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Volume: 11 Issue 03 March 2025


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Volume - 11 Issue - 3


Volume: 11 Issue: 3 March 2025

Animal Intrusion Device Using Arduino Nano

Area of research: Electronics And Communication Engineering

Despite Advances In Technology, The Field Of Animal Incursion Detection Has Frequently Been Neglected And Understudied. This Is An Important Issue, Particularly In Rural And Agricultural Regions Where Animal Invasion May Cause Considerable Crop Damage, Financial Loss, And Pose Risks To Both Humans And Wildlife. To Close This Gap, We Offer A Sensor-based Method That Tracks Animal Ingress Onto Human-occupied Or Agricultural Land, Giving A Real-time Solution For Identifying Possible Invasions. This Project Uses An ARDUINO UNO Microcontroller As The Central Processing Unit, As Well As A Variety Of Necessary Components Such As A GSM (Global System For Mobile Communications) Module, A Buzzer, And A PIR (Passive Infrared) Sensor To Detect Movement. The PIR Sensor Detects Animal Movements Within Its Range Of Vision, And The Arduino Analyzes The Sensor Data. When The System Detects The Presence Of An Animal, It Activates The GSM Module, Which Is Set To Send SMS Messages With Particular Information About The Movements Location. This Real-time Notice Is Transmitted To Both Law Enforcement Officers And The Farm Owner, Giving Them With Quick Information About The Incursion And Allowing Them To Take Appropriate Measures To Limit Harm. In This Arrangement, The Buzzer Acts As A Local Alarm System, Perhaps Driving Away Smaller Animals While Also Notifying Surrounding Humans. This Setup's Simplicity Makes It A Low-cost, Scalable Alternative For Farmers Who May Not Have Access To More Advanced Monitoring Systems. Overall, This Project Aims To Create A System That Actively Monitors Agricultural Fields For Any Animal Invasions. The Arduino Nano Detects Motion Using The PIR Sensor And Analyzes The Data, Ensuring That Notifications Are Transmitted To The Appropriate Parties As Soon As Possible Using The GSM Module. This Strategy Not Only Improves The Safety And Security Of Agricultural Areas, But Also Promotes Greater Human-animal Cooperation By Avoiding Future Confrontations.

Author: Mario Joshua S | Arun S | Prabhakaran S | Jai Surya G.
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Volume: 11 Issue: 3 March 2025

Adaptive Recon Rover For Defense And Wildlife

Volume: 11 Issue: 3 March 2025

A Secure And Scalable Voting Framework

Area of research: Computer Science And Engineering

Blockchain Technology Serves As The Cornerstone For Addressing Security Issues Related To Voting, Utilizing Cryptographic Hashes To Ensure Comprehensive Verification From Start To Finish. In This Context, Each Valid Vote Is Treated As A Transaction Within The Blockchain Of The Voting Application. The Face Voting System, Which Employs Blockchain Technology, Aims To Bolster Both The Security And Transparency Of The Electoral Process. Initially, Users Are Required To Submit A Verification Request To The Administrator. Upon Approval, They Can Cast Their Votes Through A Facial Recognition Mechanism, Which Guarantees That Only Authorized Individuals Are Permitted To Participate. By Leveraging Blockchain, The System Creates Immutable Records That Thwart Fraudulent Activities, Thereby Fostering A Secure, Decentralized, And Reliable Voting Atmosphere. Votes Are Stored In The Backend Database And Subsequently Added As New Blocks To The Blockchain Following Successful Mining. The System Upholds The Principle Of One-person, One-vote By Utilizing Each Voter's Unique Fingerprint, Which Is Verified At The Beginning Of The Voting Process To Prevent Duplicate Voting. Once A Vote Is Mined, A Transaction Specific To That Vote Is Generated, And Any Fraudulent Votes Are Discarded By The Miners. Following The Validation Process, Voters Receive Immediate Notifications Via Message Or Email, Including A Transaction ID That Allows Them To Track Their Vote Within The Ledger. While This Serves As A Notification, It Does Not Disclose How Any Individual Voted, Thus Preserving Voter Privacy. It Is Crucial To Highlight That Each Voter Is Identified In The Blockchain By A Unique Cryptographic Hash, Which Enhances The Verifiability Of The Entire Voting Process. Additionally, This ID Remains Concealed, Ensuring That Even System Operators Cannot Access It.

