IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IRJET- Survey on Risk Estimation of Chronic Disease using Machine LearningIRJET Journal
This document summarizes research on using machine learning to predict chronic disease risk. It discusses how healthcare generates massive amounts of data that can be used for prediction. The paper proposes a new convolutional neural network (CNN) based model that uses both structured and unstructured data from hospitals to predict disease risk. It compares this multimodal approach to existing unimodal prediction models. The document also reviews several other studies applying machine learning to tasks like heart disease prediction using large healthcare datasets. The goal is to develop effective machine learning models for predicting disease outbreaks in communities using real hospital data.
This document presents the development of an integrated portable device for continuous monitoring of heart rate and body temperature. Such a device is important for timely medical treatment, especially in rural areas without easy access to doctors or clinics. The developed system uses an Arduino microcontroller to simultaneously acquire and display heart rate and body temperature readings in real-time on an LCD screen. It is more affordable than other similar devices due to the use of inexpensive components like Arduino and sensors. The device showed acceptable performance when compared to other measurement tools.
An Ill-identified Classification to Predict Cardiac Disease Using Data Cluste...ijdmtaiir
The health care industry contains large amount of
health care data with hidden information. This information is
useful for making effective decision. For getting appropriate
result from the hidden information computer based data mining
techniques are used. Previously Neural Network (NN) is
widely used for predicting cardiac disease. In this paper, a
Cardiac Disease Prediction System (CDPS) is developed by
using data clustering. The CDPS system uses 15 parameters to
predict the disease, for example BP, Obesity, cholesterol, etc.
This 15 attributes like sex, age, weight are given as the input.
In this paper by using the patient’s medical record, an illdefined classification is used at the early stage of the patient to
diagnose the cardiac disease. Based on the result the patients
are advised to keep the sensor to predict them.
Engineering 4 Life provides biomedical engineering services including converting medical scans into 3D models for improved surgical planning and device selection. They use patient-specific 3D data to enable faster, less painful procedures with better outcomes. Services also include creating customized implants and guides through 3D printing, as well as supporting radiologists with clearer visualization for more accurate diagnoses.
IRJET- Review Paper on Patient Health Monitoring System using Can ProtocolIRJET Journal
This document summarizes a research paper on a patient health monitoring system using CAN protocol. The system measures the heart rate and body temperature of one or more patients at a time using sensors connected to a microcontroller. It sends the measured data over a CAN bus to a receiving node, which then transmits the data serially to be displayed on a single monitor. This allows doctors to remotely monitor multiple patients' vital signs from one location in real-time. The system aims to reduce monitoring time and increase flexibility for doctors compared to traditional monitoring methods.
IRJET - Digital Assistance: A New Impulse on Stroke Patient Health Care using...IRJET Journal
1) The document presents a study that uses deep learning algorithms and artificial bee colony optimization to predict stroke using medical dataset features.
2) A neural network architecture is developed to classify patients' risk of stroke based on 13 variables from their medical records, with the artificial bee colony algorithm used to preprocess data and extract meaningful features.
3) The random forest algorithm achieved the highest prediction accuracy of over 88% based on metrics like precision, recall, and F1 score compared to other models like logistic regression, naive bayes, and decision trees.
Home Care Heart Diagnosis and Measurement of Biological Signals Using Intelli...ijsrd.com
the importance behind this work is the development of intelligent, accurate diagnosis of heart rate using blood pressure. BP is the parameter which does not abide by a single range, but it depends upon the factors like age, family history. By using blood pressure system, heart rate of a person is measured. At the present situation the mortality rate has been increased due to rise in blood pressure and heart malfunctions. A Biosensor is used in forth to detect the range of heart rate. Intelligent system used here is fuzzy system which takes age, gender, BMI for the verification. Lab view is other end of the project which is used to connect the hardware to show the progress of measurement. Parameters such as Smoke detection, Temperature measurement, unauthorized entry were are included for additional facilities.
Intelligent Healthcare Monitoring in IoTIJAEMSJORNAL
The developing of IoT-based health care systems must ensure and increase the safety of the patients, their quality of life and other health care activities. We may not be aware of the health condition of the patient during the sleeping hours. To overcome this problem. This paper proposes an intelligent healthcare monitoring system which monitors and maintains the patient health condition at regular intervals. The heart rate sensor and temperature sensor would help us analyze the patients’ current health condition. In case of major fluctuations in consecutive intervals a buzzer is run in order to notify the hospital staff and doctors. The monitored details are stored in the cloud "ThingSpeak". The doctor can view the patient health condition using Virtuino simulator. This system would help in reducing the random risks of tracing a patient medical highly. Arduino UNO is used to implement this intelligent healthcare monitoring system.
IRJET- Survey on Risk Estimation of Chronic Disease using Machine LearningIRJET Journal
This document summarizes research on using machine learning to predict chronic disease risk. It discusses how healthcare generates massive amounts of data that can be used for prediction. The paper proposes a new convolutional neural network (CNN) based model that uses both structured and unstructured data from hospitals to predict disease risk. It compares this multimodal approach to existing unimodal prediction models. The document also reviews several other studies applying machine learning to tasks like heart disease prediction using large healthcare datasets. The goal is to develop effective machine learning models for predicting disease outbreaks in communities using real hospital data.
This document presents the development of an integrated portable device for continuous monitoring of heart rate and body temperature. Such a device is important for timely medical treatment, especially in rural areas without easy access to doctors or clinics. The developed system uses an Arduino microcontroller to simultaneously acquire and display heart rate and body temperature readings in real-time on an LCD screen. It is more affordable than other similar devices due to the use of inexpensive components like Arduino and sensors. The device showed acceptable performance when compared to other measurement tools.
An Ill-identified Classification to Predict Cardiac Disease Using Data Cluste...ijdmtaiir
The health care industry contains large amount of
health care data with hidden information. This information is
useful for making effective decision. For getting appropriate
result from the hidden information computer based data mining
techniques are used. Previously Neural Network (NN) is
widely used for predicting cardiac disease. In this paper, a
Cardiac Disease Prediction System (CDPS) is developed by
using data clustering. The CDPS system uses 15 parameters to
predict the disease, for example BP, Obesity, cholesterol, etc.
This 15 attributes like sex, age, weight are given as the input.
In this paper by using the patient’s medical record, an illdefined classification is used at the early stage of the patient to
diagnose the cardiac disease. Based on the result the patients
are advised to keep the sensor to predict them.
Engineering 4 Life provides biomedical engineering services including converting medical scans into 3D models for improved surgical planning and device selection. They use patient-specific 3D data to enable faster, less painful procedures with better outcomes. Services also include creating customized implants and guides through 3D printing, as well as supporting radiologists with clearer visualization for more accurate diagnoses.
IRJET- Review Paper on Patient Health Monitoring System using Can ProtocolIRJET Journal
This document summarizes a research paper on a patient health monitoring system using CAN protocol. The system measures the heart rate and body temperature of one or more patients at a time using sensors connected to a microcontroller. It sends the measured data over a CAN bus to a receiving node, which then transmits the data serially to be displayed on a single monitor. This allows doctors to remotely monitor multiple patients' vital signs from one location in real-time. The system aims to reduce monitoring time and increase flexibility for doctors compared to traditional monitoring methods.
IRJET - Digital Assistance: A New Impulse on Stroke Patient Health Care using...IRJET Journal
1) The document presents a study that uses deep learning algorithms and artificial bee colony optimization to predict stroke using medical dataset features.
2) A neural network architecture is developed to classify patients' risk of stroke based on 13 variables from their medical records, with the artificial bee colony algorithm used to preprocess data and extract meaningful features.
3) The random forest algorithm achieved the highest prediction accuracy of over 88% based on metrics like precision, recall, and F1 score compared to other models like logistic regression, naive bayes, and decision trees.
