As an active member of the IoT Lab society, I specialized in robotics and gained hands-on experience with technologies such as Raspberry Pi, Arduino, sensors, ESP-32, servos, and actuators.My passion for practical projects led me to create solutions that simplify tasks for individuals and communities, ranging from smart home systems to assistive robotics.Through this journey, I learned to bridge the gap between the physical and digital worlds, using technology to address real-world challenges.TECH STACK: C/C++, Python, Linux, IoT, Cloud(Things Speak) , Data Analytics, MQTT, API, Embedded System, Sensors

Innovated IoT integration for military applications, enhancing real-time data collection and communication; increased operational efficiency by 40% and expanded system range by 25%.Gained experience with Technologies such as LoRa, and Radio Signals. Data Encryption, ARM Microcontroller, GPS, Linux, Bash Scripting, Signal Processing, PCB Designing, and a lot of troubleshooting and debugging.Mastery over microcontroller interfaces ( I2C, SPI, PWM, UART), Conducted rigorous environmental testing following military standards to ensure product reliability and performance also analyzed test results, identified areas for improvement, and iteratively refined product designs.Utilized ADB Android CLI commands to modify the boot animation and developed a shell script for auto-starting IFF application on boot along with a custom boot animation, ensuring seamless operation and enhancing user experience, and implemented robust error handling and logging.

Developed a cutting-edge healthcare wearable prototype capable of the prevention of Falling/Fainting for old age by integrating sensors with BLE(Bluetooth Low Energy) and retracting the data from Python modules like bluepy/pygatt, leading to a 50% reduction in sensor data optimization and compression time.I collaborated effectively with team members remotely to implement version control practices, resulting in an increase in project efficiency and successful delivery ahead of schedule.I gained proficiency in incorporating multiple motion sensors over multiple interfaces into the device and analyzing sensor data to extract valuable insights using machine-learning algorithms for prediction.