Food intake gesture technology is one of a new strategy for obesity people managing their health care while saving their time and money. This approach involves combining face and hand joint point for monitoring food intake of a user using Kinect Xbox One camera sensor. Rather than counting calories, scientists at Brigham Young University found dieters who eager to reduce their number of daily bites by 20 to 30 percent lost around two kilograms a month, regardless of what they ate [1]. Research studies showed that most of the methods used to count bite are worn type devices which has high false alarm ratio. Today trend is going toward the non-wearable device. This sensor is used to capture skeletal data of user while eating and train the data to capture the motion and movement while eating. There are specific joint to be capture such as Jaw face point and wrist roll joint. Overall accuracy is around 94%. Basically, this increase in the overall recognition rate of
this system.
A non-invasive and non-wearable food intake monitoring system based on depth ...journalBEEI
The food intake counting method showed a good significance that can lead to a successful weight loss by simply monitoring the food intake taken during eating. The device used in this project was Kinect Xbox One which used a depth camera to detect the motion of a person’s gesture and posture during food intake. Previous studies have shown that most of the methods used to count food intake device is worn device type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect camera and monitors the gesture of the user while eating. Then, the gesture data is collected to be recognized and it will start counting the food intake taken by the user. The system recognizes the patterns of the food intake from the user by following the algorithm to analyze the gesture of the basic eating type and the system get an average accuracy of 96.2%. This system can help people who are trying to follow a proper way to avoid being overweight or having eating disorders by monitoring their meal intake and controlling their eating rate.
Measurement Straight Leg Raise for Low Back Pain Based Grayscale DepthTELKOMNIKA JOURNAL
This document summarizes a study that used the Kinect sensor to measure the angle of the straight leg raise (SLR) test for patients with low back pain. The SLR test is commonly used to diagnose nerve root irritation but traditional measurement with a goniometer can be inaccurate. The study developed an algorithm to track skeleton joints with Kinect and calculate the angle between the legs during the SLR. Testing on 12 subjects found the Kinect measurements were on average within 5% of goniometer readings. Measuring the SLR angle with Kinect could provide an affordable and precise method to diagnose low back pain and monitor rehabilitation progress.
Iaetsd an effective alarming model for danger and activityIaetsd Iaetsd
This document proposes a child activity monitoring system using wearable sensors. It uses an accelerometer and ultrasonic sensor attached to a waist belt to classify 8 daily activities like moving, climbing, and standing. It aims to prevent injuries by detecting dangerous activities or locations via RFID and sending alerts. The system was tested on 10 children and achieved 90% accuracy in activity recognition using sensor fusion algorithms. It provides real-time monitoring of activities and environmental dangers to promote child safety.
This document proposes a food calorie and nutrition measurement system that uses images taken by mobile device cameras to measure consumption and manage daily food intake. It analyzes food photos before and after eating using nutritional databases and image processing. The system aims to improve current manual calorie counting methods. It requires a PC with at least 2GB RAM and 100GB HDD along with MATLAB software and toolboxes to implement image and signal processing algorithms. The project will be developed over three reviews, first surveying existing methods, explaining the design, and enhancing the base paper. It will then implement 40% of the base paper in the second review and the remaining 60% with modifications in the third review.
This document describes an envisioned future health and nutrition tracking system called the HANT. It utilizes three components: 1) nanoscale spectrometer sensors attached to molars that identify foods consumed, 2) a pill containing a programmable nanoscale ring sensor that measures esophageal expansion to determine food volume, and 3) a smartwatch-like device that aggregates this data to track calorie intake and provide personalized nutrition information to users. The system aims to seamlessly monitor diets and help with weight loss or diabetes management through continuously monitoring food consumption at an individual level.
Using smartphones in healthcare and to save livesphonecom
Smartphones can be used in healthcare and to save lives in several ways:
1) They can track nutrition, exercise, and fluid intake to help maintain a healthy lifestyle. Sensors and apps help calculate calorie needs and provide reminders.
2) They can assist those with medical conditions by tracking medication schedules, tailoring nutrition to diseases, and monitoring vital signs.
3) For those living alone, sensors can detect emergencies and send alerts to caregivers if issues like falls or changes in vitals are detected, potentially saving lives. Location data and medical histories could also help emergency responders.
A mother, with new born baby if needs to be away from baby due to employment, household work, shopping, etc. in that case health status intensifies the stress for mothers. The number of approx. 7,00,000 life births in the world is overshadowed by a large number of infant deaths for various reasons like apparently life threatening events (ALTE) or sudden infants death syndrome (SIDS). Continues monitoring of physiological parameters and notification updates is need of current scenario. Child health status is important aspect and health monitoring system is ultimate solution for that. The new era wearable technologies can be easily adoptable for monitoring systems. Wearable health monitoring system with fully integrated sensors can sense the physiological parameters and accordingly, synchronize the real time data to user application. The mobile application will help user to get real time body temperature and heartbeat count of the baby. It will also provide health and report analysis as well as emergency notifications.
Bionic arm is a revolutionary idea for amputees across the globe. This is as close as we can get to our natural limb. The fundamental point is to make the arm move with our brain unlike previous prosthetic upper limbs
A non-invasive and non-wearable food intake monitoring system based on depth ...journalBEEI
The food intake counting method showed a good significance that can lead to a successful weight loss by simply monitoring the food intake taken during eating. The device used in this project was Kinect Xbox One which used a depth camera to detect the motion of a person’s gesture and posture during food intake. Previous studies have shown that most of the methods used to count food intake device is worn device type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect camera and monitors the gesture of the user while eating. Then, the gesture data is collected to be recognized and it will start counting the food intake taken by the user. The system recognizes the patterns of the food intake from the user by following the algorithm to analyze the gesture of the basic eating type and the system get an average accuracy of 96.2%. This system can help people who are trying to follow a proper way to avoid being overweight or having eating disorders by monitoring their meal intake and controlling their eating rate.
Measurement Straight Leg Raise for Low Back Pain Based Grayscale DepthTELKOMNIKA JOURNAL
This document summarizes a study that used the Kinect sensor to measure the angle of the straight leg raise (SLR) test for patients with low back pain. The SLR test is commonly used to diagnose nerve root irritation but traditional measurement with a goniometer can be inaccurate. The study developed an algorithm to track skeleton joints with Kinect and calculate the angle between the legs during the SLR. Testing on 12 subjects found the Kinect measurements were on average within 5% of goniometer readings. Measuring the SLR angle with Kinect could provide an affordable and precise method to diagnose low back pain and monitor rehabilitation progress.
Iaetsd an effective alarming model for danger and activityIaetsd Iaetsd
This document proposes a child activity monitoring system using wearable sensors. It uses an accelerometer and ultrasonic sensor attached to a waist belt to classify 8 daily activities like moving, climbing, and standing. It aims to prevent injuries by detecting dangerous activities or locations via RFID and sending alerts. The system was tested on 10 children and achieved 90% accuracy in activity recognition using sensor fusion algorithms. It provides real-time monitoring of activities and environmental dangers to promote child safety.
