Research IoT, which has widespread application in various

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Last updated: December 25, 2019

Research gap Over the years the use of technologies and advancement in medical field has improved the life expectancy of people globally and has increased the proportion of elderly people. People aged 65 or older fall in the elderly people group and in the year 2010, eight percent of the world population were in this group which is around an estimate of 524 million people. By the year 2050, this number is expected to raise to 1.

5 billion people in the world which is around 16 percentage of the world’s population. According to the Association of American Medical Colleges, the increasing demand for healthcare will cause a shortage of 124 400 physicians by 2025. The percentage of elderly people in developed nations are way too less when compared to developing nations.

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Its heartening to see the increase in life expectancy and more people living beyond the age of 65, however the question is, are they healthy or are they suffering from disabilities. It is a concern to see that the percentage of people living without disabilities are equal to the percentage of people living with disabilities. Irrespective of whether they suffer from disabilities or not, loneliness glooms on the elderly people and for many due to their disabilities they are isolated in the society. To assist  the elderly and to support them to have a better comfortable life, technology can be used effectively to facilitate. With the emergence of IoT, which has widespread application in various fields like agriculture, transportation, smart parking, water usage management, is currently being researched to be used in healthcare. Smart healthcare can be implemented to constantly monitor the vital signs of elderly and will assist the medical practitioner and family members to support in providing medication.

The crucial parameters  for an efficient smart healthcare system are low power consumption, small form factor, system reliability, quality of service, enriched user experience, higher efficien­cy, ability to interoperate across multiple platforms, ease of deployment, scalability of the system to upgrade to newer versions and technologies as well as to accommodate new feature, and provide ample con­nectivity. Smart healthcare solutions for older adults can be categorised into health monitoring, nutrition monitoring, safety monitoring, and localization and navigation.The following are the gaps in the current smart care solutions which shall be bridged to provide an effective and robust healthcare solution:  1. Health monitoring – For monitoring health and various vital signs and movements, IoT based system can be used extensively. This facilitates in monitoring and obtaining values from indoor activities as well as from outdoor activities seamlessly.

Since, data are received from heterogeneous devices there is a need to convert into a common format without any loss. The sensor devices capture data on predefined interval and are to be integrated well so that vital data are not missed. The received data are to be stored in a common storage for processing. Cloud computing can be used to address the computational and storage needs.

Use of big data analytics will facilitate in better interpretation of the observed data and will assist in providing the needed care. The effective utilisation of big data analytics shall facilitate in handling huge volume of data from multiple IoT devices and would also assist in taking decision based on the historical data and current data.2.

Long term monitoring – Certain diseases / medical conditions like impairments and chronic diseases are to be monitored throughout the lifespan or for a long period of time. The data which are collected with respect to these conditions cannot be archived but would be needed anytime to take a well informed decision. Since, the data will be captured from multiple IoT devices, enormous volume of data will be generated which must be processed and then stored at the appropriate device occupying minimal space.

3. Emergency monitoring – Elderly adults are prone to medical accidents as well as environmental accidents. A remote monitoring system which can detect such accidents and which will pass on the information immediately to the medical caregivers will minimize the damage. This can be achieved by reducing the latency incurred in the transmission of data. The features of fog computing can be integrated to the cloud which in turn increase the processing of data at various regions in the network to minimize the overhead of data transmission.4.

Personalized monitoring – Personalized monitoring is vital for older people and can be done through big data analytics. However, a finer solution can be provided by using artificial intelligence and machine learning techniques. 5. Securing data and systems – Medical information is vulnerable to security breaches due to its potential for identity theft, fraud and abuse. By using IoT and Cloud, the amount of data generated is enormous. Hence, data security shall be provided at each level in the system during transmission and also at the storage.

          Identification of Research Problem People will be in control of their health if they are provided with healthcare resources with needed information. Also, the burden on hospitals will be reduced if non critical patients are monitored continuously and treated at home. Let’s take the case of chronic health issue like hypertension, using multiple sensors attached to the body, the pressure can be measured and sent to the cloud. Medication can be provided effectively using machine learning techniques from the stored information. Critical health vitals can also be monitored using a system comprising of wearable sensors that monitor vital and other important signs, including pulse, respiratory rate, body temperature, and blood pressure.

These healthcare scenarios pave way for ample amount of research to be carried out from fetching of needed data to processing and providing care. The following major challenges in the field of healthcare which can be worked:1. The continuous real time monitoring is done through heterogeneous sensors. However, all these sensors are to communicate the information to the controller. Research work has to be done to improve the quality of sensors to ensure its easily wearable, reliable and reads data with high accuracy. Keeping this concept in mind, monitor to read blood pressure and other body vitals can be designed. 2.

Short distance communication and long distance communication is used to transfer the data from the sensors. NB-IoT is an emerging standard and the viability of this standard shall be examined in healthcare usage. Performance evaluation of NB-IoT with existing communication algorithm shall be done and it’s suitability for healthcare shall be verified.

 3. It is the cloud controller which does the task of mapping the application services to physical infrastructure. While doing the mapping there are several expected targets like, to accept more service needs simultaneously to increase the income of the cloud supplier, using minimal servers to accomplish the task to save energy and also to balance the load of the servers through equal mapping of the service demand to the available servers. However, the expected targets are contradictory to each other. Hence, necessary architectural changes and suitable algorithms are needed to meet the mentioned expectations.4. Machine learning is not widely used in healthcare yet. The benefits of machine learning can be applied in high power computing to develop treatment methodologies and also will assist in making new discoveries about disease trends.

5. In a cloud based healthcare system, much focus shall be given in improving the security and privacy of data. ABE and FHE are schemes which are not lightweight but provide appealing characteristics.

Improving these schemes is an area of focus.6. Developing an end-to-end system for general or specific purposes that contains all components; wearable sensors, short- and long-range communications, cloud-based storage, and machine learning.Literature Review 1. Ted Cohen et al (2004), explained the convergence between clinical and information technologies. This paper elaborates the evolution of IT in healthcare from primarily business-related applications to a large variety of clinically relevant information systems such as integrated electronic medical records (EMR), picture archiving communication systems (PACS), telemedicine etc,.

In future IT and clinical staff would work together without technological boundaries to support the complex healthcare environment and would provide the patients with the best possible technological healthcare solutions. In-text CitationA short statement explaining the main purpose of each referenceA short summary of the theory and research findingsConsideration of the usefulness and limitations of the workA sentence on your view or reaction to the work mentioned in each referencePurpose of your ResearchRationale for your ProjectYour project JustificationGap in the knowledge, research problem/questionsMethodology (what will be done and how)Expected outcomesLimitations and ethical implicationsTimelines of your project (how long it will take and what will be covered and when)Reference list of your project

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