Optimization of culinary processes through the implementation of Functional Object-Oriented Network (FOON).

Utilization of Iterative Deepening Search (IDS) and Greedy Best-First Search (GBFS) guided by heuristic functions.

Focus on extracting task trees for a wide range of dishes to enhance culinary operations' efficiency and accuracy.

Investigated the impact of bioactive Ag-hydrosol nanoparticles (NPs) on drug-resistant E. faecium 1449 and explored the use of artificial intelligence (Faster RCNN model) for automated bacteria detection.

Highlighted the potential of Ag-hydrosol NPs for combating drug-resistant bacteria and the usefulness of AI in assessing treatment effects, offering a significant contribution to the field of antibacterial therapies.

Found the suitable path automatically through Arduino which decided the path observing the data from the Sonar Sensors.

Detected faces by training CNN model on Raspberry Pi3 and captured a 2-minute video by Pi Camera.

Implemented a wireless device along with a PCB board to log the PPG and GSR data through Bluetooth.

Estimated the heart rate from PPG signal through a dynamic HR model provided by DFT - based frequency analysis and careful Kalman Filter tuning. 

Extracted the SCL and SCR features of GSR signal applying SparseEDA algorithm to the processed data.

Applied Image Processing Tools to extract vein features from hand images.

Made a GUI Interface using MATLAB GUI to ease the process of extraction of the features.

Wrote a Python code to make my own robust Database of seven vehicle classes from ImageNet.

Applied ResNet18 Model with necessary learning rate and got 90% Training accuracy, 89% validation accuracy and 91% Test accuracy.

Design a PCB board to place all the hardware including Arduino UNO

Get the gesture of hands using gesture sensor which is placed in hand with hand gloves.

To implement the falling objects on the LED display, each row of LEDs has been connected to a single 3:8 DEMUX (74LS138).

We used a 4-bit comparator to compare the address of a falling object in the bottom row to the address of the platform light to determine whether the score or death count should be incremented.

Continuously monitor the soil moisture level to decide whether irrigation is needed, and how much water is needed in the soil.

When sensing unit senses moisture level of the soil is less than 30 percent then pumping unit starts to work and when moisture level reaches up to 50 percent then it stops watering.

Simulated a full model of a MPPT charge controller along with a solar panel on Proteus and design the controller for the best suited with the panel.

Designed a PCB board for the controller part and implemented a hardware to charge the solar panel.

Monitored the charging power of the batteries and use Incremental Conductance Method to charge the batteries at maximum power.