Monika

Vol.4 Issue 1

International Engineering Journal For Research & Development

Impact factor : 3.35

E-ISSN NO:-2349-0721

A REVIEW PAPER ON: SMART PERSONAL ASSISTANTS GATEWAY SERVICES BASED ON INTERNET OF THINGS Ms. Puja V. Gawande (Assistant Professor) Dept. of Electronics & Communication Engg.

Email: - p.gawande07@gmail.com

Monika N. Ambhorkar Dept. of Electronics & Communication Engg.

Email:-monikaambhorkar@gmail.com

_________________________________________________________________________________________

ABSTRACT

INTRODUCTION

Management

of

various

diseases

is

important to self-management for health. The internet of things (IOT) concept plays a significant role in management of our personal health.

Nowadays, automation is becomes very popular by using wireless communication which makes the system smart and accurate. In the field of medical science, monitoring the patient’s parameters plays vital role in detecting and for proper treatment. In order to execute it, personal health devices and intelligent service are required. The patients are scanned by personal computer which are attached to them and makes them to be scanned time to time by doctors in existing system. The system proposed an intelligent model which uses sensors to measure different framework of the patient like temperature, blood pressure, etc. The sensors are Wireless Sensors Nodes (WSN) which spatially distributed autonomous

sensors

to

detect

physical

or

environmental conditions and cooperatively pass their data through the network to a main location.

In addition to this, it updates the complete scenario of the patient to the server. The information is updated by the server using local area network (LAN), so that the physicians can record the ranking of the patients within that area. The success was affirmed on proposed system finally.

Wireless communication is one of the best methods in day to day life. Use of wireless tremendously increased with number of leads over the wired communication such as, usability, decreased risk of factors, non-success and un-comfort ability of patient,

to

increase

strength.

In

hospitals,

temperature, blood pressure, respiration rate, heart beats detectors are the important devices. Normally, it is tough to record the status of the patients which are kind of connected with pertinent sensors to the body. Ultimately the patient is scanned from their respective intensive cares and shows the scenario to the connected personal computers through wired transmission. The use of Wireless Sensor Nodes (WSN) will make health care system more constructive with the help of global system for mobile

communication.

Periodically,

Wireless

Sensor Networks (WSN)is used to detect the physiological orders by using Zigbee technology.

The Zigbee modules are handled as router, administrator or end devices. The communication of the patient’s data is done by Zigbee based sensor network to faraway main centres. A health care detecting system during the censorious situation plays an important character in every area. Point of care (POC) recorder introduce to alongside patient testing, generally exterior the centralise hospital or foremost care provision.

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International Engineering Journal For Research & Development

Vol.4 Issue 1

RELATED RESEARCH

Mamoru Sekiyamal, Bong Keun Kim2,

There have been various researches in the area of

Seisho

health management system and a number of papers

“Sensor Data Processing Based on the

have been reviewed.

Irie3,

and

Tamino

Tanikwa4,

Data Log System Using the Portable IOT

Vaibhav Gandhi, Shashank Heda, Rishab

Device and RT-Middleware”. In this paper [5],

Anand, Zarin A S, Abhishek Upadhyay and

a portable IOT device and RT-Middleware based

Arup Lal Chakraborty, “A Raspberry Pi-

single-board-computer Raspberry Pi, the extendsensor board and the positional information system is

based field-deployable tunable diode laser

presented. Various sensors for data sensing is

spectroscopy system for the detection

explained based on a single board computer firstly.

ofCO2at 2003.5nm”.In this proposed approach

The obtained data is presented with the help of RT-

[4], they work with an actual time, non-invasive, dense and field-deployable CO2 sensor done by tunable diode laser spectroscopy (TDLAS). Direct observation and 2f-WMS are applied for the measurement of gas variable by using low power vertical cavity surface emitting laser (VCSEL). For the data sensing and logging, to make the system compact a Raspberry Pi with a serial analogy to

Middleware based on the Hadoop database system.