This document proposes a food calorie and nutrition measurement system that uses images taken by mobile device cameras to measure consumption and manage daily food intake. It analyzes food photos before and after eating using nutritional databases and image processing. The system aims to improve current manual calorie counting methods. It requires a PC with at least 2GB RAM and 100GB HDD along with MATLAB software and toolboxes to implement image and signal processing algorithms. The project will be developed over three reviews, first surveying existing methods, explaining the design, and enhancing the base paper. It will then implement 40% of the base paper in the second review and the remaining 60% with modifications in the third review.
This document describes an envisioned future health and nutrition tracking system called the HANT. It utilizes three components: 1) nanoscale spectrometer sensors attached to molars that identify foods consumed, 2) a pill containing a programmable nanoscale ring sensor that measures esophageal expansion to determine food volume, and 3) a smartwatch-like device that aggregates this data to track calorie intake and provide personalized nutrition information to users. The system aims to seamlessly monitor diets and help with weight loss or diabetes management through continuously monitoring food consumption at an individual level.
Using smartphones in healthcare and to save livesphonecom
Smartphones can be used in healthcare and to save lives in several ways:
1) They can track nutrition, exercise, and fluid intake to help maintain a healthy lifestyle. Sensors and apps help calculate calorie needs and provide reminders.
2) They can assist those with medical conditions by tracking medication schedules, tailoring nutrition to diseases, and monitoring vital signs.
3) For those living alone, sensors can detect emergencies and send alerts to caregivers if issues like falls or changes in vitals are detected, potentially saving lives. Location data and medical histories could also help emergency responders.
A mother, with new born baby if needs to be away from baby due to employment, household work, shopping, etc. in that case health status intensifies the stress for mothers. The number of approx. 7,00,000 life births in the world is overshadowed by a large number of infant deaths for various reasons like apparently life threatening events (ALTE) or sudden infants death syndrome (SIDS). Continues monitoring of physiological parameters and notification updates is need of current scenario. Child health status is important aspect and health monitoring system is ultimate solution for that. The new era wearable technologies can be easily adoptable for monitoring systems. Wearable health monitoring system with fully integrated sensors can sense the physiological parameters and accordingly, synchronize the real time data to user application. The mobile application will help user to get real time body temperature and heartbeat count of the baby. It will also provide health and report analysis as well as emergency notifications.
Bionic arm is a revolutionary idea for amputees across the globe. This is as close as we can get to our natural limb. The fundamental point is to make the arm move with our brain unlike previous prosthetic upper limbs
This document describes a study to design a smart plantar to support correct posture and movement during sports activities. The plantar would use sensors to monitor a user's movements and provide data on any incorrect behaviors via a mobile application. An early evaluation would involve users testing a prototype plantar during activities while providing feedback. The goal is to help users identify postural issues and motivate behavioral changes through personalized data visualization.
The document describes the i-LIMB Hand, the world's first fully articulating bionic hand. It has four independently powered fingers and an articulating rotatable thumb, allowing for a wide range of natural grips and motions that were previously not possible with prosthetic hands. The i-LIMB Hand provides levels of flexibility, durability, aesthetic presentation and overall functionality that exceed all other prosthetic hands. It allows users to perform many activities of daily living.
This document summarizes a research paper that developed a wheelchair control system using hand gestures recognized by MEMS accelerometers. The system is intended to help quadriplegics navigate wheelchairs without assistance. MEMS accelerometers are attached to the fingers and back of the hand to detect gestures. The sensor values are sent to a microcontroller which controls the wheelchair's movement in different directions depending on the detected gesture. The aim is to allow disabled people to control wheelchair movement through intuitive hand gestures.
Biomechatronics is an interdisciplinary field that aims to integrate biological organisms with mechanical and electrical elements to create innovative prosthetics. Historically, prosthetics have evolved from simple designs in ancient Egypt to modern versions with increased range of motion and new control interfaces. Current research at universities like MIT, Carnegie Mellon, and Arizona State focus on developing prosthetics with muscle actuation, neural control interfaces, tactile feedback skin, and customized designs tailored to individual users. The iLimb hand provides variable control of each digit and uses tendon activity to power natural movement.
Robot Arm Utilized Having Meal Support System Based on Computer Input by Huma...Waqas Tariq
A robot arm utilized having meal support system based on computer input by human eyes only is proposed. The proposed system is developed for handicap/disabled persons as well as elderly persons and tested with able persons with several shapes and size of eyes under a variety of illumination conditions. The test results with normal persons show the proposed system does work well for selection of the desired foods and for retrieve the foods as appropriate as usersf requirements. It is found that the proposed system is 21% much faster than the manually controlled robotics.
Cycling Management using IoT – Keeping Track of Fitness Regime and Fall Detec...IRJET Journal
This document proposes a system to track cycling fitness routines and detect falls using IoT technologies. The system uses sensors in a smartphone like the accelerometer, gyroscope, electric compass and GPS to record cycling data like acceleration, orientation, direction of travel and route taken. It also connects to external hardware modules using Bluetooth to track speed, distance and calories burned in real-time. The accelerometer can also detect if a fall occurs during cycling and alert an emergency contact by sending the rider's location via GPS. The goal is to keep track of cycling workouts and provide safety in case of accidents.
This document proposes an algorithm to calculate angles of the lower limbs using inertial measurement units (IMUs) placed on the lower back, calves, and thighs while a patient performs an overhead squat exercise. The algorithm was tested on patients and compared theoretical measurements to experimental measurements from the IMUs. Error rates were low, ranging from 0.95-10.11% for different joints, showing the potential of using IMU sensors to help physical therapists evaluate rehabilitation exercises more efficiently.
E YE S CRUTINIZED W HEEL C HAIR FOR P EOPLE A FFECTED W ITH T ETRAPLEGIAijcsit
Nowadays the requirement for developing a wheel cha
ir control which is useful for the physically disab
led
person with Tetraplegia. This system involves the c
ontrol of the wheel chair with the eye moment of th
e
affected person. Statistics suggest that there are
230,000 cases of Tetraplegia in India. Our system h
ere is
to develop a wheelchair which make the lives of the
se people easier and instigate confidence to live i
n
them. We know that a person who is affected by Tetr
aplegia can move their eyes alone to a certain exte
nt
which paves the idea for the development of our sys
tem. Here we have proposed the method for a device
where a patient placed on the wheel chair looking
in a straight line at the camera which is permanent
ly
fixed in the optics, is capable to move in a track
by gazing in that way. When we change the directio
n, the
camera signals are given using the mat lab script t
o the microcontroller. Depends on the path of the e
ye,
the microcontroller controls the wheel chair in all
direction and stops the movement. If there is any
obstacle to be found before the wheel chair the sen
sor mind that and it stop and move in right directi
on
immediately. The benefit of this system is too easi
ly travel anywhere in any direction which is handle
d by
physically disabled person with Tetraplegia
Piezoelectric Insoles and Mobile Application for Osteoarthritis Pain and Exer...Christopher Wong
Osteoarthritis is a painful and common disease that affects joints like the knees and hips. While exercise can help, patients must carefully monitor their activity levels to avoid overuse. The authors propose a system using piezoelectric sensors in shoe insoles connected to a smartphone app to objectively track patients' exercise and pain levels. This would help clinicians personalize exercise recommendations and correlate activity to disease progression. A prototype successfully measured and transmitted pressure data. Further testing is needed but such a low-cost system could help manage osteoarthritis long-term.