Home Care Heart Diagnosis and Measurement of Biological Signals Using Intelli...ijsrd.com
the importance behind this work is the development of intelligent, accurate diagnosis of heart rate using blood pressure. BP is the parameter which does not abide by a single range, but it depends upon the factors like age, family history. By using blood pressure system, heart rate of a person is measured. At the present situation the mortality rate has been increased due to rise in blood pressure and heart malfunctions. A Biosensor is used in forth to detect the range of heart rate. Intelligent system used here is fuzzy system which takes age, gender, BMI for the verification. Lab view is other end of the project which is used to connect the hardware to show the progress of measurement. Parameters such as Smoke detection, Temperature measurement, unauthorized entry were are included for additional facilities.
Intelligent Healthcare Monitoring in IoTIJAEMSJORNAL
The developing of IoT-based health care systems must ensure and increase the safety of the patients, their quality of life and other health care activities. We may not be aware of the health condition of the patient during the sleeping hours. To overcome this problem. This paper proposes an intelligent healthcare monitoring system which monitors and maintains the patient health condition at regular intervals. The heart rate sensor and temperature sensor would help us analyze the patients’ current health condition. In case of major fluctuations in consecutive intervals a buzzer is run in order to notify the hospital staff and doctors. The monitored details are stored in the cloud "ThingSpeak". The doctor can view the patient health condition using Virtuino simulator. This system would help in reducing the random risks of tracing a patient medical highly. Arduino UNO is used to implement this intelligent healthcare monitoring system.
IRJET - Prediction and Analysis of Multiple Diseases using Machine Learni...IRJET Journal
This document discusses using machine learning techniques to predict and analyze multiple diseases. It presents research using KNN, support vector machine, random forest, and decision tree algorithms applied to a medical database to predict future and previous diseases. The goal is to provide a smart card method for easily and accurately diagnosing disease by storing an individual's full medical record. It reviews related work applying various machine learning classifiers like decision trees, naive Bayes, and logistic regression to diseases such as heart disease, diabetes, and cancer. The conclusion is that machine learning applied to medical data can help predict disease and save time for patients and doctors.
IRJET- Heart Rate Monitoring System using Finger Tip through IOTIRJET Journal
This document describes a heart rate monitoring system that measures heart rate through the fingertip using a pulse sensor and displays the results on an LCD screen and online using WiFi. The system works by using a photoplethysmography sensor to detect changes in blood volume in the fingertip with each heartbeat. The heartbeat signal is amplified and sent to an Arduino board, which processes the data and displays the heart rate in beats per minute on the LCD. The WiFi module then transmits the data to a local server webpage and online server to view the results remotely over a network. The system provides a low-cost way to continuously monitor heart rate for healthcare applications.
Centralized patient monitoring with real time dengue outbreak detection systemSonu Kumar
This document proposes a centralized patient monitoring system with real-time dengue outbreak detection. It describes a solution that uses IoT devices connected to patients to continuously monitor vitals and send data to an Azure IoT Hub for analysis. If vitals go outside normal ranges, alerts are sent to doctors' phones. A similar system could detect dengue outbreaks by monitoring patients' locations, temperatures, and other symptoms reported by IoT medical devices on a blockchain network. This would allow timely public health interventions for dengue, which can be fatal if not treated early.
SAP Leonardo or IOT (internet of things) much focused on the manufacturing but have its scope everywhere from daily household utilities to elite defense warfare to hospitals in health care.
The document describes several healthcare IT systems implemented in Tamil Nadu, India:
1. A disease surveillance system for HIV/AIDS that automates data gathering, reporting, and provides mapping and analytics at the village level.
2. An electronic medical record system for ART patients with biometric identification and access to records across centers.
3. A patient management system using digital pen technology for physicians to record exam notes and prescriptions.
4. Remote patient monitoring services for ICU, radiology and cardiology using devices like ECG monitors and mobile transmission of data.
5. An ambulatory patient monitoring system called SmartChair that measures vital signs and transmits data via SMS or to a central
This document discusses the design of a personalized 3A health monitoring system using sensor networks. It begins with an overview of current challenges in healthcare like an aging population and increasing costs. It then describes the proposed system which would use sensors, edge computing, blockchain and other technologies to provide continuous remote health monitoring anywhere and anytime. Key aspects of the system include a heart rate monitoring solution, data exchange centers, smart health homes and eHealth labs. The system aims to address issues like data ownership and security while providing personalized care. It concludes by discussing next steps to test and implement the continuous monitoring system.
Computers are used in many areas of medicine like medical education, storing health records, diagnostics, scientific work, and therapy. They can store large amounts of patient information, assist with online appointments, help analyze medical scans, guide surgeries, and process large data sets for research. Computers also aid in knowledge sharing between medical professionals.
The essence of cardiac monitoring devicesKaty Slemon
Blog explains the need and importance of heart rate monitoring, methods to accomplish, benefits & why accurate cardiac monitoring devices are the need of hour.
IRJET- Medical Database Mining for Heart Disease Precautions and Early Ca...IRJET Journal
The document discusses using machine learning algorithms like Naive Bayes and Decision Trees to predict heart disease risk from medical data. It proposes extracting parameters like age, blood pressure, and cholesterol from patient medical records to train models. The models would then generate risk predictions for new patients, represented as values from -1 (high risk) to 1 (low risk). Experimental results on test data sets show the Naive Bayes algorithm has faster execution times than Decision Trees, with both improving accuracy as more training data is added. The goal is to help identify patients at risk of heart disease early to improve medical outcomes.
This document is a project report submitted by group 7 for the ECE:5995 Spring 2016 course at the University of Iowa. It details the development of a system called LiveLongTM to monitor heart rate and environmental sensors over 3 weeks under the supervision of two professors. The system uses an Arduino, Bluetooth LE, Raspberry Pi, BME280 sensor and heart rate sensor to collect and analyze biometric and environmental data with the goals of predicting health issues and providing alerts. It discusses the hardware and software components, security considerations, data analytics, limitations and future work.
Computers have played an increasingly important role in medicine over generations. Early uses included accounting and patient billing, while later generations saw uses like experimental patient monitoring and microcomputer applications like inventory and billing. Today, computers are integral to areas like storing patient data, online medical information, 3D imaging like tomography, remote patient care, and have future potential in areas like neural repair and disease prevention. Computers have become essential in healthcare and are expected to continue improving medical care.
One of the major purposes manufacturers incorporate AI or ML in their applications is to ease software computations and to predict precise results. I think compared to any other application, a medical application requires a lot of precise computations and therefore, AI is a perfect solution to enhance performance and productivity. While reading the health-tech news, I came across recent research in this regard, the use of AI in predicting a potential stroke or cardiac arrest. ..
In the last decade the healthcare monitoring systems have drawn considerable attentions of the researchers. The prime goal was to develop a reliable patient monitoring system so that the healthcare professionals can monitor their patients, who are either hospitalized or executing their normal daily life activities. In this work we present a mobile device based wireless healthcare monitoring system that can provide real time online information about physiological conditions of a patient. Our proposed system is designed to measure and monitor important physiological data of a patient in order to accurately describe the status of her/his health and fitness. In addition the proposed system is able to send alarming message about the patient’s critical health data by text messages or by email reports. By using the information contained in the text or e-mail message the healthcare professional can provide necessary medical
advising. The system mainly consists of sensors, the data acquisition unit, microcontroller (i.e., Arduino), and software (i.e., LabVIEW). The patient’s temperature, heart beat rate, muscles, blood pressure, blood glucose level, and ECG data are monitored, displayed, and stored by our system. To ensure reliability and accuracy the proposed system has been field tested. The test results show that our system is able to measure the patient’s physiological data with a very high accuracy.
Smart Health Prediction Using Data Mining.Data mining is a new powerful technology which is of high interest in computer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of Artificial Intelligence, machine learning and database management to extract new patterns from large data sets and the knowledge associated with these patterns. The actual task is to extract data by automatic or semi-automatic means. The different parameters included in data mining includes clustering, forecasting, path analysis and predictive analysis.
Intelligent Emergency Patient Support System || Diu app contest project descr...A. Z. M. JALAL UDDIN JOY
DIU APP CONTEST-2017
Team Name: SWE HEALTH CARE
Category: Health
Project: Intelligent Emergency Patient Support System.
