International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 06 | June 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 677 A SURVEY ON IOT BASED PATIENT VITAL MEASURING SYSTEM Ashwini R Hirekodi 1 , Bhagyashri R Pandurangi 2 , Uttam U Deshpande 3 , Ashok Magadum 4 1 M.Tech Student, Department of Electronics and Communication, KLS Gogte Institute of Technology, Karnataka, India 2 Assistant Professor, Department of Electronics and communication, KLS Gogte Institute of Technology, Karnataka, India 3 Assistant Professor, Department of Electronics and Communication, KLS Gogte Institute of Technology, Karnataka, India 4 Project Manager, Osteos India Pvt.Ltd, Karnataka, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Technologies have been improving day by day where all the works are being done digitally. Health specialists and doctors are using the old method of storing the data which is the manually writing which can being out a lot of errors. There can be improved ways for doing this where we can store the readings of the vital parameters such as pulse sensor and ECG digitally. This step avoids errors encountered due to the manual entry of the data in the EMR system and related application. The readings of the pulse will be published to Node JS application once the patient ID is received via kafka message broker topic. Node JS then stores the readings to MongoDB database along with the patient’s ID. The key objective of this automatic update of pulse or ECG measurements of patient and it prevents any errors caused due to the manual entry of the pulse or ECG readings. Key Words: Pulse sensor, ECG, Node JS, MongoDB database, Internet of things, Raspberry pi, EMR. 1. INTRODUCTION The vital parameters like pulse and ECG readings of a patient are measured using the sensors that are connected to a Single Board Computer such as Raspberry Pi. The Raspberry Pi has been chosen for collecting sensor data as it has all the necessary resources and powerful CPU to run multiple applications on a standalone board. IoT was first proposed by Kevin Ashton in 1999 [1]. This is the physical communication network where billions of data are collected from the very different devices we use and transforms them into usable information [2]. IoT can be used in the medical field so that the doctors can monitor the patients from anyplace at any time. This system can be used for the patients who need continues monitoring of their health. By 2020 unprecedented growth in the Internet of Things (IoT) technologies will make it possible to talk about 50 billion connected devices through the internet [3]. IoT can be used in the medical field so that doctors can monitor patients from anyplace at any time. This system can be used for patients who need continuous monitoring of their health. A systematic review of various mobile healthcare approaches was carried out by [4]. A mobile cloud-based ECG monitoring service was presented [5]. IoT establishes bridge between the ‘Digital world (Internet)’ and the ‘Real world (physical device)’. The devices are connected to the cloud-based services (e.g. distributed micro services or monolithic application) and create unique identification over the internet [6]. Low power programmable Systems on Chip (SoC) is built in microcontroller which integrates and controls all of the programmed components [7]. Raspberry pi is used to interact with outside world and transfer the data. The transferred data is stored in the private cloud. Here the obtained data is in the analog output. The ADS1115 is a 16- bit ADC chip is used for the conversion the data from analog to digital which are obtained from the sensors. The digital data which are obtained are sent to the Raspberry pi where the python application runs and the samples are sent to the Node JS web server which is the open source of the cloud. These digital samples are then stored in the MongoDB database along with the patient ID. The data’s obtained from the patients are stored in their respective ID’s. After submitting the form, the vital parameters pulse and ECG values will be sent to controller via REST API and stored in respective patient’s collection in the MongoDB database. When the doctors need any health details of the patients, they have to just enter the patients ID then the EMR trigger start pulse and ECG measurements which are updated in the websocket can be obtained. 1.1 Parameter Readings The parameters which have been considered are the pulse sensor and the Electro cardiogram. These parameters are obtained using the sensors which can give the accurate readings of the patient. Readings are