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Received: 31 May 2021 Revised: 15 December 2021 Accepted: 21 December 2021
DOI: 10.1002/ett.4448
SURVEY ARTICLE
Importance of semantic interoperability in smart
agriculture systems
P Salma Khatoon Muqeem Ahmed
Department of CS & IT, Maulana Azad
National Urdu University, Hyderabad,
India
Correspondence
P Salma Khatoon, Department of CS & IT,
Maulana Azad National Urdu University,
Hyderabad, India.
Email: salmakhatoon537@gmail.com
Abstract
The Internet of Things (IoT) connects people with real-world objects to exchange
data. It is performed using services and devices present in the user’s activi-
ties based on the IoT. Based on a common vocabulary or mappings, knowl-
edge and information can be exchanged by different agents, services, and
devices in this scenario. The heterogeneous sources can be represented and
integrated by an ontology. The Semantic Web offers semantic interoperability
that facilitates communication between heterogeneous devices and technol-
ogy platforms. The state-of-the-art of IoT semantic interoperability is assessed
and reviewed in this work. The importance and challenges of interoperabil-
ity are discussed in detail with an in-depth analysis of the requirements. IoT
based semantic interoperability model is discussed with semantic annotations
of data required for heterogeneous IoT devices. Additionally, it has been pre-
sented which Semantic Web technologies are incorporated, and the challenges
have been studied in this research area. Agriculture is a domain where IoT
applications have a lot of potentials. The market is filled with several devices
that collect data from the farms and send it to the cloud. Semantic Web tech-
nology for applications in agriculture has been discussed in detail with data
integration. Semantic resources for agriculture have been enlisted with linked
data hubs and semantic data standards. The article aims to address the need
and requirement of IoT with semantic interoperability in the field of agricul-
ture. The use of IoT interoperability in agriculture can bring long term bene-
fits to the farmers and increase productivity while reducing the overall costs
incurred.
1INTRODUCTION
The objects or the things in the atmosphere for being the active members1in sharing the data using additional items
and transmitting through wired or wireless networks frequently with the help of Internet protocol (IP)2is enabled by the
Internet of Things (IoT). The variations and changes in the neighboring atmospheres and the things that could operate
and respond independently are enabled by IoT data processing. Nevertheless, exchanging data within an inter-operability3
manner for making the information and services available and explainable using additional facilities and things is required
by the heterogeneous objects.
Trans Emerging Tel Tech. 2022;33:e4448. wileyonlinelibrary.com/journal/ett © 2022 John Wiley & Sons, Ltd. 1of22
https://doi.org/10.1002/ett.4448
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A new domain in which developing the infrastructure in addition to the capability of distributing modern facilities
to support various scalable (cloud-based) as well as interoperable (multi-domain) submissions4,5 is required. The realiza-
tion of a regular issue of IoT, which is interoperability of the information and services that must be resolved within the
IoT design racing based on the architecture of the Future Internet, academic in addition to the communities of Informa-
tion and Communication Technology (ICT)6,7 industry. The new developments and problems upon the interoperability
are reviewed, and the process of supporting the interoperability8information within the Future Internet designing, con-
sidering IoT and cloud computing9is discussed by the information models, open service frameworks, and semantic
technologies in this article. With the continual progressions in the wireless sensor and actuator networks10 and with
the manufacture of energy effective and less cost hardware for sensor11 and device communications, primary support
is provided by IoT. Expanding the solutions of the generic IoT globally is a challenging issue owing to the underlying
device’s heterogeneity, communication techniques, and interoperability within the several layers12,13 using the seamless
integration and communication of the apparatus toward IoT generated data interoperability.
Although the data that can transmit the inventive facilities aimed by IoT is realized, several issues related to paral-
lel and inter-related interoperability14 that ensures the transmission of the data by the technologies using a continuous
way is presented by this study.15 The interoperability problems nowadays must be solved for ongoing transmission and
interaction using realistic objects always and everywhere in the coming years.
1.1 Smart agriculture—Need and gaps
In smart agriculture, utilizing cutting-edge technologies such as IoT and automation technology makes it possible to
achieve ultra-labor saving and high-quality production. In recent years, smart agriculture has been used not only by
farmers but also by other industries and consumers and is increasingly attracting people’s attention. In agriculture, it is
difficult to maintain the agricultural production base, such as waterways, due to the decrease in the number of farmers
and population ageing. It is one factor that promotes the expansion of abandoned cultivated land. Also, based on the
experience and intuition of skilled farmers, there is a danger of losing the agricultural production technology based on
it. There have been many cases of leaving farms in recent years. As the number of elderly farmers who retire increases,
the number of non-farmers who own land is increasing year by year. It is believed that there are many cases in which
inheritance does not go well, and the land becomes abandoned cultivated land. Due to the decrease in the number of
contractors, it becomes difficult to maintain it, which leads to the loss of vitality in rural areas.
Based on the situation surrounding such agriculture, smart agriculture will cooperate with conventional agricul-
tural technology. Further improvement in production efficiency can be found by utilizing technology and knowledge
accumulated in other industries through collaboration between different sectors. The promotion of smart agriculture
includes:
•Utilizing IoT.
•Developing and disseminating new varieties and technologies.
•Knowledge innovation in agriculture through comprehensive utilization of property.
•The sophistication of production and distribution systems.
By smart agriculture, the input of chemical fertilizer to increase yield. In spraying of pesticides, it can be optimally
adjusted according to the situation of soil and crops, was of large-scale production Agricultural machinery, such as because
of a tractor, the GPS expects practical use of automatic operation. In addition, by analyzing big data obtained by sensors,
etc., techniques performed by skilled farmers can be studied, predicting the occurrence of pests, such as entirely new
possibilities are also expected.
In smart agriculture, new agricultural methods such as AI agriculture and precision agriculture, Networks, informa-
tion terminals, cloud computing, remote sensing, robots have been introduced. It utilizes general-purpose hardware and
software technology that is common to other fields. In addition, with the aim of smart agriculture aiming for a solution,
the additional benefits are
1. Super labor saving and large rules realization of imitation production.
2. Maximization of crop capacity.
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3. Free from hard work, dangerous work.
4. Realization of agriculture that is easy for everyone to work on.
5. Providing peace of mind and trust to consumers and actual consumers.
It is requested to utilize AI agriculture efforts in
1. improvement of agricultural industrial competitiveness,
2. sophistication of related industries,
3. market development and strengthening of sales force.
Web server, multiple sensors, network camera, wireless LAN communication module, ultra-bright LED lighting,
equipped with various electronic devices and installed in the field for a long period of time to monitor the conditions in
the farm. The smart agriculture concept can enable improvements and developments such as:
•Latest agriculture equipment such as tractors by introducing an automatic driving system, etc.