Team Members
(01) Moniruz Zaman Shojol
(02) Abu Zahid Md Jalal Uddin Joy
(03)Md Asrafuzzaman
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
Real time health monitoring using gprs technologyRahul Sharma
Advances in sensor technology, personal mobile devices, and wireless broadband communications are enabling the development of an integrated personal mobile health monitoring system that can provide patients with a useful tool to assess their own health and manage their personal health information anytime and anywhere. Personal mobile devices, such as PDAs and mobile phones, are becoming more powerful integrated information management tools and play a major role in many people's lives. Here I focus on designing a Mobile health-monitoring system for people who stay alone at home or suffering from Heart Disease. This system presents a complete unified and mobile platform based connectivity solution for unobtrusive health monitoring. Developing a hardware which will sense heart rate and temperature of a patient, using Bluetooth modem all information lively transmitted to smart phone, from smart phone all information transmitted to server using GPRS. At server the received data compared with the standard threshold minimum and maximum value. The normal range of heart rate is 60 to 135 and the temperature of the patient is said to be normal above 95^F and below 104^F. If at all the rate increases above 145 or decreases below 55,it may be fatal and if it crossed this threshold limit then SMS will be sent to the relative of patient and Doctors along with measured values. The build-in GPS further provides the position information of the monitored person. The remote server not only collects physiological measurements but also tracks the position of the monitored person in real time. For transmitting data from Smartphone to the server using GPRS, here we need to create a website on data will be continuously transmitted from Smartphone to the website and from website data will be downloaded continuously on the server.
IRJET - Cloud based Enhanced Cardiac Disease Prediction using Naïve Bayesian ...IRJET Journal
This document describes a proposed cloud-based system for enhancing cardiac disease prediction using the Naive Bayesian algorithm. The system would collect patients' medical data and store it securely in the cloud after encryption. It would analyze the data using Naive Bayesian classification to predict diseases and generate reports. The reports would be accessible to clinicians and patients through the cloud using private keys for authentication and authorization. The goal is to build an accurate and private disease prediction and monitoring system to help detect cardiac issues early and improve patient care.
This document discusses the various uses of computers in healthcare. It describes how computers are used for hospital information systems, diagnostic testing, education, and research. Computers are utilized for applications like electronic medical records, scheduling, monitoring patients, and performing diagnostic tests. The document also outlines the history of computers and how computer technology has significantly improved healthcare and enhanced the quality of patient care.
This document reviews a wireless biomedical parameter monitoring system using an ARM microcontroller. The proposed system continuously monitors key patient vital signs like temperature, heartbeat, ECG, blood sugar, and oxygen levels using biosensors. The data is transmitted wirelessly to an ARM server using a Zigbee network. If any measurements exceed thresholds, an alarm is triggered and a message is sent to the doctor's phone via GSM. The system aims to allow for remote monitoring of patients after discharge to alert doctors to emergencies in real-time.
A gsm based intelligent wireless mobile patient monitoring systemeSAT Journals
Abstract Monitoring one’s heart rate and body temperature continuously from a remote area is impossible for a medical expert by using typical monitoring devices. To overcome this problem we can implement a GSM based system using microcontroller and LM35 sensor which is low-cost and use-friendly. Here, a heart beat sensor is used to detect the heart rate and an LM35 sensor to sense the body temperature. These signals are processed by a PIC microcontroller. Then, an SMS alert will be sent to the medical expert by using a GSM module. Thus, doctors can monitor the health condition of a patient continuously from a remote place and can suggest the patient about taking an immediate remedy. As a result, we can save many lives by providing them a quick service using this system. Keywords: Telemedicine, Remote monitoring system, Heart Beat Rate, Body Temperature, Photoplethysmograph, LM35, Microcontroller, GSM Modem etc…
IRJET - Prediction and Analysis of Multiple Diseases using Machine Learni...IRJET Journal
This document discusses using machine learning techniques to predict and analyze multiple diseases. It presents research using KNN, support vector machine, random forest, and decision tree algorithms applied to a medical database to predict future and previous diseases. The goal is to provide a smart card method for easily and accurately diagnosing disease by storing an individual's full medical record. It reviews related work applying various machine learning classifiers like decision trees, naive Bayes, and logistic regression to diseases such as heart disease, diabetes, and cancer. The conclusion is that machine learning applied to medical data can help predict disease and save time for patients and doctors.
IRJET- Heart Rate Monitoring System using Finger Tip through IOTIRJET Journal
This document describes a heart rate monitoring system that measures heart rate through the fingertip using a pulse sensor and displays the results on an LCD screen and online using WiFi. The system works by using a photoplethysmography sensor to detect changes in blood volume in the fingertip with each heartbeat. The heartbeat signal is amplified and sent to an Arduino board, which processes the data and displays the heart rate in beats per minute on the LCD. The WiFi module then transmits the data to a local server webpage and online server to view the results remotely over a network. The system provides a low-cost way to continuously monitor heart rate for healthcare applications.
Centralized patient monitoring with real time dengue outbreak detection systemSonu Kumar
This document proposes a centralized patient monitoring system with real-time dengue outbreak detection. It describes a solution that uses IoT devices connected to patients to continuously monitor vitals and send data to an Azure IoT Hub for analysis. If vitals go outside normal ranges, alerts are sent to doctors' phones. A similar system could detect dengue outbreaks by monitoring patients' locations, temperatures, and other symptoms reported by IoT medical devices on a blockchain network. This would allow timely public health interventions for dengue, which can be fatal if not treated early.
SAP Leonardo or IOT (internet of things) much focused on the manufacturing but have its scope everywhere from daily household utilities to elite defense warfare to hospitals in health care.
The document describes several healthcare IT systems implemented in Tamil Nadu, India:
1. A disease surveillance system for HIV/AIDS that automates data gathering, reporting, and provides mapping and analytics at the village level.
2. An electronic medical record system for ART patients with biometric identification and access to records across centers.
3. A patient management system using digital pen technology for physicians to record exam notes and prescriptions.
4. Remote patient monitoring services for ICU, radiology and cardiology using devices like ECG monitors and mobile transmission of data.
5. An ambulatory patient monitoring system called SmartChair that measures vital signs and transmits data via SMS or to a central
This document discusses the design of a personalized 3A health monitoring system using sensor networks. It begins with an overview of current challenges in healthcare like an aging population and increasing costs. It then describes the proposed system which would use sensors, edge computing, blockchain and other technologies to provide continuous remote health monitoring anywhere and anytime. Key aspects of the system include a heart rate monitoring solution, data exchange centers, smart health homes and eHealth labs. The system aims to address issues like data ownership and security while providing personalized care. It concludes by discussing next steps to test and implement the continuous monitoring system.
Computers are used in many areas of medicine like medical education, storing health records, diagnostics, scientific work, and therapy. They can store large amounts of patient information, assist with online appointments, help analyze medical scans, guide surgeries, and process large data sets for research. Computers also aid in knowledge sharing between medical professionals.
The essence of cardiac monitoring devicesKaty Slemon
Blog explains the need and importance of heart rate monitoring, methods to accomplish, benefits & why accurate cardiac monitoring devices are the need of hour.
IRJET- Medical Database Mining for Heart Disease Precautions and Early Ca...IRJET Journal
The document discusses using machine learning algorithms like Naive Bayes and Decision Trees to predict heart disease risk from medical data. It proposes extracting parameters like age, blood pressure, and cholesterol from patient medical records to train models. The models would then generate risk predictions for new patients, represented as values from -1 (high risk) to 1 (low risk). Experimental results on test data sets show the Naive Bayes algorithm has faster execution times than Decision Trees, with both improving accuracy as more training data is added. The goal is to help identify patients at risk of heart disease early to improve medical outcomes.
