AgriFog- A Fog Computing based IoT for Smart Agriculture
Sucharitha. V1, Prakash. P2, Ganesh Neelakanta Iyer3
1Sucharitha.V, Department of Computer Science and Engineering, Amrita School of Engineering, Amrita University, Coimbatore, (Tamil Nadu), India.
2Prakash .P, Department of Computer Science and Engineering, Amrita School of Engineering, Amrita University, Coimbatore, (Tamil Nadu), India.
3Ganesh Neelakanta Iyer, Department of Computer Science and Engineering, Amrita School of Engineering, Amrita University, Coimbatore, (Tamil Nadu), India.
Manuscript received on 13 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 210-217 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2189037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The smart agriculture or precision agriculture is contemplated to play a vital role in augmenting the various farming activities. IoT based farm management systems have emanated from the rapid expansion of connectivity. The smart agriculture or precision agriculture is contemplated to play a vital role in augmenting the various farming activities. The existing systems which are based on traditional cloud models are inadequate to handle the large amounts and variety of data generated by the IoT devices connected. In order to decrease the latency in aiding the real time decisions based on the data produced, it is essential to bring the data processing closer to the source of its production. This can be addressed by adopting the fog based models. An IoT-Fog based farm management system can be more competent in terms of optimal bandwidth utilization and low latency for real time decision making. The architecture of the proposed approach has been presented and elucidated. The AgriFog application has been modelled and simulated using iFogSim. The results substantiate the postulate that the fog based model of the farm management system is more efficient and preferable for adoption because of its support for effective scalability with better response time and reduced latency.
Keywords: Fog Computing, Farm Management System, IoT, Smart Agriculture
Scope of the Article: Soft Computing