Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review

—It is essential to increase the productivity of agricultural and farming processes to improve yields and cost-effectiveness with new technology such as the Internet of Things (IoT). In particular, IoT can make agricultural and farming industry processes more efficient by reducing human intervention through automation. In this study, the aim to analyze recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies, and sub-verticals such as water management and crop management. In this review, data is extracted from 60 peer-reviewed scientific publications (2016-2018) with a focus on IoT sub-verticals and sensor data collection for measurements to make accurate decisions. Our results from the reported studies show water management is the highest sub-vertical (28.08%) followed by crop management (14.60%) then smart farming (10.11%). From the data collection, livestock management and irrigation management resulted in the same percentage (5.61%). In regard to sensor data collection, the highest result was for the measurement of environmental temperature (24.87%) and environmental humidity (19.79%). There are also some other sensor data regarding soil moisture (15.73%) and soil pH (7.61%). Research indicates that of the technologies used in IoT application development, Wi-Fi is the most frequently used (30.27%) followed by mobile technology (21.10%). As per our review of the research, we can conclude that the agricultural sector (76.1%) is researched considerably more than compared to the farming sector (23.8%). This study should be used as a reference for members of the agricultural industry to improve and develop the use of IoT to enhance agricultural production efficiencies. This study also provides recommendations for future research to include IoT systems' scalability, heterogeneity aspects, IoT system architecture, data analysis methods, size or scale of the observed land or agricultural domain, IoT security and threat solutions/protocols, operational technology, data storage, cloud platform, and power supplies.


I. INTRODUCTION
IoT is a combination of worldwide data, web associated items or things, and is an integral component of the future Internet.IoT focuses on the automation of processes by lessening human interaction.In the process of automation, IoT collects data using sensors and processes the data using controllers and completing the automation processes by using actuators [1], [2].IoT in agriculture and farming focus is on automating all the aspects of farming and agricultural methods to make the process more efficient and effective.Traditional approaches in livestock management (such as cattle detection) are not fully automated and have many inefficiencies such as higher human interaction, labour cost, power consumption, and water consumption [1], [3], [4], [5], [6].The central concept of this review is to analyse the IoT sub-verticals, collected data for measurements and used technologies to develop applications.It is essential to identify the most researched sub-verticals, data collections and technologies to create new IoT applications in the future.www.ijacsa.thesai.orgThis review provides an overall picture of currently developed IoT applications in agriculture and farming between 2016 and 2018.
As a solution to the existing problems, researchers have focused on smart agricultural and farming automated systems with the help of IoT [7], [8], [9], [10].IoT is the network of things which identifies elements clearly with the help of software intelligence, sensors and ubiquitous connectivity to the Internet.In IoT, the data that collects from Internetconnected items or things contains with gadgets, sensors and actuators [1].Many researchers have focused on smart systems for monitoring and controlling agricultural parameters by enhancing productivity and efficiency.Smart systems collect data for measurements to get accurate results that can lead to appropriate actions.Current use of smart agricultural systems relates to collecting data on environmental parameters such as temperature, humidity, soil moisture and pH [11], [12], [13].With accurate sensor data collection using a range of different sensors, researchers have implemented smart agricultural systems to make the farm process more effective [9], [14].Research has mainly focused on sub-verticals such as water management, crop management and smart farming to make processes automated by reducing human intervention, costs, power consumption and water consumption.
The automation process of agricultural and farming reduced human interaction and improve the efficiency.The reason for that is every country population depends on agriculture thus consumers of these resources should use water and land resources optimally [19], [20].Moreover, it is imperative to have good quality production and crop management in order to maximize profitability.Hence, IoT base agricultural management systems are integral for an agriculturally based country.The new systems developed using IoT technologies have reduced the drawbacks associated with traditional approaches and provided many advantages to farmers.For example, IoT-based water management systems collect environmental attributes such as temperature, water level and humidity through the sensors and provide accurate irrigation timing [19], [21].In addition, crop management systems developed using IoT monitor the temperature, humidity and soil through sensors thus providing adequate information so that farmers can manage the crops appropriately [25].Overall, these IoT-based systems help to reduce human interaction, power utilization and reduce cost in the field of agriculture.Moreover, IoT-based agricultural related applications have been used in the area of pest control, weather monitoring, nutrient management and greenhouse management.
IoT for agriculture uses sensors to collect big data on the agricultural environment.It discovers, analyses and deals with models built upon big data to make the development of agriculture more sustainable [34].IoT can provide efficient and low-cost solutions to the collection of data.Weather, Water Scarcity, Soil fertility and Pesticides are the significant players in it.IoT will make agriculture beneficiary.Agriculture and farming depend on water [35].Farmers depend on rainfall for all their agricultural needs.
Fertilizer also plays a very significant role in the field of agriculture by helping to increase the productivity of plants [36].By using IoT, farmers can manage soil condition more effectively and at less expense by monitoring them from any location [37].The primary objective of this study is how IoT and technologies are used in conserving water, fertiliser and energy in the agricultural industry by combining new technologies.This has benefits for the development of the economy of countries as well as the wealth of the people [38].With the combination of both advanced technologies in hardware and software, IoT can track and count all relevant aspects of production which can reduce the waste, loss and cost [39].The information needed to make smart decisions can be obtained merely by using electronic devices [40].IoT transforms the agricultural industry and enables farmers to overcome different challenges.Innovative applications can address these issues and therefore increase the quality, quantity, sustainability and cost-effectiveness of crop production [41], [42], [43].IoT provides more benefits to the farming industry by improving the health of animals through better food and environment, addressing the labour shortage issue as well cost savings through automation, increase in milk production, and increase in some animals during the breeding period through detection of estrus cycle and additional revenue streams from waste.
Our study has analyzed recently developed IoT applications in the fields of agriculture and farming to address current issues such as unnecessary human interaction leading to higher labour cost, unnecessary water consumption and water-saving measures for the future, higher energy consumption, energy-saving measures for the future and crop monitoring difficulties.According to our analysis, we can identify a focus on water and crop management as subverticals in the agriculture and farming sectors.This survey also focusses on other agriculture and farming sub-verticals to identify the gap between IoT application developments in the least researched areas.The IoT generates enormous data, socalled big data (high volume, at a different speed and different varieties of data) in varying data quality.Analysing the IoT system and its key attributes are the key to advancing smart IoT utilization.Therefore, the primary aim of our paper is to explore recently created IoT applications in the agriculture and farming industry to give the more profound understanding about sensor data collection, used technologies, and subverticals, for example, water and crop management.The secondary aim of this study is to analyse the current issues such as higher human interaction, high labour cost, higher water consumption and save water for future, higher energy consumption and save energy/electricity for future, crop monitoring difficulties in IoT for agriculture and farming.
The remainder of this paper is as follows: In Section II we include raw data collection methodology, data inclusion criteria, and data analysis methods.Finally, the results of Agriculture and Farming based on IoT Sub verticals, Sensor Data, and Technologies are presented in Section III, and in Section IV we discuss the results.Section V concludes the paper.The raw data collected from 60 peer-reviewed publications used in this paper are summarised in Table I. www.ijacsa.thesai.org

