Adoption of The IoT in Agriculture and Smart Farming - 1556640764
Adoption of The IoT in Agriculture and Smart Farming - 1556640764
Adoption of The IoT in Agriculture and Smart Farming - 1556640764
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This review provides an overall picture of currently Fertilizer also plays a very significant role in the field of
developed IoT applications in agriculture and farming agriculture by helping to increase the productivity of plants
between 2016 and 2018. [36]. By using IoT, farmers can manage soil condition more
effectively and at less expense by monitoring them from any
As a solution to the existing problems, researchers have location [37]. The primary objective of this study is how IoT
focused on smart agricultural and farming automated systems and technologies are used in conserving water, fertiliser and
with the help of IoT [7], [8], [9], [10]. IoT is the network of energy in the agricultural industry by combining new
things which identifies elements clearly with the help of technologies. This has benefits for the development of the
software intelligence, sensors and ubiquitous connectivity to economy of countries as well as the wealth of the people [38].
the Internet. In IoT, the data that collects from Internet- With the combination of both advanced technologies in
connected items or things contains with gadgets, sensors and hardware and software, IoT can track and count all relevant
actuators [1]. Many researchers have focused on smart aspects of production which can reduce the waste, loss and
systems for monitoring and controlling agricultural parameters cost [39]. The information needed to make smart decisions can
by enhancing productivity and efficiency. Smart systems be obtained merely by using electronic devices [40]. IoT
collect data for measurements to get accurate results that can transforms the agricultural industry and enables farmers to
lead to appropriate actions. Current use of smart agricultural overcome different challenges. Innovative applications can
systems relates to collecting data on environmental parameters address these issues and therefore increase the quality,
such as temperature, humidity, soil moisture and pH [11], quantity, sustainability and cost-effectiveness of crop
[12], [13]. With accurate sensor data collection using a range production [41], [42], [43]. IoT provides more benefits to the
of different sensors, researchers have implemented smart farming industry by improving the health of animals through
agricultural systems to make the farm process more effective better food and environment, addressing the labour shortage
[9], [14]. Research has mainly focused on sub-verticals such issue as well cost savings through automation, increase in milk
as water management, crop management and smart farming to production, and increase in some animals during the breeding
make processes automated by reducing human intervention,
period through detection of estrus cycle and additional
costs, power consumption and water consumption. revenue streams from waste.
The automation process of agricultural and farming Our study has analyzed recently developed IoT
reduced human interaction and improve the efficiency. The applications in the fields of agriculture and farming to address
reason for that is every country population depends on current issues such as unnecessary human interaction leading
agriculture thus consumers of these resources should use water to higher labour cost, unnecessary water consumption and
and land resources optimally [19], [20]. Moreover, it is water-saving measures for the future, higher energy
imperative to have good quality production and crop consumption, energy-saving measures for the future and crop
management in order to maximize profitability. Hence, IoT monitoring difficulties. According to our analysis, we can
base agricultural management systems are integral for an identify a focus on water and crop management as sub-
agriculturally based country. The new systems developed verticals in the agriculture and farming sectors. This survey
using IoT technologies have reduced the drawbacks associated also focusses on other agriculture and farming sub-verticals to
with traditional approaches and provided many advantages to identify the gap between IoT application developments in the
farmers. For example, IoT-based water management systems least researched areas. The IoT generates enormous data, so-
collect environmental attributes such as temperature, water called big data (high volume, at a different speed and different
level and humidity through the sensors and provide accurate varieties of data) in varying data quality. Analysing the IoT
irrigation timing [19], [21]. In addition, crop management system and its key attributes are the key to advancing smart
systems developed using IoT monitor the temperature, IoT utilization. Therefore, the primary aim of our paper is to
humidity and soil through sensors thus providing adequate explore recently created IoT applications in the agriculture and
information so that farmers can manage the crops farming industry to give the more profound understanding
appropriately [25]. Overall, these IoT-based systems help to about sensor data collection, used technologies, and sub-
reduce human interaction, power utilization and reduce cost in verticals, for example, water and crop management. The
the field of agriculture. Moreover, IoT-based agricultural secondary aim of this study is to analyse the current issues
related applications have been used in the area of pest control, such as higher human interaction, high labour cost, higher
weather monitoring, nutrient management and greenhouse water consumption and save water for future, higher energy
management. consumption and save energy/electricity for future, crop
IoT for agriculture uses sensors to collect big data on the monitoring difficulties in IoT for agriculture and farming.