This document is a project report submitted by group 7 for the ECE:5995 Spring 2016 course at the University of Iowa. It details the development of a system called LiveLongTM to monitor heart rate and environmental sensors over 3 weeks under the supervision of two professors. The system uses an Arduino, Bluetooth LE, Raspberry Pi, BME280 sensor and heart rate sensor to collect and analyze biometric and environmental data with the goals of predicting health issues and providing alerts. It discusses the hardware and software components, security considerations, data analytics, limitations and future work.
Computers have played an increasingly important role in medicine over generations. Early uses included accounting and patient billing, while later generations saw uses like experimental patient monitoring and microcomputer applications like inventory and billing. Today, computers are integral to areas like storing patient data, online medical information, 3D imaging like tomography, remote patient care, and have future potential in areas like neural repair and disease prevention. Computers have become essential in healthcare and are expected to continue improving medical care.
One of the major purposes manufacturers incorporate AI or ML in their applications is to ease software computations and to predict precise results. I think compared to any other application, a medical application requires a lot of precise computations and therefore, AI is a perfect solution to enhance performance and productivity. While reading the health-tech news, I came across recent research in this regard, the use of AI in predicting a potential stroke or cardiac arrest. ..
In the last decade the healthcare monitoring systems have drawn considerable attentions of the researchers. The prime goal was to develop a reliable patient monitoring system so that the healthcare professionals can monitor their patients, who are either hospitalized or executing their normal daily life activities. In this work we present a mobile device based wireless healthcare monitoring system that can provide real time online information about physiological conditions of a patient. Our proposed system is designed to measure and monitor important physiological data of a patient in order to accurately describe the status of her/his health and fitness. In addition the proposed system is able to send alarming message about the patient’s critical health data by text messages or by email reports. By using the information contained in the text or e-mail message the healthcare professional can provide necessary medical
advising. The system mainly consists of sensors, the data acquisition unit, microcontroller (i.e., Arduino), and software (i.e., LabVIEW). The patient’s temperature, heart beat rate, muscles, blood pressure, blood glucose level, and ECG data are monitored, displayed, and stored by our system. To ensure reliability and accuracy the proposed system has been field tested. The test results show that our system is able to measure the patient’s physiological data with a very high accuracy.
Smart Health Prediction Using Data Mining.Data mining is a new powerful technology which is of high interest in computer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of Artificial Intelligence, machine learning and database management to extract new patterns from large data sets and the knowledge associated with these patterns. The actual task is to extract data by automatic or semi-automatic means. The different parameters included in data mining includes clustering, forecasting, path analysis and predictive analysis.
Intelligent Emergency Patient Support System || Diu app contest project descr...A. Z. M. JALAL UDDIN JOY
DIU APP CONTEST-2017
Team Name: SWE HEALTH CARE
Category: Health
Project: Intelligent Emergency Patient Support System.
Team Members
(01) Moniruz Zaman Shojol
(02) Abu Zahid Md Jalal Uddin Joy
(03)Md Asrafuzzaman
The heart is a vital organ that serves to pump blood to the whole body. A heart rate can be used as a healthy body parameter conditions. Growing evidence suggests that IT-based health records play essential role to drive medical revolution especially on data storage and processing. The heart rate measurement (HRM) process usually involves wearable sensor devices to record patient’s data. This data is recorded to help the doctors to analyze and provide a better diagnose in order to determine the best treatment for the patients. Connecting the sensor system through a wireless network to a cloud server will enable the doctor to monitor remotely. This paper presents fit-NES wearable bracelet, an alternative method for integrating a HR measurement device using optical based pulse sensor and Bluetooth-based communication module. This paper is also present the benchmarking of proposed system with several various commercial HR measurement devices.
Real time health monitoring using gprs technologyRahul Sharma
Advances in sensor technology, personal mobile devices, and wireless broadband communications are enabling the development of an integrated personal mobile health monitoring system that can provide patients with a useful tool to assess their own health and manage their personal health information anytime and anywhere. Personal mobile devices, such as PDAs and mobile phones, are becoming more powerful integrated information management tools and play a major role in many people's lives. Here I focus on designing a Mobile health-monitoring system for people who stay alone at home or suffering from Heart Disease. This system presents a complete unified and mobile platform based connectivity solution for unobtrusive health monitoring. Developing a hardware which will sense heart rate and temperature of a patient, using Bluetooth modem all information lively transmitted to smart phone, from smart phone all information transmitted to server using GPRS. At server the received data compared with the standard threshold minimum and maximum value. The normal range of heart rate is 60 to 135 and the temperature of the patient is said to be normal above 95^F and below 104^F. If at all the rate increases above 145 or decreases below 55,it may be fatal and if it crossed this threshold limit then SMS will be sent to the relative of patient and Doctors along with measured values. The build-in GPS further provides the position information of the monitored person. The remote server not only collects physiological measurements but also tracks the position of the monitored person in real time. For transmitting data from Smartphone to the server using GPRS, here we need to create a website on data will be continuously transmitted from Smartphone to the website and from website data will be downloaded continuously on the server.
IRJET - Cloud based Enhanced Cardiac Disease Prediction using Naïve Bayesian ...IRJET Journal
This document describes a proposed cloud-based system for enhancing cardiac disease prediction using the Naive Bayesian algorithm. The system would collect patients' medical data and store it securely in the cloud after encryption. It would analyze the data using Naive Bayesian classification to predict diseases and generate reports. The reports would be accessible to clinicians and patients through the cloud using private keys for authentication and authorization. The goal is to build an accurate and private disease prediction and monitoring system to help detect cardiac issues early and improve patient care.
This document discusses the various uses of computers in healthcare. It describes how computers are used for hospital information systems, diagnostic testing, education, and research. Computers are utilized for applications like electronic medical records, scheduling, monitoring patients, and performing diagnostic tests. The document also outlines the history of computers and how computer technology has significantly improved healthcare and enhanced the quality of patient care.
This document reviews a wireless biomedical parameter monitoring system using an ARM microcontroller. The proposed system continuously monitors key patient vital signs like temperature, heartbeat, ECG, blood sugar, and oxygen levels using biosensors. The data is transmitted wirelessly to an ARM server using a Zigbee network. If any measurements exceed thresholds, an alarm is triggered and a message is sent to the doctor's phone via GSM. The system aims to allow for remote monitoring of patients after discharge to alert doctors to emergencies in real-time.
A gsm based intelligent wireless mobile patient monitoring systemeSAT Journals
Abstract Monitoring one’s heart rate and body temperature continuously from a remote area is impossible for a medical expert by using typical monitoring devices. To overcome this problem we can implement a GSM based system using microcontroller and LM35 sensor which is low-cost and use-friendly. Here, a heart beat sensor is used to detect the heart rate and an LM35 sensor to sense the body temperature. These signals are processed by a PIC microcontroller. Then, an SMS alert will be sent to the medical expert by using a GSM module. Thus, doctors can monitor the health condition of a patient continuously from a remote place and can suggest the patient about taking an immediate remedy. As a result, we can save many lives by providing them a quick service using this system. Keywords: Telemedicine, Remote monitoring system, Heart Beat Rate, Body Temperature, Photoplethysmograph, LM35, Microcontroller, GSM Modem etc…
IoT and machine learning (ML) are becoming increasingly efficient in the medical and telemedicine areas all around the world. This article describes a system that employs latest technology to give a more accurate method of forecasting disease. This technology uses sensors to collect data from the body of the patient. The obtained sensor information is collected with NodeMcU before being transferred to the Cloud Platform "ThinkSpeak" through an ESP8266 Wi-Fi module. ThinkSpeak is a cloud server that provides real-time data streams in the cloud. For the best results, data currently saved in the cloud is evaluated by one of the machine learning algorithms, the KNN algorithm. Based on the findings of the analysis and compared with the data sets, the disease is predicted and a prescription for the relevant disease is issued.