II. MATERIALS AND METHODS
Data collection involves identifying important criteria in research articles on the Internet of Things (IoT) in the agriculture and farming sectors.
As shown in Table I, these essential criteria were used to analyse relevant research papers.In particular, 60 peerreviewed scientific publications on IoT in the agriculture and farming sectors published in scientific journals between 2016 and 2018 were used.

1) Collection of raw data:
The data gathered for this review is from 60 peer-reviewed publications (2016-2018) that were collected from the IEEE database.All these publications have different data applications that have been studied and analyzed in this survey.The attributes compared were sub-verticals, data collection measurements, used technologies, challenges in current approach, benefits, countries and drivers of IoT.
2) Data inclusion criteria: To evaluate the data inclusion criteria a comparison table was drawn to include as the following attributes: Author, Sub vertical, Data collection measurements, Technologies, Benefits, Challenges, Solutions and Drivers of IoT.Nevertheless, in our study, articles were excluded when the selected attributes were not present.In our analysis, the number of sensors, amount of data collected, underlying technologies, sensor topology and other intermediate gateways were not included since no information can find with all the peer-reviewed publications (2016-2018).
3) Data analysis: We pooled and analyzed the reported studies based on data collected through peer reviewed articles and displaying emerging themes in a table.The data sets included attributes such as Sub vertical, Data collection measurements, Technologies, Benefits, Challenges, Solutions, Countries focused on automation of the agriculture proses and Drivers of IoT.The descriptive details of the study based on the publication year were analyzed to observe the results from 2016 to 2018.