agricultural environment. It discovers, analyses and deals with The remainder of this paper is as follows: In Section II we
models built upon big data to make the development of include raw data collection methodology, data inclusion
agriculture more sustainable [34]. IoT can provide efficient
criteria, and data analysis methods. Finally, the results of
and low-cost solutions to the collection of data. Weather, Agriculture and Farming based on IoT Sub verticals, Sensor
Water Scarcity, Soil fertility and Pesticides are the significant Data, and Technologies are presented in Section III, and in
players in it. IoT will make agriculture beneficiary. Section IV we discuss the results. Section V concludes the
Agriculture and farming depend on water [35]. Farmers paper. The raw data collected from 60 peer-reviewed
depend on rainfall for all their agricultural needs. publications used in this paper are summarised in Table I.
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30
25
Percentage %
20
15
10
5
0
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25
Percentage %
20
15
10
Sensor Data
Fig. 2. Utilization of Sensor Data based on Farming Activities Referred to in the Data Pool of 60 Peer Reviewed Published Articles.
35%
30%
Precentage %
25%
20%
15%
10%
5%
0%
ZigBee
Bluetooth
RFID
GPRS
LAN
Wi-fi
Raspberry pi
LoRa
Radio Communication
Mobile Technology
Wireless Sensor
Network (LPWAN)
Network
Technologies
Fig. 3. Overview of different Technologies Referred to in the Data Pool of 60 Peer Reviewed Published Articles and Frequency of Mentions Shown in Order of
High Frequency to Low.
80
70
60
Percentage %
50
40
30
20
10
0
Agriculture Farming
IoT Vertical
Fig. 4. Overview of Comparing the usage of Internet of Things in two Verticals as Agriculture and Farming in 60 Peer-Reviewed Research Articles to
understand which is mostly used Internet of Things from Year 2016-2018.
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TABLE I. IOT IN AGRICULTURE AND FARMING CRITERION-APPROACH-DATA EXTRACTED FROM 60 SCIENTIFIC ARTICLES IN 2016-2018
Benefits of Challenges in
N Year/Autho IoT Sub Measures (Data Technologie Solution for Drivers of Applicatio
Proposed Current
o r Verticals collection) s Used Current Issues IoT n
System Approach
Can detect
the
Detect
temperature,
Human temperature, Can deploy
humidity
Raspberry interaction humidity, it in any
Environmental and
Venkate pi Labour cost moisture using type of
Water temperature moisture.
et al Wi-Fi. Wastage of sensors. environmen Agricultu
1 Managem Humidity Continuous
(2017) RFID water Maximize the t for, re
ent Soil monitoring
[1] Bluetooth Crop from yield of crop monitoring
moisture all the
Zigbee abnormal by monitoring flexibility
places
irrigation. agricultural robust
including
parameters.
critical
areas.
Irrigation
process is
completely
controlled
by
Predict and
computer-
tackle
based
drought
systems.
Pest Only works Low cost situations
System
controllin Soil moisture based on Efficient to prevent
Athira et al analyses the
g Temperature ZigBee the commands growth of to loss of Agricultu
2 (2017) weather
Weather Water level from user crops crops. re
[2] reports.
monitorin Faster growth Keep
Keep pest
g of plants. monitoring
away from
climate
the crops.
conditions.
Help to
faster the
growth of
plants.
Power
efficient.
Minimize the
To identify the cost of
appropriate deployment
time and in the and Users can
right amount maintenance. remotely
Can utilize
Zhao et al Water LoRa of water. More efficient. access
the water Agricultu
3 (2017) Managem Water level technology High power Cover wider irrigation
usage. re
[3] ent consumption. area than system and
High cost. ZigBee and check the
Low coverage Wi-Fi. status.
of ZigBee and Energy
Wi-Fi. consumption is
low.
