A BIG DATA APPROACH FOR HEALTH CARE
APPLICATION DEVELOPMENT
G.Sravya [1], A.Shalini [2], K.Raghava Rao [3]
@ B.Tech Students, dept. of Electronics and Computers. K L University, Guntur, AP.
*.Professor, dept. of Electronics and Computers. K L University, Guntur, AP sravyagunturi93@gmail.com , shaliniaramandla@gmail.com, raghavarao@kluniversity.in

ABSTRACT:
Big data is playing a vital role in present scenario. big data has become the buzzword in every field of research. big data is collection of many sets of data which contains large amount of information and little ambiguity where other traditional technologies are lagging and cannot compete with it .big data helps to manipulate and update the large amount of data which is used by every organization in any fields The main aim of this paper is to address the impact of these big data issues on health care application development but health care industry is lagging behind other sectors in using big data .although it is in early stages in health care it provides the researches to accesses what type of treatment should be taken that are more preferable for particular diseases, type of drugs required and patients records

I. Introduction
Health care is one of the most prominent problems faced by the society now a day.
Every day a new disease is take birth which leads to illness of millions of people. Every disease has its own and unique medicine for its cure. Maintaining all the data related to every disease in a single database is not possible using the legacy system in order to solve this

problem we use different types of external memory devices which again results in expensive maintenance of the system. To avoid this we use Big Data where we can achieve the data storage easily. The introduction of Big Data in health care management system made the needy i.e. the stake holders to have the right to access the data stored using Big Data and acquire knowledge about the diseases. The use of big data must undergo a series of privacy setting in order to protect the patient’s data from getting into the public hand in order to acquire the trust of people and get success in the field of health care.
This health management system is not based on the profit gained by the users this is mainly based on the use of mobile application sensors by the patients who are in need and maintain their profile according to the doctors instructions and help the patients by getting the immediate information from the nearest doctor in reacting and prescribing the medicine without actually consulting the doctor. The important challenges faces developing the application are inferring the information and knowledge about the diseases and keeping the patients records stored in a particular area and sensing the patient behavior and conditions using the sensor.
The application must also consider the patients social interactions and communications which increases the goals

of the application to a next level by acquiring a massive amount of data and provide a complete personalized health care assistant to the user.
This project the application requires the complete details of the patient like age weight, BMI etc.to be stored in the application. The application stored the information of the patient in the cloud using Big Data model i.e. Hadoop. This application is fed with the detail information about the frequent diseases caused in the surroundings and the protecting precautions form the diseases.
The application is connected to the internet which gives online access to the data base and gets the up-to-date information about the diseases affection the people

II .BACKGROUND
A data is considered as Big data only when it meets three criteria i.e. volume, variety and velocity of data [1]. The tools processes and procedures used by the organization in creating and manipulating very large data and storage facilities is referred as Big data [2]. The big data in health care organization had developed form single physician offices to large hospitals and healthcare organization by digitizing, combining and effective use of big data [3]. The information stored in the
Big Data can be updated by any of the pharmaceutical R&D in the form of drug and what drug can be used for a disease
[4]. Gathering the information from the patients and holding the information in longitudinal records is a complex task [2].
Big Data technology stack refers to software that processes and prepares all types of structured and unstructured data for analysis [5].Now a days big data in health care is overwhelming just not only because of its volume and also diversity in some of the data types and also the speed at which it can be managed[6].Where as

drug discovery is also related to big data analysis ,because the process is defined by the requirement of collection, processing and large volumes analyzing[7].In health care, big data encompasses a whole range of data types which includes clinical data which can be derived from the electronic records within any laboratories, pharmacies, organizations where the services are delivered. Claims where services are delivered[8].

III .Big Data usage in Health Care
The serious problem faced by the present world is increase of population which results in aging of people of some age group people which results in many health care issues as the aging people have a low immunity levels to fight towards an disease and the stress caused daily also makes them week. These people must be protected from different kinds of illness by constantly providing a system to look after them by checking their health conditions and providing solutions for their regular problems and reminding them for their regular checkups services. The users are dispersed in the whole country and with enormous diversity. Managing such a diverse user group is a challenge faced by the health service providers. A new ear of medication is done by collaborating the mobile computing and big data. Every person can have an access to preloaded and instant service for any health issue by using the information form Big Data.
There services can be of different types regarding different issues e.g., daily health checks, medication reminders, first aid instructions, commonly affected diseases and their precautions. Application present in the cloud can be downloaded to the mobiles for an instant service for any emergency health issue. Storing all such information in a single system quite a big task which requires large amount of

physical data in order to avoid that healthcare is collaborated with the Big
Data by completely using the data entry and data analyst.

IV. Big data model for health care
There are many challenges faced by the healthcare industry in processing the data to deliver the services to each and every user according to their profile. Hadoop provides the solution for processing the medical images from different sources and storing at one place. The following interface called HIPI explains how image processing can be accomplished .We create a Hadoop database and access it by using any programming language like C,
C++, HTML, and PHP where the user can have parallel access to the data present in the Hadoop database.

answered using the direct application which accesses the internet. for suppose if the patient having any health problem can be detected by the various sensors and send through Bluetooth lower energy and android applications which can be directly sent to the health care organization system.