Mechanism Design and Debugging of an Intelligent Rehabilitation Nursing BedIJRES Journal
The document describes the design and development of an intelligent rehabilitation nursing bed. Key features of the bed include mechanisms to support the back, curve the legs, and enable side turning over of patients. The side turning mechanism uses a six degree of freedom screw-slider-link design to achieve 90 degree rotations. Testing showed the bed runs smoothly and parameters are reasonable. The bed aims to meet rehabilitation needs and facilitate nursing care for patients.
This document proposes a real-time tracking system using Android GPS and GPRS to locate patients suffering from Alzheimer's disease. The system consists of two modules - a caregiver module and a patient module. The patient module uses the device's GPS to continuously monitor and report the patient's location to the caregiver module. The caregiver module displays the patient's location on a map and allows caregivers to track the patient in real-time. The system is designed to provide a low-cost solution to locate Alzheimer's patients and help caregivers monitor them.
The document describes a system to measure nutrient intake levels using non-invasive sensors. It uses piezoelectric sensors to detect throat movement during eating, ECG sensors to measure calorie intake, and temperature sensors to measure calorie burn. The Raspberry Pi collects and analyzes sensor data, which is stored and displayed on the cloud. This allows continuous monitoring of dietary intake levels using a wearable IoT device.
Eating Habit and Health Monitoring System using Android Based Machine LearningIRJET Journal
This document describes a proposed system called the Eating Habit and Health Monitoring System Using Android Based Machine Learning. The system uses a wearable device with a vibration sensor that is worn around the neck to collect acoustic signals during eating. The signals are processed by an embedded hardware prototype and sent via Bluetooth to a smartphone. The smartphone application analyzes the signals using hidden Markov models to detect chewing and swallowing events and recognize food types. It provides notifications to the user about their food intake and suggests healthier habits based on their calorie consumption goals. The overall goal is to develop an easy-to-use, non-invasive solution for continuously monitoring daily food intake using machine learning techniques.
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 paper proposes a design for using a smart watch to automatically detect a person's hunger level and order food from nearby restaurants when their hunger reaches a threshold. The smart watch would use electroencephalogram (EEG) sensors to monitor electrical signals in the brain associated with hunger. When the measured hunger level reaches a predefined threshold, the linked smartphone would use GPS to find nearby food options and allow the person to select and pay for a meal to be delivered within 30 minutes. The proposed system aims to help busy people more efficiently manage their daily schedules and food needs.
Smart health monitoring system using IoT based smart fitness mirrorTELKOMNIKA JOURNAL
The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user’s body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user’s body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
Last minute decisions 'Chubby-Checker 3000'Killian Vigna
The document summarizes a directed study report for a smartphone application called the "Chubby-Checker 3000" that is designed to help users monitor their weight, body composition, and fitness progress over time. The application would sync with Bluetooth-enabled skin fold callipers to automatically input body measurements and body fat percentage into the app. Users could also take photos to track their external progress. The product aims to help motivate users by providing a more complete picture of their internal changes compared to just weight alone. The target market is 18-50 year old smartphone users looking to improve their appearance without expensive personal trainers or gym memberships.
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.
Advance IoT-based BSN Healthcare System for Emergency Response of Patient wit...IJMTST Journal
BSN is a prior and emerging technology in the medical field .BSN care system first deploy light weight ,tinypowered
sensors on patient body which communicate with each other and the coordinator node which is on
the body.This system mainly focuses on the measurement and estimation of important parameters like
ECG,temperature,level of blood. This real time system focuses on several parameters like patient location,
data storage, motion detection and transmission of data as well as alert messages to first responder and
server of hospital.In this system we are using three types of sensors ECG sensor,temperature sensor and
level sensor which gathers patients information and sends to micro-controller via which it goes to
BTC(Bluetooth Controller) through it is transferred to an Android smart phone of patient via Wi-Fi/Internet it
goes to server and from the server data is sends to doctors Android App. We are additionally using NFC(Near
Field Communication) technology,motion detection of patient by continuous grabbing of feed from
camera.Subsequently, by using this customized algorithm we proposed IOT based healthcare system using
body sensors which efficiently accomplish requirement.
Human Activity Recognition using Smartphone's sensor Pankaj Mishra
Human activity recognition plays significant role in medical field and in security system. In this project we have design a model which recognize a person’s activity based on Smartphone.
A 3- dimensional Smartphone sensor named accelerometer and gyroscope is used to collect time series signal, from which 26 features are generated in time and frequency domain. The activities are classified using 2 different dormant learning method i.e. k-nearest neighbor algorithm, decision tree algorithm.
An Algorithm for In-Place Vision-Based Skewed 1D Barcode Scanning in the CloudVladimir Kulyukin
The document presents an algorithm for in-place, vision-based scanning of skewed 1D barcodes using a cloud-based system. The algorithm does not require alignment of the smartphone camera with the barcode. It is implemented in a distributed system with a smartphone app frontend and a 4-node Linux cluster backend for image recognition and data storage. The algorithm was evaluated on over 500 videos of grocery products and results are presented.
Ligia Alexandra Gaspar - bachelor thesis in collaboration with OAMK Digital Patient project I developed a prototype of a health application that contains 3D human body modeling and is inspired from doctor Peter D'Adamo's work on nutrition and blood types
This document describes a study to design a smart plantar to support correct posture and movement during sports activities. The plantar would use sensors to monitor a user's movements and provide data on any incorrect behaviors via a mobile application. An early evaluation would involve users testing a prototype plantar during activities while providing feedback. The goal is to help users identify postural issues and motivate behavioral changes through personalized data visualization.
The document describes the i-LIMB Hand, the world's first fully articulating bionic hand. It has four independently powered fingers and an articulating rotatable thumb, allowing for a wide range of natural grips and motions that were previously not possible with prosthetic hands. The i-LIMB Hand provides levels of flexibility, durability, aesthetic presentation and overall functionality that exceed all other prosthetic hands. It allows users to perform many activities of daily living.
This document summarizes a research paper that developed a wheelchair control system using hand gestures recognized by MEMS accelerometers. The system is intended to help quadriplegics navigate wheelchairs without assistance. MEMS accelerometers are attached to the fingers and back of the hand to detect gestures. The sensor values are sent to a microcontroller which controls the wheelchair's movement in different directions depending on the detected gesture. The aim is to allow disabled people to control wheelchair movement through intuitive hand gestures.
Biomechatronics is an interdisciplinary field that aims to integrate biological organisms with mechanical and electrical elements to create innovative prosthetics. Historically, prosthetics have evolved from simple designs in ancient Egypt to modern versions with increased range of motion and new control interfaces. Current research at universities like MIT, Carnegie Mellon, and Arizona State focus on developing prosthetics with muscle actuation, neural control interfaces, tactile feedback skin, and customized designs tailored to individual users. The iLimb hand provides variable control of each digit and uses tendon activity to power natural movement.
Robot Arm Utilized Having Meal Support System Based on Computer Input by Huma...Waqas Tariq
A robot arm utilized having meal support system based on computer input by human eyes only is proposed. The proposed system is developed for handicap/disabled persons as well as elderly persons and tested with able persons with several shapes and size of eyes under a variety of illumination conditions. The test results with normal persons show the proposed system does work well for selection of the desired foods and for retrieve the foods as appropriate as usersf requirements. It is found that the proposed system is 21% much faster than the manually controlled robotics.
