SAGRO-Lite: A Light Weight Agent Based Semantic Model …
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4 Proposed Model
4.1 Agent Based Semantic Model for Smart Agriculture
(ABSMSA)
A digital ecosystem is a distributed, adaptive, open socio-technical system with
properties of self-organization, scalability and sustainability inspired from natural
ecosystems. Digital eco-system models are inspired by knowledge of natural ecosystems especially for aspects related to competition and collaboration among diverse
entities [63, 64].
MAS is decentralized and its functioning in accordance with the cloud systems
forms the foundation for the heterogeneous style of horticulture. Even each and every
stakeholder who is associated with agriculture including buyers, sellers, and also third
party people like pesticide, fertilizers, seeds and farming equipment suppliers will
benefit.
The constituents of ABSMSA are discussed below.
4.1.1 Cloud Based Platform
The services provided here are through intelligent agents that are autonomous and
can react to events. The cloud based platform provides for securely saving the data
in the form of big data and conduct analytics and prediction through negotiations via
enterprise service bus.
4.1.2 Ontologies in Smart Agronomics
Is formed by the entities recognized in the domain of smart horticulture like all the
information needed about the seeds, crops, diseases, pests, seasons, weathers, soil,
machines, etc. and the relationships between these entities in the form of predicate
logic. These ontologies are designed by the authors keeping in mind the requirements
of agriculture by the agronomists of developing countries. Here careful consideration
is made in order to eliminate too extensive ontologies and focused selection of terms
and attributes are made to help the farmer and for better performance. Three separate
knowledge bases are used. Existing Light weight ontology called IoT-Lite is user for
the purpose of sensory data in heterogeneous IoT platforms [16]. Another ontology,
named Complex Event Service Ontology (CESO) is used to trigger and manage farm
events, like immediate need to irrigate, detection of sick animals or pests in crops
[65]. This also aids in better decision power by the agronomist.
279
4 Proposed Model
4.1 Agent Based Semantic Model for Smart Agriculture
(ABSMSA)
A digital ecosystem is a distributed, adaptive, open socio-technical system with
properties of self-organization, scalability and sustainability inspired from natural
ecosystems. Digital eco-system models are inspired by knowledge of natural ecosystems especially for aspects related to competition and collaboration among diverse
entities [63, 64].
MAS is decentralized and its functioning in accordance with the cloud systems
forms the foundation for the heterogeneous style of horticulture. Even each and every
stakeholder who is associated with agriculture including buyers, sellers, and also third
party people like pesticide, fertilizers, seeds and farming equipment suppliers will
benefit.
The constituents of ABSMSA are discussed below.
4.1.1 Cloud Based Platform
The services provided here are through intelligent agents that are autonomous and
can react to events. The cloud based platform provides for securely saving the data
in the form of big data and conduct analytics and prediction through negotiations via
enterprise service bus.
4.1.2 Ontologies in Smart Agronomics
Is formed by the entities recognized in the domain of smart horticulture like all the
information needed about the seeds, crops, diseases, pests, seasons, weathers, soil,
machines, etc. and the relationships between these entities in the form of predicate
logic. These ontologies are designed by the authors keeping in mind the requirements
of agriculture by the agronomists of developing countries. Here careful consideration
is made in order to eliminate too extensive ontologies and focused selection of terms
and attributes are made to help the farmer and for better performance. Three separate
knowledge bases are used. Existing Light weight ontology called IoT-Lite is user for
the purpose of sensory data in heterogeneous IoT platforms [16]. Another ontology,
named Complex Event Service Ontology (CESO) is used to trigger and manage farm
events, like immediate need to irrigate, detection of sick animals or pests in crops
[65]. This also aids in better decision power by the agronomist.