SRM University-AP preserves a research-empowered ecosystem stimulating its faculty and students to roll out original and discerning studies capable of making instrumental contributions aiming the scientific and societal progress. Making strides with impactful research publications and groundbreaking achievements, the institution has carved a niche for itself in the academic milieu. We are glad to present yet another success story of our research community that keeps bringing laurels to the institutions from far and wide.

Dr Pradyut Kumar Sanki and his PhD scholar Bevara Vasudeva, from the Department of Electronics and Communications Engineering, along with a group of Computer Science and Engineering students: Medarametla Depthi Supriya, Devireddy Vignesh, Peram Bhanu Sai Harshath, and Sravya Kuchina have got their paper titled ‘’VLSI Implementation of a Real-Time Modified Decision-Based Algorithm for Impulse Noise Removal’’ accepted in the IEEE conference IEMTRONICS 2022. This publication is a part of the Capstone project contributed by the students.

IEMTRONICS 2022 (International IOT, Electronics and Mechatronics Conference) is an international conclave that aims to bring together scholars from different backgrounds to disseminate inventive ideas in the fields of IOT, Electronics and Mechatronics. The conference will also promote an intense dialogue between academia and industry to bridge the gap between academic research, industry initiatives, and governmental policies. This is fostered by panel discussions, invited talks, and industry exhibits where academia and industry will mutually benefit from each other.

Through the research paper, the team proposes a real-time impulse noise removal (RTINR) algorithm and its hardware architecture for denoising images corrupted with fixed valued impulse noise.

Abstract of the Research

A decision-based algorithm is modified in the proposed RTINR algorithm where the corrupted pixel is first detected and is restored with median or previous pixel value depending on the number of corrupted pixels in the image. The proposed RTINR architecture has been designed to reduce the hardware complexity as it requires 21 comparators, 4 adders, and 2 line buffers which in turn improve the execution time. The proposed architecture results better in qualitative and quantitative performance in comparison to different denoising schemes while evaluated based on the following parameters: PSNR, IEF, MSE, EKI, SSIM, FOM, and visual quality. The proposed architecture has been simulated using the XC7VX330T-FFG1761 VIRTEX7 FPGA device and the reported maximum post place and route frequency is 360.88 MHz. The proposed RTINR architecture is capable of denoising images of size 512 × 512 at 686 frames per second. The architecture has also been synthesized using UMC 90 nm technology where 103 mW power is consumed at a clock frequency of 100 MHz with a gate count of 2.3K (NAND2) including two memory buffers.

Dr Sonam Maurya, and her research team; Soha Muskaan Sayyad, Trisha Chilukuri, Samah Maaheen Sayyad, and Juhita Naga Priya Velagapudi from the Department of Computer Science and Engineering have innovated a smart wallet model based on IoT and got their patent “Smart Wallet with Enhanced Features for Preventing Misuse and Alarm System for the Same” published. This is a fitting solution to protect against the loss and theft of the wallet.

A smart wallet is an excellent technology to safeguard your credit and debit cards. Wallets these days are getting smarter with the latest technologies induced to monitor its presence. The proposed IoT- based wallet model is more smart, intelligent, secure, and safe which encompasses the best use of the latest IoT technologies in our pocket. The prototype consists of fingerprinting access technology, Augmented Reality (AR) navigation, Interactive Air Display (IAD)/ Transparent Display (TD), Voice control mechanism, Emergency alerts, RFID features, and many more. The smart wallet is designed to overcome the shortcomings of the regular wallet types.

The new technology of AR makes the tracking of the wallet easier with a graphical pathway. And the voice control functionalities help the user to make the process easier in comparison to manual opening. IAD/ TD is used to control the mechanisms like opening the card or money case. To keep the data more secure from hackers, an RFID technology-enabled card is also embedded in the wallet. The strong Graphene outer covering is used to make the materials inside more flexible and safer. Besides, there is an emergency voice control mechanism that takes the instruction from the user and makes the surroundings alert by sending an alert message to the emergency contacts. And the cash counting facility in the wallet to keep track of the cash makes it a wholesome package of digital innovation.

The social implications of this smart wallet are:

• Enhanced features for preventing wallet misuse

• Alarm system to help in emergencies and threatening situations

• Best use of IoT technology in a user-friendly way

• Enabled with Wallet/ Card missing notifications

• Eco-friendly charging mechanism

With this innovation, the research team aims to bring technology to its fullest use to make significant transformations in the everyday life of society.