In the data log system, the positional information for visualizing the obtained GPS data on the Google map is proposed. Accordingly the GPS data is strained based on its authority.

Kasim M. Al-Abudi, Ahmad M.Derbas & Abdullah

W.

Al-Mutairi,

“Real-Time

Patient Health Monitoring and Alarming

digital (ADC) convertor was used.

Byung Mun Lee and Jinsong Ouyang,

Using

Wireless-Sensor-Network”.

They

proposed an approach [1] in which embedded

“Intelligent Healthcare Service by using

microcontroller connected to a set of medical sensors

collaborations

Personal

and a Bluetooth module. By analysing the detected

Health Devices”. They proposed a system which

medical signals, the embedded microcontroller

between

IOT

is specially used for directorate of chronic diseases.

In order to achieve it, there are two functions such as network protocol and intelligent service needed for personal health. But the functions such as denoting measured data and storing data temporarily are mostly used. This system [6] gives rise to effective comeback to an individual. They inaugurate the collaboration protocol which sends likelihood factors between personal health devices to obtain the result.

Also,

they

present

intellectualized

service

application algorithm used for the operation of personal health.

checks the patients health status is going well or not.

In a case such as, the result are unusual, the embedded unit uses the patient’s cell to send these signals via Bluetooth to the medical centre. The standard devices are tested and calibrated by implemented prototype. This gives rise to the recording, intelligent in decision making and reliable in transmission.

Punit Gupta, Deepika Agrawal, Jasmeet Chhabra, Pulkit Kumar Dhir, “IOT based Smart Health Care Kit”. The paper introduced the designing of health care system for emergency

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Vol.4 Issue 1

International Engineering Journal For Research & Development medical services which can demonstrate of data to

This shows how conducting inclusive estimate on

intensive care units (ICU), using a raspberry pi

different risk factors preferably of the measured

development board. The system [2] allows users to

values during the state of recognition of disease will

enhance risks of health and decreases the health care

give correct data to the patient. Due to these reasons,

cost. The 2

nd

generation Intel Galileo board is a

the assessment procedure for hypertension gives

single board based on the Intel Quark SOCX1000

comprehensive

which is preferred

prevalence rate following the age and gender, the

over Arduino

with high

consideration

to

SBP,

DBP,

current state of personal disease (diagnostic results

processing.

for obesity and diabetes mellitus), and family history

Prosanta Gope and Tzonelih Hwang, “BSN-

as Figure 1 [12]. But most of the medical sensor

Care:

devices don’t give inclusive appraisal.

A

Secure

IOT-based

Modern

Healthcare System Using Body Sensor Network�.

of diabetes affection, glucose measurement value is The use of internet of things

mechanization brings satisfaction to doctors and patients, since they are applied to different medical areas in the modern health care domain. The fundamental

The type 2 diabetes which contains more than 90%

technology

is

the

body

sensor

network(BSN) in a health care system [3], where patient can be recorded with a low power and lightweight body sensor nodes. Without considering security, the enhancement of this new mechanization in health care applications makes patient privacy

considered along with parameters such as obesity, drinking, age, gender, personal disease, and family history [10,11]. Table 1 is a display of each evaluative result which is in accordance to the range of measurement values for blood pressure, glucose, BMI (Body Mass Index), and waive circumference.

In appellation of the demand scale for obesity, BMI and waist circumference are used. Thus, obesity was classified as a risk parameter which caused command in diabetes and blood pressure [11, 13].

unprotected. In this paper, they advocate a secure health care system using body sensor network (BSN) which can logically consummate those necessity.

Risk factors of metabolic syndrome According to the error of the measurement value, states of diseases are estimate in comparison to the normal range [7]. When blood pressure is taken as an example, it is assessed as stage 1 hypertension when the measured systolic blood pressure (SBP) is over 140mmHg and the diastolic blood pressure (DBP) is over than 90mmHg [7, 12]. Although , in case of patients diagnosed with diabetes mellitus or chronic kidney disease, it should be assessed as stage 1 hypertension when they are over 130mmHg or

Figure 1. Risk factors of Hypertension, Diabetes and Obesity Table 1. Classifications of Pressure, Diabetes and Obesity

Blood

80mmHg, so that accurate assessment takes places when the fixed range is readjusted [7, 12].