Author: Mrs.Sasikala | Daniyal Rax T | Ijas Ahamed | Jayapraveen | Shaam Sundar
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Volume: 11 Issue: 3 March 2025

A NOVEL PIPELINED TECHNIQUE FOR IMAGE ENCRYPTION & DECRYPTION BASED ON AES CRYPTOGRAPHY

Area of research: ECE

The Project Presents A Fault-efficient Advanced Encryption Standard (AES) Design For Image Cryptography, Focusing On Customizing SubBytes And MixColumns, Which Are The Most Critical Hardware Components. The Proposed AES Architecture, Implemented Using Verilog HDL And Simulated In ModelSim 6.4c, Aims To Reduce Area And Delay While Maintaining High Security. Both Application-Specific Integrated Circuit (ASIC) And Field-Programmable Gate Array (FPGA) Implementations Are Targeted, With Performance Evaluation Performed Using Xilinx Synthesis Tools.An 8-bit Datapath Is Employed, Where Two Dedicated Register Banks Store Plaintexts, Keys, And Intermediate Results. To Reduce Logic Consumption, The ShiftRows Operation Is Performed In The State Register Using An I/O Combination Of A Serial Solution. Round Modules, Including SubBytes, MixColumns, And AddRoundKey, Operate In Parallel And Repeat 10 Times During Encryption And Decryption. A Global Counter Applies The EN_SIG Signal, Which Generates Critical Control Signals Such As DATA_IN_SEL, LAST_RND_SIG, And KEY_IN_SEL To Manage Data Flow Effectively.The AES Decryption Process Mirrors The Encryption Process By Reversing The Transformations In The Round Module, Ensuring Robustness And Security. This Design Is Particularly Suitable For Lightweight, Resource-constrained IoT Devices, Addressing Growing Concerns About Data Privacy And Unauthorized Access. By Customizing The AES Datapath, The Proposed Architecture Reduces Hardware Footprint And Clock Cycles, Making It Highly Efficient For Real-time Cryptographic Applications. The Modular And Parallel Structure Of The Design Enhances Processing Speed While Maintaining The Required Security Standards.Overall, The Presented AES Accelerator Ensures A Balance Between Security, Fault Efficiency, And Performance, Making It Ideal For Secure Image Encryption In IoT And Embedded Systems.

Author: M.Shanmugam | K.Nandhakumar | M.Selvabharathi | L.Srihari | A.Venugopal
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Volume: 11 Issue: 3 March 2025

Enhancing Automative Face Recognition And With Distraction Detection System

Area of research: Computer Science And Engineering

Driver Distraction Is A Significant Factor Contributing To Road Accidents Worldwide. According To Statistics, Distracted Drivers Are Three Times More Likely To Be Involved In A Crash Than Non-distracted Drivers. Therefore, Detecting Driver Distraction Is Crucial For Improving Road Safety. Many Previous Studies Have Proposed Various Methods For Driver Distraction Detection, Including Image-based, Sensor-based, And Machine Learning-based Approaches. However, These Methods Have Limitations In Terms Of Accuracy, Complexity, And Real-time Performance. This Project Proposes A Novel Approach To Driver Distraction Detection Using The You Only Look Once (YOLO) Object Detection Algorithm With A Convolutional Neural Network (CNN). The Proposed Model Consists Of Two Main Stages: Object Detection Using YOLO And Classification Of The Detected Objects. The YOLO Algorithm Is Used To Detect And Locate Various Objects In The Driver's Environment, Including The Driver's Face And Hands, And Other Objects That May Cause Distraction. Then, The Detected Objects Are Classified Using A CNN To Determine Whether The Driver Is Distracted Or Not. The Proposed Model Is Evaluated Using A Public Dataset And Achieves High Accuracy In Detecting Driver Distraction. And Also Analyse The Drowsiness Of Driver Based On Eye Features Using CNN Algorithm. The Proposed Method Has The Potential To Be Integrated Into Advanced Driver Assistance Systems To Improve Road Safety With Real Time Environments.

