ppt seminar.pptx

SJM VIDYAPEETHA®
◦ S J M INSTITUTE OF TECHNOLOGY
Department of Computer science and Engineering
Technical Seminar on,
“SMART HEALTHCARE IN THE AGE OF AI”
PRESENTED BY UNDER THE GUIDANCE OF
SPOORTHI M Dr. KRISHNAREDDY K R
USN: 4SM21SCS01 PROFFESOR
M.Tech 2ND SEM CS & E BRANCH
CS & E BRANCH S.J.M.I.T.
S.J.M.I.T.


The significant increase in the number of individuals with chronic ailments (including
the elderly and disabled) has dictated an urgent need for an innovative model for
healthcare systems. The evolved model will be more personalized and less reliant on
traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes,
and long-term healthcare centres. The smart healthcare system is a topic of recently
growing interest and has become increasingly required due to major developments in
modern technologies, especially artificial intelligence (AI) and machine learning (ML).

CONTENT
 INTRODUCTION
 LITERATURE SURVEY
 HEALTHCARE MONITORING DEVICES IN IoT
 AI AND ML IN IoHT
 AMBIENT ASSISTED LIVING
 CHALLENGES AND FUTURE DIRECTIONS
 CONCLUSION
 REFERENCES

With the development of information technology, the concept of smart
healthcare has gradually come to the fore.
 Smart healthcare uses a new generation of information technologies, such as
the internet of things (IoT), big data, cloud computing, and artificial
intelligence, to transform the traditional medical system in an all-round way,
making healthcare more efficient, more convenient, and more personalized.
With a decline in the ratio between working-age people, fewer professional
healthcare workers for increased demand.

 The need for more caregivers and healthcare facilities increases to with-stand
the increase in demand – increase in cost
 A great candidate for such a situation is utilizing the recent advancements in
smart and miniaturized sensors, communication technologies, and artificial
intelligence to provide technological solutions at an affordable price to the
broadest range of the population without sacrificing the quality of care.
 Since around 90% of older adults prefer staying in their own homes, many
solutions are based on smart home systems.
The importance of including robotic agents capable of social interactions
with the user to provide both psychological and physical assistance to older
adults.

 The main aim is to explore the state-of-the-art smart healthcare systems
that highlight the significant areas of research, including wearable and
smartphone-based health monitoring, machine learning for predictive
analytics, and assistive frameworks developed for assisted living
environments, including social robots.
 Provide a systemic review of state-of-the-art research in smart medical
devices, machine learning for disease prediction, AAL, and software
architectures.

Davide Calvaresi and Daniel Cesarini [1] presents Exploring the ambient
assisted living domain
 The review indicates a clear need for: – rigorously evaluating and validating
both new and existing AAL solutions; – investigating and better understanding
the relationships among the actual user’s needs and the proposed solutions.
 In conclusion, a solution would be more effective if designed with less
technological and technical commitments, giving more room to the actual
‘‘needs/goal’’ analysis of the involved end users.
 For example, the evidence raised in this review suggests as promising future
direction the empowerment of the interaction among all the AAL actors
throughout a single solution, that, nowadays is still missing.

Amine Rghioui [2] presents Challenges and Opportunities of Internet
of Things in Healthcare
 This paper has described here that the healthcare system today is on a
trajectory that is unsustainable.
 The bulk of costs in the current system are due to patients having chronic
care diseases.
 Thus, a focus in the future should be on preventive care as well as
population health management and overall wellness.
 With Internet of Things, health management of a population can be
understood better.

Stephanie B. Baker; Wei Xiang; Ian Atkinson [3] presents Internet of
Things for Smart Healthcare: Technologies, Challenges, and
Opportunities.
 They have proposed a unique model for future IoT-based healthcare systems,
which can be applied to both general systems and systems that monitor specific
conditions.
 We then presented a thorough and systematic overview of the state-of-the-art
works relating to each component of the proposed model.
 Several wearables, non-intrusive sensors were presented and analyzed, with
particular focus on those monitoring vital signs, blood pressure, and blood
oxygen levels.
 The most significant drawback of using cloud is that it introduces security
risks, and as such we presented several works focused on improving security in
the cloud.

Wearable Devices for Health Monitoring:
 Useful demand Smart healthcare services using wearable sensors provide
an appropriate and cheaper alternative to the costly hospital environment.
 These systems enable medical professionals to screen the significant
symptoms of the patients evaluate the general health of the users, and
detect abnormalities remotely.
 There are many developed health monitoring systems considering some
properties like the used sensors and edge devices, the communication
channel, the data visualization tools for ensuring the real-time monitoring,
and comments.

