scholarly journals Internet of Things(IoT) Based Multilevel Drunken Driving Detection and Prevention System Using Raspberry Pi 3

2020 ◽  
Author(s):  
Viswanatha V ◽  
Venkata Siva Reddy R ◽  
Ashwini Kumari P ◽  
Pradeep kumar S
Keyword(s):  
Internet Of Things ◽  
Alcohol Intake ◽  
Heart Beat ◽  
The Body ◽  
Raspberry Pi ◽  
Ignition System ◽  
Prevention System ◽  
Heart Beat Rate ◽  
Drunken Driving ◽  
Death Cases

In this paper, the proposed system has demonstrated three ways of detecting alcohol level in the body of the car driver and prevent car driver from driving the vehicle by turning off the ignition system. It also sends messages to concerned people. In order to detect breath alcohol level MQ-3 sensor is included in this module along with heartbeat sensor which can detect the heart beat rate of driver, facial recognition using webcam & MATLAB and a Wi-Fi module to send a message through the TCP/IP App, a Raspberry pi module to turn off the ignition and an alarm as prevention module. If a driver alcohol intake is more than the prescribed range, set by government the ignition will be made off provided either his heart beat abnormal or the driver is drowsy. In both the cases there will be a message sent to the App and from the App you can send it to family, friend, and well-wisher or nearest cop for the help. The system is developed considering the fact if driver is drunk and he needs a help, his friend can drive the car if he is not drunk. The safety of both the driver and the surroundings are aimed by this system and this aids in minimizing death cases by drunken driving and also burden on the cops.

scholarly journals Design a Prototype for Detecting Abnormalities in Heart Rhythm by Applying Technological Interventions

2019 ◽  
Vol 9 (1) ◽  
pp. 2265-2268
Keyword(s):  
Internet Of Things ◽  
Heart Rhythm ◽  
Patient Data ◽  
Heart Beat ◽  
Raspberry Pi ◽  
Technological Interventions ◽  
Arduino Uno ◽  
Python Programming

This paper demonstrates the basic dialogue for heart rhythm examination of arrhythmia patients who’s heart beat is conventionally irregular. In this approach, designed a device which supervises and record the heart beat by evaluating the PQRS complexes. Despite the fact as alone, there are many ECG devices which examine the heart rhythm but they are little precise because, firstly they are not taking the live data for analysis of PQRS complexes inspite many hospital clinic’s are taking pre-loaded heart rhythm from few days and months and analysis is done on the data either by mathematical theorems or else by using other techniques like wavelet theorem, matlab etc. Here, focus is mainly on analysis of pqrs complexes from live data. Internet of things is been far-flung technology in extant days. So by IoT the heart rhythm and PQRS values are been displaying on web so that doctor monitor patient data up-to-date from anywhere and at any time. The device has been implemented and evaluated by using the Heart beat sensor AD8232, Raspberry Pi 3 b board, Arduino Uno, Python programming.

scholarly journals A Secured IoT Based Advanced Health Care System for Medical Field using Sensor Network

2018 ◽  
Vol 7 (2.20) ◽  
pp. 105 ◽  
Author(s):  
Paparao Nalajala ◽  
S Bhagya Lakshmi
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Heart Beat ◽  
The Body ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Health Awareness ◽  
Medical Field ◽  
Controlling System ◽  
Heart Beat Rate

In day to day life health awareness and controlling system is important to monitor those patient’s physiological parameters frequently. In the recent health awareness environment those usage of IOT innovation organization acquires accommodation of professionals and also patients, since they are connected to different medical fields. A sensor node needs to be arranged on the apparent of the patient body will gather the entire signal from those wireless sensor and also send them of the body sensor node. Those connected sensor nodes on the patient’s body can make in the structure of a wireless body sensor network furthermore they have the capacity with sense those heart beat rate, temperature of surroundings. That basic focus to this system may be on transmitting the individuals’ patient’s health watching parameters through wireless communication in crucial conditions. We propose a secure IOT built health awareness monitoring and will check that saline level of the patient.  

scholarly journals Contact and Non-contact Heart Beat Rate Measurement Techniques: Challenges and Issues

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Wei Leong Khong ◽  
Muralindran Mariappan ◽  
Chee Siang Chong
Keyword(s):  
Mobile Application ◽  
Measurement Techniques ◽  
Circulatory System ◽  
Heart Beat ◽  
The Body ◽  
Rapid Progression ◽  
Imaging Method ◽  
Body Parts ◽  
Heart Beat Rate ◽  
Electrocardiogram Ecg