Lessen the
human Higher the
intercession. Save water for revenue by
Flood
Lessen the the future. faster the
Sagar S et al Mobile avoidance.
Flood Water level probability Save growth of Agricultu
4 (2017) technology Power cutoff is
Avoidance Soil moisture of the flood electricity for crops. re
[4] being reduced.
occurrences. the future. Ensure the
Faster the durability
growth of of the soil.
the crops.
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Lessen the
Wireless
Water level. human The water
sensor
Soil interaction. High water consumption is Reduced
Saraf et al Water network.
Moisture. Efficiently consumption. reduced. water Agricultu
5 (2017) Managem ZigBee.
Environment managed the Human Lessen the consumptio re
[5] ent Mobile
temperature. irrigation interaction. human n.
technology
Humidity water interaction.
.
system.
Captured
moisture
No attention to
values
water Water
stored in
management. requirements
Wi-Fi Broader the cloud.
No economic monitored.
Soil Moisture Mobile coverage. Compare
Upadhyaya et Water feasibility. Immediate
Water technology Notify user captured Agricultu
6 al (2017) Managem Complicated notification
requirements when any values with re
[6] ent data for sends to
change predefined
understanding. farmer.
happens. moisture
Data display is User friendly
values.
not user data collection.
Used solar
friendly.
powered
battery.
Monitor
plants
through
Raspberry
Udhayakuma Soil moisture smart Overhead Analyze
Water pi Watering crop
r S et al Environment mobile. sprinklers. moisture Agricultu
7 Managem Mobile without human
(2017) temperature. Efficient Wastage of level of re
ent technology interaction.
[7] Humidity water water. ground.
supply
management
.
Higher the Farmers can
crop. Hard to water know field
Efficient to crop equally status even
Soil moisture water due to unequal they are at Automatic
Kumar et al Water Mobile
Environment supply. rain water home. plan Agricultu
8 (2017) Managem technology
temperature. Reduced distribution. Efficient water watering re
[8] ent
Humidity cost. Amount of management. system.
Resource water not Provide real
optimization defined. time
. information.
Can monitor
whether
conditions.
Cost Whether
Environment Raspberry Low or high
Nutrient effective conditions Can
Mathew et al temperature. pi watering.
Managem Automatical detected. enhance the Agricultu
9 (2017) Humidity Mobile Lack of
ent ly Enhanced the fertilizer re
[9] Nitrogen level technology nutrition
monitored fertilizer amount.
Prosperous level Wi-Fi management.
disease amount.
associated
with rice
species.
Temperature Cost
Higher water
Moisture level effective.
consumption. Reduced water Automated
Suhas et al Water Humidity Bluetooth High
High power consumption. water Agricultu
10 (2017) Managem Light Intensity Wi-Fi efficient
utilization. Better power supply re
[10] ent Nitrogen, water
Lack of useful utilization. system.
Phosphorus management
inference.
Potassium .
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Reveals the
positive
comparison
Efficient Managed water results
Wicha et al Water
Soil level Wi-Fi water High water system from the Agricultu
11 (2017) Managem
Temperature management consumption. effective adaptive re
[11] ent
. manner. Wetting
Front
Detector
(WFD).
Due to
Increase the
improper
crop
maintenance, Enhance the Interfacing
production.
Rajakumar et Mobile the crop crop. different
Crop Soil level Can get Agricultu
12 al (2017) technology becomes Control the soil
production Soil nutrient current re
[12] damaged agricultural nutrient
fertilizer
which causes a product costs. sensors.
requirement
huge loss for a
s.
farmer.
Temperature
Humidity Poor risk
Seed
Soil Enhanced management.
recognition
Crop moisture crop Poor water
Raspberry system
Productio Leaf wetness production. management. Enhanced
Sachapara et pi helps to
n Wind Enhanced Poor crops yield by Agricultu
13 al (2017) Mobile know
Water speed/direction quality. infrastructure. proper water re
[13] technology sustainable
Managem Rainfall Reduced Poor crops management.
environmen
ent detection costs. yield and big
tal
Soil ph. loss for
conditions.
