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Crop Recommendation device
Crop Recommendation device
Developed ML models achieving 87% accuracy.
Deployed and tested models on FPGA.
Pynq-z2 board is configured initially using pynq.io OS. Later the ML code is dumped in the FPGA board.The other part of the device takes a soil sample and then by this algorithm we can predict the temperature and humidity in the region.
Pynq-z2 board is configured initially using pynq.io OS. Later the ML code is dumped in the FPGA board.The other part of the device takes a soil sample and then by this algorithm we can predict the temperature and humidity in the region.
I wrote two algorithms using Linear Regression and the other using Random Forest Classifier. Both the models gave good accuracy but the linear model was more accurate.
I wrote two algorithms using Linear Regression and the other using Random Forest Classifier. Both the models gave good accuracy but the linear model was more accurate.
Luminosity Drone - Eyantra IIT Bombay 2023
Luminosity Drone - Eyantra IIT Bombay 2023
Developed Python algorithms for object detection.
Deployed real-time detection on drone MCU.
• I developed image processing algorithms using Python and OpenCV to accurately detect infrared-emitting objects within a specified area.
• I developed image processing algorithms using Python and OpenCV to accurately detect infrared-emitting objects within a specified area.
• Implemented and deployed the algorithms on the drone’s MCU, enabling real-time processing and detection capabilities.
• Implemented and deployed the algorithms on the drone’s MCU, enabling real-time processing and detection capabilities.
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