Internet of Things and Analytics for Agriculture, Volume 2

297 Pages·2020·12.563 MB·English

by  Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal

Studies in Big Data 67
Prasant Kumar Pattnaik
Raghvendra Kumar
Souvik Pal   Editors
Internet
of Things
and Analytics
for Agriculture,
Volume 2
Studies in Big Data
Volume 67
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Prasant Kumar Pattnaik
(cid:129)
Raghvendra Kumar Souvik Pal
(cid:129)
Editors
Internet of Things
and Analytics for Agriculture,
Volume 2
123
Editors
PrasantKumar Pattnaik Raghvendra Kumar
Schoolof Computer Engineering Department ofComputer Science
KIIT Deemed tobeUniversity andEngineering
Bhubaneswar, Odisha, India LNCT College
Jabalpur, MadhyaPradesh, India
SouvikPal
Department ofComputer Science
andEngineering
Brainware University
Kolkata, West Bengal, India
ISSN 2197-6503 ISSN 2197-6511 (electronic)
Studies in BigData
ISBN978-981-15-0662-8 ISBN978-981-15-0663-5 (eBook)
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Preface
The main aim of this book is to bring together leading academic scientists,
researchers, and research scholars to exchange and share their experiences and
research results on all aspects of wireless IoT and analytics for agriculture. It also
provides a premier interdisciplinary platform for researchers, practitioners, and
educators to present and discuss the most recent innovations, trends, and concerns
as well as practical challenges encountered and solutions adopted in the fields of
IoT and analytics for agriculture. This book is organized into 13 chapters.
Chapter “IoT-Based Soil Health Monitoring and Recommendation System”
discussesasoilhealthmonitoringsysteminwhichafarmerwillbeabletomonitor
soil moisture, soil temperature, and soil pH in his android smartphone. The farmer
willalsogettherecommendationsoflimeandsulfuronthebasisofpHofthesoil.
The area of study is Jaipur, Rajasthan (26.9124° N, 75.7873° E). The proposed
system is tested with the results taken from authorized laboratories. The proposed
system is validated with T-test having no significant difference between calibrated
values and laboratory recorded values. The proposed system is implemented on
android smartphone, so it is useful to farmers, agriculture scientists, agriculture
professionals, and IoT experts.
Chapter “Implementing IoT and Wireless Sensor Networks for Precision
Agriculture” affords the deployment of an Internet of things (IoT)-based precision
agriculture technology using wireless sensor networks (WSNs) in crop manage-
ment. Anonlinecropmanagement system (OCMS)was developedtocomplement
theIoT platform layer. The application aimed atproviding thefarm environmental
conditions including the temperature, water level, pH value, and dissolved oxygen
measurements from the paddy field with food crops and horticulture crops being
grown. Further studies could be done by analyzing the inter- and intra-field vari-
abilities such as soil herbicide weed control, side dressing, late blight control, and
haulm killing.
Chapter “Bayesian Network for Development of Expert System in Pest
Management” discusses the application of Bayesian network which may greatly
assist in development of innovative methods of selecting appropriate management
option based on uncertain or tentative information of identified agroecological
v
vi Preface
factorsbesidescropconditionthatfarmersprovide.Applicationofthemethodsthus
developed in information and communication technology (ICT)-based expert sys-
tems (ESs) of agriculture would automate and speed up the process of providing
real-time decision support on insect pest management to the farmers.
Chapter “An IoT and Wireless Sensor Network-Based Technology for a
Low-Cost Precision Apiculture” presents the foundational space of apiculture,
challenges, and emerging techniques of the apiarists in beekeeping including pre-
cision apiculture and a low-cost IoT and remote sensing technology deployed for
data gathering and monitoring the vigor and productivity of beehive colonies. The
system has redundancy components and utilized the three-level hierarchical model
including wireless node, local information server, and the cloud data server. The
system also consists of sensors deployed across distinct locations to capture the
beehives’ temperature, relative humidity, and loads of the hives and honeycombs,
and the information is stored to the local and cloud server. This system will
complement the urgent need to countervail the honeybee colonies' collapse by
helping the apiarists, apiculture sub-sector, and agriculture sector to embark
emerging precision apiculture technologies.
Chapter“AdaptiveEncryptionTechniqueforCollaborativeCloudEnvironments”
presentsarealisticsolutiontotheproblemwherenumericdataaretransformedinto
alphanumeric types, and hence, there is minimal probability of storing encrypted
data in the existing numeric field. The proposed algorithm allows translucent
verification of intensity encryption that does not modify the data field category or
the fixed time span.
Chapter“RoleofInternetofThingsandITinHealthCare”exploresindepththe
importance of the Internet of things devices in health care and also the role of
information technology in managing the massive volume of high-security medical
information of patients. This chapter proposes few IoT applications in rural health
care and ways to boost primary health desires of the developing nations.
Chapter “Adopting Big Data Analysis in the Agricultural Sector: Financial and
SocietalImpacts”summarizesthestate-of-the-artanalyticalmethodsthathavebeen
recently used in the agriculture industry, along with their financial and societal
impacts.
Chapter “AI-Based Yield Prediction and Smart Irrigation” acknowledges the
past breakthroughs and emerging artificial intelligence-based techniques in preci-
