Smart Healthcare Monitoring System for War-End Soldiers Using CNN

2021 ◽  
pp. 166-199
Author(s):  
Preethi S. ◽  
Prasannadevi V. ◽  
Arunadevi B.
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Military Personnel ◽  
Vital Role ◽  
Monitoring Systems ◽  
Health Issues ◽  
Smart Healthcare ◽  
Emergency Assistance ◽  
Healthcare Monitoring ◽  
Wearable Monitoring Systems

Health monitoring plays a vital role to overcome the health issues of the patients. According to research, approximately 2000 people die due to carelessness of monitoring their health. Wearable monitoring systems record the activities of daily life. A 24-hour wearable monitoring system was developed and changes were identified. This project is designed for helping the soldiers to maintain their health conditions and to identify their health issues at war's end. Different health parameters are monitored using sensors, and the data are transmitted through GSM to the receiver, and the received data are analyzed using convolutional neural networks, which is performed in cloud IoT. If any abnormalities are found during the analyzing process, the message is sent to military personnel and the doctor at the camp so that they could take necessary actions to recover the ill soldier from the war field and provide emergency assistance on time. The location of the soldier is also shared using the input from GPS modem in the smart jacket.

Smart Healthcare Monitoring System for War-End Soldiers Using CNN

2020 ◽  
pp. 97-131 ◽  
Author(s):  
Preethi S. ◽  
Prasannadevi V. ◽  
Arunadevi B.
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Military Personnel ◽  
Vital Role ◽  
Monitoring Systems ◽  
Health Issues ◽  
Smart Healthcare ◽  
Emergency Assistance ◽  
Healthcare Monitoring ◽  
Wearable Monitoring Systems

Health monitoring plays a vital role to overcome the health issues of the patients. According to research, approximately 2000 people die due to carelessness of monitoring their health. Wearable monitoring systems record the activities of daily life. A 24-hour wearable monitoring system was developed and changes were identified. This project is designed for helping the soldiers to maintain their health conditions and to identify their health issues at war's end. Different health parameters are monitored using sensors, and the data are transmitted through GSM to the receiver, and the received data are analyzed using convolutional neural networks, which is performed in cloud IoT. If any abnormalities are found during the analyzing process, the message is sent to military personnel and the doctor at the camp so that they could take necessary actions to recover the ill soldier from the war field and provide emergency assistance on time. The location of the soldier is also shared using the input from GPS modem in the smart jacket.

scholarly journals Internet Of Things (IOT) Based Smart Health Monitoring System

2021 ◽  
Vol 9 (VII) ◽  
pp. 1733-1737
Author(s):  
Sougata Karmakar
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Mobile Application ◽  
Healthcare Professionals ◽  
Wearable Devices ◽  
Vital Role ◽  
Wireless Sensor ◽  
Health Issues ◽  
Health Monitoring System ◽  
Cloud Server

IOT is one of the flourishing fields in coming years and it has a vital role in the health care sector. IOT helps us to connect with people by collecting major parameters of the patients directly through some wearable devices transmitted to smartphones and laptops of the authorized person using the cloud server. We are using devices which gives flexible operations to both for the patients and also for healthcare professionals. IOT is slowly becoming a trend in recent times by improvement in the wireless sensor networks. We are fetching such parameters like body temperature, oxygen saturation percentage, heart rate by using NodeMCU WIFI module and cloud computing. Patients with serious health issues can be quickly identified and can be provide a rapid solution by this health monitoring system. And by using BLYNK mobile application we can have those measurements of the parameters from anywhere in the world.

scholarly journals Analysis on E-Healthcare Monitoring System with Iot and Big Patient Data

2021 ◽  
Vol 10 (5) ◽  
pp. 97-102
Author(s):  
Deepa V. ◽  
Rajeswari, K.
Keyword(s):  
Big Data ◽  
Monitoring System ◽  
Healthcare System ◽  
Health Monitoring ◽  
New Technologies ◽  
Patient Data ◽  
Similar Data ◽  
Time Consumption ◽  
Smart Healthcare ◽  
Healthcare Monitoring