Cycling Management using IoT – Keeping Track of Fitness Regime and Fall Detec...IRJET Journal
This document proposes a system to track cycling fitness routines and detect falls using IoT technologies. The system uses sensors in a smartphone like the accelerometer, gyroscope, electric compass and GPS to record cycling data like acceleration, orientation, direction of travel and route taken. It also connects to external hardware modules using Bluetooth to track speed, distance and calories burned in real-time. The accelerometer can also detect if a fall occurs during cycling and alert an emergency contact by sending the rider's location via GPS. The goal is to keep track of cycling workouts and provide safety in case of accidents.
This document proposes an algorithm to calculate angles of the lower limbs using inertial measurement units (IMUs) placed on the lower back, calves, and thighs while a patient performs an overhead squat exercise. The algorithm was tested on patients and compared theoretical measurements to experimental measurements from the IMUs. Error rates were low, ranging from 0.95-10.11% for different joints, showing the potential of using IMU sensors to help physical therapists evaluate rehabilitation exercises more efficiently.
E YE S CRUTINIZED W HEEL C HAIR FOR P EOPLE A FFECTED W ITH T ETRAPLEGIAijcsit
Nowadays the requirement for developing a wheel cha
ir control which is useful for the physically disab
led
person with Tetraplegia. This system involves the c
ontrol of the wheel chair with the eye moment of th
e
affected person. Statistics suggest that there are
230,000 cases of Tetraplegia in India. Our system h
ere is
to develop a wheelchair which make the lives of the
se people easier and instigate confidence to live i
n
them. We know that a person who is affected by Tetr
aplegia can move their eyes alone to a certain exte
nt
which paves the idea for the development of our sys
tem. Here we have proposed the method for a device
where a patient placed on the wheel chair looking
in a straight line at the camera which is permanent
ly
fixed in the optics, is capable to move in a track
by gazing in that way. When we change the directio
n, the
camera signals are given using the mat lab script t
o the microcontroller. Depends on the path of the e
ye,
the microcontroller controls the wheel chair in all
direction and stops the movement. If there is any
obstacle to be found before the wheel chair the sen
sor mind that and it stop and move in right directi
on
immediately. The benefit of this system is too easi
ly travel anywhere in any direction which is handle
d by
physically disabled person with Tetraplegia
Piezoelectric Insoles and Mobile Application for Osteoarthritis Pain and Exer...Christopher Wong
Osteoarthritis is a painful and common disease that affects joints like the knees and hips. While exercise can help, patients must carefully monitor their activity levels to avoid overuse. The authors propose a system using piezoelectric sensors in shoe insoles connected to a smartphone app to objectively track patients' exercise and pain levels. This would help clinicians personalize exercise recommendations and correlate activity to disease progression. A prototype successfully measured and transmitted pressure data. Further testing is needed but such a low-cost system could help manage osteoarthritis long-term.
Mechanism Design and Debugging of an Intelligent Rehabilitation Nursing BedIJRES Journal
The document describes the design and development of an intelligent rehabilitation nursing bed. Key features of the bed include mechanisms to support the back, curve the legs, and enable side turning over of patients. The side turning mechanism uses a six degree of freedom screw-slider-link design to achieve 90 degree rotations. Testing showed the bed runs smoothly and parameters are reasonable. The bed aims to meet rehabilitation needs and facilitate nursing care for patients.
This document proposes a real-time tracking system using Android GPS and GPRS to locate patients suffering from Alzheimer's disease. The system consists of two modules - a caregiver module and a patient module. The patient module uses the device's GPS to continuously monitor and report the patient's location to the caregiver module. The caregiver module displays the patient's location on a map and allows caregivers to track the patient in real-time. The system is designed to provide a low-cost solution to locate Alzheimer's patients and help caregivers monitor them.
The document describes a system to measure nutrient intake levels using non-invasive sensors. It uses piezoelectric sensors to detect throat movement during eating, ECG sensors to measure calorie intake, and temperature sensors to measure calorie burn. The Raspberry Pi collects and analyzes sensor data, which is stored and displayed on the cloud. This allows continuous monitoring of dietary intake levels using a wearable IoT device.
Eating Habit and Health Monitoring System using Android Based Machine LearningIRJET Journal
This document describes a proposed system called the Eating Habit and Health Monitoring System Using Android Based Machine Learning. The system uses a wearable device with a vibration sensor that is worn around the neck to collect acoustic signals during eating. The signals are processed by an embedded hardware prototype and sent via Bluetooth to a smartphone. The smartphone application analyzes the signals using hidden Markov models to detect chewing and swallowing events and recognize food types. It provides notifications to the user about their food intake and suggests healthier habits based on their calorie consumption goals. The overall goal is to develop an easy-to-use, non-invasive solution for continuously monitoring daily food intake using machine learning techniques.
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 paper proposes a design for using a smart watch to automatically detect a person's hunger level and order food from nearby restaurants when their hunger reaches a threshold. The smart watch would use electroencephalogram (EEG) sensors to monitor electrical signals in the brain associated with hunger. When the measured hunger level reaches a predefined threshold, the linked smartphone would use GPS to find nearby food options and allow the person to select and pay for a meal to be delivered within 30 minutes. The proposed system aims to help busy people more efficiently manage their daily schedules and food needs.
Smart health monitoring system using IoT based smart fitness mirrorTELKOMNIKA JOURNAL
The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user’s body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user’s body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
Last minute decisions 'Chubby-Checker 3000'Killian Vigna
The document summarizes a directed study report for a smartphone application called the "Chubby-Checker 3000" that is designed to help users monitor their weight, body composition, and fitness progress over time. The application would sync with Bluetooth-enabled skin fold callipers to automatically input body measurements and body fat percentage into the app. Users could also take photos to track their external progress. The product aims to help motivate users by providing a more complete picture of their internal changes compared to just weight alone. The target market is 18-50 year old smartphone users looking to improve their appearance without expensive personal trainers or gym memberships.
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.
Advance IoT-based BSN Healthcare System for Emergency Response of Patient wit...IJMTST Journal
BSN is a prior and emerging technology in the medical field .BSN care system first deploy light weight ,tinypowered
sensors on patient body which communicate with each other and the coordinator node which is on
the body.This system mainly focuses on the measurement and estimation of important parameters like
ECG,temperature,level of blood. This real time system focuses on several parameters like patient location,
data storage, motion detection and transmission of data as well as alert messages to first responder and
server of hospital.In this system we are using three types of sensors ECG sensor,temperature sensor and
level sensor which gathers patients information and sends to micro-controller via which it goes to
BTC(Bluetooth Controller) through it is transferred to an Android smart phone of patient via Wi-Fi/Internet it
goes to server and from the server data is sends to doctors Android App. We are additionally using NFC(Near
Field Communication) technology,motion detection of patient by continuous grabbing of feed from
camera.Subsequently, by using this customized algorithm we proposed IOT based healthcare system using
body sensors which efficiently accomplish requirement.
Human Activity Recognition using Smartphone's sensor Pankaj Mishra
Human activity recognition plays significant role in medical field and in security system. In this project we have design a model which recognize a person’s activity based on Smartphone.