Seed farmers.
recognition.
Crop
productivity
Temperature increased.
Humidity Improve the Reduced
Weather Wastage of
Soil crop wastage of Use of
Pooja S et al Monitorin Raspberry- crops.
Moisture traceability. crops. decision Agricultu
14 (2017) g Pi Poor water
Light intensity Increase Reduced water making re
[14] Precision Wi-Fi system
overall use. algorithm.
Farming management.
yield. Minimal
maintenance
required.
High accuracy
Difficulties in
monitoring.
Harvesting
Soil moisture Effective water Reduced
Improved related
pH level management. costs
Kavitha et al Crop Mobile crop growth. problems.
Temperature Effective between Agricultu
15 (2017) manageme technology Efficient Poor crop
Humidity power central re
[15] nt watering growth.
Light intensity management. server and
system. Poor power
Water level software.
management.
Poor water
management.
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Provide
advice for
farmers to
properly
grow and
treat the Provide
crops. efficient
Provide
Provide suggestions
Whether High human farmer
Soil moisture suggestions about when
manageme Mobile interaction. friendly
Nibi K V et Temperature to and how mush
nt technology Hard to deal alerts and Agricultu
17 al (2017) pH level monitoring to irrigate.
Crop Wi-Fi with changing guidance re
[17] crops. Provide
manageme whether with their
Ex: adequate
nt parameters. local
Irrigation fertilizer
language.
timings information.
Optimum
usage of
fertilizers.
Provide
whether
information.
Reduced
Crop Reduce the
High energy energy
manageme consumptio
Tran et al Temperature ZigBee Could consumption. consumption.
nt n of energy Agricultu
18 (2017) Humidity Raspberry prevent soil Soil and Could react
Nutrient Increase re
[18] Pi erosion. nutrient changes in
Detection the number
depletion. environment
of sensors
and soil.
Wireless
Sensor Efficient Climate Monitoring Smart
Muhammad Water
Water level Network water changes. water in water Agricultu
19 et al (2017) Managem
Soil Moisture Radio management Scarcity of watercourses. metering re
[19] ent
Communica . water. system.
tion
Remote
controlled
processes to
perform
such tasks
as;
Spraying
Reduced cost.
Crop Weeding
Temperature Lessen human
manageme Bird and
Humidity High cost interaction. Smart
Viswanathan nt. animal
Soil Moisture Wi-Fi Human High warehouse Agricultu
20 et al (2017) Warehous scaring
Rain fall interaction for reliability. manageme re
[20] e Keeping
Light intensity all activities. Improved crop nt.
Managem vigilance
production.
ent. Provide
smart
warehouse
management
.
Theft
detection in
warehouse.
Soli
environment:
Water Temperature
Managem Humidity of soil Low irrigation
ent Soil CO2 High efficiency Powerful
Lessen labour
Dai et al Agricultur Soil pH irrigation High labour servers to
ZigBee cost. Agricultu
21 (2017) al Environmental: efficiency. cost handle
Reduced water re
[21] Greenhous Temperature High Low precision storage
wastage.
e Humidity flexibility. High water data.
Managem Wind speed consumption.
ent Air pressure
Rainfall
Agricultur
Short distance
al More Automated
Yuan et al communicatio
Greenhous Temperature flexible. Lessen power greenhouse Agricultu
22 (2017) ZigBee n.
e Humidity Low power consumption. manageme re
[22] High power
Managem consuming. nt.
consumption.
ent
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Low cost
irrigation Lessen human Autonomou
Water Device
Irrigation evets control. interaction. s decision
Managem scalability is
Garcia et al as: Autonomou Efficient water making
ent LoRa low. Agricultu
23 (2017) Flow level s decision management. without
Energy Wi-Fi Device re
[23] Pressure level making Efficient human
Managem manageability
Wind speed without power interactions
ent is low.
human management. .
interactions.