Software Solutions for Health Monitoring
 The growing penetration of mobile phones, integrated sensors, and advanced
communication technologies makes it an appropriate infrastructure that allows
continuous and virtual monitoring of patients’ health.
 The built-in sensors in smartphones for health monitoring are a camera,
accelerometer, gyroscope, proximity sensor, microphone, light sensor, and
Global Positioning System (GPS).
 The major health parameters that can be monitored through smartphone sensors
are heart rate and variability, blood pressure, oxygen levels (SpO2), and
respiratory rate. They are used to identify skin, eye, ear diseases. As almost all
people are now using a smartphone, it has become a great choice to research
smartphone applications that ensure portability and reduce the additional cost
of the developed systems.

Novel Coronavirus (COVID-19):
 The novel coronavirus 19 has become a public health crisis due to this
virus’s communicable nature in recent times. This is an ongoing pandemic,
and all the sectors of the whole world are fighting to recover from this
ailment.
 The statistic shows that approximately 98 million cases have already
found, and the death cases are about 2 million worldwide. Numerous works
were conducted to reduce the severity of this disease using modern
technologies.
 In the current section, we describe the frameworks that used machine
learning algorithms to diagnose COVID-19 in IoT environments.

Heart Disease:
 Heart disease has become a very crucial and acute ailment for every aged
people, especially for adults. An estimation shows that heart disease is
responsible for approximately 30% (18 million individual) deaths among
all death cases per year.
 Hence, the researchers focus on the development decision support system
in the smart healthcare environment to reduce the severity of heart disease.
The significant developments of heart disease diagnosis using machine
learning in the IoT environment are demonstrated here.

Diabetes:
 Diabetes is another life-threatening disease for humankind that results in
many deaths per year. An estimation shows that almost 463 million
individuals had diabetes in 2019, and the numbers are expected to grow to
578 million and 700 million by 2030 and 2045, respectively.
 As this ailment is rising rapidly, early diagnosis of diabetes is necessary for
the sake of people. Various studies are conducted to diagnose diabetes
early, utilizing artificial intelligence, IoT, and big data.
 The works that have been developed recently for diabetes detection are
illustrated in this section.

The requirements of needs of older adults can be summarized as:
 Provide a natural means of interaction that require minimum to no learning
by the older adult.
 Remind the users of medications, appointments, and events.
 Provide infotainment services such as music, movies, and cognitive games.

 Provide a natural means of interaction that require minimum to no learning
by the older adult.
 Remind the users of medications, appointments, and events.
 Provide infotainment services such as music, movies, and cognitive games.
 Real-time monitoring of health vitals and detection of emergencies.
 Include a robotic platform for task achievement as well as social
companionship.

 A low-cost system to detect older adults’ activity and early signs of frailty.
using a Random Forest classifier.
 Indoor environmental monitoring system
 A mobile application called InfoSage.
Social Robots:
 Social Robot - can adapt to user’s preferences and includes human-robot
interaction (HRI), emotion and facial recognition, and speech interaction.
 Home Mate project
 Sympartner. - Robot companion for private homes

Smart healthcare provides a secure, effective, and easily deployable health
monitoring system that can ensure quality healthcare services at a fraction of
the cost currently incurred by hospitals or assisted living centers .
 Briefly discussed the state-of-the-art wearable devices and smartphones for
basic signs monitoring, machine learning for three significant diseases
(COVID-19, heart disease, and diabetes) diagnosis, and the frameworks
developed to aid the adults in ambient assisted living.
It is quite impossible to replace the whole medical system with technology,
but it can reduce the burden of medical experts by introducing some novel
architectures.

 D. Calvaresi, D. Cesarini, P. Sernani, M. Marinoni, A. F. Dragoni, and A. Sturm,
‘‘Exploring the ambient assisted living domain: A systematic review,’’ J. Ambient
Intell. Humanized Comput., vol. 8, no. 2, pp.239–257, Apr. 2017
 A. Rghioui and A. Oumnad, ‘‘Challenges and opportunities of Internet of Things in
healthcare,’’ Int. J.Electr. Comput. Eng., vol. 8, no. 5, p. 2753, Oct. 2018
 S. B. Baker, W. Xiang, and I. Atkinson, ‘‘Internet of Things for smart healthcare:
Technologies,challenges, and opportunities,’’ IEEE Access, vol. 5, pp. 26521–
26544, 2017.
 H. Zhu, C. K. Wu, C. H. Koo, Y. T. Tsang, Y. Liu, H. R. Chi, and K.-F. Tsang,
‘‘Smart healthcare in the Era of Internet-of-Things,’’ IEEE Consum. Electron.
Mag., vol. 8, no. 5, pp. 26–30, Sep. 2019.

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