A 3- dimensional Smartphone sensor named accelerometer and gyroscope is used to collect time series signal, from which 26 features are generated in time and frequency domain. The activities are classified using 2 different dormant learning method i.e. k-nearest neighbor algorithm, decision tree algorithm.
An Algorithm for In-Place Vision-Based Skewed 1D Barcode Scanning in the CloudVladimir Kulyukin
The document presents an algorithm for in-place, vision-based scanning of skewed 1D barcodes using a cloud-based system. The algorithm does not require alignment of the smartphone camera with the barcode. It is implemented in a distributed system with a smartphone app frontend and a 4-node Linux cluster backend for image recognition and data storage. The algorithm was evaluated on over 500 videos of grocery products and results are presented.
Ligia Alexandra Gaspar - bachelor thesis in collaboration with OAMK Digital Patient project I developed a prototype of a health application that contains 3D human body modeling and is inspired from doctor Peter D'Adamo's work on nutrition and blood types
The document summarizes the academic work and achievements of Jimmy Majumder. It includes details of his ongoing PhD thesis on developing a smart robotics walker system for Parkinson's disease rehabilitation and monitoring. It also lists his previous undergraduate thesis, research projects involving robotics and AI applications, publications, certifications, and roles mentoring students. The various projects described focus on assistive technologies, healthcare robots, home automation, and more.
The document discusses developing a smartphone application for human activity recognition with a focus on health and well-being. It would utilize the smartphone's accelerometer to monitor and track calories burned, weight, sleep patterns, and provide personalized health advice. The application would also include features like sleep analysis, disease recognition through advanced algorithms, and an interactive chatbot for assistance. A use case table compares the proposed application to existing health and fitness apps. The project timeline outlines kicking off the project in the first week by finalizing details and establishing the development team structure.
Accelerometer-Based Recorder of Fingers Dynamic Movements for Post-Stroke Reh...UniversitasGadjahMada
Stroke is a disease that currently attracts more attention in Indonesia according to the statistics provided by the Ministry of Health of the Republic of Indonesia. This research was motivated by the shortage of physiotherapists which can not catch the increasing number of stroke patients. The therapy becomes less effective and less efficient since each therapist must handle too many patients during his/her work hours. This research has developed a device prototype that can help the therapy to measure and monitor patient exercise, especially at the final stage of rehabilitation when the patient gets therapy to move actively. The angle of the moving body parts that can represent the ability of patient motion was measured using accelerometers. The developed prototype was in the form of a glove, equipped with an Arduino Nano and two accelerometer modules, that measures the motion of the thumb and index finger. The device was calibrated and tested to determine the characteristics of the sensors. This test showed that the gloves prototype had an accuracy of 95,8% and precision of 99,6%. The application of the prototype was carried out on four types of finger movements, namely thumb abduction-adduction, thumb flexion-extension, finger flexion-hyperextension, and finger abductionadduction. The prototype was also tested for its ability to work in variations of direction and position of the hand.
Fitomatic: A Web Based Automated Healthcare Supervision and Monitoring AppIRJET Journal
1) The document describes Fitomatic, a web-based app that tracks users' fitness activities, diet, and meal plans. It detects exercise postures using machine learning to provide feedback and help users improve their form.
2) Existing fitness apps have limitations like not integrating all needed features, requiring payment for personalized support, or using complex hardware. Fitomatic aims to offer affordable virtual training and monitoring without specialized equipment.
3) The system analyzes users' BMI and recommends healthier diets and exercise plans tailored to individual goals and lifestyles. This allows people to conveniently workout and get coaching from home.
Real time Health Monitoring using the Embedded Sensors of Mobile PhoneIRJET Journal
This document summarizes a research paper that proposes a real-time health monitoring system using the embedded sensors in mobile phones. The system collects health data like step counts, falls, location, vital signs through sensors. It stores the data in a database and displays trends graphs. It also transmits data to a cloud server for access by medical professionals. The document describes various sensors in mobile phones that can be used for health monitoring like accelerometers, gyroscopes, GPS. It provides algorithms for step counting and fall detection using sensor data. Results show the system could accurately count steps and detect falls. Trend graphs from a mobile app demonstrate how the health data is visualized.
An intelligent approach to take care of mother and baby healthIJECEIAES
This is the era of technology and is widely used in every sector. In Bangladesh the use of technology is increasing day by day in many sectors. Health sector is one of them. This research is designed and developed to help the pregnant women to get weekly information on development and conditions of their health and the growing child inside their womb. This system will notify expectant mothers automatically about their health checkup date and time. It provides general and special health information to the expectant mothers. It is designed with user friendly interface so that an expectant mother can use this system very effectively. This system allows a unique secure login system and provides a unique suggestion to the expectant mothers.This system is very user friendly and useful.
Monitoring as a_servihttp://www.slideshare.net/upload#ce_4_healthcareprovidersmobi fly
Health monitoring as a service allows patients to easily track vital signs using mobile phones. It offers healthcare providers new revenue streams and enhances patient relationships. The solution involves a mobile monitoring platform that collects biometric data from wireless sensors and shares it with users and providers through mobile apps and web dashboards. This allows real-time monitoring that improves health oversight and care quality while increasing provider productivity.
Similar to Food intake gesture monitoring system based-on depth sensor (20)
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
The document proposes using a particle swarm optimization (PSO) algorithm to optimize the hyperparameters of a convolutional neural network (CNN) for image classification. The PSO algorithm is used to find optimal values for CNN hyperparameters like the number and size of convolutional filters. In experiments on the MNIST handwritten digit dataset, the optimized CNN achieved a testing error rate of 0.87%, which is competitive with state-of-the-art models. The proposed approach finds optimized CNN architectures automatically without requiring manual design or encoding strategies during training.
Supervised machine learning based liver disease prediction approach with LASS...journalBEEI
In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of this deadly disease. By diagnosing the disease in a primary stage, early treatment can be helpful to cure the patient. In this research paper, a method is proposed to diagnose the LD using supervised machine learning classification algorithms, namely logistic regression, decision tree, random forest, AdaBoost, KNN, linear discriminant analysis, gradient boosting and support vector machine (SVM). We also deployed a least absolute shrinkage and selection operator (LASSO) feature selection technique on our taken dataset to suggest the most highly correlated attributes of LD. The predictions with 10 fold cross-validation (CV) made by the algorithms are tested in terms of accuracy, sensitivity, precision and f1-score values to forecast the disease. It is observed that the decision tree algorithm has the best performance score where accuracy, precision, sensitivity and f1-score values are 94.295%, 92%, 99% and 96% respectively with the inclusion of LASSO. Furthermore, a comparison with recent studies is shown to prove the significance of the proposed system.
A secure and energy saving protocol for wireless sensor networksjournalBEEI
The research domain for wireless sensor networks (WSN) has been extensively conducted due to innovative technologies and research directions that have come up addressing the usability of WSN under various schemes. This domain permits dependable tracking of a diversity of environments for both military and civil applications. The key management mechanism is a primary protocol for keeping the privacy and confidentiality of the data transmitted among different sensor nodes in WSNs. Since node's size is small; they are intrinsically limited by inadequate resources such as battery life-time and memory capacity. The proposed secure and energy saving protocol (SESP) for wireless sensor networks) has a significant impact on the overall network life-time and energy dissipation. To encrypt sent messsages, the SESP uses the public-key cryptography’s concept. It depends on sensor nodes' identities (IDs) to prevent the messages repeated; making security goals- authentication, confidentiality, integrity, availability, and freshness to be achieved. Finally, simulation results show that the proposed approach produced better energy consumption and network life-time compared to LEACH protocol; sensors are dead after 900 rounds in the proposed SESP protocol. While, in the low-energy adaptive clustering hierarchy (LEACH) scheme, the sensors are dead after 750 rounds.
