Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications

310 Pages·2020·9.944 MB·English

by  Aboul Ella Hassanien, Roheet Bhatnagar, Ashraf Darwish

Studies in Computational Intelligence 912
Aboul Ella Hassanien
Roheet Bhatnagar
Ashraf Darwish   Editors
Artificial
Intelligence
for Sustainable
Development:
Theory, Practice and
Future Applications
Studies in Computational Intelligence
Volume 912
Series Editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
The series “Studies in Computational Intelligence” (SCI) publishes new develop-
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Aboul Ella Hassanien Roheet Bhatnagar
(cid:129) (cid:129)
Ashraf Darwish
Editors
fi
Arti cial Intelligence
for Sustainable Development:
Theory, Practice and Future
Applications
123
Editors
AboulElla Hassanien RoheetBhatnagar
Information Technology Department, Department ofComputer Science
Faculty of Computers andInformation andEngineering, Faculty of Engineering
CairoUniversity Manipal University
Giza, Egypt Jaipur,Rajasthan, India
Ashraf Darwish
Faculty of Science
HelwanUniversity
Cairo, Egypt
ISSN 1860-949X ISSN 1860-9503 (electronic)
Studies in Computational Intelligence
ISBN978-3-030-51919-3 ISBN978-3-030-51920-9 (eBook)
https://doi.org/10.1007/978-3-030-51920-9
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Preface
Currently,AIisinfluencingthelargertrendsinglobalsustainability;itcouldplaya
significantrolewherehumanityco-existsharmoniouslywithmachines,orportenda
dystopianworld filledwithconflict,povertyandsuffering. Itwouldalsoaccelerate
ourprogressontheUnitedNationsSustainableDevelopmentGoals(SDGs).Inthis
context, the SDGs are defining the development goals for the countries of the
world, and AI is rapidly opening up a new ways in the fields of industry, health,
business, education, environment and space industry. As a result, AI has been
incorporated in various forms into the SDGs through experimentation and in sus-
tainable management and leadership programmes. Therefore, there are many
countries all over the world started to establish nation AI strategies.
AI, when is applied for sustainability inducing applications and projects, will
present massive and geographically wide-ranging opportunities, enable more effi-
cient and effective public policy for sustainability, and will enhance connectivity,
access and the efficiency in many different sectors.
The academic community has an important role to play to be ready for this AI
revolution, in preparing the future generations of national and international
policy-makers and decision-makers in addressing the opportunities and the chal-
lenges presented by AI and the imperative to advance the global goals. In this
regard, AI for sustainability is challenged by large amount of data in machine
learning models, increased cybersecurity risks and adverse impacts of AI
applications.
This book includes future studies and researches of AI for sustainable devel-
opment and to show how AI can deliver immediate solutions without introducing
long-term threats to environmental sustainability.
Thisbookaimsatemphasizingthelatestdevelopmentsandachievementsinthe
field AI and related technologies with a special focus on sustainable development
and eco-friendly AI applications. The book describes theory, applications and
conceptualization of ideas and critical surveys which are covering most of aspects
ofAIforSDGs.Thisbookwillhelptoidentifythoseaspectsofconnectedsmarter
world that are key enablers of AI sustainable applications and its sustenance as a
futuristic technology.
v
vi Preface
Thecontentofthisbookisdividedintofourparts:firstpartpresentstheroleand
importance of AI technology in agriculture sector as one of the main SDGs.
Healthcare sector is considered as one of the important goals of SDGs. Therefore,
secondpartdescribesandanalysestheeffectiveroleofAIinhealthcareindustryto
enable countries to overcome the developing of diseases and in crisis times of
pandemicsuchasCOVID-19(Coronavirus).Thirdpartintroducesthemachineand
deeplearningasthemostimportantbranchesofAIandtheirimpactinmanyareas
ofapplicationsforSDGs.ThereareotheremergingtechnologiessuchasInternetof
Things,sensornetworksandcloudcomputingwhichcanbeintegratedwithAOfor
thefutureofSDGs.Asaresult,thefourthpartpresentstheapplicationsofthemost
merging technologies and smart networking as integrated technologies with AI to
fulfil the SDGs.
Finally, editors of this book would like to acknowledge all the authors for their
studiesandcontributions.Editorsalsowouldliketoencouragethereadertoexplore
and expand the knowledge in order to create their implementations according to
their necessities.
Book Editors
Giza, Egypt Aboul Ella Hassanien
Jaipur, India Roheet Bhatnagar
Cairo, Egypt Ashraf Darwish
Contents
Artificial Intelligence in Sustainability Agricultures
Optimization of Drip Irrigation Systems Using Artificial Intelligence
Methods for Sustainable Agriculture and Environment. . . . . . . . . . . . . 3
Dmitriy Klyushin and Andrii Tymoshenko
Artificial Intelligent System for Grape Leaf Diseases Classification . . . . 19
Kamel K. Mohammed, Ashraf Darwish, and Aboul Ella Hassenian
Robust Deep Transfer Models for Fruit and Vegetable Classification:
A Step Towards a Sustainable Dietary. . . . . . . . . . . . . . . . . . . . . . . . . . 31
Nour Eldeen M. Khalifa, Mohamed Hamed N. Taha,
Mourad Raafat Mouhamed, and Aboul Ella Hassanien
The Role of Artificial Neuron Networks in Intelligent Agriculture
(Case Study: Greenhouse) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Abdelkader Hadidi, Djamel Saba, and Youcef Sahli
Artificial Intelligence in Smart Health Care
Artificial Intelligence Based Multinational Corporate Model for EHR
Interoperability on an E-Health Platform . . . . . . . . . . . . . . . . . . . . . . . 71
Anjum Razzaque and Allam Hamdan
Predicting COVID19 Spread in Saudi Arabia Using Artificial
Intelligence Techniques—Proposing a Shift Towards a Sustainable
Healthcare Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Anandhavalli Muniasamy, Roheet Bhatnagar,
and Gauthaman Karunakaran
vii
viii Contents
Machine Learning and Deep Learning Applications
A Comprehensive Study of Deep Neural Networks for Unsupervised
Deep Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Deepti Deshwal and Pardeep Sangwan
An Overview of Deep Learning Techniques for Biometric Systems . . . . 127
Soad M. Almabdy and Lamiaa A. Elrefaei
Convolution of Images Using Deep Neural Networks
in the Recognition of Footage Objects . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Varlamova Lyudmila Petrovna
A Machine Learning-Based Framework for Efficient LTE
Downlink Throughput . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
Nihal H. Mohammed, Heba Nashaat, Salah M. Abdel-Mageid,
and Rawia Y. Rizk
Artificial Intelligence and Blockchain for Transparency
in Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
Mohammed AlShamsi, Said A. Salloum, Muhammad Alshurideh,
and Sherief Abdallah
Artificial Intelligence Models in Power System Analysis . . . . . . . . . . . . 231
Hana Yousuf, Asma Y. Zainal, Muhammad Alshurideh,
and Said A. Salloum
Smart Networking Applications
Internet of Things for Water Quality Monitoring and Assessment:
A Comprehensive Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Joshua O. Ighalo, Adewale George Adeniyi, and Goncalo Marques
Contribution to the Realization of a Smart and Sustainable Home . . . . 261
Djamel Saba, Youcef Sahli, Rachid Maouedj, Abdelkader Hadidi,
and Miloud Ben Medjahed
ApplianceSchedulingTowardsEnergyManagementinIoTNetworks
Using Bacteria Foraging Optimization (BFO) Algorithm. . . . . . . . . . . . 291
Arome Junior Gabriel
Artificial Intelligence in Sustainability
Agricultures