Transforming Agriculture through Advance Technology

IoT- based embedded device to identify soil type, amount of nutrients available in the soil with E-Agriculture services like Real time disease detection, Real time stress Detection, online community, Real time crop storage finder, integrated E-commerce portal for Agri product, soil test pickup system and AI Assistance for farmers.

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Why KrishiKarman?

We KrishiKarman provide end to end agriculture product and service from cultivation of crop to selling of goods or product, everything in a single platform. The platform Krishikarman is not only capable of increasing the productivity of famers/small, medium and large scale farms but also making our farmers more digitalize in terms of adoption and use of technology in the field of agriculture.

Smart IoT Devices
A framework to be developed that can measure Real time weather information, Soil Status (NPK values), Irrigation system and GPS. The device developed using the framework can be control by Android application remotely and manually by switches available on the device.
Soil test- pickup and delivery system
In many cases farmers may want to have accurate results for the type of soil for checking the macro nutrients and would like the soil sample to be tested in lab, hence in this proposal, a model is to be developed where a farmer can request for a soil test of their respective location with Geo-coordinates that will be sent to nearby pickup and delivery personals (geo co-ordinate can be acquired from both Android and IoT device, to be developed as a part of this project). Based on the co-ordinates the personals will pick up the soil sample without farmers intervention and deliver it to the nearby soil test center and results will be reflected on farmers Android/Web application as soon as test is carried out.
Classification using Remote Sensing data
Using Machine Learning or Deep Learning algorithms, the Remote Sensing data which can be acquired from our own UAV or Satellite Multispectral data, the stress of crop, diseases of crop of an area can be identified.
Prediction model
Using existing sensor archived data, in this project, machine learning algorithm will be applied to predict future possibilities of cultivation and different disease the crops might be suffering. Using past archive data, with sensor data and data generated from both android and web application, machine learning algorithm is applied to predict future possibilities of reducing the loss in agriculture which happens due to diseases, stress etc. and also identify the cause of those.

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Agriculture is our wisest pursuit, because it will in the end contribute most to real wealth, good morals, and happiness. Thomas Jefferson

“I believe in the future of agriculture, with a faith born not of words but of deeds.” E.M. Tiffany