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low cost
sensors
Improving
open
Precision Temperature Cost malt quality
Unequal source
farming humidity Mobile reduction and efficiency
Dolci (2017) distribution of application
34 Prescriptiv Soil PH technology Reduce the in production Farming
[34] air flow. s
e farming CO2 frequency with using
ability to
Artificial
increase the
Intelligence
level of
farming
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sophisticati
on
Make
Identifying
Infrastructure
Livestock the
Unable to of cattle
manageme emergency
detect illnesses farming
nt conditions. Improve
early. smarter.
Smart Mobile Improves the smart
Gokul et al Temperature Different implement a Farming,
lightening technology location lightning
35 (2017) humidity environmental noninvasive Agricultu
Smart Wi-Fi tracking. and
[35] Milk production conditions wearable to re
ventilation Improves ventilation
Irregular track
Water cattle health system
feeding physiological
manageme Improves
and biological
nt availability
activities of
cattle.
Provides
real time
Installing a
information
Water water meter
Cost
Irrigation shortage Developing to estimate
Rajkumar et Temperature Mobile reduction
manageme Different smart irrigation the amount Agricultu
36 al (2017) humidity technology Resource
nt environmental system to of water. re
[36] Soil Moisture Wi-Fi optimization
conditions monitor at Using
Reduce
anywhere. Wireless
water
sensors.
logging and
shortage
Improve
by adding
Wi-Fi
several
Crop Soil GPRS Providing
Unpredictable modern
manageme Temperature Zig Bee reliable and
Sri et al Improve the weather techniques
37 nt Humidity Raspberry efficient Agricultu
(2017) yield Water scarcity like
. Irrigation Rain fall pi agricultural re
[37] Low cost Improper irrigation
manageme Fertilizer Mobile system to
water usage Method,
nt efficiency technology monitor the
solar power
field
source
usage.
Agro loan
Inexpensiv
Build a well- e
Improve the
connected Agricultura
efficiency
farming l
Rajarsri et al Water Mobile Optimize
38 Unequal water network and consultatio Agricultu
(2017) manageme Water level technology resource
. distribution create a n re
[38] nt Maximize
knowledge better ROI
the profit
sharing Agro
platform. networking
Low cost
products
Symmetric
al
plantation
Can farm in
Temperature Differential of to check
less space
Ruengittinun Humidity temperature Build a smart the
39 Smart Provides
et al (2017) PH Wi-Fi Lack of time hydroponic eco accuracy of Farming
. farming many
[39] Electrical to manage and system the HFE
products
conductivity plant. across
multiple
farms in the
same area.
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can
overcome
distance
System for
and place Power Build a system
studying
constraints. problem with using
Smart the
Yoon et al Temperature Bluetooth save Space Bluetooth and
farming developme Farming,
40 (2018) Humidity Wi-Fi maintenance limitation LPWAN to
Irrigation nt of Agricultu
. CO2 LPWAN cost of difficulties in solve the
[40] manageme
existing installing power problem
environmen re
nt tal
devices additional and space
Algorithms
provide devices limitation.
.
compatibilit
y with new
devices
Enrich the
productivity
WSN Developing a
Plant health of food
Zig Bee water scarcity system to Increasing
Ezhilazhahi Smart Soil Moisture grains.
Wi-Fi unpredictable monitor the number
41 et al (2017) Farming Temperature Prevent the Farming
Raspberry weather continuously of sensors.
[41] Humidity plant from
pi conditions soil moisture
blight and
GPRS of the plants.
harmful
insects.
Reduces the
wastage of Using
Raspberry pesticides Bacterial multicolor
Crop Implementing
Tanmayee Temperature pi Reduces the diseases detection
manageme a rice crop Agricultu
42 (2017) Soil Moisture Mobile human unpredictable for detect
nt monitoring re
[42] technology effort weather the disease
System
Increase conditions in any
agricultural stage.
productivity
Implementing
Improve
Increase the a system to
Machines Soil Moisture the
Takecar et al income Lack of look after the
for routine Temperature component
43 (2017) Wi-fi. Cost Resource plantation Farming
operations Humidity s in the
[43] reduction Management without
PATRIOT
disturbing busy
system
schedule.
