Intelligent IoT Based Automatic Vehicle Speed Control and Alert System

Abstract

This project introduces an intelligent vehicle safety system designed to enhance road safety through the integration of modern technologies. Poweredbya12V battery,thesystem supportsa roboticchassisdrivenby DCmotors andmanaged through amotor driver for smooth and controlled movement. At the core of the system is an Arduino Uno microcontroller, which coordinates all functions and responds to real-time data. A key feature of the system is the use of RSSI (Received Signal Strength Indicator) technologytodetectschoolzones. Whenthevehicleenterssuchazone,thesystemautomaticallyreducesspeedtoensurethe safety of pedestrians, particularly children and high risk zones. This automation reduces the need for manual intervention and increases responsespeedtoenvironmentalcues.AnLCDdisplayisincludedtoprovidereal-timeupdatesonvehiclespeedandsystemstatus. The integration of these components results in a responsive and adaptive system. By focusing on zone-based speed control, the project promotes safer driving behavior. The robotic platform allows for flexible deployment and testing. The system is ideal for smartvehicleapplications,whereautomationplaysacriticalrole. Itdemonstratesthepotentialofmicrocontroller-basedsystemsin real-worldsafetysolutions.Thisapproachminimizesrisksinsensitiveareaslike sharpedgesandsuddenturns.Overall,theproject contributes to building safer, smarter, and more responsive transportation systems.

Introduction

The project presents an automated vehicle safety system designed to enhance driver and pedestrian safety, especially in high-risk zones like school areas and sharp turns. It uses RSSI (Received Signal Strength Indicator) technology to detect proximity to restricted zones and automatically reduces vehicle speed, reducing human error and improving road safety.

?? System Features and Architecture

???? Hardware Components

• Arduino Uno: Acts as the central controller, processing sensor inputs and controlling the vehicle.

• ESP8266: Detects Wi-Fi signal strength (RSSI) to determine proximity to high-risk zones.

• DC Motors + Motor Driver: Enable vehicle motion and adjust speed in response to RSSI data.

• GSM Module: Sends SMS alerts when the vehicle enters restricted zones.

• LCD Display: Shows current speed, signal strength, and zone status.

• 12V Battery + Regulator: Powers the entire system with safe voltage distribution.

???? Functional Highlights

• RSSI-Based Detection: Identifies entry into restricted zones using Wi-Fi signal strength.

• Automatic Speed Control: Reduces speed in real-time without requiring driver input.

• Real-Time Monitoring: LCD displays key vehicle stats continuously.

• GSM Alerts: Notifies users or authorities when a restricted area is entered.

• IoT Connectivity: Allows for remote monitoring via smart devices without needing GPS.

???? Literature Review Highlights

1. Singh & Prakash (2024) – RSSI-Based Adaptive Speed Control

• Focus: Dynamic speed adjustment in sensitive zones.

• Strength: Cost-effective use of RSSI.

• Limitation: Environmental interference impacts accuracy.

2. Bose & Karthik (2023) – AI-Based Driver Monitoring

• Focus: Combines AI with RSSI for proactive alerts.

• Strength: Reduces human error.

• Limitation: Raises privacy concerns and requires high processing power.

3. Kim, Lee & Park (2022) – Machine Learning with RSSI

• Focus: Machine learning for speed optimization using RSSI.

• Strength: Enhances traffic flow and efficiency.

• Limitation: Needs large datasets; urban interference can affect accuracy.

? Problems in Existing Systems

1. Driver Dependence: Traditional systems rely too much on driver awareness.

2. Limited Adaptability: GPS-based systems aren’t responsive to real-time conditions.

3. No Early Warning: Current systems often lack proactive alerts.

4. Inflexibility: Can’t adapt to sudden road changes or environmental factors.

???? Proposed System Advantages

• Works effectively without GPS—suitable for tunnels or remote areas.

• Low-cost components like Arduino, IR sensors, and DC motors.

• Scalable and modular: Easily upgradable and customizable.

• Energy-efficient: Runs on a compact 12V battery.

• Provides instant alerts via GSM, and real-time data on an LCD.

• IoT-enabled: Allows remote diagnostics and control.

• Promotes automation, minimizing reliance on human judgment.

???? Implementation Methodology

• Power Supply Setup: Uses a 12V battery regulated to 5V for safe component operation.

• RSSI Monitoring: ESP8266 tracks signal strength to identify zone entry.