A gsm enabled real time simulated heart rate monitoring & control systemeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document proposes a remote health monitoring system using wearable body sensors to monitor cardiovascular patients. The system has three tiers: 1) Wearable sensors like a Holter monitor collect physiological data. 2) A personal server stores and analyzes the data using an intelligent assistant and notifies medical staff of emergencies. 3) A medical server connected to the cloud allows doctors and family to access the data from anywhere. The system prioritizes critical data like ECG to ensure emergency situations are addressed promptly while compressing other data to efficiently use storage. This new technology could help reduce mortality by enabling real-time monitoring of patients' cardiovascular health.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Wearable System for Vital Signs MeasurementIRJET Journal
This document describes a wearable device that can monitor vital signs such as temperature and heartbeat. The device is designed to be worn like a shirt and contains sensors to measure temperature and heartbeat. It also contains a GPS and GSM module. If the temperature or heartbeat readings go above or below normal ranges, the device will send an SMS alert with the person's location to concerned contacts. The goal is to remotely monitor patients and elderly people's health and send alerts if issues arise. The system was tested and found to reliably measure vital signs and send location alerts by SMS.
This document summarizes a remote health monitoring system using wearable body sensors to monitor cardiovascular disease patients. The system consists of three parts: 1) Wearable body sensors that collect physiological data from patients, 2) A personal server (PDA) that prioritizes and transfers data to 3) A medical server connected to the cloud where data can be accessed by medical staff. The system aims to efficiently respond to emergencies by prioritizing vital sign data and notifying medical staff of changes in a patient's heart health.
IoT Based Intelligent Medicine Box with AssistanceIRJET Journal
This document describes an intelligent medicine box that stores medicines and alerts patients to take their medicines on time. It measures various health parameters like pulse rate, blood pressure, temperature, and ECG and sends this data to the cloud for doctors to monitor. The system has two units - a GSM timer unit that sends medicine reminders to patients, and a sensor unit that measures health parameters and uploads the data to the cloud using Firebase IoT so doctors can monitor patients' health online. The system is designed to improve medication adherence and allow remote patient monitoring.
IOT Based Patient Health Monitoring System Using WIFIijtsrd
Health is given the extreme importance now a days by each country with the advent of the novel corona virus. So in this aspect, an IOT based patient health monitoring system is the best solution for such an epidemic. With an improvement in technology and miniaturization of sensors, there have been attempts to utilize the new technology in various areas to improve the quality of human life. As a result, this project is an attempt to solve a health care problem currently society is facing covid 19.The main objective of the project was to design for to reduce the corona virus, reduce the components and man power. The framework can be utilized to constantly screen the wellbeing parameters of a patient. The body temperature, heart rate and spo2 can be measured from anyplace on the globe utilizing IOT Internet of Things . IOT monitoring of health helps in preventing the spread of disease as well as to get a proper diagnosis of the state of health, even if the doctor is at far distance. We proposed a nonstop checking and control instrument to screen the patient condition and store the patient information’s in server utilizing Wi Fi Module based remote correspondence. Hence the proposed architecture collects the sensor data through ESP32 microcontroller and relays it to the WIFI where it is processed and analyzed for remote viewing. Feedback actions based on the analyzed data can be sent back to the doctor or guardian through Google sheet and or SMS alerts in case of any emergencies. Marupuri Usha Priya | Muthu Pandi K | Priya S | Dr. Kishore Kumar Arjunsingh "IOT Based Patient Health Monitoring System Using WIFI" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45143.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/45143/iot-based-patient-health-monitoring-system-using-wifi/marupuri-usha-priya
This document describes a proposed health monitoring companion device that would measure various health parameters for users through sensors. It would use an Arduino Uno microcontroller connected to an e-health sensor shield with four sensors: ECG to measure heart rate, temperature to measure body temperature, GSR to measure skin conductance, and SpO2 to measure blood oxygen levels. Readings would be displayed on a graphical LCD and sent to an Android application. The goal is to help users monitor their health at home without needing to visit medical facilities by making the device simple to use and understand.
IRJET- Health Monitoring System using ArduinoIRJET Journal
This document describes a health monitoring system using Arduino that monitors patients' pulse rate, vital signs, and saline level. Sensors are used to collect this medical data, which is then sent to the cloud for storage and access by doctors. The system is meant to continuously monitor patients and alert doctors if any parameters exceed thresholds, to save lives in emergencies or when doctors are not present. It discusses how technologies like the Internet of Things and wireless sensors can help create remote health monitoring systems.
An Integrated Approach of Blood Pressure and Heart Rate Measurement SystemsIRJET Journal
This document describes a new integrated device that can measure both blood pressure and heart rate through the wrist and fingertip using a single device. The device uses infrared sensors placed on the wrist and fingertip to detect blood flow and pulses. It counts the pulses to determine the heart rate and blood pressure. The measurements from this new device were compared to manual measurements on 100 subjects, and it was found to have a negligible error rate. The goal was to create an affordable, easy-to-use device that could help both literate and illiterate people regularly monitor their vital signs without visiting a doctor.
Proposed Model for Chest Disease Prediction using Data Analyticsvivatechijri
Chest diseases if not properly diagnosed in early stages can be fatal. Because of lack of skilled
knowledge or experiences of real life practitioners, many a times one chest disease is wrongly diagnosed for the
other, which leads to wrong treatment. Due to this the actual disease keeps on growing and become fatal. For
example, muscular chest pains can be treated for the heart disease or COPD is treated for Asthma. Early
prediction of chest disease is crucial but is not an easy task. Consequently, the computer based prediction system
for chest disease may play a significant role as a pre-stage detection to take proper actions with a view to recover
from it. However the choice of the proper Data Mining classification method can effectively predict the early
stage of the disease for being cured from it. In this paper, the three mostly used classification techniques such as
support vector machine (SVM), k-nearest neighbour (KNN) and artificial neural network (ANN) have been studied
with a view to evaluating them for chest disease prediction.
1. The document describes a multiple disease prediction system that uses machine learning to predict three diseases: heart disease, liver disease, and diabetes.
2. It aims to build a single system that can predict multiple diseases, unlike existing systems that typically only predict one disease. This would allow users to predict different diseases without needing multiple different tools.
3. The system is designed to take user inputs related to symptoms and features of the selected disease and use machine learning algorithms like KNN, random forest and XGBoost trained on disease datasets to predict the likelihood of the disease. The models would be integrated into a web interface using Django for users to get predictions.
Deep Spectral Time‑Variant Feature Analytic Model for Cardiac Disease Predict...BASMAJUMAASALEHALMOH
The document proposes a Deep Spectral Time-Variant Feature Analytic Model (DSTV-FAM) using SoftMax Recurrent Neural Network (SMRNN) in a wireless sensor network to improve cardiac disease prediction accuracy. The model initially collects data from IoT sensors, preprocesses it, estimates a Cardiac Immunity Influence Rate, and trains marginalized spectral features into classifiers. A Soft-Max Activation Function then creates a logical function based on cardiac affection rates. Trained neurons are constructed into a Recurrent Neural Network with feed-forward feature values to classify disease affection rates. The proposed structure aims to yield high prediction accuracy, classification accuracy, and recall to enable early treatment and cardiac risk prediction.
Smart Phone for Personal Health Care Monitoring Systemijcisjournal
Health is of great concern for everyone. Both investment and efforts on health monitoring, care and maintenance are ever increasing. Smart phones are affordable for every one nowadays. This paper discusses an innovative method ofdesigninga smart phone based health care system which can measure some of the body parameters such as temperature, pulse rate and blood glucose level. The key feature here is to embed the smart phone with required sensors, process their data, store in the memory.Further, these data can be transmitted to a doctor or hospital authority for future references using an application designed in the same smart phone. The system can be used to suggest some precautions and also remedies for the user, if these body parameters are outside the normal range. This makes the smart phone really the smartest.
SMART PHONE FOR PERSONAL HEALTH CARE MONITORING SYSTEMijics
This document proposes and describes a smart phone-based personal health monitoring system. The system embeds sensors in a smart phone to measure body temperature, pulse rate, and blood glucose level. It stores the measurements and allows them to be transmitted to a doctor for reference. If parameters are abnormal, the phone can suggest precautions or remedies. The system aims to allow individuals to conveniently self-monitor vital signs and consult doctors without direct visits, reducing costs and improving access to healthcare.