Reducing
lack of
labor costs
moisture in the
Helps to Using wireless
Smart Soil Moisture fields Develop
Raspberry track the mobile robot
Krishna et al Farming Light intensity salinity the
pi changes performing
44 (2017) livestock Humidity lack of capabilities Farming
Zig Bee accurately various
[44] manageme Temperature application of of the
Wi-Fi occurring operations of
nt Soil pH fertilizers robot.
instantly in the field.
Different
real time at
sowing time.
the field.
Irrigation low
Reduce the Implement
manageme Zig Bee production Green house
labour cost. a
Li et al nt Humidity Wi-Fi efficiency management to
Improve the comprehen Agricultu
45 (2017) Greenhous Temperature Bluetooth Waste of improve the
efficiency of sive re
[45] e LAN resources agricultural
agricultural promotion
manageme Environmental production.
production. system.
nt pollution.
Allowing
Improve the
system to
quality and Climatic
measure
Mobile safety of the change Assist for crop
Suciu et al Smart basic
Temperature technology products High management
46 (2016) Farming parameters Farming
GPRS Detecting temperature by using smart
[46] for
plant Low profit agriculture
irrigation
diseases, margin
manageme
flood. Etc.
nt.
Developing
the sensor
Improve the Implement a
Humidity and control
Putjaika et al Intelligent production Unpredictable system to
Temperature system by
47 (2017) farming Wi-Fi process weather monitor the Farming
Soil moisture adding
[47] Managing harmful
Light intensity more
resources diseases.
component
s.
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Reduce Improve
High Monitoring the
Humidity production the
Okayasu et al Growth production plant growth
Temperature cost accuracy of
48 (2017) measurem Wi-Fi cost measurement Farming
Solar radiation Improve the measureme
[48] ent Less quality in using smart
CO2 quality of nts.
products agriculture.
the products
Detection of generalize
Irrigation seed, water event-
manageme level, pest, condition-
Zig Bee Environmental Enhance the
nt. Temperature animal action
Sreekantha et Mobile changes productivity by
49 Greenhous Soil moisture intrusion to framework Agricultu
al (2017) technology High water using crop
e Weather the field. for re
[49] Wi-Fi consumption monitoring
manageme Fertility of soil Reduce cost programmi
system.
nt and time ng reactive
Enhance sensor
productivity networks
Providing
Rajendrakum Water Increase information to
Mobile Uncertain
ar et al manageme Soil moisture harvest understand
technology monsoon Develop
(2017) nt Temperature efficiency how to monitor Agricultu
50 Wi-Fi Water scarcity multiple
[50] Crop Humidity Decrease and control the re
Climatic systems.
manageme Soil pH water data remotely
variation
nt wastage and apply to
the fields.
Researching
modules
Smart Climate Developing
related to IoT,
Farming changes. all the apps
Ferreira et al Temperature Mobile Improve the event
Machines Insufficient and
51 (2017) Soil pH technology production. processing, Farming
for routine available experiment
[51] Oxygen flow situational
operations lands. with real
awareness and
Air toxins. cases.
data
harmonization
Smart
Increase
Livestock Temperature Mobile aquaponic
Vernandhes the manual
manageme Humidity technology Improve the Limited lands. system to
52 et al (2017) response Farming
nt Light Wi-Fi cultivation Water scarcity monitor and
[52] speed.
control
cultivation
Can monitor
Weather Upstream
Livestock the
condition Gaining data and
manageme performance
Vaughan et al Mobile Maintaining under the downstrea
nt. Animal Weight of their
53 (2017) technology balance hostile m the Farming
Farm animals.
[53] Large number conditions of a supply
manageme Improve the
of livestock farm. chain.
nt. livestock
measurements.
production
Estimate
Conserve Implementing the
Temperature water system to to irrigation
Water Water scarcity
Padalalu et al Humidity Mobile Avoidance make the cost.
manageme High power Agricultu
54 (2017) Light technology of constant irrigation Introducing
nt consumption re
[54] CO2 vigilance. system smart, wireless
Soil pH Remote autonomous sensor.
automation and efficient Automatic
watering
Heat detection By collecting
Cattle Increase Developing
Bellini et al Temperature Intensification activity data
detection LoRa milk power
55 (2017) Milk management for heat Farming
manageme production reduction
[55] consumption techniques detection for
nt systems.
the cattle.