•In addition to night time running of industrial machines, simultaneous running of multiple machines, automatic
running, due to the automation of weeding work and water management, the conventional scale is limited.
•Cost reduction is possible.
•Soil monitoring between fields and in fields using sensing technology.
•Accurately grasp “variations” such as loam, water temperature, and crop growth ability of crops by grasping and
responding finely achieve high-level stabilization of quality and yield by maximizing present.
•Accurate farming is possible, which is directly linked to quality.
•Reduce variations in components such as sugar content and acidity that makes the most of the abilities of horticultural
crops.
•Labor saving and quality control/information utilizing IoT.
•Early detection of abnormalities, improvement of productivity and reduction of material costs are possible.
•Significant labor savings for heavy-duty work such as feeding management.
By integrating and utilizing existing data, the history of each farm efficient and effective management improvement,
technical guidance from outside, etc. This smart agriculture concept is feasible only when the different domains com-
municate with one another effectively. IoT interoperability ensures that the data exchanged is meaningful and can be
interpreted by other devices. Thus, IoT interoperability is the need of the hour in improving the present-day agriculture
condition.
1.2 IoT interoperability
IoT’s various responsibilities and operations16 are explored in this method rather than producing a novel definition upon
interoperability. As there are multiple definitions of interoperability, a usual definition that extracts several definitions
is provided in this approach. The capability to exchange information and data usage between various components or
systems is referred to as interoperability and is represented in Figure 1.
The following challenges are provided in this definition upon how to:
•Attain the data.
•Exchange information.
•Utilization of data to get better understanding and be have an ability to perform it.
The interoperability with a simple representation is shown in Figure 1.
The hardware or software components, networks and stages allow communication among the machines.17 Technical
interoperability generally involves them. This interoperability focuses on the communication protocols and operating
procedures by the infrastructure.
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FIGURE 1 The dimensions of interoperability
The data formats are commonly by syntactical interoperability. A definite syntax and encoded18 must be possessed
by the data transmitted with the help of the communication protocols, although it is in the bit tables. Nevertheless, the
information is carried by various protocols, and high degree syntaxes like HTML or XML are used for representing them.
By the significance of the content, the semantic interoperability is generally involved, and the humans are concerned
mainly compared to the content interpretation of the machine.19 Therefore, this interoperability refers to the mutual
apprehension among them who exchange the significance of the data.
The data are communicated and transferred effectively, although various statistical networks are employed by mul-
tiple infrastructures20 around several cultures and regions by a process called organizational interoperability. Effective
technical, syntactical, and semantic interoperability are the various factors that affect organizational interoperability.
Static and dynamic interoperability21 can be added by considering the tendencies and definitions of the ICT region
regarding the sensing information.
1.2.1 Dynamic interoperability
As long as a similar group of services are not implemented, it could not be possible to perform interoperation of the
two products. The issues of severe interoperability may occur whenever the definitions include a wide variety of choices.
Distinct documentation in which the entire options are listed, including the overall situations and several profiles,22
provides a resolution for overcoming the components of the definition. In this situation, the verification of interoperability
amid two solutions within a similar or dissimilar family could be helpful in the definition of the profile. This kind of
aspect is considered as follows:
In the case of defining a static conformance review, the implementation of static interoperability is done with the
help of a popular OSI overall test methodology, ISO 9646. The fulfillment of the entire essentials of static and dynamic
conformance by implementation under test (IUT) is verified by the conformance test.23 Review operations of the choices
(PICS) that are sent using the IUT24 are represented by the static conformance requirements and are called a review of
static conformance. As a result of the wide-ranging uses, a severe issue occurs within the field of IoT that can be appeared
quickly.
The complications within the communication and interpretation of the information and services25 are increased by
the non-interoperable solutions. The variations and potential non-interoperability of the two protocols must be accepted
during the process, and it can be experienced in the intelligent gateways and middleware features. It is an unceasing
investigation domain, particularly by the complications in the development and IoT environment’s26,27 heterogeneity, and
moreover, it is named dynamic interoperability.
1.3 Interoperability: Challenges and requirements
Stabilizing the real data/services basics, verifying the technical interoperability in delivering huge amounts of data and
using the technology, and finally verifying the complementing problems to understand and process the data19 and
represented in Figure 2.
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FIGURE 2 The dimensions of interoperability and their associated general challenges
TABLE 1 IoT semantic interoperability challenges or requirements
Requirement(s) Rationale and remarks
Integration: Multiple ICOs like actuators and sensors are
supported and different related types of data sources
that are not depending on ICO location and vendor.
•Enables the accessible distribution as well as integration of dis-
tributed information sources.
•Various heterogeneous devices and Orchestrate ICOs are
involved by the entire IoT applications for formulating the com-
posite workflows according to end-user applications.
Annotation: The automated linking of related data sources
is enabled.
•Application integration is facilitated by linking the information
sources and by reusing the information.
•The interactions between ICOs and IoT services are enabled.
•For the explanation of sensors as well as ICOs, it is constructed
upon the standards such as W3C SSN standard ontology.
Management: Based on the fusion and composition of
streams stemming from multiple data sources ICOs, the
virtual sensors and virtual ICOs have been created and
managed.
•The parallel processing of multiple heterogeneous and dis-
tributed data sources have been involved in the application
development and integration.
•The integration of applications are made easier based on the
virtual sensors management.
Discovery: To discover and choose the data sources and
ICOs that ensures to requests of application, it is
provided based on their capabilities.
•An accessing of a high-level interface is required by end users.
•Based on high-level descriptions, the formulation or describing
IoT services and applications are provided.
•The multiple integrated data sources in a mash-up manner with
the visualization capabilities have been provided.
Analysis and reasoning: Among major semantic level
capabilities, reasoning and analytical tools are provided.
•The large-scale environments with various ICOs that featuring
different capabilities and functionalities are addressed by IoT.
•The controlling of virtual and physical sensors is involved in the
end-user applications.
Visualization: The resources utilization is optimized like
sensor usage, computing cycle and storage among
multiple users sharing these resources.
•Object-to-object interactions like M2M or interactions between
services are included in various applications. Here, the interac-
tions could be either derived implicitly according to the context
of application or defined explicitly by end users.
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Table 1 presents a review concerning the challenges in semantic interoperability. Upon semantic interoperability, the
research and innovation are made on the IoT.
Increasingly, raw data are generated using sources like soil sensors, drones, and local weather stations by precision
agriculture. A small benefit is offered to the farmers by the raw data since it is insignificant and secluded. The context,
meaning, and their accumulation using additional data sources lead to the value of information. A condition and an
implication for the information and the accumulation are provided with the help of References 28 and 29 data description
languages and standard data interchange formats.