This document proposes and describes a smart phone-based personal health monitoring system. The system embeds sensors in a smart phone to measure body temperature, pulse rate, and blood glucose level. It stores and analyzes the sensor data, compares it to normal ranges, and can transmit abnormal results to a doctor. The system aims to allow individuals to conveniently self-monitor vital signs and receive medical advice without visiting a hospital. It could help address issues like a lack of continuous health monitoring and physician shortages.
Android Based Patient Health Monitoring SystemIRJET Journal
1) This document describes an Android-based patient health monitoring system that uses wearable sensors and a mobile application.
2) The system includes sensors that measure a patient's temperature, pulse, blood pressure, and humidity. The sensor data is sent via Bluetooth to an Android application on the patient's phone and from there to a server via WiFi.
3) The system allows doctors to monitor a patient's vital signs in real-time from their desktop. It also tracks the patient's location using latitude and longitude. An alert is triggered if the vital signs exceed preset thresholds.
Similar to Gsm and gps based medical emergency model (20)
Hudhud cyclone caused extensive damage in Visakhapatnam, India in October 2014, especially to tree cover. This will likely impact the local environment in several ways: increased air pollution as trees absorb less; higher temperatures without tree canopy; increased erosion and landslides. It also created large amounts of waste from destroyed trees. Proper management of solid waste is needed to prevent disease spread. Suggested measures include restoring damaged plants, building fountains to reduce heat, mandating light-colored buildings, improving waste management, and educating public on health risks. Overall, changes are needed to water, land, and waste practices to rebuild the environment after the cyclone removed green cover.
Impact of flood disaster in a drought prone area – case study of alampur vill...eSAT Publishing House
1) In September-October 2009, unprecedented heavy rainfall and dam releases caused widespread flooding in Alampur village in Mahabub Nagar district, a historically drought-prone area.
2) The flood damaged or destroyed homes, buildings, infrastructure, crops, and documents. It displaced many residents and cut off the village.
3) The socioeconomic conditions and mud-based construction of homes in the village exacerbated the flood's impacts, making damage more severe and recovery more difficult.
The document summarizes the Hudhud cyclone that struck Visakhapatnam, India in October 2014. It describes the cyclone's formation, rapid intensification to winds of 175 km/h, and landfall near Visakhapatnam. The cyclone caused extensive damage estimated at over $1 billion and at least 109 deaths in India and Nepal. Infrastructure like buildings, bridges, and power lines were destroyed. Crops and fishing boats were also damaged. The document then discusses coping strategies and improvements needed to disaster management plans to better prepare for future cyclones.
Groundwater investigation using geophysical methods a case study of pydibhim...eSAT Publishing House
This document summarizes the results of a geophysical investigation using vertical electrical sounding (VES) methods at 13 locations around an industrial area in India. The VES data was interpreted to generate geo-electric sections and pseudo-sections showing subsurface resistivity variations. Three main layers were typically identified - a high resistivity topsoil, a weathered middle layer, and a basement rock. Pseudo-sections revealed relatively more weathered areas in the northwest and southwest. Resistivity sections helped identify zones of possible high groundwater potential based on low resistivity anomalies sandwiched between more resistive layers. The study concluded the electrical resistivity method was useful for understanding subsurface geology and identifying areas prospective for groundwater exploration.
Flood related disasters concerned to urban flooding in bangalore, indiaeSAT Publishing House
1. The document discusses urban flooding in Bangalore, India. It describes how factors like heavy rainfall, population growth, and improper land use have contributed to increased flooding in the city.
2. Flooding events in 2013 are analyzed in detail. A November rainfall caused runoff six times higher than the drainage capacity, inundating low-lying residential areas.
3. Impacts of urban flooding include disrupted daily life, damaged infrastructure, and decreased economic activity in affected areas. The document calls for improved flood management strategies to better mitigate urban flooding risks in Bangalore.
Enhancing post disaster recovery by optimal infrastructure capacity buildingeSAT Publishing House
This document discusses enhancing post-disaster recovery through optimal infrastructure capacity building. It presents a model to minimize the cost of meeting demand using auxiliary capacities when disaster damages infrastructure. The model uses genetic algorithms to select optimal capacity combinations. The document reviews how infrastructure provides vital services supporting recovery activities and discusses classifying infrastructure into six types. When disaster reduces infrastructure services, a gap forms between community demands and available support, hindering recovery. The proposed research aims to identify this gap and optimize capacity selection to fill it cost-effectively.
Effect of lintel and lintel band on the global performance of reinforced conc...eSAT Publishing House
This document analyzes the effect of lintels and lintel bands on the seismic performance of reinforced concrete masonry infilled frames through non-linear static pushover analysis. Four frame models are considered: a frame with a full masonry infill wall; a frame with a central opening but no lintel/band; a frame with a lintel above the opening; and a frame with a lintel band above the opening. The results show that the full infill wall model has 27% higher stiffness and 32% higher strength than the model with just an opening. Models with lintels or lintel bands have slightly higher strength and stiffness than the model with just an opening. The document concludes lintels and lintel
Wind damage to trees in the gitam university campus at visakhapatnam by cyclo...eSAT Publishing House
1) A cyclone with wind speeds of 175-200 kph caused massive damage to the green cover of Gitam University campus in Visakhapatnam, India. Thousands of trees were uprooted or damaged.
2) A study assessed different types of damage to trees from the cyclone, including defoliation, salt spray damage, damage to stems/branches, and uprooting. Certain tree species were more vulnerable than others.
3) The results of the study can help in selecting more wind-resistant tree species for future planting and reducing damage from future storms.
Wind damage to buildings, infrastrucuture and landscape elements along the be...eSAT Publishing House
1) A visual study was conducted to assess wind damage from Cyclone Hudhud along the 27km Visakha-Bheemli Beach road in Visakhapatnam, India.
2) Residential and commercial buildings suffered extensive roof damage, while glass facades on hotels and restaurants were shattered. Infrastructure like electricity poles and bus shelters were destroyed.
3) Landscape elements faced damage, including collapsed trees that damaged pavements, and debris in parks. The cyclone wiped out over half the city's green cover and caused beach erosion around protected areas.
1) The document reviews factors that influence the shear strength of reinforced concrete deep beams, including compressive strength of concrete, percentage of tension reinforcement, vertical and horizontal web reinforcement, aggregate interlock, shear span-to-depth ratio, loading distribution, side cover, and beam depth.
2) It finds that compressive strength of concrete, tension reinforcement percentage, and web reinforcement all increase shear strength, while shear strength decreases as shear span-to-depth ratio increases.
3) The distribution and amount of vertical and horizontal web reinforcement also affects shear strength, but closely spaced stirrups do not necessarily enhance capacity or performance.
Role of voluntary teams of professional engineers in dissater management – ex...eSAT Publishing House
1) A team of 17 professional engineers from various disciplines called the "Griha Seva" team volunteered after the 2001 Gujarat earthquake to provide technical assistance.
2) The team conducted site visits, assessments, testing and recommended retrofitting strategies for damaged structures in Bhuj and Ahmedabad. They were able to fully assess and retrofit 20 buildings in Ahmedabad.
3) Factors observed that exacerbated the earthquake's impacts included unplanned construction, non-engineered buildings, improper prior retrofitting, and defective materials and workmanship. The professional engineers' technical expertise was crucial for effective post-disaster management.
This document discusses risk analysis and environmental hazard management. It begins by defining risk, hazard, and toxicity. It then outlines the steps involved in hazard identification, including HAZID, HAZOP, and HAZAN. The document presents a case study of a hypothetical gas collecting station, identifying potential accidents and hazards. It discusses quantitative and qualitative approaches to risk analysis, including calculating a fire and explosion index. The document concludes by discussing hazard management strategies like preventative measures, control measures, fire protection, relief operations, and the importance of training personnel on safety.
