AgriCom: A communication platform for agriculture sector

Jayarathna, H. M. H. R.; Hettige, B

doi:10.1109/iciinfs.2013.6732024

Cited by 8 publications

(3 citation statements)

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“…The intents for the examples from 9 to 13 were identified in our previous research (Tharindu and Ekanayake, 2018) and the provided intents by the Chat-Bot for the given examples are correct. The system developed by Jayarathna and Hettige (2013) is somewhat similar to our system. They used multi-agent technology while we used Chat-Bot technology, which is widely used in applications like question-answering systems in many areas.…”

Section: Results and Discussion Translation Chat-roommentioning

confidence: 99%

E-AGRO: Intelligent Chat-Bot. IoT and Artificial Intelligence to Enhance Farming Industry

Ekanayake

Luckshitha

2020

AOL

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This study develops a chat room and a Chat-Bot to discuss the prevailing issues related to farming with peers and expertise and support farmers to make timely decision on farming. A standard set of questions was identified through discussions and surveys with farmers, expertise and other stakeholders. Intents, which the users might want to know, and examples, which the users use to explain a specific intent and entities that are different objects referring to an intent were identified from the questions. Artificial Intelligence Markup Language (AIML) was used to train a model, which predicts an intent based on the given example. The Chat-Bot was implemented in a cloud platform and therefore, the client end does not require more computational resources.

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Section: Results and Discussion Translation Chat-roommentioning

confidence: 99%

E-AGRO: Intelligent Chat-Bot. IoT and Artificial Intelligence to Enhance Farming Industry

Ekanayake

Luckshitha

2020

AOL

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“…Hence, the driving force behind the development of I4.0 is the rapidly increasing digitization of the economy and society, in the sectors of agriculture (Jayarathna & Hettige, 2013), production (Meridou et al, 2015), and services, for example, banking (Atkinson et al, 2006), telecom (Agrawal et al, 2008), tourism (Fang et al, 2016), or insurance (Koetter et al, 2019).…”

Section: Challenges Of Industry 40mentioning

confidence: 99%

Ontologies for Industry 4.0

Ragavan

Khamis

Fiorini³

et al. 2019

The Knowledge Engineering Review

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The current fourth industrial revolution, or 'Industry 4.0' (I4.0), is driven by digital data, connectivity, and cyber systems, and it has the potential to create impressive/new business opportunities. With the arrival of I4.0, the scenario of various intelligent systems interacting reliably and securely with each other becomes a reality which technical systems need to address. One major aspect of I4.0 is to adopt a coherent approach for the semantic communication in between multiple intelligent systems, which include human and artificial (software or hardware) agents. For this purpose, ontologies can provide the solution by formalizing the smart manufacturing knowledge in an interoperable way. Hence, this paper presents the few existing ontologies for I4.0, along with the current state of the standardization effort in the factory 4.0 domain and examples of real-world scenarios for I4.0.

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“…In live session, agent does the all the activities and the move to end session to quit. This framework originally implemented for English to Sinhala Machine translation [16][17] and it has been improved as a general framework [18].…”

Section: Masmt Frameworkmentioning

confidence: 99%

Resource Sharing in Distributed Environment using Multi-agent Technology

Weerasinghe¹,

Hettige²,

Kathriarachchi³

et al. 2017

IJCA

Self Cite

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Resource sharing is very important in the world Due to limited resources. People tend to use different applications for similar purposes within the network environment making the high traffic and duplicating resource. The complexity and the dynamic behaviour of computer network do not leave a clue to predict what happen next. The multi-agent technology has proven potential results in improving efficiency and accuracy in dynamic and distributed environments. Among other features, a multi-agent technology can produce solutions that are globally accepted to the agents through communication, negotiation, and coordination among the agents. This research presents the method for reducing resource wastage and sharing resources efficiently using multi-agent technology. Network users will download the same file again and again unintentionally, bringing network performance dramatically down. With the concept of dynamic scheduling and load balancing, implement a system to share resources within a network using Multi-agent technology. The solution is developed by the MaSMT, a Java-based framework, with one manager agent and four ordinary agents, namely, file send agent, file receives agent, download agent and load balancing and dynamic scheduling agent. Using this system task has been allocated to distributed agents within a dynamic network for sharing resources. The system is successfully tested in real environments and will help to reduce the resource wastage on network environments.

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AgriCom: A communication platform for agriculture sector

Cited by 8 publications

References 0 publications

E-AGRO: Intelligent Chat-Bot. IoT and Artificial Intelligence to Enhance Farming Industry

E-AGRO: Intelligent Chat-Bot. IoT and Artificial Intelligence to Enhance Farming Industry

Ontologies for Industry 4.0

Resource Sharing in Distributed Environment using Multi-agent Technology

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