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International Engineering Journal For Research & Development

Vol.4 Issue 1

Figure 2. Conceptual Model for Internet of Things and its functionalities Therefore, the current u-Health model where data measured from the medical sensor is sent to the u-Health server can be considered approximate

Structural Characteristic of IoT

to WSN [8].The favour aspects of device and

IOT is a notional model which provides favour for human beings, which hold inherent roles, centred on the

network

conserve

mutually

autonomous

collaboration system [7, 8]. In various favour IOT can be used and same application favour elements like network ingress board, power directorate, and safety

administration

must

be

acquired

[7,

9].Moreover, there are also specific application service elements of the thing. The IOT sensor object, sensor board and sharp application of remit or

network have currently become senior and user requirements became expanded. These conditions give rise to need of more cognitive and dispensed processing [7]. This recommends a new scenario for the u-health favour to make a change from the latest WSN type to M2M type in future. As a result, it will advocate a new sharp healthcare favour model based on IOT.

INTELLIGENT SERVICE

HEALTHCARE

handling measured data are particular application favour

elements.

Therefore,

Figure

2

is

a

representation of classification between common application service elements and specific application the service elements.

The examples of IOT are WSN (wireless sensor network) and M2M (machine to machine). Data is remit from the sensor to the server or the data provided by the server hold one-sided directionality as it is sent to the mover in WSN. In case of M2M,it grasp bilateralness as processing is done by an autonomous transmission between each device [8].

Collaboration model Collaboration model includes the smart healthcare service model is which obtain risk factors needed for analysis from the network and return on them by real –time. There are two types of factors required for this favour that is the collaboration protocol required to gain the risk factors and smart application required for reflected cognitive opinion. Figure 3 defined the IOT based service model regarding the risk factors of 3 major metabolic syndromes. First of all, IOTXX is represented as a device which enables connection to the IOT network and autonomous collaboration and the functions of each device was indicted as xx. In Figure 3, (a) is a specific representation of this. In terms of the blood pressure monitor (IOTBP), only the measured blood pressure is not displayed. Instead, data on diabetes measured by the glucose meter (IOTGL) and the data on obesity measured by the weight scale (IOTOB) are requested to acquire the result [7]. Data stored by gateway

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(IOTGW)

is

appealed

for

and

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International Engineering Journal For Research & Development

Vol.4 Issue 1

accomplished, if information cannot be immediately

duration, but IOTGL is unable to obtain it. IOTBP

sent by other IOT’s. Also, risk parameters of the

measures the blood pressure and sends the Data.Req

patient such as the gender, age, and family history

message so that risk factors needed for assessment

are acquired by the u-Health server (IOTSVR).

are gathered.

When the IOT device is turned off or not within the

IOTOB and IOTGW, which receive Data.Req

network, it is shown in (b) or (c), data sent from

message, send the Data.Ack message and the risk

IOTGW or IOTSVR are used to rate the dimension

factor information of relevant patients stored by each

value IOTXX must store important data by real-time

device. Data.Nak is forwarded to indicate that there

to construct a collaboration model. To achieve this,

is no data present, if the prospect factors about

seamless collaboration model is demanded between

patients are not available. To get the newest

the devices of IOTXX. We present the collaboration

informant, Data.Req is sent periodically the blood

protocol at the next section.

pressure was determined so that the current data is returned on the analysis. When the power of the

Figure 3.Collaboration model between

IOTBP switched off or dimension was aborted, it

IOTs for the smart health care service.

was constructed so that the leave message is passed

Collaboration protocol between IoT personal health devices

to know the In Figure 4, (b) represents the format of the messages used during the transmission process of (a). The number of message type is 5 in this protocol. ‘Join’ and ‘Leave’ were defined without ‘Payload’ in order to minimize the transmission overhead. The categorization was made between blood pressure, glucose, and obesity in medical data type (M). The source address (S) and destination address (D) were assigned in the message of the IOT

The

application

protocol

named

collaboration

protocol which post and acquires risk parameter data required between IOT devices [7]. Home connects to the home networks like Bluetooth or Zigbee, uses uhealth devices. In Figure 4, (a) displays an example of a protocol process in the case of (b) of Figure 3.