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Customized moodle-based learning management system for socially disadvantaged...journalBEEI
This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Understanding the role of individual learner in adaptive and personalized e-l...journalBEEI
Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.
Prototype mobile contactless transaction system in traditional markets to sup...journalBEEI
1) Researchers developed a prototype contactless transaction system using QR codes and digital payments to support physical distancing during the COVID-19 pandemic in traditional markets.
2) The system allows sellers and buyers in traditional markets to conduct fast, secure transactions via smartphones without direct cash exchange. Buyers scan sellers' QR codes to view product details and make e-wallet payments.
3) Testing showed the system's functions worked properly and users found it easy to use and useful for supporting contactless transactions and digital transformation of traditional markets. However, further development is needed to increase trust in digital payments for users unfamiliar with the technology.
Wireless HART stack using multiprocessor technique with laxity algorithmjournalBEEI
The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.
Implementation of double-layer loaded on octagon microstrip yagi antennajournalBEEI
This document describes the implementation of a double-layer structure on an octagon microstrip yagi antenna (OMYA) to improve its performance at 5.8 GHz. The double-layer consists of two double positive (DPS) substrates placed above the OMYA. Simulation and experimental results show that the double-layer configuration increases the gain of the OMYA by 2.5 dB compared to without the double-layer. The measured bandwidth of the OMYA with double-layer is 14.6%, indicating the double-layer can increase both the gain and bandwidth of the OMYA.
The calculation of the field of an antenna located near the human headjournalBEEI
In this work, a numerical calculation was carried out in one of the universal programs for automatic electro-dynamic design. The calculation is aimed at obtaining numerical values for specific absorbed power (SAR). It is the SAR value that can be used to determine the effect of the antenna of a wireless device on biological objects; the dipole parameters will be selected for GSM1800. Investigation of the influence of distance to a cell phone on radiation shows that absorbed in the head of a person the effect of electromagnetic radiation on the brain decreases by three times this is a very important result the SAR value has decreased by almost three times it is acceptable results.
Exact secure outage probability performance of uplinkdownlink multiple access...journalBEEI
In this paper, we study uplink-downlink non-orthogonal multiple access (NOMA) systems by considering the secure performance at the physical layer. In the considered system model, the base station acts a relay to allow two users at the left side communicate with two users at the right side. By considering imperfect channel state information (CSI), the secure performance need be studied since an eavesdropper wants to overhear signals processed at the downlink. To provide secure performance metric, we derive exact expressions of secrecy outage probability (SOP) and and evaluating the impacts of main parameters on SOP metric. The important finding is that we can achieve the higher secrecy performance at high signal to noise ratio (SNR). Moreover, the numerical results demonstrate that the SOP tends to a constant at high SNR. Finally, our results show that the power allocation factors, target rates are main factors affecting to the secrecy performance of considered uplink-downlink NOMA systems.
Design of a dual-band antenna for energy harvesting applicationjournalBEEI
This report presents an investigation on how to improve the current dual-band antenna to enhance the better result of the antenna parameters for energy harvesting application. Besides that, to develop a new design and validate the antenna frequencies that will operate at 2.4 GHz and 5.4 GHz. At 5.4 GHz, more data can be transmitted compare to 2.4 GHz. However, 2.4 GHz has long distance of radiation, so it can be used when far away from the antenna module compare to 5 GHz that has short distance in radiation. The development of this project includes the scope of designing and testing of antenna using computer simulation technology (CST) 2018 software and vector network analyzer (VNA) equipment. In the process of designing, fundamental parameters of antenna are being measured and validated, in purpose to identify the better antenna performance.
Transforming data-centric eXtensible markup language into relational database...journalBEEI
eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.
Key performance requirement of future next wireless networks (6G)journalBEEI
The document provides an overview of the key performance indicators (KPIs) for 6G wireless networks compared to 5G networks. Some of the major KPIs discussed for 6G include: achieving data rates of up to 1 Tbps and individual user data rates up to 100 Gbps; reducing latency below 10 milliseconds; supporting up to 10 million connected devices per square kilometer; improving spectral efficiency by up to 100 times through technologies like terahertz communications and smart surfaces; and achieving an energy efficiency of 1 pico-joule per bit transmitted through techniques like wireless power transmission and energy harvesting. The document outlines how 6G aims to integrate terrestrial, aerial and maritime communications into a single network to provide ubiquitous connectivity with higher
Noise resistance territorial intensity-based optical flow using inverse confi...journalBEEI
This paper presents the use of the inverse confidential technique on bilateral function with the territorial intensity-based optical flow to prove the effectiveness in noise resistance environment. In general, the image’s motion vector is coded by the technique called optical flow where the sequences of the image are used to determine the motion vector. But, the accuracy rate of the motion vector is reduced when the source of image sequences is interfered by noises. This work proved that the inverse confidential technique on bilateral function can increase the percentage of accuracy in the motion vector determination by the territorial intensity-based optical flow under the noisy environment. We performed the testing with several kinds of non-Gaussian noises at several patterns of standard image sequences by analyzing the result of the motion vector in a form of the error vector magnitude (EVM) and compared it with several noise resistance techniques in territorial intensity-based optical flow method.
Modeling climate phenomenon with software grids analysis and display system i...journalBEEI
This study aims to model climate change based on rainfall, air temperature, pressure, humidity and wind with grADS software and create a global warming module. This research uses 3D model, define, design, and develop. The results of the modeling of the five climate elements consist of the annual average temperature in Indonesia in 2009-2015 which is between 29oC to 30.1oC, the horizontal distribution of the annual average pressure in Indonesia in 2009-2018 is between 800 mBar to 1000 mBar, the horizontal distribution the average annual humidity in Indonesia in 2009 and 2011 ranged between 27-57, in 2012-2015, 2017 and 2018 it ranged between 30-60, during the East Monsoon, the wind circulation moved from northern Indonesia to the southern region Indonesia. During the west monsoon, the wind circulation moves from the southern part of Indonesia to the northern part of Indonesia. The global warming module for SMA/MA produced is feasible to use, this is in accordance with the value given by the validate of 69 which is in the appropriate category and the response of teachers and students through a 91% questionnaire.
An approach of re-organizing input dataset to enhance the quality of emotion ...journalBEEI
The purpose of this paper is to propose an approach of re-organizing input data to recognize emotion based on short signal segments and increase the quality of emotional recognition using physiological signals. MIT's long physiological signal set was divided into two new datasets, with shorter and overlapped segments. Three different classification methods (support vector machine, random forest, and multilayer perceptron) were implemented to identify eight emotional states based on statistical features of each segment in these two datasets. By re-organizing the input dataset, the quality of recognition results was enhanced. The random forest shows the best classification result among three implemented classification methods, with an accuracy of 97.72% for eight emotional states, on the overlapped dataset. This approach shows that, by re-organizing the input dataset, the high accuracy of recognition results can be achieved without the use of EEG and ECG signals.
