Farmyzer

Sri Harsha Gajavalli

Sri Harsha Gajavalli

Tempe, Arizona

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  • 0 Collaborators

In our research on the possible issues for the farmers not being able to make enough profits, we found the failure of disease detection at the right time has become one of the important. In order to overcome this problem, Deep Learning models were developed for plant disease detection with the inspiration ofAlexNet and GoogleNet Architectures as a part of my startup for farmers. This software predicts the disease from the image of the crop and suggests suitable pesticides and insecticides cure it. ...learn more

Project status: Under Development

Internet of Things, Artificial Intelligence

Intel Technologies
oneAPI, Intel Opt ML/DL Framework, Movidius NCS, DevCloud

Overview / Usage

Agriculture is the backbone of the Indian economy and contributes to about 17% of its GDP. Yet, the condition of farmers in India is quite poor. The main reason for this condition can be credited to the lack of information and the ability to process available information to make informed choices. The main objective of this project is to overcome these problems and to boost the output of each farm thereby uplifting the economic condition of the farmer as well as stabilize the food security of the country. With our objectives clear, we at Farmyzer have been working on an AI-powered tool that helps farmers become self-sufficient by providing personalized suggestions, monitoring fertility, identifying and countering plant diseases and maximizing the overall yield and profit, thus arming them with the resources required to tackle problems such as unreliable weather conditions, overdependence on middlemen, lack of soil fertility and outbreak of plant diseases.

Farmyzer takes on a novel way in approaching the problem. Along with the traditional statistical analysis employed by various other products, we had been working on bringing in state of the art methods in computer vision and machine learning to develop a product like none other. And thus Farmyzer would be able to be a fully automated solution whose efficiency wouldn’t be limited by the cognitive abilities of humans. Our solutions give personalized suggestions to the farmers at the right time along with the right information

This product consists of four main features: ‘Grow A New Crop’, ‘Farm Health’, ‘Right Day To Harvest’ and ‘Sell Your Produce’.

Methodology / Approach

Technology Stack: Intel optimized caffe, Intel optimized TensorFlow, Keras, OpenCV, Numpy, Scipy, Scikit-learn, matplotlib

Hardware used: Intel Core i7 processor, Intel Xeon Phi, Intel Movidius Neural Compute Stick with Raspberry Pi, AI Vision Kit

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