Developing
WSN Energy irrigation
Energy Implement a
Mobile efficiency services
manageme smart
Cambra et al Temperature technology Reduction Scalability system in
nt communication Agricultu
56 (2017) Humidity LoRa in fertilizers Manageability the domain
Water system to re
[56] Zig Bee in products of
manageme monitor the
Saving agricultural
nt agriculture
water decision
systems
Temperature Improve Applying lossy Use lossy
Moon et al
Smart Humidity crop yield. Managing big compression compressio
57 (2017) Wi-Fi Farming
farming Rain fall Reduce data on IoT n
[57]
Wind speed unnecessary big data. techniques
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costs. to reduce
the high
cost of data
storage and
transit
Increases
Develop a Making
poultry High cost
poultry wireless
production. Maintenance
management communica
Temperature optimizes of labour
Raghudathes Poultry Raspberry system using tion
Humidity resource Wrong
58 h et al (2017) manageme pi low cost between Farming
Light intensity utilization. knowledge in
[58] nt Wi-Fi commodity sensor
Air quality Saves time farming
hardware and module and
Reduces practices.
open source coordinator
human
software .
intervention
Improving
Livestock Temperature Improve the system
Heat detection Use prototype
manageme Size of the cattle RFID productivity capability
Maina (2017) Death of sensor to detect
59 nt Activity of the Raspberry Can to detecting Farming
[59] livestock the activity of
Smart cow pi effectively cow
cow.
farming detect heat activity in
real time
Provide
required
Water feed and
manageme water. Develop a
Improve
Memon et al nt Temperature Exhaust the system to
Wi-Fi Stock theft the features Agricultu
60 (2016) Waste Humidity excess of control and
LAN of the smart re
[60] manageme biogas of monitor the
system
nt animals farm remotely
Surveillance
of the entire
farm
IV. DISCUSSION Although our results demonstrate the results in such a way, a
In this review we have identified important attributes to study [62] analyzed that use of RFID, a Wireless Sensor
analyse the research findings in agriculture and farming Network (WSN) technology that can be effectively used to
processes. We have gathered and analyzed data by using 60 increase the crop production to meet the growing needs of the
recent scientific articles. Our survey shows the most increasing population. In developing countries with limited
researched sub-verticals are water management, crop Internet speed, the other IoT technologies utilised rather than
management and smart farming. Water management is the Wi-Fi include Low-Power, Short-Range IoT Networks, low-
most researched sub-vertical for the last few years as most rate wireless PAN (LoRaWAN) or Low-Power and Wide-
countries mainly focus on the utilization of water resources Area Networks.
due to its lack of abundance [61]. Irrigation patterns in Further research [61] shows that WSN is used in many
agriculture influence crop production making irrigation applications such as health monitoring, agriculture,
management a central focus to increase productivity [8], [10]. environmental monitoring, and military applications whereas
The second most considered sub-vertical is crop management our study demonstrates the agriculture sector using IoT in and
due to the importance of producing food for a growing global farming sector using IoT. Our observations show that
population. It is important to manage the quality, quantity and Agriculture is the primary source of income in developing
effectiveness of the agricultural production for sustainability countries, such as India with the sizeable geographical area
[13]. Although a study [18] discussed that the widely used when comparing with other countries [9].
