The Internet of Things (IoT) encompasses a network of interconnected devices (Things) capable of communication via local networks or the Internet, employing machine-to-machine communication protocols. These devices typically integrate sensors and even Artificial Intelligence models to monitor and analyze their physical surroundings. With computing resources often limited, IoT devices primarily perform data processing at the edge. IoT networks establish local storage and communication brokers or leverage cloud services to transmit and store captured data. A wholly local network provides enhanced data control to owners and reduces network costs.
My involvement in the Internet of Things dates to early 2017 when I was awarded a development board from A-1 Labs for my inaugural project. Since then, I've contributed to numerous open-source IoT projects, leveraging my role as an AI Developer in Afiniti Software Holdings. I specialize in crafting comprehensive solutions, ranging from the software embedded in IoT devices to online management systems and mobile applications that interact with these devices and harness their data.
Feel free to explore my portfolio showcasing IoT device and application designs and developments, offering insights into my past projects and providing inspiration for your endeavor.
Few Keywords which define me:
• Problem Solver
• Engineer
• Logical
• Developer
• Researcher
Tallahassee, US (Jan 2021 - Jan 2023)
- Developed a speech depression recognition (SDR) model using transformer networks and generative adversarial networks (GANs); achieved an RMSE of 3.783 on the E-DAIC dataset, representing a 10% improvement over the previous state-of-the-art model.
- Evaluated the loss function for SDR using metrics such as MSE or RMSE; achieved an MAE of 4.634 and an RMSE of 5.520 on the DAIC-WOZ dataset, demonstrating the effectiveness of the model in predicting depression severity even in the presence of unbalanced or small samples.
- Taught a range of courses like Electromagnetics Lab, Digital Logic Design Lab, Introduction to EE using lab tools like VNA, QUARTUS Altera hardware and software tools, etc
- Developed a face mask detection CNN model; achieved an accuracy of 98% on the FER2013 dataset.
Lahore, Pakistan (Aug 2019 – Dec 2021)
- Developed a Vessel Monitoring System using network communication protocols, BPSK-500 modulation; created a network of 25,000 vessels to share a common transmission medium reducing overall cost by 80%.
- Developed and deployed a Hidden Markovian-based pattern recognition model using privately collected data received at the base station; achieved a 95% accuracy rate in vessel detection and tracking.
- Designed and implemented embedded firmware using C/C++ for maritime navigation applications, resulting in efficient and reliable solutions.
- Researched and developed speech enhancement and noise suppression algorithms in MATLAB translated to Java in Android Studio, resulting in a 30 dB improvement in SNR.
Lahore, Pakistan (March 2019 – June 2019)
- Developed a web app for real-time data visualization and analysis of IoT sensor data, utilizing machine learning algorithms to improve the overall efficiency of the monitoring system by 20%.
- Optimized the performance of predictive models using advanced machine learning techniques, resulting in a 15% reduction in error rates.
- Automated the process of installing Arduino-based devices with sensors in a pharmaceutical factory, contributing to a 25% increase in operational efficiency.
Tallahassee, US
- Implemented advanced game mechanics using Object-Oriented Programming (OOP), resulting in a highly engaging and interactive gaming experience that increased user session times by 10%.
- Designed and developed a computer opponent using Reinforcement Learning techniques, such as Deep Q-Networks (DQN) and Monte Carlo Tree Search (MCTS), providing a challenging gameplay experience that increased player retention by 20%.
- Utilized the alpha-beta pruning algorithm to optimize the AI opponent’s decision-making process, reducing decision-making time by 25% and improving overall gameplay responsiveness.
Tallahassee, FL
Grade: 3.6/4.0
Lahore, Pakistan
Final grade: 3.45/4.0
This is a system to detect face mask as well as the temperature of the body.
- Designed an algorithm using Convolutional Neural Networks and Tensorflow, OpenCV, and OpenVINO libraries for real-time detection of masks on faces of multiple people simultaneously in video frames with an accuracy of 93% on the training set and 98% on the test set.
- Developed software to detect the overall temperature of the body using FLIR cameras in video frames.
- Developed a prototype using Orange PI and FLIR camera to provide a security solution and attendance system; compared to available such solutions, we reduced the cost from $2900 to $300.
