Smart Agriculture IOT with Cloud Computing, Fog Computing and Edge Computing
S. Nandhini1, Shivcharan Bhrathi2, D. Dheeraj Goud3, K. Pranay Krishna4
1S. Nandhini, Assistant Professor, SRM Institute of Science and Technology, Chennai (Tamil Nadu) India.
2Shivcharan Bhrathi, SRM Institute of Science and Technology, Chennai (Tamil Nadu) India.
3D. Dheeraj Goud, SRM Institute of Science and Technology, Chennai (Tamil Nadu) India.
4K. Pranay Krishna, SRM Institute of Science and Technology, Chennai (Tamil Nadu) India.
Manuscript received on November 24, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 3578-3582 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B2600129219/2019©BEIESP | DOI: 10.35940/ijeat.B2600.129219
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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: Smart Farming could be a explained as a farming method which works on the thought process of a fashionable technology to increase the yield of the amount and quality of agricultural merchandise. IoT-based smart farming, a system solely made for the observation of crops in the field with the assistance of sensors and automating the irrigation system in accordance to our needs. Antique cloud-based system which uses mostly IoT models are inadequate to handle the traffic and the database of knowledge. So as to an extent it turns out to be lower latency, longer battery life for IoT devices, a lot of efficient money-based knowledge management, access to knowledge management and AI, ML IoT-EDGE based system is proposed or may be adopted. Edge for the IoT brings potential edges for several IoT deployments, as well as removal of interval in conjunction with geometric communications potency, compared to exploitation of the cloud to process and store knowledge. For example, several IoT processes will have a high level of automation at the sting leading to low latency for fast processing. The machine ifogsim is employed for modelling and simulating the sting based mostly on the IoT system which also includes the edge and the fog. The results of this method are to indicate that Edge computing based mostly IoT models are a lot of economical and extremely fast and may turn out and provide higher results when put next to different systems.
Keywords: IOT (Internet of Things) Cloud Computing Fog Computing Edge computing Smart Farming.