• Speed Regulation: Arduino processes RSSI and sends speed control signals.

• Data Display: LCD continuously updates speed and status.

• Alerts: GSM module sends real-time SMS alerts during safety events.

Conclusion

In conclusion, this project demonstrates a practical and intelligent approach to enhancingvehicle safety through the integration of modern technologies. By utilizing an Arduino Uno microcontroller as the system’s brain, it effectively coordinates the operation of key components such as DC motors, an LCD display, and various sensors. Powered by a 12V battery, the system remains energy- efficientwhiledeliveringreliableperformance.TheimplementationofRSSItechnologyenablesaccuratedetectionofrestrictedzones likeHighriskzonesandSharpEdges,automaticallyreducingvehiclespeedtoensurepublicsafety.TheinclusionofGSM-basedreal- time alerts further empowers drivers by notifying them of upcoming risk zones by its distance, allowing for proactive speed adjustments. The LCD interface provides continuous updates on speed and system status, enhancing situational awareness. The system\'s adaptability allows it to respond dynamically to both permanent and temporary zones, making it suitable for diverse environments.Withitsmodularandscalabledesign,itisalsowell-suitedforintegrationintoIoT-basedsmartcityinfrastructures.The robotic platform offers a flexible base for testing and deployment, supporting future upgrades and experimentation. The controlled movement enabled by motor drivers ensures smooth navigation, even in complex routes. Moreover, by promoting consistent speed regulation, the system helps reduce fuel consumption and harmful emissions, contributing to greener transportation. It also proves highly effective in high-risk areas like sharp turns and blind spots. The solution mirrors intelligent traffic systems used globally, offering a cost-effective and accessible model. Overall, this project highlights the immense potential of microcontroller-based safety systems in shapingsafer,smarter, and moreresponsive transportationnetworks, pavingthewayforthenextgenerationof intelligent vehicles.

References

[1] Singh,M.,&Prakash,R.(2024).\"EnhancingRoadSafetywith AdaptiveSpeedControlUsingRSSITechnology.\"IEEE Transactions on Vehicular Technology, 73(1), 402-418. [2] Bose,S.,&Karthik,R.(2023).\"Real-TimeAI-BasedDriverMonitoringforAccidentPrevention.\"AutomotiveSafety& Engineering Journal, 45(4), 87-102. [3] Kim,J.,Lee,S.,&Park,D.(2022).\"IntelligentVehicleSpeedControlUsingRSSIandMachineLearning.\"Journalof Intelligent Transportation Systems, 26(3), 255-270. [4] Gupta,S.K.,Verma,A.,Singh,P.,&Sharma,R.K.(2025).\"SafeTrax:SmartCollisionPredictionandAlertSystemUsing IoT for Road Safety.\" IEEE Internet of Things Journal. [5] Maurya,A.K.,Singh,D.,&Kumar,R.(2024).\"IoT-BasedFrameworkforVehicleOver-SpeedDetection.\"IEEESensors Journal. [6] Basha,M.S.,Krishna,K.M.,&Kumar,S.S.(2024).\"Real-TimeAutomaticSpeedControlUnitforVehicles.\"IEEE Transactions on Intelligent Transportation Systems. [7] Zadeh,A.Y.,Khayyam,H.,Mallipeddi,R.,&Jamali,A.(2024).\"IntegratedIntelligentControlSystemsforEcoandSafe Driving in Autonomous Vehicles.\" IEEE Transactions on Intelligent Transportation Systems, 25(12), 19444-19456. [8] Aslam,N.,Phillips,W.,Robertson,W.,&Siew,W.H.(2024).\"AnIoT-BasedAutomaticVehicleAccident Detectionand Visual Situation Reporting System.\" Journal of Advanced Transportation. [9] Pande,A.S.,Pathare,A.A.,Thorat,R.D.,Kandalkar,A.C.,Rode,A.B.,&Mokal,V.A.(2024).\"IoT-BasedAutomatic Electric Vehicle Accident Prevention and Speed Control.\" International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 4(7), 355-357. [10] Satyanarayana,K.N.V.,Yaswanthini,G.,Kartheeka,P.L.,&Rajkumar,N.(2018).\"IoT-BasedVehicleSpeedControl Automatically in Restricted Areas Using RFID.\" International Journal of Engineering & Technology, 7(3.31), 72-74

Copyright

Copyright © 2025 Gunasekar K, N Manoj, Rakesh T, Mrs. P. Arthi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.