Review study on performance of seismically tested repaired shear wallseSAT Publishing House
This document summarizes research on the performance of reinforced concrete shear walls that have been repaired after damage. It begins with an introduction to shear walls and their failure modes. The literature review then discusses the behavior of original shear walls as well as different repair techniques tested by other researchers, including conventional repair with new concrete, jacketing with steel plates or concrete, and use of fiber reinforced polymers. The document focuses on evaluating the strength retention of shear walls after being repaired with various methods.
Monitoring and assessment of air quality with reference to dust particles (pm...eSAT Publishing House
This document summarizes a study on monitoring and assessing air quality with respect to dust particles (PM10 and PM2.5) in the urban environment of Visakhapatnam, India. Sampling was conducted in residential, commercial, and industrial areas from October 2013 to August 2014. The average PM2.5 and PM10 concentrations were within limits in residential areas but moderate to high in commercial and industrial areas. Exceedance factor levels indicated moderate pollution for residential areas and moderate to high pollution for commercial and industrial areas. There is a need for management measures like improved public transport and green spaces to combat particulate air pollution in the study areas.
Low cost wireless sensor networks and smartphone applications for disaster ma...eSAT Publishing House
This document describes a low-cost wireless sensor network and smartphone application system for disaster management. The system uses an Arduino-based wireless sensor network comprising nodes with various sensors to monitor the environment. The sensor data is transmitted to a central gateway and then to the cloud for analysis. A smartphone app connected to the cloud can detect disasters from the sensor data and send real-time alerts to users to help with early evacuation. The system aims to provide low-cost localized disaster detection and warnings to improve safety.
Coastal zones – seismic vulnerability an analysis from east coast of indiaeSAT Publishing House
This document summarizes an analysis of seismic vulnerability along the east coast of India. It discusses the geotectonic setting of the region as a passive continental margin and reports some moderate seismic activity from offshore in recent decades. While seismic stability cannot be assumed given events like the 2004 tsunami, no major earthquakes have been recorded along this coast historically. The document calls for further study of active faults, neotectonics, and implementation of improved seismic building codes to mitigate vulnerability.
Can fracture mechanics predict damage due disaster of structureseSAT Publishing House
This document discusses how fracture mechanics can be used to better predict damage and failure of structures. It notes that current design codes are based on small-scale laboratory tests and do not account for size effects, which can lead to more brittle failures in larger structures. The document outlines how fracture mechanics considers factors like size effect, ductility, and minimum reinforcement that influence the strength and failure behavior of structures. It provides examples of how fracture mechanics has been applied to problems like evaluating shear strength in deep beams and investigating a failure of an oil platform structure. The document argues that fracture mechanics provides a more scientific basis for structural design compared to existing empirical code provisions.
This document discusses the assessment of seismic susceptibility of reinforced concrete (RC) buildings. It begins with an introduction to earthquakes and the importance of vulnerability assessment in mitigating earthquake risks and losses. It then describes modeling the nonlinear behavior of RC building elements and performing pushover analysis to evaluate building performance. The document outlines modeling RC frames and developing moment-curvature relationships. It also summarizes the results of pushover analyses on sample 2D and 3D RC frames with and without shear walls. The conclusions emphasize that pushover analysis effectively assesses building properties but has limitations, and that capacity spectrum method provides appropriate results for evaluating building response and retrofitting impact.
A geophysical insight of earthquake occurred on 21 st may 2014 off paradip, b...eSAT Publishing House
1) A 6.0 magnitude earthquake occurred off the coast of Paradip, Odisha in the Bay of Bengal on May 21, 2014 at a depth of around 40 km.
2) Analysis of magnetic and bathymetric data from the area revealed the presence of major lineaments in NW-SE and NE-SW directions that may be responsible for seismic activity through stress release.
3) Movements along growth faults at the margins of large Bengal channels, due to large sediment loads, could also contribute to seismic events by triggering movements along the faults.
Effect of hudhud cyclone on the development of visakhapatnam as smart and gre...eSAT Publishing House
This document discusses the effects of Cyclone Hudhud on the development of Visakhapatnam as a smart and green city through a case study and preliminary surveys. The surveys found that 31% of participants had experienced cyclones, 9% floods, and 59% landslides previously in Visakhapatnam. Awareness of disaster alarming systems increased from 14% before the 2004 tsunami to 85% during Cyclone Hudhud, while awareness of disaster management systems increased from 50% before the tsunami to 94% during Hudhud. The surveys indicate that initiatives after the tsunami improved awareness and preparedness. Developing Visakhapatnam as a smart, green city should consider governance
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.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
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.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Embedded machine learning-based road conditions and driving behavior monitoring
Gsm and gps based medical emergency model
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Special Issue: 03 | May-2014 | NCRIET-2014, Available @ http://www.ijret.org 42
GSM AND GPS BASED MEDICAL EMERGENCY MODEL Ramachandra Turkani1, Bharat Sukumar Biraj2 1Assistant Professor, KLE College of Engineering & Technology, Chikodi, Karnataka, India 2Student, ISE Department KLE College of Engineering & Technology, Chikodi, Karnataka, India Abstract The medical emergency service is one of the most important needs of the human being in case any type of the diseases or the attacks. The recent numbers shows that there is a need in the service when we look at the rate of heart attacks. A first aid treatment could be given if it could be known as soon as possible after the attack. About 25% of deaths occur in the age between 25-69 because of heart attacks And hence here we propose an idea to get the treatment or the emergency service for the heart attacks by sensing and sending the required information to the doctor and the listed people using GSM and with the location using GPS modems. Keywords: GSM, GPS, Heart attack.
---------------------------------------------------------------------***--------------------------------------------------------------------- 1. INTRODUCTION There are among 48% of people in Mumbai are at risk of heart attack (27 sep. 2013 11:04 IST). About 25% of deaths in the age of group 25-69 years occur because of heart attack. In urban areas, 32.8% deaths occur because of heart ailments, while this percentage in rural area is 22.9% [Times of India]. In order to make this cause to be under control we must learn how to detect the heart attack on time & to get information about the person is going to have this kind of attack. In order to detect the heart attack is not enough in the emergency cases. We have to inform the doctor about particular patient. It is very common thing that people will not take the precautions after doctor’s prescriptions or warning also. In the much busy schedule of the common person, the patient is going to make his/her self busy in work. So it is the area that we have to inform the doctor and the relatives or the care takers of the patient that where the patient currently is and is there any emergency treatment needed. In this paper we propose an efficient and effective system that to detect attack and the patient location, so this model is very useful for the people suffering with heart stroke. The proposed solution is based on mobile-cloud computing that does not require any modifications in signal infrastructure, while providing guidance in real time and being highly available. The paper explains about the introduction first and the related work which have carried out and proceeds with the proposed model and concludes with the conclusions and future work. 2. HEART FAILURE
Coronary artery disease (CAD) is the most common type and is the leading cause of heart attack. When you have CAD, your arteries become hard and narrow. Blood has a hard time getting to the heart, so the heart does not get all the blood it needs. CAD can lead to:
Angina is discomfort that happens when the heart does not get enough blood. It may feel like a pressing or squeezing pain, often in the chest, but sometimes the pain is in the shoulders, arms, neck, jaw, or back. It can also feel like upset stomach. Angina is not a heart attack, but having angina means you are more likely to have a heart attack.
Heart attack. A heart attack occurs when an artery is severely or completely blocked, and the heart does not get the blood it needs for more than 20 minutes.
A heart attack occurs when blood flow to a part of your heart is blocked for a long enough time that part of the heart muscle is damaged or dies. This means that other organs, which normally get blood from the heart, do not get enough blood. It does not mean that the heart stops. The medical term for this is myocardial infarction. A hard substance called plaque can build up in the walls of your coronary arteries. This plaque is made up of cholesterol and other cells. A troponin blood test can show if you have heart tissue damage. This test can confirm that you are having a heart attack. Signs of heart failure include:
Feeling like you can't get enough air
Swollen ankles and swollen feet
Fatigue
Stress-and anxiety
Cough
Fainting
Dizziness
Sweating
Breathing- difficulty
Your blood pressure may be normal, high, or low.
