Current Issue

Volume: 11 Issue: 6 June 2025

DATA-DRIVEN SOLUTIONS FOR BACK AND KNEE PAIN ASSESSMENT, THERAPY OPTIMIZATION, AND EFFECTIVENESS ANALYSIS USING MACHINE LEARNING

Area of research: MCA

A Lot Of People Experience Regular Occurrences Of Back And Knee Pain Throughout Their Daily Routines. This Project Provides Users With A Systematic Approach To Control And Diminish These Two Types Of Pain. Users First Need To Create An Account And Provide Information About Their Symptoms Which Includes Their Pain Intensity And Stiffness And Swelling Levels. The Platform Provides Users With Login Access After Receiving Approval From Administrators. After Users Log Into The Platform, They Have The Ability To Provide Additional Information About Their Condition. The System Analyzes The User-provided Data To Determine The Specific Pain Type And Its Intensity Level. The System Provides Users With An Appropriate Therapy Plan Recommendation And The Estimated Treatment Duration. After Users Complete Their Therapy, They Need To Update Their Symptoms In The System. The System Uses The Updated Data To Compare It Against The Original Data And Determine The Amount Of Progress Made. The Process Includes Administrative Monitoring Along With Report Generation At All Stages. The Systematic Approach Allows Every Patient To Obtain Precise Care According To Their Medical Situation While Receiving Visible Results From Their Treatment. Technology Provides A Straightforward And Beneficial Method For Pain Management And Recovery.

Author: Dr. T. Amalraj Victoire | M. Vasuki | S. Amirtha

Volume: 11 Issue: 6 June 2025

Smart School Bus Monitoring System Using IOT

Area of research: IOT

This Paper Presents An IoT-based Approach Of School Bus Tracking, With A Focus On Increasing Child Safety And Providing Real-time Communication With Parents. The System Uses RFID Tags As The Primary Means Of Verification, Followed By A Secondary Verification Process Using Cameras. The Camera Captures Images Of Students And Checks Them Against Previously Stored Images, Also Checking Compliance With Mask-wearing Protocols. In Addition, The System Monitors The Students' Temperature Using An IR Sensor. The Proposed System Uses ESP8266 Controllers And SIM800L Modules With Integrated GSM Modem And GPS Receiver. GPS Tracking Enables Precise Determination Of A Vehicle's Location, With Data Transmitted To A Remote Server Over TCP Via A GPRS Service. The System Also Includes A Web-based Application For Data Visualization. Significantly, The Proposed System Shows Superior Accuracy Compared To Previous Methods. It Provides Real-time Data On Various Vehicle Features Including Location, Route, Speed, Passenger List, Driver Compliance And Schedule. The System Uses ESP8266 To Connect GPS, RFID, And Firebase Servers To The Cloud Via WiFi, Enabling Seamless Integration And Efficient Data Transmission. Introducing A Smart School Bus Security System Using IoT Offers Many Benefits, Including Increased Student Safety, Increased Accountability, And Reduced Practices Costs And Better Communication Between Parents, Schools And Transport Agencies.

Author: P.S.Mhetre | Harshad Shivale | Abhishek Tikone | Pratik Waste

Volume: 11 Issue: 6 June 2025

IoT Based Smart Biofloc Monitoring System For Fish Farming Using Machine Learning

Area of research: Electronics And Communication Engineering

Biofloc Technology Has Emerged As A Sustainable And Space-efficient Method For Fish Farming, Particularly Valuable In Regions With Limited Water Resources. However, Its Operation Is Highly Sensitive To Variations In Water Quality Parameters Such As PH, Total Dissolved Solids (TDS), Ammonia Levels, Turbidity, And Temperature. This Paper Presents A Cost-effective, Solar-powered Internet Of Things (IoT)-based Biofloc Monitoring System Integrated With Machine Learning (ML) Techniques To Detect Early Signs Of Fish Mortality In Aquaculture Tanks. Designed For Low-income Fish Farmers In Southern Punjab, Pakistan, The System Continuously Measures Critical Water Quality Parameters Using Affordable Sensors Connected To Arduino UNO And NodeMCU ESP8266 Microcontrollers. Over A Period Of 1.5 Months, Data Was Collected At Two-minute Intervals And Uploaded To The ThingSpeak Cloud Platform. After Preprocessing And Balancing The Dataset Using ADASYN, Several ML Algorithms—including Random Forest, XGBoost, Decision Trees, Support Vector Machines, And Naïve Bayes—were Trained And Evaluated. The Random Forest And XGBoost Classifiers Outperformed Others, Achieving Up To 98% Accuracy In Predicting Fish Mortality. This System Not Only Enhances Operational Efficiency In Biofloc Fish Farming But Also Reduces Fish Mortality And Economic Losses By Issuing Timely Warnings. The Results Demonstrate The Potential Of IoT-ML Integration In Transforming Small-scale Aquaculture Into A More Data- Driven And Sustainable Practice.

Author: Mr. R. Guruprasath | Amrit Raj | Avinash Kumar | Nagaraj K | Sanjay T

Volume: 11 Issue: 6 June 2025

E-rakshak- The Border Surveillance Robot

Area of research: Electronics & Telecommunication Engineering

In This Project, We'll Carefully Examine A E-Rakshak The Border Surveillance Robot As We Know Surveillance Is A Difficult Task Of International Border Areas. It Is Not Possible By The Border Guarding Forces To Watch The Border At Each & Every Moment. In This Case The Essential Requirement Is To Have A System Security Control Unit. Nowadays, To Carry Out Risky Jobs The Robots Are Used That Cannot Be Done By The Soldiers. The Main Purpose Of Developing Such A New Technology In This Present System-based Spy Robot Platform With Remote Monitoring & Control Algorithm Through Internet Of Things (IOT) Has Been Developed Which Will Save Human Live, Reduces Manual Error And Protect The Country From Enemies. The System Comprises The Raspberry Pi (small Single- Board Computer), Camera, PIR Sensor And Shooting Gun. The Raspberry Pi Is The Brain Of The System. Android App Control The Moving To A Specific Direction And Camera For Live Streaming Videos Of Required Areas For Tracing And Attacking & The PIR Sensor Are Activated Depend On External Stimuli Via IOT. The User Is Able To Access The System With Control Buttons On The Android App From Control Room.

Author: Mr. H.K.Bhangale | Dukale Pranali | Pund Prashant | Vahadane Pallavi | Burte Vedant