This project demonstrates a voice-controlled wheelchair navigation system. Speech to text conversion part of the project was performed by using Google Cloud API. Instead of using Arduino, an STM32 Bluepill microcontroller was used for better performance. The project was completed in both hardware & software. For software demonstration, simulations in Proteus & CubeIDE were performed. For hardware demonstration, a prototype wheelchair was built with PVC boards. In the future, our goal is to implement the hardware part on a real wheelchair. A PCB layout was also designed for this project by using the easyEDA tool.

This project was completed for our "EEE 416: Microprocessor & Embedded Systems Laboratory" course. Check out the video for a detailed project demonstration.

The project is based on a traffic light controller that is responsive to real-time vehicle density on a four-way junction. Here, we designed a state machine that consists of 27 states. The controller is fed by vehicle detecting sensors & sound sensors. Based on that, our system provides an optimum way for the traffic lights to turn on or off. The system also enables emergency vehicles to pass through & can detect any traffic rule violation. The intelligent traffic light control system proposed in this project can be much more efficient and energy-saving than the existing system.

This project was completed for our "EEE 304: Digital Electronics Laboratory" course. Check out the video for a detailed project demonstration.

This project was completed for "EEE 310: Communication System I Laboratory" course. Here, at first, we generated a high-frequency carrier signal and modulated a random message signal with it. After the modulation, we transmitted & finally demodulated the overall signal with a demodulator circuit. In our case, the demodulator circuit was a diode detector. After demodulation, we successfully retrieved the original message signal. We also designed & printed the PCB versions of all the circuits used in the project & converted it into a trainer board.

Check out the video for a detailed project demonstration.

The goal of this project is to take input data from a person through our website, use a machine-learning algorithm to analyze that data, and predict whether the person is at risk of Covid-19 or not. This is a form of pre-testing which will enable doctors to prioritize which patients to test first, and allow patients to know if it is necessary for them to go for a Covid-19 test. Our project can be regarded as a classification problem, where the machine learning algorithm takes a particular set of input data (which are known as input features) from a person and then categorizes them into positive or negative classes. The set of input features we supplied to our machine learning algorithm are:

1. Age

2. Travel History

3. The presence of symptoms such as fever, cough and sore throat, breathing problems, pneumonia, headache, Weakness and nausea

According to the World Health Organization(WHO), 285 women die from preventable diseases related to pregnancy and childbirth every day all over Bangladesh. Most of it is due to a lack of proper information, quick service, and nearby healthcare facilities. On the other hand, 1 in 5 new specialist female doctors is currently unemployed in Bangladesh. So, We built a mobile application that works as a link between doctors and female patients and solves both these problems at once. The aim of this project is to digitalize our existing analog health care system & create a revolution in the medical sector. Our team is still continuously working on this project & we also won some awards regarding this.

Check out the video to know the details.

This video demonstrates a 4-bit microcomputer design using Verilog. The design mainly takes inspiration from SAP-1, SAP-2, SAP-3 architectures. Data memory set, stack segment, address pointer, stack pointer, etc were designed for this purpose. The microcomputer can perform simple mathematical and logical operations which are illustrated in the video. A specific instruction set was given beforehand to implement the design. This project was a part of our "EEE 415: Microprocessor & Embedded Systems Course." It was an individual project.

Check out the video to know the details.

This project was completed for our "EEE 460: Optoelectronics Laboratory" course. In this project, we designed optical filters & resonators using DBR mirrors and explored the effects of tuning different parameters of our design. The following tasks were performed:

• Varying different parameters of a DBR mirror to check for different reflectance values using MATLAB.

• Simulation of DBR mirrors with different parameters using Lumerical & comparing with the calculated results.

• Using the designed DBR mirrors, constructing an optical resonator.

• Varying different parameters of an optical resonator to check for different optical modes using MATLAB.

• Simulation of the designed optical resonator with different parameters using Lumerical & comparing with the calculated results.

This project was completed for our "EEE 206: Energy Conversion Laboratory" course. In this project, we performed rewinding & testing of a squirrel-cage induction motor. We performed the following procedures:

• Inserting new insulators

• Making a demo coil with new wires

• Making coils & inserting them into the motor

• Final insulation

• Providing connection between coils

• Applying varnish & reconstruction of the motor

• DC testing, No-load testing & Locked-rotor testing

This project was completed for "EEE 306: Power System I Laboratory" course. Power systems in most countries around the world today are based on analog, back-dated methods with no measures for complex data measurements (such as power factor), data storage, and data interpretation. To solve all these problems, we have developed a smart energy meter that is basically a digital electric meter integrated into an IoT (Internet of Things) based system enabling it to transfer data onto a server over a local area (our current project) or wide area (future large scale application) network.

In our current project, we have focused more on the consumer side. We have built an electric meter that incorporates a voltage measurement and current measurement circuit. This circuit is operated using an Arduino Nano microcontroller unit, step-down voltage transformer, current sensor, voltage regulator, capacitor, and resistors. The readings on this meter (real power, RMS voltage, and power factor) are displayed on an LED display and simultaneously transmitted from the microcontroller unit to a local server website via a NodeMCU (ESP 8266) using a local WiFi network where the data for each load connected to the system can be continuously viewed by the customer in a smart device connected to the same local network. This data can be stored and examined for later purposes.

In this project, we analyzed & reproduced the work of an article titled "Analysis of variable gain control for respiratory system".

Here, we work on a variable-gain control strategy for mechanical ventilators in the respiratory systems. Respiratory systems assist patients who have difficulty breathing on their own. For the comfort of the patient, fast pressure buildup (and release) and a stable flow response are desired. However, linear controllers typically need to balance between these conflicting objectives. In order to balance this tradeoff in a more desirable manner, a variable-gain controller is proposed, which switches the controller gain based on the magnitude of the patient flow. The effectiveness of the control strategy is demonstrated in experiments on different test lungs.

This project was completed for our "EEE 318: Control System I Laboratory" course.

This project was completed for our "EEE 312: Digital Signal Processing I Laboratory" course.

In this project, we perform the following tasks:

• Observe the corrupted ECG signal in the frequency domain

• Create a band-pass filter that passes signals between 30 bpm to 200 bpm

• Observe the ECG signal before and after filtering

• Calculate the heart rate from the highest peak on the frequency spectrum after filtering

• Verify our results by correlating the filtered signal with the original signal and again calculating the heart rate

I also participated in some line follower robot competitions along with my group. For that purpose, I worked on building line follower robots from scratch. They were programmed by using basic Arduino. The hardware of the robots was also designed by us. Our robots performed quite well in these competitions.

Check out this video of me participating in "IUT MECCELARATION 2019". Our team reached the finals of the line follower robots segment.

This project was completed for our "EEE 414: Electrical Service Design" course.

In this project, we had to choose a floor plan for a multi-storied building. Next, we had to logically place the fittings & fixtures on the floor plan. We also had to design the conduit layout for our plan. Finally, we performed calculations for switchboards & distribution boards to ensure a constant power supply. The design also included a lightning protection system & emergency power supply.