Several significant semantic resources and information standards of interchange are provided by the Food and
Agriculture Organization of the United Nations (FAO)30 as a result of the activities from the organizations. However,
agriculture is unserved during the semantic web technology’s application documentation. A study of essential seman-
tic resources, particulars regarding the primary semantic data interchange standards and analysis of the semantic web
technology’s application towards the issues of agriculture is provided by the investigators, which is the main objective of
this study.
2LITERATURE SURVEY
This section is presented a detailed description of the technologies implemented in the domain of IoT semantic
interoperability. The papers published by various authors have been analyzed and summarized thoroughly.
2.1 IoT interoperability frameworks
The point of interoperability of IoT frameworks has a significant gaining and an expanded consideration from the explo-
ration network, particularly during the ongoing years, which likewise gives a clear sign displayed in writing.31,32 For
encouraging information interoperability in IoT, this survey examined the principal methodology: the adjustment of
Semantic Web dialects, apparatuses and advancements used for depiction with disclosure of things along with administra-
tions, organization of administrations, and applying thinking calculations over IoT assets. By taking help of the meaning
of starting semantic interoperability measures, planning to counteract fracture of IoT and diminish general expenses of
improvement W3C association has as of late propelled the Web of Things Working Group (https://www.w3.org/WoT/)33,34
in like way.
The Next Generation Service Interface (NGSI)35 be the Another settled methodology for IoT interoperability at
stage range which is as of now a proper standard that has been released by Open Mobile Alliance (OMA) with it
bolsters getting, preparing,36 contextualizing, also distributing of IoT information. By critical organizations in the IoT
institutionalization endeavors, for example, with the development of the Orion Context Broker, the NGSI API, the
activity of FIWARE37 has been characterized the ETSI and AIOTI WG3 based on the received relevant setting replica
of NGSI while a RESTful official of OMA NGSI-9/10.38 Through 31 urban communities from nations, for example,
Brazil, Spain, Italy, Portugal, Belgium, Denmark, and Finland, that received NGSI open standard in their brilliant
city stages, an available and nimble keen urban areas activity has been marked in the savvy urban areas application
space.39
Based on the fact that investing considerable efforts for IoT biological systems is underlined by the EU,
among others, is the importance of interoperability and is communicated both as financial and admin-
istrative help in pushing forward the cross-area, cross-stage IoT worldview. To convey structural ideas
for semantic interoperability for “Stages for Connected Smart Objects,”40 expecting to shield different use
cases while responding to explicit necessities as far as security, steadfastness, perception and organized
event processing, various research and development ventures were subsidized with on 2015 by pointing
50M Euros.
The future of WWW is called semantic web, proposed by Gyrard et al.41 The organization stone of the semantic
web was nothing but this academic research paper. They gave an innovative track of WWW. This work demonstrated
the ontologies and agents’ appropriate role in the semantic web. Providing defined and meaningful web information to
users is the main objective of the semantic web. Primarily the semantic web deals with machine learning and artificial
intelligence.
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An information management system was proposed by Fountas et al,42 and the uncertainty of domain-specific appli-
cations can be avoided by them and gave a new power infrastructure to users for making a flexible task-oriented model.
The model could exploit data on the semantic web in a flash with no supplementary infrastructure or applications. Their
work also referenced the boundary that comes into the method for semantic web developments and proposed a right
answer to accomplish that objective.
The necessity of a knowledge representation system in the modern communication paradigm was defined by Atzori
et al.43 This work outlined the knowledge representation of four individual characteristics. These characteristics are sub-
stitute, ontological obligation, intelligent interpretation and medium of human expressions. By thinking while ontological
obligation provides universal domain understandability as per the authors, substitute enables the entity to determine con-
sequences. And with the logically efficient computations, the intelligent interpretation and medium of human expressions
are arranged.
The provision of the general appraisal of semantic web and social web generated a few precious outcomes based on
thesecomparisonsaredonebyRistoskietal.
44 The appearance of the wisdom web was described, and he also sum-
marized the journey of WWW from its origin to the current web. They also highlight the influential function of an
intellectual agent with web mining in the wisdom web. Web for retrieving knowledge-based information, they designed
a high-level prototype model of wisdom. Anyway, this work required a progressively pragmatic structure. Adding to
these developments, a cosmology based format for the semantic web (OIL) was also published. OIL assumes a signifi-
cant job in trading data among a few spread networks. It works in two utilitarian territories: information the executives
and web commerce. The executives are connected with overseeing and trading an organization’s data to look through
data, remove data, and maintain programmed record preparation. Then again, web commerce extends existing busi-
ness structures to diminish costs and characterize innovative distribution potential outcomes. Making well-defined
formal semantics that enables the reasoning properties to ensure accuracy and effectiveness is the primary goal of
this work.
An audit of different metaphysics coordinating frameworks from their starting to exhibit advancements mirrors that
cosmology coordinating holds a tight submit semantic web. Authors have played out the top to bottom assessment of
different articles with their attributes and confinements and condensed that a high measure of research work has been
done hypothetically while coming up short on down-to-earth usage. Adding to the improvements, Ngo and Bellahsene45
presented YAM++, a cosmology matching system that adventures AI procedure to discover the mappings among two
different ontological elements, regardless of whether the connection is not found in the equivalent natural language.
It at that point matches results at component and auxiliary level too. Some terminological metrics measure the sim-
ilarity, and on the other hand, the structural level measures the similarity by flooding algorithm propagation at the
element level.
A survey about WordNet46 in cosmology coordinating procedure proposes that WordNet is an online lexi-
cal database dependent on psycholinguistic speculations of human lexical memory. It is connected with seman-
tic and lexical connection, and further, metaphysics matching uses the equivalent to discover comparable cor-
respondence between various ontologies. Semantic similarity among ontologies had been figured utilizing Word-
Net. The work makes use of edge-based, data-based and a half and half based strategies. Conversely to an
information-based methodology that finds a uniform connection separation, the edge-based approach computes the
semantic closeness between two words based on their distance premise. A hybrid approach combined the above two
methods.
The standard technique was ontology, which can promise interoperability between heterogeneous resources such as
the web and provide machine-readable information to users.
And in this interoperability, the XML and RDF play an important role; here, XML is deliberate as a markup language
for logical document structure. RDF is a critical technology that allows machines to craft conclusions related to data
collected from the web. To improve the algorithms about ontology developments and knowledge representation (KR),
many researchers have been put so much effort. The issues like uncertainty or heterogeneity are addressed in ontology
matching and are appreciable. The available approaches continue to fall short of addressing the new problems due to the
exponential growth of information. Ontology coordinating is an indispensable methodology used in different research
fields, for example, information combination, friend to peer communication and web administration, and it requests con-
sistent upgrades. In continuation to these endeavors, concept hierarchy based mapping approach (CHM)47 was proposed.
