PipeIRJET Journal
This document summarizes a research paper that proposes an AI personal trainer system using computer vision techniques. The system uses OpenCV and MediaPipe to detect a user's body pose and angles in real-time video to correct their form during exercises. It aims to help users safely and effectively work out at home without a physical trainer. The system would also connect users with similar fitness goals to encourage motivation. The researchers believe this AI trainer could make exercise more accessible and convenient for users.
IRJET- Review on Human Action Detection in Stored Videos using Support Vector...IRJET Journal
This document discusses human action detection in stored videos using support vector machines. It describes the major steps in activity detection as feature detection, feature description, video representation, and classification. It explains that supervised learning uses labeled training samples to build models for normal and abnormal behavior detection, but it is limited by the need for sufficient training data for less defined events. Unsupervised learning builds models of normal behavior but classifies any samples not fitting a model as abnormal. The document reviews various approaches to human activity detection and outlines challenges, such as dealing with limited or low-quality video data.
Study of AI Fitness Model Using Deep LearningIRJET Journal
1. The document describes an AI fitness app called "AI Fitness Genie" that uses computer vision algorithms like YOLO and OpenPose to track a user's exercise poses, count repetitions, and provide feedback to improve form.
2. It detects body position using skeleton or contour modeling and compares the user's pose to 3D models to assess accuracy and provide recommendations for corrections.
3. An evaluation of the app found it could detect poses with 98.51% accuracy to guide users through proper exercise form.
Pose Trainer: “An Exercise Guide and Assessment in Physiotherapy”IRJET Journal
This document describes a project called Pose Trainer that uses computer vision and machine learning to assess and provide feedback on physiotherapy exercises. The system uses OpenPose models to extract key points from user-uploaded exercise videos. It then compares the user's pose to sample poses to evaluate accuracy and provide real-time feedback on form. This guidance helps users perform exercises correctly at home without an in-person trainer. The project aims to make physical therapy more accessible and avoid potential injuries from improper exercise form.
Enhancing the measurement of clinical outcomes using Microsoft Kinect choices (Philip Breedon, Bill Byrom, Luke Siena and Willie Muehlhausen)
Interactive Technologies and Games (ITAG) Conference 2016
Health, Disability and EducationDates: Wednesday 26 October 2016 - Thursday 27 October 2016 Location: The Council House, NG1 2DT
IRJET - 3D Virtual Dressing Room ApplicationIRJET Journal
This document describes a 3D virtual dressing room application that was developed using the Microsoft Kinect sensor. The application aims to address issues with traditional dressing rooms like wasting time trying on clothes, limited variety, and privacy concerns. The proposed approach uses Kinect to extract the user from the video stream, align 3D cloth models to the user's body, and apply skin color detection to handle occlusions. The body joints are used for positioning, scaling, and rotating the cloth models. The models are then overlaid on the user in real-time. The document discusses related work on virtual dressing rooms and 3D alignment of clothes to user models. It also outlines the methodology, including using Kinect's image and depth streams to develop
IRJET- IoT based Facial Recognition Biometric AttendanceIRJET Journal
1. The document proposes an IoT-based facial recognition system for automated student attendance marking using a Raspberry Pi.
2. The system uses a web camera to capture student faces, detects faces in images using Haar cascades, encodes faces using Local Binary Patterns (LBP), and recognizes faces to mark attendance in a database.
3. By automating attendance marking through facial recognition, the proposed system aims to save time compared to manual methods, eliminate proxy attendance issues, and mark attendance periodically in classes without disruption.
The document describes a project to develop an interface using a Kinect sensor and Unity game engine to motivate neurorehabilitation through a game. The game aims to quantify irregular hand movements in patients by having them grab and move objects. Prior work showed games can aid rehabilitation but marker-based systems have downsides. The project captures motion markerless using Kinect to track arm movements navigating a ball into targets of varying sizes for adaptive difficulty. Future work includes analyzing data to track patient progress.
GYM MANAGEMENT SYSTEM USING AUGMENTED REALITYIRJET Journal
This document presents a research paper on developing a Gym Management System using Augmented Reality. The proposed system aims to address issues with current manual gym management systems by developing a mobile application. Key features of the app include displaying nearby gyms and their fees to users, keeping attendance records of members, and using augmented reality to scan gym equipment and display the proper way to use each machine. The system will also provide workout and diet plans to users. The document discusses the literature on existing gym management systems and augmented reality technologies. It provides details on the proposed app's features and the problems it aims to solve compared to manual systems. The results and performance of the system are yet to be seen once developed.
Similar to IRJET- Virtual Fitness Trainer with Spontaneous Feedback using a Line of Motion Sensing Input Device Kinect Xbox 360 (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network