sion farming specifically for yield prediction and smart irrigation. Artificial
intelligence-based system provides sufficient information about crop yields at an
early stage, and its associated smart irrigation management system is effective in
judicious use of essential resources such as water and energy for agriculture.
Chapter “IoT-Based Smart Tree Management Solution for Green Cities” dis-
cusses key challenges faced by transformation of smart cities and integration of
greentechnologies,initiatives,andexistingsystemsthatareinplacetosolvethese
challenges. With overpopulation, fast urbanization, and environmental changes,
powerfuladministrationoftreesandplantsisrequiredlikeneverbefore.Wepresent
Preface vii
an Internet of things (IoT)-based smart tree management architecture for cities
whichisabletotrackvariouscharacteristics ofagiventreesuchastheairquality,
sunlightlevel,soundpollutionlevel,andotherimportantcharacteristicsforefficient
city planning, afforestation plans, and higher-quality produce.
Chapter“DataAnalysisandPredictionUsingBigDataAnalyticsinAgriculture”
iscomposedoffoursections.Thefirstsectionprovidesanoverviewofanalyticson
bigdatainagriculture.Thisisfollowedbythesecondsectionwhichhighlightsthe
different big data techniques in agriculture. The third section describes two case
studies that apply techniques for big data analysis in the agricultural domain. The
fourth section analyzes the various research areas related to agriculture that can be
explored by the academicians and researchers. The summary of the chapter is
provided at the end.
Chapter “Generic IoT Platform for Analytics in Agriculture” aims in creating a
universal platform used especially in the field of agriculture for data transmission
and reception from various sensors and plotting the statistical graphs on a dash-
board.Apartfromthisasapurposeofprovidingeasyusageandextensibility,smart
devices can also be installed, which provide the plug-and-play capability of our
system.
Chapter “Mission SDGs Through Food Waste Management: Nature and
Approaches” attempts to assess and account the loss of economy for wastage of
fooditems from globalcanvas tonationalperspective.Thisstudyhasalso focused
on how to use IoT platform so that the food wastage can be reduced up to a
considerable amountboth inthesupplychain and eveninthehouseholdpractices.
Thisresearchworkisbasedonsecondaryinformationlikeresearchpapers,reports,
and results of other relevant studies. The chapter has attempted to develop and
devise a conceptual and strategic model where the IoT ecosystem can be incor-
poratedtoensurereal-timesolutionsandtocurbonmassivefoodwastagepractices.
If the model is implemented and practiced with appropriate case-specific modifi-
cationsandcustomizations,itwouldmaketheeconomymoreefficientandaddress
different perspectives and dimensions of UN Sustainable Development Goals
(UNSDGs) to a larger extent primarily in the Indian context.
Chapter “Frost Prediction in Highland Crops Management Using IoT-Enabled
System and Multiple Regression” discusses the concepts of precision agriculture,
applicationsoftheInternetofthings(IoT)inagriculture,thedesignandchallenges
of an IoT-enabled system for highland crop management, and utilized multiple
regression as a frost prediction technique. The remote sensing devices deployed in
the farm collect the frost climatic events including air velocity, temperature, and
humidity, and transmit the information to the Web server. The system provides
early warnings and frost forecast for the farmers using SMS. The system helped
farmers as a useful resource to conduct frost protection activities on the farm,
thereby reducing the frost harm to the crops.
We are sincerely thankful to the Almighty for supporting and standing at all
times with us, whether it is good or tough times and given ways to concede us.
Startingfromthecallforchapterstillthefinalizationofchapters,alltheeditorshave
giventheircontributionsamicably,whichisapositivesignofsignificantteamwork.
viii Preface
The editors are sincerely thankful to all the members of Springer, especially Prof.
Aninda Bose for the providing constructive inputs and allowing an opportunity to
edit this important book. We are equally thankful to reviewers who hailed from
differentplacesinandaroundtheglobe,sharedtheirsupport,andstoodfirmtoward
quality chapter submission.
Bhubaneswar, India Prasant Kumar Pattnaik
Jabalpur, India Raghvendra Kumar
Kolkata, India Souvik Pal
Contents
IoT-Based Soil Health Monitoring and Recommendation System. . . . . . 1
Vaibhav Bhatnagar and Ramesh Chandra
Implementing IoT and Wireless Sensor Networks for Precision
Agriculture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
D. D. Dasig Jr.
Bayesian Network for Development of Expert System in Pest
Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Niranjan Singh and Neha Gupta
An IoT and Wireless Sensor Network-Based Technology
for a Low-Cost Precision Apiculture . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
D. D. Dasig Jr. and J. M. Mendez
Adaptive Encryption Technique for Collaborative Cloud
Environments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Y. Harold Robinson, E. Golden Julie and A. Vegi Fernando
Role of Internet of Things and IT in Health Care . . . . . . . . . . . . . . . . . 119
Rohit Sharma and Rajendra Prasad Mahapatra
Adopting Big Data Analysis in the Agricultural Sector:
Financial and Societal Impacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Rasha Kashef
AI-Based Yield Prediction and Smart Irrigation . . . . . . . . . . . . . . . . . . 155
Deepak Sinwar, Vijaypal Singh Dhaka, Manoj Kumar Sharma
and Geeta Rani
IoT-Based Smart Tree Management Solution for Green Cities . . . . . . . 181
Bilal Shabandri, Sahith Reddy Madara and Piyush Maheshwari
ix