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Successfully developed a biometric attendance system with a capacity of up to 1000 students(Hardware limitation), Conducted rigorous testing on 300 samples, achieving a remarkable 98.2 % accuracy rate.Implemented a secure mode to prevent unauthorized access and tampering, Created an accessible attendance sheet on an SD card, downloadable via HTTP requests.Engineered a custom 3D-printed housing, seamlessly integrating a rechargeable LiPo battery with a built-in charging adapter for enhanced portability, while streamlining student enrollment and data management through Bluetooth integration. Generated attendance can be downloaded via the net and saved in the device as backup.

Modulation and Alamouti Encoding: Implemented QPSK modulation to encode binary input data. Utilized Alamouti Space-Time Coding to combine and transmit symbols over two paths. Achieved an effective coding gain of approximately 3 dB, enhancing signal reliability.Error Probability Analysis: Simulated a range of Signal-to-Noise Ratios (SNR) from -20 dB to 30 dB. Calculated and plotted the Error Probability (Pe) curve, revealing a Pe of 0.01% at 10 dB SNR, demonstrating the system’s robustness against noise and fading.

Repetition Coding and OFDM Modulation:Implemented repetition coding with factors 2 and 4 on random binary data. Utilized QPSK modulation and OFDM modulation with FFT size of 1024 and cyclic prefix length of 256.Error Correction and Performance Evaluation: Simulated the system across SNR values from -20 dB to 30 dB. Achieved a Symbol Error Rate (Pe) of 0.002% at 10 dB SNR for Repetition 2 and 0.0002% for Repetition 4, showcasing improved reliability with higher repetition factors.

Bachelor Of Technology - Btech, Electrical, Electronics And Communications Engineering

Coursework: Probability models and application, Digital & Wireless communication, Analog IC design, VLSI design, Micro-processors &.

Intermediate