Internet of Things (IoT) technology helped the development of healthcare from face-to-face consulting to the telemedicine. Smart healthcare system in IoT environment monitored the patient basic health signs such as heart rate, body temperature, and hospital room condition in real-time applications. The IoT and big data is an important challenge in many fields including smart healthcare systems due to its significance. Big data is employed to analyse the huge volume of data. Big data are significantly used in healthcare technique to determine the normal and abnormal patient condition. The doctors are easily analysed the patient condition in a short time. This system is very easy to design and use. It is employed to enhance the present healthcare system which preserves the lot of lives from death. Healthcare monitoring system in hospitals has experienced large development and portable healthcare monitoring systems with new technologies. Connected healthcare is an essential solution for hospital to record and analyse the patient data and to save money. The clustering and classification methods are used in existing methods. The clustering method is employed to group the similar data. The classification method is utilized to classify the patient data. A lot of healthcare technique was introduced by many researchers ranging from diagnosis to treatment and prevention on efficient e-health monitoring system. But, the accuracy level was not improved and time consumption was not reduced by existing techniques. In order to address these problems, different methods and techniques were reviewed for performing the e-healthcare monitoring system with big data. The machine learning techniques are used for efficient diseased patient health monitoring through the effective performance of feature selection, clustering and patient classification with increase the accuracy and minimum time consumption. The results are is performed using on different factors such as clustering accuracy, clustering time, classification accuracy, classification time, and error rate with respect to number of patient data.

scholarly journals An Overview of Post-COVID-19 Patient’s Health Monitoring Systems

2021 ◽  
Vol 7 (10) ◽  
pp. 61-67
Author(s):  
Chirag Satapathy, Hrishikesh Gokhale, Ali Zoya Syed, Keerti Srivastava and Ruban Nersisson
Keyword(s):  
Health Monitoring ◽  
Human Life ◽  
Vital Role ◽  
Health Conditions ◽  
Smart Sensors ◽  
Monitoring Systems ◽  
Comprehensive Review ◽  
Global Pandemic ◽  
Health Monitoring Systems ◽  
Time Basis

COVID-19 is a global pandemic infecting human life. There are many patients who have recovered from this deadly virus and need to be monitored constantly even when they are at home. IoT plays a vital role in health systems that help to monitor patient’s health conditions. These healthcare frameworks consist of smart sensors to keep a track of patient’s vitals on a real-time basis. These systems will help bridge gaps between the patients and doctors during the pandemic situation. In order to make our system competitive against the already existing devices, we prepared a comprehensive review where we extensively studied other products and compared them to find what's best for the patients.

IoT based Smart Healthcare Monitoring Systems: A Review

2021 ◽  
Author(s):  
Divyanshu Tiwari ◽  
Devendra Prasad ◽  
Kalpna Guleria ◽  
Pinaki Ghosh
Keyword(s):  
Monitoring Systems ◽  
Smart Healthcare ◽  
Healthcare Monitoring

Review on the wearable health-care monitoring system with robust motion artifacts reduction techniques

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aarthy Prabakaran ◽  
Elizabeth Rufus
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Learning Algorithm ◽  
Motion Artifacts ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Design Modification ◽  
Content Type ◽  
Wearable Monitoring Systems ◽  
Health Care Monitoring

Purpose Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users. Design/methodology/approach MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored. Findings According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems. Originality/value This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems

2022 ◽  
pp. 181-208
Author(s):  
Joseph Bamidele Awotunde ◽  
Rasheed Gbenga Jimoh ◽  
Roseline Oluwaseun Ogundokun ◽  
Sanjay Misra ◽  
Oluwakemi Christiana Abikoye
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud System ◽  
Monitoring Systems ◽  
System Framework ◽  
Smart Healthcare ◽  
Healthcare Monitoring
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