As a Corporate Applications Engineer at Microchip, I have been extensively involved in leveraging my expertise with various Microchip products, including PICs, AVR, ATMEL, SAM and USB other offerings. I have played a crucial role in supporting and implementing advanced functionalities in these microcontrollers and Embedded Hardware. My experience in corporate applications at Microchip has provided me with the opportunity to work on challenging projects that demand a deep understanding of microcontroller architectures and their associated peripherals. I have actively collaborated with cross-functional teams, including hardware engineers, software developers, and customers, to provide technical support and solve complex problems. I also designed a gain block filter part of ECG system using Altium. Overall, my role as a Corporate Applications Engineer at Microchip has allowed me to demonstrate my expertise in microcontroller technologies, including PIC, AVR, and other Microchip products. I have gained extensive experience in utilizing Embedded Technologies to deliver robust solutions for a variety of applications.

Developed a system that predicts traffic using a combination of a microcontroller, pre-polarized microphone, LTE connectivity, and a machine learning model.The microphone captures audio data from the environment, such as vehicle noises and traffic flow sounds.This data is processed by the microcontroller to extract key features, which are then transmitted via LTE to a server(MQTT).Used machine learning model to analyze the data to predict traffic conditions in real time. This system enables accurate, location-independent traffic monitoring, making it ideal for smart city applications.

As we know GPS has limitation of providing accurate positioning for indoor architecture. Due to this limitation, researchers have been trying to find alternative methods for localisation. Currently Researchers have focused on using Radio waves, Bluetooth signals, Etc for localization, but they are prone to multi-path propagation. Prof. Herald Haas recently started using Light to transmit data, which is known as LiFi and this is an application of Visible Light Communication. Like VLC, VLP is similar, the research work at ford was based on VLP using IR light. I studied and built a prototype for this application and submitted the final limitation of the system.

Most of the asset tracking systems are non real time. Real time asset tracking system becomes necessary when an asset is of high value and critical to be located in time. Examples of such high value assets could be manufacturing parts lying in various locations on shop floor, critical medical equipments lying in various locations in hospitals etc. This system would enable users to locate critical assets in real time with an accuracy of about 3 feet without having to spend time searching for the same.