sensor data collections for measurements are soil conditions as
pH and humidity, as per our analysis it shows environmental Most of the research studies have performed on water
temperature followed by humidity and soil moisture are the management by monitoring such environmental parameters as
most commonly measured data. temperature, humidity and soil moisture [1], [3], [5], [19],
[25]. Many of the findings have focused on better water
IoT can further be defined as a fusion of heterogeneous utilization, reduction inhuman intervention and the cost of
networks including chip technology that scopes gradually production [18], [27]. Future research could draw more
more and more, expanding due to the rapid growth of Internet attention to further automate current processes in waste
applications such as logistics, agriculture, smart community, management, smart lightening and pest controlling sub-
intelligent transposition, control and tracking systems. verticals by reducing existing drawbacks since it has received
According to researchers’ analysis, in 2020 IoT objects will be the least research attention in the considered period. Fog
semi-intelligent and an important part of human social life computing, as an innovation with cross over any barrier
[46]. As analyzed in our review Wi-Fi,mobile technology are between remote data centres and IoT devices, should be
the technologies which have a wide range of demand in considered in future IoT analysis [63], [64], [65], [66], [67].
agriculture and farming domain to monitor land and water While IoT has solved many issues related to agriculture and
resources in contrast to other technologies [33], [35]. farming there are limitations that we need to consider. Lack of
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(IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 10, No. 4, 2019
interoperability and compatibility in devices, network technical knowledge among farmers, current centralised
flexibility issues when more devices are connecting, and architecture to support IoT systems is not much advanced as
sensor lifetime is some of the limitations to be addressed in the growth of the network, centralised systems will turn into a
future research. bottleneck. Moreover, sensor battery capacity and lifetime and
sensor data storage also more concentrated when IoT system
This study has found that industry 4.0 in agriculture deployment. Smart farming is the association with new
focuses on IoT aspects transforming the production advancements in technologies and the different crop and
capabilities including the agricultural domain. This study has livestock, agriculture and farming in the digital age. Smart
[68] considered soil quality, irrigation levels, weather, the farming can deliver agriculture more beneficial for the farmer.
presence of insects and pests as sensor data. Some of the This is because decreasing input resources will save farmers'
significant aspects they have been researched are the driver’s money and labour, and hence, will increase reliability [71] and
assistance to optimise routes and shorten harvesting and crop business outcome [72], [73].
treatment while reducing fuel consumption CISCO [69].
Producing enough food for the entire world is a big challenge Furthermore, studying diverse approaches for fog
since the global population is rapidly changing as well as computing structure [63], decision making using prediction or
climate change and labour shortage. Currently researchers pattern analysis [74], [75], [76], big data databases [77] could
have focused more on robotics to address these problems. A be an exciting way to make the Internet of Things (IoT) into
growing number of researchers and companies have focused the future dominating technology.
on Robotics and Artificial Intelligence (AI) to weeding by
reducing the amount of herbicide used by farmers. This survey will fill the gap by the identification of the
different IoT sub-verticals and data collections for the
In contrast to edge computing, cloud computing requires a measurements in the agriculture and farming process. Results
high-speed internet connection with sending and retrieving are clearly showing that most considered sub-verticals and
data from the cloud. As the process involves transferring and data collections for measurements in the field of agriculture
receiving data from the cloud, the process is time-consuming. and farming. Our study also indicates the technologies used
Since the data capacity is higher than bandwidth, it is always for IoT application development in the reviewed period. To
essential to process data locally instead of sending data to the summarise this survey, this has broader knowledge about IoT
cloud. Edge computing is more efficient than cloud processing applications developed for automating the agriculture and
when processing data since the capacity doubles faster than farming process. Moreover, this study identifies most
the bandwidth doubles [70]. Since IoT uses sensor data considered sub-verticals, collected sensor data and
collection for decision making, to process collected data, the technologies for the development of IoT based applications in
cloud, or the edge based can be used on the system agriculture and farming sector towards the significant
requirements. improvement of the business.
Still, there are some challenges associated with IoT system Table II shows the other necessary data collection criteria
deployment. Connecting so many devices to the IoT network which were not included in all studies.
is the biggest challenge in the future following lack of
TABLE II. IMPORTANT DATA INCLUSION CRITERIA FOR FUTURE IOT STUDIES
To be Addressed in Future
Criteria Information to be Collected in IoT Domain Addressed in this Review
Research
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Vol. 10, No. 4, 2019
V. CONCLUSION [2] G. Arvind and V. Athira and H. Haripriya and R. Rani and S. Aravind,
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