The heart is the most important organ in the human body as it circulates the blood throughout the body through blood vessels. In the human circulatory system, the heart beats according to the body’s physical needs. Therefore, the physical condition of a person can be determined by observing the heartbeat rate (HBR). There are plenty of methods that can be used to measure the HBR. Among the methods, photoplethysmography (PPG), electrocardiogram (ECG) and the oscillometric method are the standard methods utilised in medical institutes for continuous measurement of the HBR of a patient. Out of these three methods, PPG is the only method which has evolved to a non-contact imaging-based method from the conventional contact sensory based method. The incentive for developing the non-contact-based imaging PPG method in measuring the HBR provides the advantage of excluding the direct contact of sensors on specific body parts. This brings huge improvements to remote monitoring of healthcare especially for the purpose of social distancing. Moreover, the rapid progression of technology (particularly the interactive electronic gadgets advancement) also motivates researchers and engineers to create a mobile application using the PPG imaging method, which is feasible in measuring the HBR. Hence, this study seeks to review and present the fundamental concept, the present research and the evolution of the aforementioned methods in measuring the HBR.

scholarly journals Healthcare Monitoring System using Cloud and Machine Learning

2020 ◽  
Vol 9 (6) ◽  
pp. 549-552
Keyword(s):  
The Elderly ◽  
Health Condition ◽  
Heart Beat ◽  
Raspberry Pi ◽  
Close Relative ◽  
Web Page ◽  
Critical Situation ◽  
Healthcare Monitoring ◽  
Heart Beat Rate ◽  
Made In

The prototype is a working model, incorporating sensors for measuring human parameters like body temperature, heart beat rate. A Raspberry pi microcontroller board is used to analyze the patient's Temperature, heartbeat inputs. This project offers a system that will track the crucial parameters a patient's condition to track continuously. If a patient experiences some critical situation, the unit also triggers an alarm in a patient’s close relative and to the doctor in various methodology. This is very useful for future analyzes and review of the health condition of patients. This project can be adapted for more flexible medical applications, by integrating dental sensors and announcement systems, As a very effective and devoted patient care network, it thus makes it useful in hospitals. The world is facing a widespread problem in recent years, which is increasing the number of elderly people. The home-care dilemma for the elderly is something that is very important. In this, Wireless section is becoming a major platform for many services & applications, Web page tracking is also used here, but also a controller. Paper introduces a standardized health monitoring framework as a step towards the progress that has been made in this department to date

scholarly journals Internet of things issues related to psychiatry

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Scott Monteith ◽  
Tasha Glenn ◽  
John Geddes ◽  
Emanuel Severus ◽  
Peter C. Whybrow ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Cognitive Abilities ◽  
Healthcare Providers ◽  
Emotional Reactions ◽  
The Body ◽  
Psychiatric Research ◽  
Main Body ◽  
Personal Safety ◽  
Healthcare Organizations ◽  
Iot Devices

Abstract Background Internet of Things (IoT) devices for remote monitoring, diagnosis, and treatment are widely viewed as an important future direction for medicine, including for bipolar disorder and other mental illness. The number of smart, connected devices is expanding rapidly. IoT devices are being introduced in all aspects of everyday life, including devices in the home and wearables on the body. IoT devices are increasingly used in psychiatric research, and in the future may help to detect emotional reactions, mood states, stress, and cognitive abilities. This narrative review discusses some of the important fundamental issues related to the rapid growth of IoT devices. Main body Articles were searched between December 2019 and February 2020. Topics discussed include background on the growth of IoT, the security, safety and privacy issues related to IoT devices, and the new roles in the IoT economy for manufacturers, patients, and healthcare organizations. Conclusions The use of IoT devices will increase throughout psychiatry. The scale, complexity and passive nature of data collection with IoT devices presents unique challenges related to security, privacy and personal safety. While the IoT offers many potential benefits, there are risks associated with IoT devices, and from the connectivity between patients, healthcare providers, and device makers. Security, privacy and personal safety issues related to IoT devices are changing the roles of manufacturers, patients, physicians and healthcare IT organizations. Effective and safe use of IoT devices in psychiatry requires an understanding of these changes.

scholarly journals On the Stability of a Stochastic Nonlinear Model of the Heart Beat Rate During a Treadmill Exercise

2020 ◽  
Vol 53 (2) ◽  
pp. 16457-16461
Author(s):  
Mohammad Mostafa Asheghan ◽  
Bahram Shafai ◽  
Joaquín Míguez
Keyword(s):  
Nonlinear Model ◽  
Treadmill Exercise ◽  
Heart Beat ◽  
Beat Rate ◽  
Heart Beat Rate ◽  
The Stability
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