The objectives of the project are to develop assistive technologies for the rural environment in health care with the following services:
1. Remote monitoring services for the people in the villages. One of the important problems in rural India is the lack of health care centers.
2. To improve the awareness of people towards healthcare. Most of the people in villages do not care about the importance of frequent health checks which is one of the main important contribution to the number of health issues faced by them.
3. On time emergency services to the people in the rural environment. Lack of emergency services still remains one of the main reasons for primary health issues reaching its extreme.
4. Disease based predictive analysis for people in villages to increase the accuracy of diagnose given to the patients.
Health is not everything but everything else is nothing without health. Healthcare is the right of every individual but lack of quality infrastructure, dearth of qualified medical functionaries, and non-access to basic medicines and medical facilities thwarts its reach to 60% of population in India. A majority of 700 million people lives in rural areas where the condition of medical facilities is deplorable. 31% of the population travels more than 30km to seek healthcare in rural India and 66% of rural Indians do not have the access to the critical medicines. Though a lot of policies and programs are being run by the Government but the success and effectiveness of these programs is questionable due to the gaps in the implementation. In rural India, where the number of Primary health care centers (PHCs) is limited, 8% of the centers do not have doctors or medical staff, 39% do not have lab technicians and 18% PHCs do not even have a pharmacist. Information Technology (IT) is set to play a big role with IT applications being used for social-sector schemes on a large scale. Some of the IT technologies which have key roles in enhancing the healthcare is the Internet of Things, Artificial Intelligence, Data mining and Predictive Analytics. These technologies helps in providing right medication to the patients, improving the medication efficiency, helps in providing preventive medicines.
Providing communities with essential health care is no easy task. The distribution of health care around the world is notoriously uneven. Remote rural areas do not get their fair share of resources. Attempts to attract healthcare professionals to work in rural areas to redress this imbalance have been only partially successful. So, we need an alternative approach. Drones are potentially a solution to this logistical problem. Drones make it possible to deliver medicines to rural areas and have the ability to reach victims who require immediate medical attention within minutes, which in some cases could mean the difference between life and death.
This proposal intends to exploit the IT technologies to diagnose and monitor patients remotely using wearable medical devices and smartphones, to provide on time emergency services to the people in the rural villages using drones and to avail predictive models on the data collected from the patients for a long-time welfare of the people.
All the related works that have been done by other researchers that are related to the above stated problem are as follows
· In-home healthcare services based on the Internet-of-Things (IOT) have great business potential; but it is not affordable in rural India since the average amount a person can spend in rural India is 32 per day. Instead of providing in-home healthcare services, this proposal aims at educating the social workers and local medical practitioners to make use of these IoT devices to make frequent assessment on the people’s health condition. This approach may reduce the cost spent by the Government, people and it will provide various employment opportunities to the local people.
· The current evolution of the traditional medical model toward the participatory medicine can be boosted by the Internet of Things (IoT) paradigm involving sensors (environmental, wearable and implanted) spread inside domestic environments with the purpose to monitor the user’s health and activate remote assistance. RF identification (RFID) technology is now mature to provide part of the IoT physical layer for the personal healthcare in smart environments through low-cost, energy-autonomous, and disposable sensors. The disadvantage is that RFID technology covers only short area.
· Another proposed method involves a health monitoring system comprises several sensors connected to a person and they communicate with a data aggregator and processing unit. The data aggregator and processing unit may be a specialized device and p.c. The aggregator unit has the responsibility of collecting each sensor data following strict sampling rate. An ARM7LPC2148 microcontroller is used for aggregation. Hospital computer is used as a processing unit for the health monitoring system. The aggregator uses wired USB serial connection to communicate with the data processing unit. Services will be provided to the users based on the data. This system can receive valuable medical advice from the doctors for the patients and can set alarms or reminders for timely medications and appointments and graphic files. The drawbacks include limitation in the classical databases, lack of global suggestion for the patient health, delayed responses for the given query, no automated alerting system, unable to handle the situation instantly and no personal connection between doctor and patient. All these drawbacks has been overcome in our proposal.
· Zipline, a California-based company started flying commercial drones from its distribution center in Muhanga, Rwanda, to nearly two dozen hospitals in the country. Health workers, social workers or medical practitioners at remote clinics and villages can order supplies via text. And Zipline promises to air drop the delivery in as soon as 15 minutes, cutting time on trips that once took hours to complete by car. Currently, our country fails to facilitate drone services to improve medication in rural India. This proposal would be a promising initiative to provide drone-based emergency services in rural India.