It performs balanced, numerous to one and one to some mapping simultaneously. It abuses semantic-based coordinating
and structure-based coordinating ways to manage philosophy mapping. Phonetic based matching computes the seman-
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tic comparability between words with WordNet, and the structure-based matcher utilizes the philosophy to process the
semantic closeness between two entities. The work considered the rationale of the parent-kid relationship in the various
leveled structure of ontology.
A new mapping approach that can minimize the time required for reconciling ontology mapping among dynamic
ontologies was proposed and provided re-establishing mappings among different ontologies in less time. A new ontol-
ogy matching technique that provided interoperability across domains where security plays a crucial role was proposed
by Oter-Cerdeira et al.48 Matching metrics to guaranty that the information can be sent with an appropriate match-
ing concept to the receiving domain is the first step of their approach description. Evaluating that concept in the
ontology best matches with available data is the second step of matching ontologies. To receive resultant metrics,
the graph search algorithms are applied. Metadata selection is based on the most probable scenario for the send-
ing domain to prioritize on a given property. The final step is data storage is the third step. The recently received
information can be categorized by using the correspondent concept when once the answer from the sending domain
is received, then receiving domain. The quality of their matching approach is highly dependent on the selection of
anchors.
Portrayed an operator based cosmology coordinating system that enables agent correspondence in homogeneous just
as heterogeneous ontologies. Sun et al49 proposed RiMOM2, a philosophy coordinating system for ontology composition
and occasion coordination. RiMOM2 used the cosmology matching task with markup language to portray the coordinat-
ing procedure sequentially, just as in parallel. The coordinating procedure is conveyed at five stages, that is, preprocessor,
matcher, aggregator, postprocessor, and evaluator. Preprocessor gave a set of uniform operations for ontology matching
approach with different parameters.
The schema and ontology matching tool called COMA++ is an ontology matching system. Aumueller et al50
was introduced to determine semantic correspondences among metadata elements such as XML and RDF is the
central idea of COMA++. This can also provide the graphical user interface that describes the four main com-
ponents of the COMA++ system such as repository, mapping pools (to deal with the mappings and schemas
memory), customizer mapper (classifying the match techniques), and execution engine (to evaluate the matching
operations).
The FoLksonomy Ontology enrichment (FLOR) algorithm was introduced by Angeletou et al,51 which takes a set of
tags as input and automatically extracts the most relevant semantic entities from online ontologies. In three phases, this
has been executed.
The first phase is about lexical representation that defines the list of lexical tags such as nouns and several delimited
types of compound tags. The synonyms and hypernyms for each tag are called sense definition and semantic expan-
sion in the second phase. The list of entities termed Semantic Web Entities (SWEs) is generated in the last phase. An
SWE is an ontological element that thinks about class and connection. The main advantage of connecting labels and
semantic substances is that the tag is automatically related to the semantic neighborhood, giving the most relevant
answers.
Sanjeevi et al52 proposed a wireless sensor network framework for under precision agriculture for crop
monitoring using IoT. Under the concept of precision agriculture and farming, the optimal utilization of the
resources that are provided to the farm is analyzed. This would improve the farmers’ productivity and pre-
serve the natural resources. Parameters such as throughput, latency, and signal efficiency are studied in the
research.
Patel et al53 proposed an efficient credit system for improving the food supply chain in agriculture. The system allows
the farmers to buy quality natural products for lower amounts. Blockchain technology has been used in the proposed
framework to ensure security. A score-based farm-food quality assurance system is proposed, which guarantees optimal
quality grading.
Georgiadis et al54 have presented the works for developing the hydroponics monitoring system based on IoT tech-
nology to grow the plants in the water-based nutrient-rich solution rather than soil. The solution parameters can be
determined using the multiple sensor networking systems, and all required data are sent to the farmers or agronomists
to adjust or control the operating conditions. The proposed novel system can enhance the quality through predictions or
suggestions.
Solodovnik et al55 have analyzed the IoT benefits for agriculture and rural development to enhance the efficiency and
safety of products in the agriculture department. The controlling and tracking of production is provided while improving
the productivity and efficiency of agriculture applications through digitalization.
KHATOON AHMED 9of22
Jamil et al56 have proposed a blockchain-enabled optimization method for greenhouse system to predict, control, and
optimize the greenhouse environment. The sensor data prediction is performed using the Kalman filter algorithm, and
the optimized parameters are used to regulate and operate the conditions of the system. The proposed approach achieves
19% of improved energy consumption against the prediction method and 41% against the baseline scheme based on the
simulation results of an emulation tool.
Treiber and Bernhardt57 have enabled seamless communications standards and implemented the machinery for differ-
ent cloud services. The IoT ecosystems play a crucial role in improving network connectivity, data flow, and compatibility
for agricultural digital products to resolve agriculture problems.
Subeesh and Mehta58 focused on digital technology-driven agriculture and implemented applications in agriculture
based on the IoT and artificial intelligence. The agriculture digitalization with the involved challenges for adoption has
been discussed.
Akhter and Sofi59 has proposed a prediction model of Apple disease in the apple orchards of Kashmir valley based on
machine learning and data analytics in an IoT system. This article has reviewed the trending technologies adoption and
impacts on precision agriculture.
Symeonaki et al60 have presented and analyzed different approaches’ existence, interoperability, and functionality
and their integration toward Agriculture 4.0. The author has detected the challenges in related to the management and
exchanging the heterogeneous data of precision farming environments.
2.2 Semantic interoperability
The accomplishment of this is the fundamental point of W3C. It is accomplished by empowering articulations of the
semantics of things and space imperatives related to them, expanding W3C’s widespread effort on semantic sensor net-
work (SSN) philosophy,61,62 RDF, and linked data innovations. Through an EU IoT stage63 improvement activity known
as IoT-EPI (https://iot-epi.eu/) and the individual book entitled “Advancing IoT Platforms Interoperability Book,” these
exploration ventures are as of now arriving at their finish intriguing results are displayed.
To help physicians and patients remotely, the IoT gadgets from various sellers can be incorporated into medic-
inal services conditions. As well as, when needed, the physicians can screen their patients whenever and any-
place and can refresh medicine. The intelligent personal assistant (IPA)64 has used that can act as a software
agent in IoT devices for providing real-time data about patients to the physicians. The AMBRO mobile gate-
way collects the information from various IPA devices and takes action(s). Among different IPA devices, this
can enable interoperability. This can be used only for correct information never integrated among any other
operating system like iOS or windows phone. To exchange and share the services efficiently and to communi-
cate a huge amount of smart devices among heterogeneous abilities, semantic web advancements are promising
instruments.