Parking detection system using background subtraction and HSV color segmentationjournalBEEI
Manual system vehicle parking makes finding vacant parking lots difficult, so it has to check directly to the vacant space. If many people do parking, then the time needed for it is very much or requires many people to handle it. This research develops a real-time parking system to detect parking. The system is designed using the HSV color segmentation method in determining the background image. In addition, the detection process uses the background subtraction method. Applying these two methods requires image preprocessing using several methods such as grayscaling, blurring (low-pass filter). In addition, it is followed by a thresholding and filtering process to get the best image in the detection process. In the process, there is a determination of the ROI to determine the focus area of the object identified as empty parking. The parking detection process produces the best average accuracy of 95.76%. The minimum threshold value of 255 pixels is 0.4. This value is the best value from 33 test data in several criteria, such as the time of capture, composition and color of the vehicle, the shape of the shadow of the object’s environment, and the intensity of light. This parking detection system can be implemented in real-time to determine the position of an empty place.
Quality of service performances of video and voice transmission in universal ...journalBEEI
The universal mobile telecommunications system (UMTS) has distinct benefits in that it supports a wide range of quality of service (QoS) criteria that users require in order to fulfill their requirements. The transmission of video and audio in real-time applications places a high demand on the cellular network, therefore QoS is a major problem in these applications. The ability to provide QoS in the UMTS backbone network necessitates an active QoS mechanism in order to maintain the necessary level of convenience on UMTS networks. For UMTS networks, investigation models for end-to-end QoS, total transmitted and received data, packet loss, and throughput providing techniques are run and assessed and the simulation results are examined. According to the results, appropriate QoS adaption allows for specific voice and video transmission. Finally, by analyzing existing QoS parameters, the QoS performance of 4G/UMTS networks may be improved.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
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.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
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
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
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.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
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Food intake gesture monitoring system based-on depth sensor (Muhammad Fuad bin Kassim)
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Besides, detection accuracy by combining using a head-mount accelerometer which is Google Glass
technology and using a wrist-worn accelerometer (Pebble watch) [8]. The depth sensing approach is an action
to detect gesture of body skeleton or hand skeleton based on [9-13] they use Kinect version 1 which has
limited body joint track and using additional sensor such as Myo band combine with RGB from Kinect
sensor to achieve accurate result. This system can help people follow a proper way to overcome overweight
or eating disorders by monitoring their meal intake and controlling eating rate. The bite counter is measured
by using wrist joint and jaw motion detection when taking food. By detecting this pattern, the food intake can
be identified when a bite of food has been taken thus it can monitor food intake in real time monitoring while
showing bite count to the user. The system could tell the user to slow down or to stop eating after a bite count
threshold reached.
These methods also help the user to track long-term eating patterns and can help people track their
daily intake. Generally, fingers are aimed downwards to pick something up and roll the hand to place it into
the mouth [14]. This pattern holds regardless of the type of food. The aim of this research is to keep the
complexity minimum so that it could be potentially applied in real time.
2. RESEARCH METHOD
In this section, it is explained the research method and at the same time is given the comprehensive
discussion to achieve the objectives of this paper.
2.1. Overview of the monitoring system
The proposed methodology is divided into 2 stages, which are hand skeletal recognition and face
recognition. This project is developed by using Microsoft Visual Studio, this system uses Kinect sensor for
capturing depth images. The depth camera can work both day and night [15, 16]. The system monitoring was
placed in front of user table with 1.4 meters while taking user daily food intake. Kinect will track skeleton
body of the user and recognize the eating pattern.
The gesture recognition of pitch, roll, and yaw are measured using Kinect sensor by detecting the
joint rotation point. During food intake, the pitch and roll data arm can be used to trigger food intake
detection. Thus, by capturing this data could be used for tracking and recognition. Therefore, the system can
detect food intake without using wearable sensors such as Myo armband or gyroscope. Figure 1 shows all the
system for food intake monitoring.
Figure 1. Flowchart of the food intake monitoring system
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2.2. Gesture detection and distance measurement
As discussed, this system uses Kinect for capturing depth images and skeletal joint tracking. The
depth images are generated by the IR sensor. Using skeletal tracking function, Kinect can detect movement
of the arm and the angle position of the user.
The Kinect sensor used here can detect location of 25 joints on each body for six people using
Kinect SDK. This function to track the skeleton image within the Kinect‟s field of view using the infrared
(IR) camera. In default range mode, Kinect can track people standing between 0.8 meters to 4.0 meters away,
therefore, user able to use their arm at that distance and allowing the recognition of body parts to be tracked.
The Kinect sensor was placed at a specific distance which is around 1.4 meters from the user eating
table, at a height of 1.4 meters from the floor. The distance was made to avoid overlapping of the hands and
face detection while eating and like the position for which the sensor was designed in front of the user
eating place.
The lunch activity basically consisted of eating specific food and drinking water. The user will have
instructed to eat only during the sessions, using foods given that are easy to grasp by using a hand. The
shoulder joint can be tracked using a point from angle calculation from the depth camera. The skeletal
tracking will detect the angle of upper limb joint and the data will be training with Support Vector Machine
(SVM) to classify the posture. The upper limb joint is divided into the shoulder, arm elbow, wrist, and hand.
Figure 2 shows system structure design of our project. SVM classification will be used to predict the eating
posture of the user. The system will use internet dataset which available online to train the data.
Figure 2. System structure design of food intake counting
2.3. Food intake gesture analysis
Food classification gesture analysis features can be detected by each person‟s eating patter style by
monitoring and training the data. First, the user will be asked to seat in a chair while eating this is to obtain
skeleton‟s joints from the Kinect sensor and it was observed that the joints can be detected and be used to
train SVM for seated position recognition. The user‟s arm and shoulder joints, which represent the key-points
of this data. The system will analyze and monitoring the situation of user‟s hand if it close to mouth and
counting the food intake by displaying the bite counter in the GUI of the system. The system will be able to
differentiate between drinking and eating.
To analyze the gestures, the system will focus on the head part of user which is the jaw movement
and hand wrist joints gesture. This method should help the system differentiate whether the hand is near of
far from mouth and monitor the jaw point movement while eating thus can use this point for tracking and
monitoring for food intake. To avoid overlapping, the decision technique will be used as a stated in the
flowchart. This distance allows us to better understand the variation of distance hand and the jaw movement.
Figure 3 shows the illustration of right arm angle calculation by Kinect. Kinect‟s 3-dimensional
coordinate system defines the three-dimensional coordinate of the shoulder, elbow, and wrist. And uses the
vector formula.
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̅̅̅̅ ( ) ( ) (1)
Figure 3. Illustration of right arm angle calculation by Kinect
To find the vector formula of shoulder to elbow and of the elbow to wrist. The vector formula is
shown below.
̅̅̅̅ ( ) ( ) (2)
̅̅̅̅̅ ( ) ( ) (3)
After solving the vector formulas between joints, the elbow bending angle could be found by the law of
cosines and anti-law of cosines of vector formula. The formula is shown below.
̅̅̅̅ ̅̅̅̅̅
|̅̅̅̅| |̅̅̅̅̅|
(4)
( ) (5)
Data were also taken of the movements of right hands when they leave the plate in a direction to the
mouth and from the body to the mouth. The bite counters can count the total number of bites the user has
taken and provided the rate of bites taken (bites per minute) of the user.