VI. METHODOLOGY

V. IMPLEMENTATION
The speech which is used as input is fed into the wrist watch which supports
Bluetooth and decoding the information.
This is connected to mobile phone via
Bluetooth. Bluetooth is the right medium of data transfer from the wrist watch to mobile phone because there will be no much distance from the watch to our phone. So Bluetooth is the perfect medium of data exchange. The decoding technique is done in the mobile application which connects to the internet for the right solution to the problem. Information is fetched from the sources like call center, application store, big data clusters
(Hadoop).
The main advantage is that we can use the application directly from the mobile phone without the help of wrist watch. The questions asked by the user can be

Fig. working of health care system using big data
A. Wrist Device
A
wrist device which is designed to have connectivity modules, sensors. The connectivity can consist of Bluetooth low energy (BLE) technology for low power consumption. When it is connected with a smart phone with Android operating system it forms a personal area network.
TI CC2540 chip consists of the BLE support is used in the wrist watch. The watch also includes of the accelerometer to calculate the activities of the person, temperature sensor, a thermopile to measure temperature of the skin, two reflective photoplethysmography sensors for heartbeat sensing and SPO2 content in the blood.

All the sensors in the device like thermopile, temperature sensor and accelerometer have digital serial interfaces which use CC2540 for reading. photoplethysmography (PPG) sensor is controlled by the analog switcher which helps to choose the type and intensity of the light as red (660 nm) or infrared
(905nm) for the sake of heartbeat rate and
SPO2 measurement. For the robust measurement of the heartbeat rate an adaptive threshold algorithm is followed.

B. Mobile Application: The data which consists of the measured parameters are sent to the mobile phone through BLE communication. The mobile application with the Android platform was made to process the data and make the decision for the person. The data is gathered in the mobile phone and acts as the main intelligence of the system. Mobile application receives the data from the wrist watch in form of the sampling frequencies controlled by different timers, for e.g., speed for every 0.1s, temperatures for every 2s, heart beat rate for 3s and ambient temperature for 10s.

C. Big Data Server
All the readings which were taken from the wrist watch are need to be sent to the big data system for analysis, which in turn helps to customized care of the person.
The efficient usage of the professional expertise and provide the required statistics to the government will help to plan strategically. The patients will know to follow specific medication and how their health must be cared by using the access to health care aids.

To increase the efficiency for large scale data extraction which is random in nature,
A Map reduction model is used. It leads to parallelization of data avoiding the synchronization problems. Map reduction is a framework made to support the data which is distributed on larger amounts using cluster of computers. It is the most prominent model in big data systems. This includes the indexing of data in parallel and search operations. It receives the data from the mobile application In general,
UDP is not followed to transmit the important signals because the packets are not guaranteed to be delivered. But in some communication UDP is faster than
TCP if the checking of delivery is done.
It’s also flexible enough.

VII. CONCLUSION
Though the big data was into the consumer markets, it’s still a big challenge to implement in the healthcare. The main problem and challenge with the big data is the large amount of data in the present systems are not related with each other and multiple file formats is another challenge.
The main challenge in healthcare is privacy. The information regarding the patient is stored and shared between the networks. If all the above challenges are achieved, then the cost factor plays an important role. Lower cost with better outcomes lead to very good set up in health care. The implementation in R&D, clinical trials, clinical outcomes is strong support for the advancement in health care.

References
[1] Bill Hamilton “Big data is future of Health care” Cognizant 20-20 insights 2013.

[2]Jimeng Sun,
Chandan k. Reddy ”Big Data
Analytics for Healthcare” SIAM international
Conference on Data Mining, TX, 2013.

received a best paper award from DST Secretary and Best Teacher award from KL University He is also member of several technical organizations.

[3]
Wullianallur
Rughupathi and Viju
Rughupathi”Big data analytics in healthcare: promise and potential” Health information science and system 2014
[4] Peter Groves, Basel Kayyali, David Knott,
Steve Van Kuiken.” The ‘big data’ revolution in health care” Center for US Health System Reform.
[5] Silvia Piai, Massimiliano Claps “Bigger Data for Better Healthcare” September 2013, IDC
Health Insights.
[6] Wullianallur Raghupathi1 and Viju Raghupathi
“Big data analytics in healthcare: promise and
Potential “
[7] Keith C.C. Chan ,The Hong Kong
Polytechnic university
“Analytics for Drug Discovery on big data”
[8] “A Policy Forum on the Use of big data”

Authors profile
G. Sravya is studying B.Tech (Electronics and
Computer Engineering) at KL UNIVERSITY,
VIJAYAWADA. Her areas of interest includes
Computer Networks, DBMS, Web Technologies.
Previously she had done research paper in area of Data mining Titled as “Privacy Preserving
Data Mining Using LBG”. She attended various workshops on App Development
,wireless sensor networks and RC Aircraft. She participated in various National and International conferences and Seminar Related to her subjects of interest.

Policy Forum on the
Use of Big
Authors profile

Authors Profile
K.Raghava Rao, Professor in CSE, working in the dept. of ECM. He is having 15 years of experience in teaching for UG and PG engineering students and 3 years of Software Development experience in Singapore. He received B.E(CSE) from MG state
University, M.Tech(CSE) from RVP University,
Udaipur and Ph.D(CSE) from Mahatma Gandhi
University (Kasi Vidyapeeth), Varanasi, in the years
1995, 2005 and 2009 respectively. He published several papers in national & international conferences and journals. He published 3 text books. Currently he is carrying a DST funded project in the area of Wireless sensor networkssensor web enablement. His research interests are
Wireless sensor networks, Embedded Sensor networks and Sensor Web Enablement. He

A.Shalini is studying B.Tech (Electronics and
Computer Engineering) at KL UNIVERSITY,
VIJAYAWADA. Her areas of interest includes
Computer Networks, Data Base Management
System, Web technologies, Data mining.
Previously she had done research paper in area of Data mining titled as
“Privacy Preserving
Data Mining Using LBG and ELBG”. She attended various workshops on wireless sensor networks, web development, App development, and entrepreneurship. She participated in various
National and International conferences and seminars related to her Subjects of interest.