To portray keen items utilizing ontologies and description logics to empower semantic interoperability, the cre-
ators proposed65 a semantic model. Further observational analysis is still required in this semantic model to advance
the administration orders for semantic interoperability among smart objects. It is necessary to gather data about
harvest development checking and water system through support through excellent goals to digitize the agricul-
ture domain. An Open IoT platform used for the digital agriculture use case (Phenonet) was described by Jayara-
man et al.66 The OpenIoT stage utilized ontologies to speak to Phenome area ideas to gather a smart collection of
data,67 comment, and approval processes to empower semantic interoperability. An adaptable and keen IoT engi-
neering is needed for the future period to improve the physical sensors revelation and semantic and linguistic
interoperation.
2.3 Semantic web technologies
Desai et al68 have proposed the semantic web empowered design to provide interoperability among savvy things. For
empowering collaboration among different protocols like MQTT, CoAP, and XMPP, the Semantic Gateway as Service
(SGS) collaborates with semantic web technologies. For providing semantic interoperability among conveyed messages,
ontologies can be utilized for semantic thinking. Still, the formal systems are absent for interoperability in innovation and
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information with standard arrangement despite created approaches for semantic interoperability for IoT gadgets. To bring
together, unify, and give semantic interoperability in IoT space, Gyrard and Serrano69 have projected SEG 3.0 system. The
principal advantage of the SEG 3.0 rose out of cosmology designing is incorporating heterogeneous information gathered
from various savvy things.
In M3framework to help engineers structure semantic-based IoT applications, VITAL EU venture for brilliant cities,
and FIESTA-IoT EU venture for semantic interoperability,70 the creator’s useful SEG 3.0 technique on over three specific
use cases. There is a need for interoperability protocols and models to fulfill the execution level amongst low-power het-
erogeneous systems. Highlights of various convention stacks like IEEE 802.15.6, IEEE 802.15.4, 6LoWPAN, Bluetooth
Low Energy, ZigBee, and Bluetooth are utilized to connect this hole and is depicted by creators in Reference 71. They
proposed the sorting out of nonexclusive show stack that discussions through different radios along with various shows
at the same time, paying little character to IP-based or non-IP-based systems. Mingozzi et al72 projected a new identi-
cal stage proposed to subsume the functionalities of context-care and exhibited how such functions might be abused
to motorize exploration and selection of things during normal language. For isolating the information through seman-
tic thinking in spending homes, this can be described that context can be used on organizations. The present insightful
phones have excellent accessibility and identifying capacities to serve the frameworks of body zone and physiologic sen-
sors. Typical models are required to enable interoperability between IoT and machine-to-machine (M2M). Pereira et al73
are demonstrated the ETSI M2M gateway plan that is united with libraries in this context. Based on the diminished devel-
opment costs, IoT applications deployment is required to foster for the purpose. Its performance is measured through
the processing of battery life, memory use, and CPU of mobile phones. In the cloud environment of IoT, a design was
proposed by the makers in Reference 74 for data that helps support semantic interoperability. Based on the Open IoT
structure, Microsoft Azure and Google Cloud were utilized as multi-cloud conditions. Another IoT proposal is described
in Reference 75 to make the digitization of the creation line. To ensure the consistency of information, data is provided
from the condition of heterogeneous IT. Based on semantic web advancements and Open Services for Life Cycle Collab-
oration (OSLC), the compromising of PLM and IoT platforms is suggested for the standard of Lifecycle on the gadget
interoperability.
Niknam and Karshenas76 described semantic web and semantic mining as fast-developing artificial intelligence
research areas. These two massive techniques amalgamation was led to an innovative web framework called semantic
web mining (SWM).77 The semantic web’s primary objective is to make the service information more supportive and
improve the search mechanisms that result in a user’s contentment. A novel path for systematic research and pushing
web services toward meaningful information exploiting several data mining approaches to retrieve desirable knowledge
from the WWW automatically was provided by web mining. Analysis features that semantic web plays a huge assignment
as it gives machine-interpretable data that delivers the information with machine comprehensible and web mining fea-
ture the issue of semantic interpretability based on the semi-structured method to recover concealed information from
the huge quantity of web information.
2.4 Interoperability ontologies
Song et al78 have proposed a probability-based and similarity-based ontology mapping technique. Calculating the similar-
ity among multi-domain ontology models is the main objective of this approach. A novel ontology mapping association
graph is presented in this approach for representing the mapping outcomes.
Twitter Space Semantic Relatedness (TSSR) approach is proposed by Feng et al,79 which is developed upon the basis
of the latent relation hypothesis for measuring the expressive relation among the words on Twitter. A graphical represen-
tation of the terms within the tweets is constructed in this approach. A random walk algorithm is applied to produce a
static distribution of every word that provides a ground for related computation.
The adaptive ontology matching system called PRIOR+that enables semantic interpretability among different web
applications in the semantic web has been proposed by Frimpong.80 The PRIOR+system presents a harmony-based
adaptive aggregation technique to calculate the various similarities among other methods and assign the higher prior-
ity and reliable similarity measure and lower priority that fails to map similar ontology; the PRIOR+system presents
a harmony-based adaptive aggregation technique. Be that as it may, this framework additionally neglected to recover
wanted outcomes with their intended importance. This is fundamental because of how the PRIOR+framework has not
been planned with the expectation of extricating significant data from the web.