III. RESULTS
This review aims to analyse the incorporation of IoT for the development of applications in the agriculture and farming sectors.The study focuses on sub-verticals and collecting data for measurements and technologies in the field of agriculture and farming to increase productivity and efficiency with the help of the Internet of Things (IoT).This study of IoT in agriculture and farming focuses on developing a criterion approach with the help of agricultural environmental parameters and IoT measures and technologies.In the field of agriculture, there are many environmental parameters that need to be considered to enhance crops, reduce water consumption and human involvement [44].Moreover, there are many sub-verticals that can be identified depending on the differences in approach.
In this review, we have gathered articles which have focused on agricultural and farming sub-verticals from 2016 to 2018.As shown in Fig. 1, 23 sub-verticals were found according to the results obtained and the topmost area was water management (28.08%).
As IoT depends on sensor data collections, a vast amount of data needs to be gathered to identify or predict accurate results.This study indicates that many researchers have focused on environmental temperature (24.87%), humidity (19.79%) and soil moisture (15.73%) as environmental measurements.As shown in Fig. 2, 28 types of data were collected for measurements with environmental temperature and humidity being considered the most critical parameters for agriculture and farming.
As shown in Fig. 3, we have categorised all technologies used in the articles.This study has identified Wi-Fi as the most used technology (30.27%) followed by Mobile Technology (21.10%) for both agriculture and farming.ZigBee, another data transfer technology, is also used but to a lesser extent.
According to Fig. 4, the use of IoT was more prominent in the agriculture industry than the farming industry (Agriculture -76.1%,Farming -23.8%).