- Won first prize in Hackathon 2022 competition organized by INTEL in FAMU-FSU College of Engineering
- Owing to the huge demand of Ventilator for the sudden pandemic situation (COVID-19), low-cost ventilator was designed with an added feature of secured remote access and control.
- Components and Tools: Android Studio, ARDUINO, and modules, SOLIDWORKS
- Research: Researched and Designed control system and created. stl printable files for mechanical ventilator; that helped in designing a low-cost ventilator at as low as U.S. Dollars 400
- Contact-less controls: Developed wireless connectivity between the ventilator and mobile phone application to control the settings of Ventilator for maximum prevention from the interaction of Human Resources (Doctors, Nurses) with COVID-19 patients.
- Patients’ parameters: Utilized sensors (ECG, temperature, and BPM sensors) to wirelessly send and plot the parameters (breath/min, temperature) of patients on the LCD screen and mobile application; helped doctors to set the ventilators remotely.
An outdoor game designed for parks or open grounds, accommodating one hundred players (25 zombies or actors, 75
players) in which the player must escape from zombies.
Components and Tools: Embedded Firmware, C/C++, RTOS, SPI, I2C, CAN, Ethernet, Raspberry Pi, Arduino, and modules.
- Developed and programmed embedded firmware in C/C++ on Arduino and Raspberry Pi to establish a reliable communication system for coordinating the game, ensuring real-time updates and responsiveness.
- Implemented a Real-Time Operating System (RTOS) to manage task scheduling and resource allocation efficiently, enhancing the overall performance of the system.
- Utilized SPI, I2C, CAN, and Ethernet protocols for seamless communication between the Raspberry Pi central node, Arduino modules, and various sensors used in the game.
- Raspberry Pi: Configured the Raspberry Pi as a central node to receive, process, and transmit signals from/to each node in the network, establishing a network of one hundred nodes attached to a single server or central node.
- Network Simulation: Modeled, simulated, and verified the network using MATLAB, ensuring robustness and reliability for real-world implementation.
A commercial personal assistant device that consists of an LCD (to show the availability status of a person) and a mobile device (to change the status on the LCD)
Components and Tools:
Raspberry Pi, Firebase, MQTT, Lineage OS (10 11), C/C++, RTOS, SPI, I2C, CAN, Ethernet.
- Assembled Touch Screen TFT LCD Display with Raspberry Pi using Lineage OS to show the profile and availability status of the client on the LCD Display, leveraging embedded firmware and C/C++ programming.
- Established reliable wireless communication between Raspberry Pi and mobile applications using MQTT and I2C protocol, resulting in a mobile application to change the status on the LCD display.
- Implemented a real-time operating system (RTOS) to efficiently manage multitasking and resource allocation for the embedded system.
- Utilized SPI, CAN, and Ethernet communication protocols to enable seamless data transfer between the Raspberry Pi, mobile device, and other connected peripherals.
- Maintained backend storage of clients using Google Firebase, ensuring secure and reliable data management Maritime.
This system aims to track and monitor the locations of ships in the ocean/sea, ensuring enhanced maritime safety and situational awareness.
• Designed and fabricated antennas for long-range communication using CST and HFSS software, enabling over-the
horizon and line-of-sight communication for maritime vessels
• Developed an Android app leveraging Java and Google Play APIs, such as Maps and Location services, to maintain a real-time track of ships, resulting in a real-time navigation app for 25,000 ships.
• Utilized HTTP-based APIs of the server to maintain a log of locations of each ship at different time stamps, enabling accurate tracking and analysis of vessel movements for maritime safety purposes.
• Implemented a Morse code-based communication system to enhance the reliability and efficiency of data transmission between ships and base stations, contributing to improved safety and coordination in maritime operations.
• ART & TECH FESTIVAL | Peshawar, Pakistan
• 3rd & 4th Robotic Expo | Lahore, Pakistan
• INTEL HACKATHON 2022 | Tallahassee, USA
• DEAN’S HONOR LIST AWARD | Lahore, Pakistan
• PEEF SCHOLARSHIP | Lahore, Pakistan
• PM LAPTOP SCHEME | Lahore, Pakistan
https://www.linkedin.com/in/ali-hassan-raza/
Email: razaahassan8@gmail.com
Phone: +1-850-345-8403