KHATOON AHMED 11 of 22
Ref. no. Proposed concept Application/test scenario Remarks
61 Specialized ontology based on the semantic sensor
networks (SSN) for smart home
Smart home The created ontology as tested on different scenarios in a
smart home environment and was found to work
efficiently
62 SSN ontology named IoT-Lite Temperature sensors in a room A set of 10 rules have been proposed to make the model
scalable and efficient
63 Assistive technology for health care applications using
IoT reference architecture model
Health monitoring An IoT framework has been presented by the authors
with a detailed layer level functioning
64 Automatic medical data collection and sends the data
to a caretaker
Healthcare The proposed intelligent personal assistant is a remote
health monitoring device for patients health care needs
65 An ontology framework based on semantic web for
smart object description and user query analysis
Smart environment The proposed model can improve the interoperability
between heterogeneous frameworks in smart
environment applications
66 The authors proposed a new ontology to provide the
data streams processing and storing, annotation,
and smart collection form the sensors placed in the
agricultural fields
Smart agriculture The developed ontology can facilitate the
interoperability between heterogeneous frameworks
that are designed for smart agricultural applications
67 A framework for semantic annotation of big data is
proposed using RDF and SPARQL query
Healthcare The semantic interoperability model for IoT Big data is
proposed for health care applications where drug
recommendations can be done to patients online
based on the medical sensors values
68 The authors propose a Semantic Web gateway for the
intercommunication between devices according to
the communication standards
-The authors experimented on XMPP, CoAP, and MQTT
protocols for the establishment of the communication
between heterogeneous devices
69 The authors proposed a methodology named SEG 3.0
to unify, offer, and federate semantic interoperability
Smart cities, smart agriculture The authors have analyzed several existing techniques
and proposed the framework needed to implement
interoperability in semantic IoT
63 The authors propose a concept named Social IoT
(SIoT) where the communication between different
IoT applications can be easily facilitated
-The paper proposes a SIoT for recommendation services
where the applications can share data and
recommendations based on the usage
64 The authors proposed a generic protocol stack for low
power wireless IoT systems
Healthcare applications The proposed system has been developed for IP and
non-IP based networks with increased reliability
65 The authors propose a context acquisition and
management solution for platforms where huge
number of IoT devices accumulate and store the
data simultaneously
-The proposed system seamlessly analyses the data
coming from various sensors based on the context and
thus help in allocating the services to the various
applications
66 The authors proposed a system named ETSI
machine-to-machine gateway on a smartphone
Physiologic sensors, body area
networks
The proposed method has been implemented keeping in
mid the various challenges faced by the researchers in
the field of IoT
67 The authors proposed a secure multi cloud
hierarchical data processing architecture that is
based on IoT semantics
-The proposed system has been implemented using
OpenIoT, Google Cloud, Microsoft Azure
68 The proposed system is designed to facilitate
information exchange between various systems in a
smart factory environment
Smart industrial applications The proposed system ensures data consistency in hybrid
IoT systems
69 The authors proposed ontologies for construction cost
estimation using sematic web technologies
Construction field The proposed system is a cost estimation and
construction management techniques using semantic
web IoT technology
70 The authors proposed a novel method to compute
structural similarity in the ontologies based on the
information content
- The authors have worked on several ontologies and
formulated the method based on the structure of
several ontologies
78 The authors proposed a probability and similarity
based otology mapping procedure to compare and
analyze different ontologies
-The heterogeneity among the ontologies are studied by
the authors and based on the analysis the proposed
method is formulated
79 The authors proposed a Twitter Space Semantic
Relatedness for Twitter feed analysis
Social media Various twitter posts have been analyzed and
summarized to formulate the proposed algorithm
80 The authors proposed an algorithm to find high-quality
correspondences between different ontologies
-The authors proposed an ontology mapping algorithm to
find the similarities in different frameworks
12 of 22 KHATOON AHMED
3SEMANTIC SCHEMES
3.1 IoT based semantic interoperability model
The human disease’s tracing and monitoring in terms of the prescription medicines within the medical field are specified
in this method. The three main elements of IoT-SIM are cloud services (CS), semantic interoperability (SI), and user
interface (UI). By the IoT devices, the doctor and patient interact with one another in UI. Excluding some of the particular
vendor constraints, the patients can be monitored and prescribed from any distance and at any moment. The SI and
the UI section interact without delay. The interoperability in various IoT devices by distinct vendors is a challenging
task. The data interchange using significant and accessible implications is referred to as SI. With the self-appointed data
packages, the semantics are included within the information. SI is implemented to ensure the interoperability of the IoT
devices out of various vendors. The information is taken from IoT devices for constructing a significant mutual vocabulary,
and semantic annotations are added. A data processing approach where the crucial outcomes are drawn out of the raw
materials is called data analytics. The cost is reduced, and this approach can effectively make the decisions. Upon the
collected data out of the IoT devices, this approach is implemented. Later, it is made significant and cost-efficient by
undergoing semantic explanations. The proposed architectural model in IoT for semantic interoperability is shown in
Figure 3.
FIGURE 3 Architecture model of semantic interoperability in IoT
KHATOON AHMED 13 of 22
3.2 Semantic annotations of data using heterogeneous IoT
Devices: With the sensors’ help, the communication among the sensors is carried out by the IoT devices. A sensor net-
work API is present in each device for filtering the data based on the field. The sensors finally communicate to the
entire people after sending the sensor data that is filtered. The sensor web enablement framework is implemented for
providing web services by using heterogeneous IoT devices. The IoT devices are discovered, accessed, and employed by
SWE. The information regarding the healthcare corresponding to human diseases is represented by the tokens called
keywords.
Each token with a description was sent to the classification section of diseases after moving the data set to the section
of semantic interoperability. The categorization of each token in a particular domain of hum diseases is made. This section
has been categorized the human condition in different ways to know about the information of a patient who has which
kind of disease. Based on heterogeneous devices in IoT, a lightweight model proposes for semantic annotation of data
depicted in Figure 4. According to the patients’ diseases, the operational flow can be represented from data collection to
their classification.
The system can recommend the medicine automatically to identify disease. Whenever recommended prescrip-
tion from the doctor to understanding is coordinated with recognized illness, it is correct drug generally spe-
cialist endorsed the wrong medicine. The information about wrong or proper medication with the doctor’s and
patients admitted proof is stored by the capacity of Intelligent Health Cloud. Grouped maladies detached classes
as per medicinal services area are sent to tagging segment in which the automatic or physical annotation by ail-
ments semantically according to the resource description framework. For relating the things semantically, RDF
is utilized uniform resource identifiers (URIs) as a standard metadata model. In Figure 4, the same appears
additionally.
FIGURE 4 Lightweight model for semantic annotation of data using heterogeneous devices in IoT
14 of 22 KHATOON AHMED
Ref. no. Proposed concept Application/test scenario Remarks
81 Optimized semantic
interoperability framework
Smart home The proposed framework has been implemented
using Restlet and RDF to achieve sematic
interoperability
82 Horizontally semantic
interoperability
Agriculture The authors have designed a middleware framework
that can be operated by both IT and non-IT experts
which makes it easy for the end users to use the
technology to the fullest
83 The current state of
ontology-based software tools
are reviewed and assessed for
semantic interoperability
- The proposed survey analyzed the IoT ecosystem
with special focus on the ontologies available that
facilitate the semantic interoperability between
heterogeneous systems
84 The semantic interoperability
current solutions and
challenges are provided
IoT The authors have analyzed the need for semantic
interoperability and emphasized on the different
existing topologies with the standard
representation and lightweight requirement to
provide interoperability
3.3 Semantic web technology for agriculture
Tim Berners-Lee has coined the word semantic web. The direction of carrying arrangement and importance toward data
depicted during site side was his intention for the semantic web. This goal has been programmed as World Wide Web
Consortium (W3C) standard. Its expressed points are: make information provisions on Web, construct vocabularies, as
well as form regulations for dealing with information. This is authentication of this appraise horticulture to be the zone
fitting for gathering semantic web developments. This section would give vital side interest to the determination of seman-
tic web advances. It can be acknowledged that the client has several essential comprehensions of the semantic web and
its related passages. Perusers who are new to this territory are encouraged to counsel for a point by point discourse of
the zone.