PROPOSED WORK WITH METHODOLOGY
The overall architecture of the proposal can be picturised as
Fig 1: An overall Architecture
The proposed model, intend to use IOT based smart sensors to monitor patient’s health condition by measuring five important vital signs. The sensors of use includes Heart Rate Sensor, ECG Sensor and Accelerometer. The vital signs or health attributes include Heart Rate (HR), Respiration Rate (RR), Electro Cardio Gram (ECG), Dissolved Oxygen (Sp02) and Blood Pressure (BP). The data collected from the precedent sensors will get transferred to a mobile app using the Bluetooth technology. The raw data gathered from the sensors will be converted into some meaningful information since all data is destined to have some value, even if not known at the time of collection. The data is then stored on a server using the WIFI technology. The private server of MIT, Anna University stores the details of the patient history, details of the doctor and many more useful information for this project. Any abnormal conditions of the patient are detected from the vital signs measured using the sensors and an alert is sent to the doctors and care takers of the patient.
Fig 2: Database Structure
A large amount of patient’s history stored in the server is further mined and analysed using suitable Data mining and Predictive modelling algorithms to improve the patient outcomes. These algorithms can be utilized to efficiently manage rising-risk and at-risk populations, triage patients who need early intervention and reduce preventable hospitalizations. The Predictive algorithms can forecast the future of a patient’s health with the help of clinical data and the medical knowledge integrated in the database. Clustering of the patient’s data is also done to improve customization and diagnoses efficiency.
The data collected from the sensors and the data generated by the algorithms running on the server will be stored on a relational database in the server. The relational database consists of a set of tables normalized to hold the information. The database tables have been related to extract significant information. The structure and the relationship among the database tables have been outlined in Fig 2. The database structure is mutable as new sets of data is collected or generated.
This model also emphasize on providing emergency services to the patients. The predictive algorithms running on the centralized server will generate primary alerts to the doctors and care takers when an abnormality has been predicted. In addition, when the patient’s health condition becomes critical, a secondary alert will be generated to all the ambulance services near to the victim’s location. The ambulance service which is prompt will carry on the patient to the nearby hospital. This model also includes creating a third level of alert when the patient is desperate of some medicines. This alert will be generated either by the social worker or the medical practitioners. The drone from the hospital which is in proximity to the patient will deliver the prescribed medicines. All these services will be automated with the help of current and scalable technologies.
The major advantages of the proposed model is that it ensures frequent monitoring of the patient’s health, decreases the travelling done by patients, improves the information continuity, builds communication between patients and doctors to personalized health care to the people, instant services for the emergency and critical issues, large storage media for the health data of the patients, runs complex algorithms for predictive analytics and machine learning on the patient’s data to improve the diagnoses efficiency and the proposed model has a rich business model.
The proposed model portrays an affluent business model. The sources of value includes the vital sign measurements, provision of on time alert and medicine services. The key stack-holders of this model will be the village people, social workers, local medical practitioners, primary health care centres and public hospitals. The business model has been picturized in the Fig 3.
Fig 3: Business model of the proposal
The architecture of our proposal is picturized in Fig 1. The first stage of implementation starts with the social workers or local medical practitioners conducting regular health checks. The health assessment is carried out by measuring the vital parameters with the help of various sensors like Zephyr BioHarness3, Wrist Worn Blood Pressure Sensing Device and Nonin fingertip pulse Oximeter. These sensors are used to measure Heart Rate, Respiratory Rate, ECG, Blood Pressure and SPO2 in order. The measurements from the sensors are shared to a smart phone using a connecting technology. The connecting technology used here is Bluetooth. The measurements from the sensor are displayed on the smartphone using a mobile application designed as a part of the project. The data from the mobile phones are stored in the server through Wireless communication. The server is the part of the architecture which runs program to process data stored on it. The processes carried on the server includes optimization of the vital parameters of the patients using Genetic algorithms, classification and personalization of the data of the patients through clustering. The clustering is done based on the vital parameters using K-means algorithm. Data mining and predictive modelling algorithms are also run on the server to improve the diagnoses efficiency in the future and to suggest primitive medicines during emergency situations.
