Volume 7, Issue 1

2026 : Volume 7 Issue 1

Title Design and Implementation of RSA Cryptography Using an Inexact Multiplier
Authors K Jyoshna, L Swathi
Affiliation Annamacharya Institute Of Technology And Sciences, Kadapa, A.P, India
DOI 10.64264/ijisea–STL0701
Abstract Cryptography used in encryption and decryption for the purpose of security in communication. Rivest Shamir Adleman or RSA is an algorithm which is used to send data. In this, mainly focuses on encryption techniques like cryptography which have large integer multiplications like modular exponentiation. However, these operations required large hardware architecture. This makes traditional RSA implementations inefficient for low power and resource constrained applications like Internet of things (IOT) devices, embedded systems and real time multimedia encryption. To overcome these limitations, this project introduces an optimized RSA cryptographic architecture that contains 8-bit Dadda multiplier and 5:2 compressor which will balance the performance. The 5:2 compressor reduces the number of addition stages in the product multiplication, while the Dadda multiplier focuses on fast multiplication. This inexact multiplier design significantly reduces the power consumption, Low area requirement, Improved Scalability and Faster computation which is well suited for energy aware hardware environments. The proposed design achieves 27% power reduction while preserving encryption accuracy. Although there is a slight decryption error that is negligible. The encryption simulation shows that the result is unaffected. The traditional RSA design uses Exact multipliers like carry save and array-based designs which consume more power and the logic structure is complex. In contrast, the approximate computing approach sacrifices a minimal amount of accuracy in Favor of Dadda-based multipliers, offers several distinct advantages over traditional RSA hardware implementations.
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Title FPGA implementation of Approximate Sobel edge detection
Authors Bandha Nagaveni, P. Anjaneya
Affiliation 1. P.G. Student, Annamacharya Institute of Technology & Science, Kadapa, A.P, India
2. Associate Professor, Dept. of ECE, Annamacharya Institute of Technology & Science, Kadapa, A.P, India
Email bandhanagaveni@gmail.com
anjiaitsk@gmail.com
DOI 10.64264/ijisea–STL0702
Abstract Image processing plays a crucial role in data processing systems, particularly in applications such as medical imaging, remote sensing, and microscopy tomography. Edge detection is a key image segmentation technique used to simplify image data and reduce computational complexity. Edges are essential as they define the boundaries within an image. The Canny edge detection algorithm significantly outperforms traditional techniques in various computer vision applications. However, its major limitation is high computational complexity, leading to increased processing time. To address this issue, a hybrid edge detection approach is proposed. This method incorporates the Sobel operator to estimate gradient magnitude and direction, reducing hardware complexity. It also integrates optimized non-maximum suppression, adaptive thresholding, and hysteresis thresholding techniques. Additionally, pipelining is introduced to reduce latency and improve processing speed. The proposed design is implemented using the Xilinx ISE Design Suite 14.2 on a Xilinx Spartan-6 FPGA platform. The synthesized architecture demonstrates efficient hardware utilization and achieves a maximum operating frequency of 935 MHz.
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Title IOT BASED TIME TABLE POSTING, DISPLAY AND INTELLIGENT NOTIFICATION SYSTEM USING MIT APP INVENTOR AND ESP32
Authors 1.P. Anjaneya ,2.M. Guru Swamy,3.M. Suresh Reddy,4.P. Ramoji,5.S. Mallikarjuna Reddy
Affiliation Annamacharya Institute Of Technology And Sciences, Kadapa, A.P, India
DOI 10.64264/ijisea–STL0703
Abstract The increasing complexity of academic schedules has made effective timetable communication a challenge in many educational institutions. Traditional methods such as notice boards and manual announcements lack real-time updates and timely alerts, often leading to missed classes and coordination issues. To address these limitations, this project proposes an IoT-Based Smart Timetable Display and Intelligent Notification System using ESP32 and MIT App Inventor. The system employs a centralized cloud-based architecture using Firebase Realtime Database to enable real-time synchronization of timetable data. Authorized faculty members can update schedules through an administrator mobile application, while students access real-time timetables and receive automated notifications through a dedicated user application. An ESP32 microcontroller interfaced with a 20×4 I2C LCD display continuously retrieves and displays timetable information, ensuring public visibility. Intelligent notification logic triggers alerts ten minutes before class commencement, even when the application runs in the background. By automating timetable dissemination and minimizing manual intervention, the proposed system enhances punctuality, reliability, and operational efficiency. The project demonstrates the practical application of IoT, cloud computing, and mobile application development in smart education systems.
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Title Comprehensive Rider Protection Through Smart Helmet Technology
Authors 1.P. Anjaneya, 2.Junnutala Tarun Achari ,3.Adiboyina Sujana, 4.Kamsetty Harsha Vardhan
Affiliation Annamacharya Institute Of Technology And Sciences, Kadapa, A.P, India
DOI 10.64264/ijisea–STL0704
Abstract The Helmet Detection for Industrial Safety Using YOLO is a machine learningbased system designed to enhance safety for both the worker and rider in machine usage scenarios. The system makes use of a Raspberry Pi, along with a USB camera, to execute a YOLO-based object detection model for helmet detection in real-time scenarios. An alcohol sensor is integrated with the system to check for the sobriety of the worker operating the machine. If alcohol levels are found to be higher than a predefined limit, the system prevents the machine from starting and simultaneously triggers a buzzer sound. To further enhance safety, a neck airbag system is integrated with the machine, which deploys in case of a sudden collision. If a safety violation, such as no helmet or alcohol presence, is detected, the Raspberry Pi stops the DC motor, which simulates the machine's engine, and triggers a buzzer sound. An LCD module is integrated with the system, which displays real-time status information on system status and object detection results. The system is designed using a 12V adapter and is automated, intelligent, and real-time in nature.
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