3.3.1 Knowledge store
Agricultural procedures are needy, leading to an interlinked assortment of information. For instance, harvest output
result depends not only on harvest species but also on dirt composition, nearby atmosphere, and bug populaces, just like
relentlessness of prepare attacks. This is impossible so that some solitary knowledge base would require the entirety of
this data by an adequate granularity that could be valuable to an entity rancher. Its reliance on information from varying
regions can compensate for utilizing semantic web innovations since it is likely that there would be secluded point by point
stores on each of these domains, as opposed to a solitary solid information pedestal. Inaccessible amass of information
be able to adjust utilizing semantic web innovation. This procedure would enable it to be questioned when a superior
interlinked asset of data.
3.3.2 Data integration
On data, the accuracy agriculture is always getting reliant. Data flood as of different information basis should incorpo-
rate with the goal that they might be moreover questioned like an aggregated data-flow otherwise put away in another
framework for disconnected dispensation. Semantic web advancements give a typically structured depiction of data
assembled from genuine-time sensors, like from non-ongoing sources, such as producer and retail frameworks. One
of the main problems in accuracy agriculture is data integration. Similarly, the web technologies are started to play a
key role.
KHATOON AHMED 15 of 22
Ref. no. Proposed concept Application/test scenario Remarks
85 Semantic web technologies for
agricultural
Agriculture The survey is indeed to motivate the research
on semantic web technologies specifically in
the field of agriculture
86 IoT and semantic web methodologies
have incorporates by the configurable
and interoperable middleware
Agriculture The authors proposed a interoperable and
configurable middleware for agriculture
applications so that individual sensors can
communicate with the global sensor
network
87 From multiple domain related
repositories, the extraction of
knowledge is enabled by the
Integrated Agriculture Information
Framework (IAIF)
Agriculture The ontology engineering methodology
proposed by the authors is designed to link
different data sources related to agriculture
88 Make a review on reengineering web
applications and semantic web
applications with the quality analysis
-The authors point out the drawbacks present
in the existing IoT system and try to validate
the role of software engineering in a
semantic web application
89 The contemporary approaches that
exploit AI characterize to explore
alternative solutions for web services
- The authors propose a survey on AI based
solutions for improving the
quality-of-service (QoS) in semantic web
applications
90 Summarizing the semantic web
research and the need is highlighted
for exploring the under-represented
topics further
-The review covers the topics of recent trends
in the semantic web technology namely
processing of information, collection of
information, policies and access control and
the research gaps existing
91 Generic semantic mapping framework
SEMAP
Agriculture The authors present an ontology for
agricultural applications where different
layers of information can be combined to
derive qualitative spatial facts about
92 The approaches of machine translation
with a systematic review that depend
on semantic web technologies to
translate the texts
Text translation The authors present a machine translation
approach where content is translated using
the semantic web technology
93 Semantic web nature and its
requirements analyze
- The authors surveyed a total of 10 different
domains related to semantic web
technologies and have presented their
unbiased views and observations
94 Overview of several active research
areas within the semantic data
integration field
Biomedical The authors presented a review of several
challenges that exist in the field of semantic
data integration and showcase the
importance of identifying complex
relationships that exist in the data
3.4 Semantic resources for agriculture
The acceptance of semantic web strategies is reliant on the presence of obtainable semantic possessions. Semantic assets
for farming are assets that utilize semantic technologies to portray information examined via association or individual.
For reasons for this overview, explain that resources are unreservedly accessible and accompany moderate client licenses.
Semantic assets that be checked on for this segment are integrated: proscribed expressions, scientific categorizations,
thesauri, and preselected conditions or expressions for a particular space. Taxonomy efficiently orchestrates proscribed
16 of 22 KHATOON AHMED
vocabularies into various leveled configurations that can be imagined like a tree. Meta-information regarding elements
is restricted in its folks, like perimeter interfacing it to its parent. Thesaurus is like a scientific classification, yet adding
to various leveled configurations, a thesaurus includes broader connections where elements might be connected and do
not contain straight progressive association. Ontologies are away to “officially replica arrangement of a framework, that
is, applicable creature and relations that arise out of its perception.” This conventional model is where hubs are entities
with edges depicting relationships among entities. Typically by ontologies, fashioners can enlarge consumer character-
ized classes that contain better granularity than generic arrangements utilized in scientific classifications along with
thesauri.
Farming is served by unreservedly accessible resources since there have been deliberate yet ungraceful attempts to
create semantic assets for horticulture via various nationwide agencies. Semantic assets are commonly one of two kinds:
usual agriculture or particular sub-spaces of agriculture.
3.4.1 Ontology repositories
A sizeable monolithic resource is AGROVOC. Aggregation of smaller ontologies into excellent resources was different
from enormous semantic resources. In the literature review is four important resources are situated. Crop Ontol-
ogy, Agro Portal, CIARD Ring, and Vest.7 via a web interface; these resources are typically accessible and can be
queried.
Many ontologies can be searched via the Crop Ontology and contain: “phenotype, breeding, germplasm, and trait
categories.” A web interface was offered via Crop Ontology, which allows collaboration between users. People, in general,
confronting web-interface be recognized as Crop Ontology CurationTool8, which be an Open Source venture that permits
distribution of ontologies. Previously mentioned devices allow the uploading of quality word references for crop rearing
and straight formation of ontologies. Characteristic word references contain Germplasm ID, which is related by typical
factors that explain the mannerism of particular germplasm, such as output and particle shading.
Using upload OBO folder that requires RDF-triples for projected Ontologies can be created. Through an interactive
interface where terms with relations might add physically. It is also possible to create an ontology. The various ontolo-
gies, the Crop Ontology, have a public-facing REST Web API, and they are: queried, developed, and updated otherwise
deleted. Directions are annexed onto the conclusion of the URL, along with data being returned in JSON arrange-
ment. Run of the mill inquiry be: http://www.cropontology.org/getontologies, which restores rundown of accessible
ontologies.
Crop Ontology and AgroPortal are alike but need a few variations. The predominant one be AgroPor-
tal carries non-crop ontologies, including Animal Disease Ontology (ADO) with Biorefinery (BIOREFINERY)
Ontology.
The preferred position that repositories contain over their bigger cousins like AGROVOC is decentralized advance-
ment. Detailed or specific data that might hold any importance with a small number of clients that might disregard by
larger ontology designers be able to include via an inspired entity to a metaphysics archive. A case of this wonders be that
Agro-Portal has FoodOn Ontology9, which describes the nation of the cause of nourishment, however its wrapping and
safeguarding process just as various other-meta-properties. The absence of fine-grained information will be done from
bigger ontologies.
3.4.2 Linked data hubs
Berners-Lee’s demonstrated the Semantic Web’s initial vision for the web data interconnection. Based on the linked
open data, the interlinking of semantic resources is made for agriculture. The data hubs are connected that involves
the platform to link the different semantic resources together. According to the normal procedure, the middle
point might be transformed from one particular resource as content providers are aligned to more diminutive
resources based on the rule asset. The associated data hubs are made so that the platform is linking with differ-
ent semantic resources together. Since the alignment of content providers is made for more diminutive resources
based on the rule resource, one particular resource may be transformed into a middle point according to the usual
procedure.
