Smart Farming: IoT Based Plant Leaf Disease Detection and Prediction using Deep Neural Network with Image Processing
Prema K1, Carmel Mary Belinda2
1Prema K, Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, (Tamil Nadu), India.
21Carmel Mary Belinda, Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, (Tamil Nadu), India.
Manuscript received on 03 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 July 2019 | PP: 3081-3083 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7707078919/19©BEIESP | DOI: 10.35940/ijitee.I7707.078919
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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: Agriculture plays a major role in human life. Almost 60% of the population is involved directly or indirectly in some agriculture activity. But Nowadays, farmers have quit agriculture and shifted to other sectors due to less adoption of automation and other reasons like increase in the requirement of agricultural laborers. So, Farmers now largely depend on adoption of cognitive solutions with technological advancements to acquire the benefits. Image processing and Internet of Things jointly produces new dimensions in the field of smart precision farming. This proposed methodology aims to create an approach for plant leaf disease detection based on deep neural network. This approach combines IoT and image processing which runs pre-processing and feature extraction techniques by considering different features such as color, texture, size and performs classification using deep learning model that expands to help identification of plant leaf disease.
Index Terms: Deep Convolutional Neural Network, Image Processing, Internet of Things, Plant Leaf Disease Detection.
Scope of the Article: IoT