Combined message is podcasted to all devices in the network as the IOTBP operates. IOTOB and IOTGW get the combined message during this

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device. In addition to this, it involves the sequence number (N) of each message and the payload length.

Not only but also, patient recognition data and risk factors were tagged in the Payload. Payload was interpreted as different size and each header field was structured as 1 byte. To provide absolute consideration between mutual diseases and

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International Engineering Journal For Research & Development parameters, the data is collected in form of the protocol is used. In the next area, annotation of smart application which can control this process will be considered.

REFERENCES [1] Kasim M. Al-Abudi, Ahmad M.Derbas & Abdullah W. Al-Mutairi, “Real-Time Patient Health Monitoring and Alarming Using Wireless-Sensor-Network”, 2016 13th International Multi-Conference on Systems, Signals & Devices.

[2] Punit Gupta, Deepika Agrawal, Jasmeet Chhabra, Pulkit Kumar Dhir, “IOT based Smart Health Care Kit”, 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT).

[3] Prosanta Gope and Tzonelih Hwang, “BSN-Care: A Secure IOT-based Modern Healthcare System Using Body Sensor Network”, IEEE sensors journal, vol.16, no.5, 2016.

[4] Vaibhav Gandhi, Shashank Heda, Rishab Anand, Zarin A S, Abhishek Upadhyay and Arup Lal Chakraborty, “A Raspberry Pibased field-deployable tunable diode laser spectroscopy system for the detection of CO2 at 2003.5nm”, 2015 IEEE. [5] Mamoru Sekiyamal, Bong Keun Kim2, Seisho Irie3, and Tamino Tanikwa4, “Sensor Data Processing Based on the Data Log System Using the Portable IOT Device and RT-Middleware”, The 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2015) October 28-30, 2015/KINTEX, Goyang city, Korea.

[6]Byung Mun Lee and Jinsong Ouyang, “Intelligent Healthcare Service by using collaborations between IOT Personal Health Devices”, International Journal of BioScience and Bio-Technology vol.6, no.1, (2014), pp.155-164 [7] B. M. Lee and J. Ouyang, “Application Protocol adapted to Health Awareness for Smart Healthcare Service”, In the proc. of International Workshop of Multimedia2013, Advanced Science and Technology Letters, vol. 43, (2013), pp. 101-104. www.iejrd.in

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[8] C. Min, W. Jiafu and L. Fang, “Machineto-Machine Communications: Architectures, Standards and applications”, KSII Trans. on Internet and Information Systems, (2012), pp.

480-497.

[9] A. Sarita and L. D. Manik, “Internet of Things – A Paradigm Shift of Future Internet Applications”, Institute of Technology, Nirma University, (2011), pp. 1-7.

[10] American Diabetes Association, “Standards of medical care in diabetes. Diabetes Care 31 (Suppl 1)”, (2008), pp. 12-54.

[11] “Definition and Diagnosis of Diabetes Mellitus and Intermediate Hyperglycemia”, World Health Organization, (2006).

[12] Joint National Committee, “Prevention, Detection, Evaluation, and Treatment of High Blood Pressure”, the 7th Report of the JNC, U.S. Dept. of Health and Human Services, (2004).

[13] M. L. James, C. Y. Donald, A. R. Joseph and M. D. Ronald, “Obesity: Assessment and Management in Primary Care”, American Family Physician, vol. 63, no. 11, (2001), pp.

2185-2196.

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