KHATOON AHMED 17 of 22
The building of the matching scheme is the complementary approach that aligns the chosen semantic resources
explicitly. The Global Agricultural Concept Scheme Core (GACS) designers were considered this advancement. The
main objectives of GACS are included the agricultural data semantic interoperability and improvement of discoverability.
Through linking together primary resources like AGROVOC, the CAB, the GACS can achieve these aims. The map plays
a key role for ′datasets about food and agriculture Thesaurus with NAL.
During thematic groups approved in hierarchical formation, the structural design of GACS is organized.
The highest range thematic groups are: “Physical sciences, general, life sciences, Earth sciences, applied science with
technology, and social sciences with humanities.′
145 s range groups, agriculture, fishery, and forestry thematic collection goes below applied science and technology
huge-range gathering. The importance of the idea chain is a known wellspring of weakness, then because the ideas are
frequently conflicting.
Thematic corporations contain associated concepts from AGROVOC, CAB and NAL. Thematic groups covered 82%
of ideas from AGROVOC, CAB, with NAL. Using custom relations unique to GACS, the principles in base sources that
contain no direct correspondent within base resources are united.
To combine perception from entity resources, the GACS takes the most significant attempt, and there be addi-
tional efforts to combine different semantic resources. Several environmental semantic resources are together by
LusTRE links, and they are EUNIS (species and habitat types), along with Environmental Application Refer-
ence Thesaurus (EARTH). Resources of them are integrated through linked Data to agricultural resources like
AGROVOC and NAL. Human comprehensible interface has taken place by Lus-TRE and permits consumers to
question related resources. Notwithstanding GACS with Luster, connected inked data hubs comprise integrated
specialized semantic agricultural assets, such as soil and land organization. The interoperability of semantic
resources using linked data is regularly alluded to as agrisemantics (http://agrisemantics.org). Linked data hubs
can view as the primary step for interoperability among semantic resources for farming in the agrisemantics
movement.
3.4.3 Semantic data standards
Agriculture requires common standards for semantic internet technology to permit free alternate of semantically
explained records with enlargement of commonplace vocabularies.
To supply the sort of standard for: “the description, useful resource innovation, interoperability along with data
exchange for unique varieties of statistics resources,” the FAO has attempted on these things. However, it refers to the
Agricultural Metadata Element set (AgMes), which includes five sub-requirements such as Job opening Meta-records
(Ag-Jobs AP), Event Metadata (Ag-Events AP), AGRIS Metadata (AGRIS AP), and Learning Resources Metadata (Ag-LR
AP) with Organization Metadata (Ag-Org AP).
The semantic assets are not more often than not designed for data exchange, and there are requirements
whose primary goal is data exchange. Agro-RDF is one such approach that is a data change preferred designed
especially for agricultural records. For Agro-XML, the AgroRDF is a semantic overlay that’s an XML fact trade
modern. Its stated objectives are: “exchange among on-farm frameworks along with outside stakeholders, large
degree documentation of agricultural techniques, records incorporation amongst distinct farming manufacturing
groups, semantic incorporation among specific standards with vocabularies and way for the consistent stipulation
of information on working supplies.” In the literature review, the AgroRDF principle became unique. Another
data exchange is the standards mainly intended toward semantic resources instead of an overlay for the standard
of XML.
Directly on machinery, client services are run and with the component of Service Registration or Invocation that will be
resulted in the registration of Semantic Service Repository references. To invoke the provider on a far off device, the patron
carrier communicates by Service Registration/Invocation module. Purchaser carrier shares facts that the machinery has
generated. And via an undescribed data analytics service, this data is then analyzed.
With semantic web technologies, the data exchange can get progressively increasingly significant as mechaniza-
tion of ranches increments, and utilization of remote sensing technologies become increasingly well known. This
be on the grounds that the dissimilar frameworks should speak with a focal system and once in a while with one
another.
18 of 22 KHATOON AHMED
Ref. no. Proposed concept Application/test scenario Remarks
95 Based on the skills of an operator, the
information is represented and subsume
into the approach of service-oriented
orchestration for a production line
Industrial automation The information representation on the
skills of an operator and it is involved in
the service-oriented orchestration
method for a production line is described
in the paper
96 Three stages have included in the strategy that
is location aspect within each phase,
international data standards, and finally
Semantic Web Technologies, ontologies, and
semantic rules
Road network The gap of harmonization of data in road
asset management in New Zealand and
Australia is filled out
97 Semantic centrality (Outdegree, Indegree,
Closeness, and Betweenness)
Disaster risk management The evaluation of semantic resources is
automated in the paper and allows to
implement a well-known theoretical
technique to the linked data semantic
issues
98 Semantic web-based technologies. Specifically,
RDF format is focused on linking and
publishing od information for the purpose
of sharing
Agriculture To share the data, RDF format is focused by
the authors to publish and link the
information that helps the farmers to
access the related and contextual
information accurately
99 For virtual reality and embedded systems,
service-oriented architecture is considered
ES and VR applications In the product life cycle, different scenarios
are made by service-oriented
architectures. Because of software reuse,
the effort of implementation is reduced
for embedded systems
100 Based on a set of features like Web Services,
business Web Services, or lack of a
standardized adoption, the recent RESTful
services, current approaches are overviewed
-The current methods overview, future
directions for service composition
mechanisms and relevant core issues are
presented with a set of features by the
authors
4CONCLUSION
This article presented a systematic mapping study related to IoT semantic interoperability. The challenges and restrictions
and how earlier technologies relate to the current state-of-the-art have been demonstrated. The mapping results provide
the research overview relevant to the investigated topic. The requirements of supporting the Semantic Web technologies
have included semantic interoperability in the IoT context. This context has included limitations because of the onto-
logical correspondence and formal representation. Generally, these issues cannot be resolved automatically. The results
indicate the gaps for the IoT semantic interoperability context:
1. The adoption of best practices suggested by the Semantic Web community is required.
2. The methodologies are not available in ontologies modeling that fulfills the application requirements in the IoT
domain.
3. Ontology catalogues are not maintained in IoT domains.
4. Lack of alignment or matching tools for describing the information in the IoT context.
The roadmap issues are provided based on these gaps, and they can be explored in further research.
DATA AVAILABILITY STATEMENT
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
KHATOON AHMED 19 of 22
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How to cite this article: Khatoon PS, Ahmed M. Importance of semantic interoperability in smart
agriculture systems. Trans Emerging Tel Tech. 2022;33(5):e4448. doi: 10.1002/ett.4448
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