Fig 4: An algorithm description of the model
The architecture also involves emergency services. To provide emergency services, the algorithms manipulating the vital parameter measurement checks for any emergency. If there is an emergency an alert message is generated in the form of voice message to the doctors associated with the patients and their care takers. The patient is also provided the ambulance service in case the patient needs immediate hospitalization. The algorithm programmed on the centralized server will find the ambulances in proximity to the patient’s location and gives an alert to all the located ambulances. The mapping of ambulances is achieved using Global Positioning System (GPS) and Location services. The mobile app used by the medical practitioners or the social workers to record the patient’s vital sign measurements will be connected to the centralized server. The ambulance will also have a receiver device which will also be connected to GPS. This helps the server in locating the ambulances which are adjacent to the patient’s location. The ambulance which is prompt in responding will carry on the patient to the nearest hospital. The drones will be programmed to deliver medicines to the ambulance or even to the patients directly in case of emergency alert by the medical practitioners or the social workers. All the above services will be delivered by adopting shortest path or optimal path selection algorithm. There are wide range of this path finding and search algorithms like Dijkstra’s algorithm, Bellman Ford’s algorithm, Floyd-Warshall’s algorithm, AStar algorithm and several other benchmark algorithms from which the one which suits the model and the environment will be adapted. Besides these path finding algorithms, this model also propels dynamic collision detection and greedy path selection algorithms to support the successful delivery of medicines during emergency situations.
The implementation of drone services in India has legal constraints. Flying of drones without prior approval from the governmental authorities is illegal in India. The reason behind this strict restriction by the Director General of Civil Aviation (DGCA) is that the Unmanned Aviation (UA) operations would present problems to the regulator in terms of ensuring the safety of other users of airspace and persons on the ground. The usage of drones came under scrutiny after the realization that the drones can be used for aerial attacks and may pose a great threat if not regulated. This complication has to be solved by registering the drones with DGCA by following the stated guidelines.
The project will mainly use the Java programming language for mobile and server applications, server-side scripting languages like PHP, relational database language like MySQL and mark up languages for presentation. The project also makes use of some of the important predictive analytical tools and data science packages.
Project Community Discussion
Submission of Project Proposal
Project Material Acquisition
Develop and Enhance the IoT
Part of the proposal
Construct predictive models and
Machine learning algorithms on the
Data received from the sensors.
Extend the alert service with
Ambulance and drone services.
Enhancing the web and
Testing the functionality of the
Submit Final Report
EXPECTED OUTCOME AND RESULTS
Fig 5: Process Flow Diagram
The process starts off with the medical practitioners and social workers, measuring the vital signs of the patients periodically with the help of the sensors and the mobile app. The vital parameters measured will be transmitted to the centralized server deployed on the cloud using the wireless technology. The server runs diverse of algorithms as listed in Fig 3 on the data collected using the sensors. An alert classified as normal and critical alert will be generated accordingly to the doctors and the care takers on any abnormality. In case of emergency situations, the ambulance and drone services will be delivered to the patients promptly.
This proposal will produce an assistive technology for an early detection of fall and detection of abnormality in the vital parameters of the people in rural areas by deploying IoT technology. This proposal also involves effective collection of the patient’s health data using body sensors and stores it in the cloud. This proposal also involves the development of a mobile application for the social workers to verify the patient’s vital parameters, a mobile application for the doctors to view the details of the patient registered with them and also a web application to achieve the same. The data collected using the sensors are mined and analysed using suitable data mining and predictive analytical models to increase diagnoses efficiency. This proposal also ensures instant emergency services which includes alert service, ambulance service and drone service to the people in the rural villages.
The current working model has a suitable IoT based mechanism to collect health data using wearable medical devices through smartphones. The data is collected, viewed and stored using android apps. A working Open Source Cloud Server operating on OpenStack and Open Nebula has been used for the storage of data.
· This application promotes healthy lifestyle to rural people. Smartphones act as a general purpose computing device and bridges the gap between the doctors and the patients in rural areas.
· This proposal intends to provide constant monitoring of elderly patients in their area of living through social workers and local medical practitioners. Doctors can constantly take clinical measurements of the vital parameters like Blood Pressure, Heart Rate, Respiration Rate, SpO2 and can track any type of motion, abnormal patterns.
· This proposal helps in avoiding emergency situations by pre-empting the patients on any abnormalities before-handed using the complex algorithms running on our server.
· This proposal also ensures that in case of emergency, care-takers and doctors registered with the patient will be notified immediately through a voice message.
· The proposal also ensures real time location services with the help of mobile application developed.
· This proposal involves a tightened budget and at the same time have updated infrastructure to provide better healthcare services to the patients.
This proposal promises the deployment of cutting-edge technologies to comfort the people in rural India with regular health check-ups and remote monitoring. The lifestyle of the people in rural India can be highly improved at a tightened cost. The project also provides a descent money flow between the social workers, local medical practitioners and the Government. The communication pattern can be greatly improved between the doctors and the patients by imparting personalization of the patient’s data. This proposal would greatly impact hundreds of thousands of lives in rural India.