IV. DISCUSSION
In this review we have identified important attributes to analyse the research findings in agriculture and farming processes.We have gathered and analyzed data by using 60 recent scientific articles.Our survey shows the most researched sub-verticals are water management, crop management and smart farming.Water management is the most researched sub-vertical for the last few years as most countries mainly focus on the utilization of water resources due to its lack of abundance [61].Irrigation patterns in agriculture influence crop production making irrigation management a central focus to increase productivity [8], [10].The second most considered sub-vertical is crop management due to the importance of producing food for a growing global population.It is important to manage the quality, quantity and effectiveness of the agricultural production for sustainability [13].Although a study [18] discussed that the widely used sensor data collections for measurements are soil conditions as pH and humidity, as per our analysis it shows environmental temperature followed by humidity and soil moisture are the most commonly measured data.
IoT can further be defined as a fusion of heterogeneous networks including chip technology that scopes gradually more and more, expanding due to the rapid growth of Internet applications such as logistics, agriculture, smart community, intelligent transposition, control and tracking systems.According to researchers' analysis, in 2020 IoT objects will be semi-intelligent and an important part of human social life [46].As analyzed in our review Wi-Fi,mobile technology are the technologies which have a wide range of demand in agriculture and farming domain to monitor land and water resources in contrast to other technologies [33], [35].
Although our results demonstrate the results in such a way, a study [62] analyzed that use of RFID, a Wireless Sensor Network (WSN) technology that can be effectively used to increase the crop production to meet the growing needs of the increasing population.In developing countries with limited Internet speed, the other IoT technologies utilised rather than Wi-Fi include Low-Power, Short-Range IoT Networks, lowrate wireless PAN (LoRaWAN) or Low-Power and Wide-Area Networks.
Further research [61] shows that WSN is used in many applications such as health monitoring, agriculture, environmental monitoring, and military applications whereas our study demonstrates the agriculture sector using IoT in and farming sector using IoT.Our observations show that Agriculture is the primary source of income in developing countries, such as India with the sizeable geographical area when comparing with other countries [9].
Most of the research studies have performed on water management by monitoring such environmental parameters as temperature, humidity and soil moisture [1], [3], [5], [19], [25].Many of the findings have focused on better water utilization, reduction inhuman intervention and the cost of production [18], [27].Future research could draw more attention to further automate current processes in waste management, smart lightening and pest controlling subverticals by reducing existing drawbacks since it has received the least research attention in the considered period.Fog computing, as an innovation with cross over any barrier between remote data centres and IoT devices, should be considered in future IoT analysis [63], [64], [65], [66], [67].While IoT has solved many issues related to agriculture and farming there are limitations that we need to consider.Lack of www.ijacsa.thesai.orginteroperability and compatibility in devices, network flexibility issues when more devices are connecting, and sensor lifetime is some of the limitations to be addressed in future research.This study has found that industry 4.0 in agriculture focuses on IoT aspects transforming the production capabilities including the agricultural domain.This study has [68] considered soil quality, irrigation levels, weather, the presence of insects and pests as sensor data.Some of the significant aspects they have been researched are the driver's assistance to optimise routes and shorten harvesting and crop treatment while reducing fuel consumption CISCO [69].Producing enough food for the entire world is a big challenge since the global population is rapidly changing as well as climate change and labour shortage.Currently researchers have focused more on robotics to address these problems.A growing number of researchers and companies have focused on Robotics and Artificial Intelligence (AI) to weeding by reducing the amount of herbicide used by farmers.
In contrast to edge computing, cloud computing requires a high-speed internet connection with sending and retrieving data from the cloud.As the process involves transferring and receiving data from the cloud, the process is time-consuming.Since the data capacity is higher than bandwidth, it is always essential to process data locally instead of sending data to the cloud.Edge computing is more efficient than cloud processing when processing data since the capacity doubles faster than the bandwidth doubles [70].Since IoT uses sensor data collection for decision making, to process collected data, the cloud, or the edge based can be used on the system requirements.
Still, there are some challenges associated with IoT system deployment.Connecting so many devices to the IoT network is the biggest challenge in the future following lack of technical knowledge among farmers, current centralised architecture to support IoT systems is not much advanced as the growth of the network, centralised systems will turn into a bottleneck.Moreover, sensor battery capacity and lifetime and sensor data storage also more concentrated when IoT system deployment.Smart farming is the association with new advancements in technologies and the different crop and livestock, agriculture and farming in the digital age.Smart farming can deliver agriculture more beneficial for the farmer.This is because decreasing input resources will save farmers' money and labour, and hence, will increase reliability [71] and business outcome [72], [73].Furthermore, studying diverse approaches for fog computing structure [63], decision making using prediction or pattern analysis [74], [75], [76], big data databases [77] could be an exciting way to make the Internet of Things (IoT) into the future dominating technology.This survey will fill the gap by the identification of the different IoT sub-verticals and data collections for the measurements in the agriculture and farming process.Results are clearly showing that most considered sub-verticals and data collections for measurements in the field of agriculture and farming.Our study also indicates the technologies used for IoT application development in the reviewed period.To summarise this survey, this has broader knowledge about IoT applications developed for automating the agriculture and farming process.Moreover, this study identifies most considered sub-verticals, collected sensor data and technologies for the development of IoT based applications in agriculture and farming sector towards the significant improvement of the business.
Table II shows the other necessary data collection criteria which were not included in all studies.V. CONCLUSION From our observations from the 60 peer-reviewed publications (2016-2018) in discussing the potential applications of the Internet of Things, it was found that water management is the highest considered IoT sub-vertical followed by crop management, smart farming, livestock management, and irrigation management with the same percentage.As per the observation, the most critical sensor data collection for the measurement is environmental temperature, environmental humidity and also there are some other such sensor data also gathered for IoT applications as soil moisture and soil pH.Wi-Fi has the highest demand of usage in agriculture and farming industry, followed by mobile technology.Other technologies as ZigBee, RFID, Raspberry pi, WSN, Bluetooth, LoRa and GPRS have less demand in the agriculture and farming sectors.When compared to the agricultural sector, farming industry has a lesser percentage amount using IoT for the automation.This survey could be useful for researchers for finding new ways and solution to challenge in the current agricultural era and for agricultural and farming industries to make the automation process more effective and efficient, consequently, to obtain the good businesses outcome.

Fig. 1 .
Fig. 1. Agriculture and Farming Sub Verticals: different Agricultural and Farming Sub Verticals Considered to Enhance Efficiency and Productivity-Pooling

Fig. 2 .
Fig. 2. Utilization of Sensor Data based on Farming Activities Referred to in the Data Pool of 60 Peer Reviewed Published Articles.

Fig. 3 .Fig. 4 .
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.

TABLE I .
IOT IN AGRICULTURE AND FARMING CRITERION-APPROACH-DATA EXTRACTED FROM 60 SCIENTIFIC ARTICLES IN 2016-

2018 N o Year/Autho r IoT Sub Verticals Measures (Data collection) Technologie s Used Benefits of Proposed System Challenges in Current Approach Solution for Current Issues Drivers of IoT Applicatio n
 Agricultu re www.ijacsa.thesai.org Farming www.ijacsa.thesai.org . Farming www.ijacsa.thesai.org

TABLE II .
IMPORTANT DATA INCLUSION CRITERIA FOR FUTURE IOT STUDIES