Author: S.R.Mathusudhanan | Mohamed Naveeth B | Sangili Saravana M | Manikandavasan S | Pavan Kumar K
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Volume: 11 Issue: 3 March 2025

State Management In Flutter: A Performance Comparison Of Getx, Provider, Riverpod And Bloc

Area of research: MCA

State Management Plays A Vital Role In Flutter Application Development, Directly Influencing Performance, Scalability, And Maintainability. With Multiple State Management Solutions Available, Selecting The Right Approach Can Significantly Impact An App’s Efficiency. This Research Paper Presents A Comparative Analysis Of Four Widely Used State Management Solutions In Flutter: GetX, Provider, Riverpod, And BLoC (Business Logic Component). The Study Evaluates These Approaches Based On Frame Rendering Time, Memory Consumption, CPU Usage, And Widget Rebuild Efficiency To Determine Their Effectiveness In Handling State Changes. To Conduct The Analysis, Identical Flutter Applications Were Implemented Using Each State Management Method. These Applications Were Tested Under Varying Conditions To Measure Their Responsiveness, Efficiency, And Ease Of Use. The Results Indicate That GetX Provides Minimal Boilerplate And Fast Reactivity, Making It Ideal For Lightweight Applications. Provider, As Flutter’s Officially Recommended Solution, Integrates Well With The Widget Tree But May Introduce Performance Overhead In Complex Applications. Riverpod Enhances Provider By Offering Better Scalability And Flexibility, Making It Suitable For Large-scale Applications. BLoC, Known For Its Structured And Event-driven Approach, Excels In Managing Complex State Transitions But Has A Steeper Learning Curve And Higher Boilerplate Code. The Findings Of This Study Aim To Help Flutter Developers Choose The Most Efficient State Management Solution Based On Their Project Needs. Future Research May Explore State Management Performance In Flutter Web And Desktop Applications, As Well As The Impact Of Asynchronous State Updates On Real-time Applications.

Author: Dr. Uday Aswalekar | Akhilesh Vishwakarma
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Volume: 11 Issue: 3 March 2025

Smart Data Distribution For Immersive Music Streaming

Area of research: MCA

The Rapidly Advancing World Of Streaming Services Has Seen The Emergence Of Innovative Data Distribution Strategies, Content Personalization Techniques, And The Incorporation Of Geo-location Information. This Paper Explores The Interdependence Of These Elements, Offering A Comprehensive Analysis Of Various Data Distribution Mechanisms, Their Impact On User Satisfaction, And How Geo-location Data Enhances User Engagement. The Study Highlights A Range Of Data Distribution Methods, Including Content Delivery Networks (CDNs), Edge Computing, And Serverless Technologies, Discussing Their Role In Ensuring Smooth Streaming Experiences For Diverse Audiences Worldwide. At The Same Time, It Evaluates How Personalized Content Suggestions, Driven By Individual User Behavior And Preferences, Are Further Optimized Through The Integration Of Geo-location Insights. Through A Case Study On Video Streaming Platforms, This Paper Demonstrates How These Advanced Techniques Are Implemented In Practice. By Examining A Popular Video-on-demand Service, We Aim To Illustrate How Real-time Data Distribution Methods And Intelligent Recommendation Algorithms Work Together To Create Customized Viewing Experiences. This Case Study Sheds Light On The Dynamic Interplay Between Content Distribution, Personalization, And Geo-location, Showcasing Their Collective Impact On Enhancing The User Experience In Digital Streaming Environments. Additionally, The Paper Discusses The Role Of Real-time Analytics In Fine-tuning Content Delivery, How Data Distribution Optimizes System Performance, And How Geo-location Data Can Help Tailor Content Recommendations Based On Regional Preferences, Ultimately Boosting Viewer Satisfaction.

Author: Dr. Uday Aswalekar | Essakimuthu Yadav
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