Nausea
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Special Issue: 03 | May-2014 | NCRIET-2014, Available @ http://www.ijret.org 43
3. RELATED WORK The problem with detecting emergency status of the patient has been studied by many researchers working in the medical emergency technologies for the people or patients. Among some proposals, to solve this problem [1] is studied the currently used medical emergency and healthcare system in Malaysia. It also gives the drawback of sharing information between the hospitals. [2] Used the concept of system that provides an medical and healthcare information services to users via interactive search for personalized patient needs. [3]It produces an new method to optimize the distribution of first- aid resources. To rise the response speed in emergence medical services (EMS) extremely critical for the pre-hospital life saving. [4] Medical sensor networks allow for pervasive health monitoring in hospitals, at home, or on the way. Each user carries a set of wireless medical sensors that allows to monitor his health state.[5] Real-time information presents a persistent challenge to the emergency response community. In emergency situations, particularly with unconscious, incoherent and unaccompanied patients, providing emergency physicians with a patientpsilas accurate medical history could be the difference between life and death. [6] Delivering first aid before transferring the patient to the hospital is among keys to survival. Emergency message concept is used in our proposed system which is going to deliver the condition of the patient in emergency. Once we got the message from the patient, we can track his/her location very easily by using the GPS and GSM. [7] Describes an heart-attack self-test application for a mobile phones. Those based on mobile information processing. The major problem with these proposals is that they are not able to detect the location of the patient and also they are not based on real time information processing. Their approach is on processing the information got from the patient in emergency cases. The application is going to work on some above dictated papers only when the user of that system is going to initiate that application. So we have to think of some different way to find the solution for the emergency situations for the persons. There was not any such application in which we that can be used at real time. A graph of heart attacks in India is rising and which needs a look in serious views. According to medical researchers there will be 25% of Indians going to suffer with heart attack in near of 2020. So we thought that, this problem is going to be very large perspective in near future and we proposed this system. And the references say that these support an existing mobile information processing techniques. 4. PROPOSED SYSTEM
A system which is going to use an wearable sensors to detect heart attack [7].The sensors are mounted on the patient which will sense the parameters like blood pressure, sugar level, body temperature etc. The two main components are the mobile device with integrated GPS receiver and the compass, which could be any smart phone device in the market and the cloud server, which is basically the web service platform that can be employed to support a variety of context-awareness functionalities. The mobile device is responsible for local navigation, as well as interacting with the user to detect a heart attack based on some parameters. There are some parameters used to detect the heart attack of a person. Those are heart rate, blood pressure, body temperature etc. The wearable sensors are used to detect the changes in the parameters in the body of the person. These sensors will transfer the information to the mobile device where this information is processed and going to generate a message in emergency cases. In emergency cases the system is going to process the information that has got form sensors then mobile device is going to process this information and generate a message to send to doctor and the relatives. Through the GPS receiver the location of the person is also going to get to the doctors only with that SMS. It is also possibility that the person is not going to have any problem with the parameters detected by the sensor but he/she can have a chest pain in very high manner. So it is possible that this type is also going to cause a heart attack. To handle this type of conditions we introduced a user interface in the system. This interface may be one button which can be hold by the patient when they have the chest pain. Holding of this button for few seconds is going to generate an emergency message and processed above. The message can be conveyed to the doctors and the relatives of that person having severe heart attack. SMS sent over the wireless area network from mobile station to destination mobile station which is multicast in nature. That is the SMS should be sent to doctor and relatives of the patient immediately. Multiple copies of SMS should be sent over the network, which is taken care by Emergency Response System shown in fig(1). Fig 1: Emergency model.
3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Special Issue: 03 | May-2014 | NCRIET-2014, Available @ http://www.ijret.org 44
The values for parameters used to detect heart attack are
collected in the mobile device which is near to the wearable
sensors. This device is used to process gathered data from the
sensors. The data fetched from the sensors should be accurate
and fast real time data generation. After the processing of the
data if the result is going to orient an severe situation then the
message should be conveyed to doctors and the relative
peoples of that person. So that they can provide the service to
patient at emergency time and can minimize the severity of the
heart attack.
Mobile device is going to send the position data. This data can
be used to track the person or patients vary easily. The position
data can be get in two ways: first by taking cell identification
number of the mobile network and second by using GPS
system to track global position of the device. The second
approach is going to use a GPS satellites orbiting around the
earth, which transmits signals that can be detected by anyone
with GPS receiver. Using receiver, it is possible to detect the
location of receiver.
4.1 Working of System Components
4.1.1 Sensors
The sensors should produce the data as fast as possible because
the severity of the patient condition may rise at every second of
time. So data generated by the sensors should be accurate and
produce a real-time result of the attribute values defined for the
parameters.
4.1.2 Mobile Device
This device is used to collect the information or parameters
form the wearable sensors. These parameters values are
processed and result is generated. If the result of parameters
leads to the emergence of the patient condition then this
information is transferred over the cloud. There is also an
alternative situation where a person can have a high chest pain
that time a person can interact with interface given with the
system such as button. By interacting with system interface for
example, by holding button more than 5 seconds, is going to
generate emergency signal.
The mobile device can be used to track the person at the
specific location by using the GPS and GSM. The person can
be at any location the doctors and relatives are going to get the
location information immediately with massages generated
from the mobile device. So doctors and relatives can reach the
patient very easily at there present location.
4.1.3 Wireless Area Network
The wireless area network is mainly used to have the
conversation between the patient’s and the doctor’s devices.
The message generated by mobile device of the patient has to
deliver to the doctors. The main job of wireless network
systems are to pass the information from one source system
point of view to another destination system as early as possible
and without any disturbance.
The network systems are going to have high rate of messages
because a patient may changing his place at time. The wireless
area network has to give highest priority to the emergency
messages generated by the patient device. The system has to
provide the location information, so we can track the patient
vary easily. Therefore cloud has to pass the data form source to
destination with very high speed.
Fig 2: signal transmission of the measurer in different ways
[9].
A mobile phone combined with physiological system
comprises a physiological function signal receivable mobile
phone, a measurer used to touch on the human skin and
transmit detection signals to the mobile phone by wire or
wireless transmission method, as shown in Fig. (2). The mobile
phone can show measured data in its display for reminding a
user of his health conditions [8].
The overall implementation is structured into three functional
layers: sensing, communication and management. fig(3).
Sensing layer implements a mobile monitoring for health data,
signal processing, and data analysis. Communication layer
includes short range wireless connection via Bluetooth, or
different technologies for short range communication, and
worldwide wireless connection via a mobile phone.
Management layer carries out data processing and management
tasks, mostly through internet. Researchers have proposed
several systems based on the above three layers [8].
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Volume: 03 Special Issue: 03 | May-2014 | NCRIET-2014, Available @ http://www.ijret.org 45
Fig 3: system implementation of mobile phone in health care.
Generally, the above inventions mainly comprise four
modules: a user management module, managing user
information: a data analysis module, analysing user’s health
condition based on the user information and health data stored
in the memory and/or received from sensors and generating
analysed result; a data management module, managing the user
health data and the result, and a communicating module
transmitting both.
5. CONCLUSIONS AND FUTURE WORK
The proposed system is giving an idea for medical emergency
by using GPS and GSM. The system is going to use the data
processing at client side so it provides a very high speed results
and real-time operating on the produced information. The
system is going to deliver the location information of the
person so emergency service can reach patient as early as
possible. The work of calculation or knowing the place of
accident in high accuracy is to be done and correct parameters
to be detected by the patient.
REFERENCES
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O, Wehrle K. Pervasive Computing and
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[6] “Emergency SMS”. Shirall-Shahreza M. SICE-ICASE,
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[7] “A self-test to detect a heart attack using a mobile
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[8] “Mobile Phone Based Health Care Technology”. Hao
Wang and Jing Liu Bentham Science Publisher Ltd
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