The data can be stored to review and evaluate the device later. Kinect can classify the bite count and
drink. The SVM will be used to train the bite pattern of user eating style. This system will have monitoring
GUI system so that user can see their daily intake or can be using to alert the user. The user will not have to
wear any sensor on their body. The goal of this system to provide the user with motivational information and
identify bite behavior to help the user lose weight effectively.
2.4. Rotation 3D hand wrist joint recognition
To create a rotation in 3-dimension, the axis and position of rotation need to be analyzed. The X, Y,
and Z of user‟s right-hand wrist point are reported based on coordinate system where the origin of the sensor
and user are specified with Kinect‟s skeleton coordinate frame.
Translations are in meters. The user‟s hand wrist rotation is captured by three angles which is pitch,
roll, and yaw. This can be used for tracking and monitoring the rotation of the hand wrist around the X, Y
and Z axis. Euler angle are used to represent the rotation in 3-dimension space.
A quaternion is a set of four vector that are used to specify a rotation in 3D space, quaternion will be
used to detect these 4 vectors in hand wrist rotation that is known as joint yaw, pitch and roll. Each
quaternion is absolute to its parent bone. The frame-based approach is to provide a continuous real time hand
wrist rotation by utilizing depth by Kinect sensor. Our approach built is to analyze the accuracy rotation of
wrist hand since most of the method to track hand wrist using wearable gyroscope but now with Kinect the
same function as gyroscope available by monitoring the roll, pitch and yaw of hand wrist. Figure 4 shows the
illustration of rotation in 3 dimensions by Kinect sensor.
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Figure 5 shows a hand gesture tracking using the Kinect sensor. Hand gesture system is widely
used in today‟s trend since it only detecting hand, finger, and gesture making it easier to identify the target.
Depth image from Kinect sensor is used to detect the Skelton's hand. The finger tracking should be able to
track both hands. The first step in finger tracking algorithm is to detect the hand joints. Next, specify the
search area and then find the contour of hand to specify only depth value of the hand and lastly, the convex
hull which is the point of valid fingertips. The fingertips are the edges of a polyline that contains all the
contour points thus the data can be used for implementing in gesture based food tracking while eating.
Figure 4. Illustration of rotation in 3 dimensions by
Kinect sensor
Figure 5. Hand gesture tracking
3. RESULTS AND ANALYSIS
Bite detections were classified as true positive (TP), false negative (FN), or false positive (FP). Bites
were considered as true positive, when the system recognize a food intake detection when the arm is near
raised near to mouth when taking a food. Any detections falling outside these or duplicate detections within a
single process were marked as false positive.
The food intake tracking is an event that occur at a point along with a continuous duration of
timeline when taking a bite therefore this cannot be consider as discrete points which cannot classified as
binary as bite taken or not thus there is no way to justify true negatives result. In gesture detection module the
test will be performed for each type of meal. The TP is the eating gesture that system detects, and the user
performed the gesture while the FP is the eating gesture that system detects but participant does not perform
the gesture and lastly, FN is the gesture where the system does not detect but participant performed gesture.
Table 1 present the bite evaluation detection system.
Table 1. Bite evaluation detection system
Accuracy=94% Eating Sit/Rest Drink Wrist Roll
Eating 48 0 2 0
Sit/Rest 0 50 0 0
Drink 10 0 40 0
Wrist Roll 0 0 0 50
Sensitivity 96% 100% 80% 100%
Table 1 shows the table of confusion matrix of food intake by Kinect. Confusion matrix for
prediction performance on data from the system. Correct predictions are given on the diagonal, and the
sensitivity is display below. The recognition rates obtained are shown in the form of confusion matrices for
the ten studied gestures of “Eating”, “Sit/rest”, “Drink” and “Wrist Roll”. Table above corresponds to the
situation when using the Kinect system GUI. It is seen that the overall accuracy is around 94%. Basically,
this increase in the overall recognition rate of this system.
Figure 6 shows the data obtained from 5 different opponents with age of 25, 26, 23, 24 and 44. The
user is asked to be seated in a chair and the Kinect obtained their upper limb angle detection. The Kinect is
positioned in front of the opponent, at 1.4 meters from the user. The Kinect will automatically detect user‟s
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Food intake gesture monitoring system based-on depth sensor (Muhammad Fuad bin Kassim)
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sitting skeleton and calculated upper limb joint. Although the angle detected is not accurately same with
another opponent because there is some factor which not same of all user, for example, the body size,
therefore, SVM classification can be used to train Kinect to detect angle when seated. Datasets such as
Kinect Activity Recognition Dataset (KARD) and Cornell Activity Dataset (CAD-60) which are available
online to train the SVM for classification. The data angle captured still in the range of 200 to 250 degree
which can be used to recognize the automatic sitting position of the user when eating.
Figure 6. Data of angle upper limb when seated vs opponent
4. CONCLUSION AND FUTURE WORK
This research involves detecting the bite count of eating motion to control the over intake of food
leading towards obesity. A bite-based measure of kilocalorie intake shows for individual use for self-
monitoring to use for monitoring free-living kilocalorie intake. It is an easily collected and based on the
motion that could be refined to more accurately estimate kilocalorie intake.
The recent development of new sensors that allow tracking important parts of the human body
resulted in a proliferation of different approaches to gesture recognition and their practical applications.
Therefore, any new improvement of previous solutions towards better recognition accuracy or shortening
recognition time is better for this project to be develop.
In the future, some defect in a proposed study of food intake can be improved such as food intake
algorithm there is still some high probability that false detection may occur. To reduce false detection and
undetected food tracking there several things to consider. For example, instead of using SVM other machine
learning can be used such as deep learning and more new technology.
The system GUI also can be improved such as adding new automatic counting calories with number
bites based on depth sensor. The system can also have database „cloud‟ system which can be accessed using
phone camera that has depth camera specification making the system portable and can be carrying anywhere
using smartphone.
ACKNOWLEDGEMENTS
This research is supported by a Fundamental Research Grant Scheme (FRGS) VOT 1580 sponsored
by the Center for Graduate Studies UTHM and KPT. The research also received funding from the Office for
Research, Innovation, Commercialization and Consultancy Management (ORICC), UTHM.
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BIOGRAPHIES OF AUTHORS
Muhammad Fuad bin kassim is a Master student at Universiti Tun Hussein Onn Malaysia
(UTHM). His research interests include Computer Vision, Depth Camera, Image Recognition,
and Patern Recognition. He received his bachelor‟s degree in Electronic Engineering from
Universiti Tun Hussein Onn Malaysia (UTHM) in 2016.
Mohd Norzali Haji Mohd is currently working as Senior lecturer, Faculty Lab Manager and
Former Industrial Training Coordinator at the Department of Computer Engineering, Faculty of
Electrical and Electronic Engineering, Univeristi Tun Hussein Onn Malaysia (UTHM). He
received Diploma in Computer Engineering from Toyama Maritime College, Japan in 2000 and
B.Eng., M.Eng. from Fukui University, Japan in 2002 and 2004 respectively. In April 2015, he
received Ph.D. from the Department of Information Sciences and Biomedical Engineering,
Kagoshima University, Japan.