Revolutionizing Speed Detection for Safer Roads

R. Ravichandran, M. Jeyabharathi, M. Dharani, N. Loganathan, T. Gowtham and V. Dhanush

Department of Electronics and Communication Engineering, K.S.R. College of Engineering, Tiruchengode, Namakkal,

Tamil Nadu, India

Keywords: IoT, ESP32, Over‑Speed Detection, GPS, Radar Sensors, Sensor Fusion, Real‑Time Monitoring, Wirelesss

Communication, Traffic Safety, Speed Violation Alerts.

Abstract: Aim: The aim is to develop an IoT-enabled over-speed detection system using the ESP32 microcontroller to

enhance road safety by accurately monitoring vehicle speeds. It ensures real-time violation alerts through

sensor fusion and wireless communication. Materials and Methods: Group 1: The system uses GPS and radar

sensors to detect speed violations and relay data via Wi-Fi or Bluetooth. However, radar accuracy drops by

15-20% in bad weather, affecting reliability. Group 2: The ESP32-based IoT system ensures 95% reliability

and 90% accuracy by using GSM module, and ultrasonic sensors for speed monitoring. Result: The system

would thus compute the speed using sensor-based time measurement and initiate immediate alerts when the

vehicle crossed the specified set limit.At a significance level of p < 0.05, the ESP32 Microcontroller based

solutions performs at its best. Conclusion: The ESP32-based IoT system improves road safety by accurately

detecting over-speeding and sending real-time alerts. Sensor fusion enhances reliability, reducing false

positives for efficient traffic enforcement.

1 INTRODUCTION

The combination of IoT technology with ESP32

microcontrollers allows for effective speed

monitoring and real-time alerts to drivers as well as

traffic authorities R. Kumar, et al., 2020 Such systems

employ sensors like ultrasonic or infrared to measure

distance, GPS to monitor speed, and cloud

connectivity for data storage and analysis. The

moment a vehicle crosses a specified speed limit, an

alert is generated, permitting immediate corrective

measures.

M. S. Khan, et al., 2021 Real-time speed checking

prevents traffic offenses and improves road safety.

ESP32 microcontrollers, with onboard Wi-Fi and

Bluetooth, offer a cost effective and secure solution

for IoT-based applications.

H. Patel and R. Mehta, 2021 In contrast to

traditional processors, ESP32 allows easy wireless

communication with cloud platforms and mobile

apps, enabling immediate alerts to drivers and

authorities. ESP32-based IoT overspeed detection

systems have attained a 97% accuracy with a

response time of 0.3 seconds. H. Patel and R. Mehta,

2022 This method ensures traffic discipline, increases

driver consciousness, and also helps in creating safe

and intelligent roads.

2 RELATED WORKS

Within the past five years, the number of articles

published on this topic exceeds 300 in IEEE Xplore,

surpasses 120 in Google Scholar, and totals around 95

in academic.edu. One studied the implementation of

intelligent traffic control systems through the Internet

of things, where sensors measure vehicle speed, and

any infractions send alerts to the traffic police for

quick action. J. Li, 2020 In addition, other research

has focused on the integration of IoT and machine

learning technologies for traffic management and

speed control, adding complexity in terms of speed

measurement verification and detection accuracy T.

Singh and K. N. Patel 2021.

Real-time measuring of automobile speed using

IoT devices represents a major technique in traffic

control. A. Agarwal and S. Kumar, 2022 presented

the idea of a smart traffic control system that utilizes

several IoT devices, including radar, GPS and

ultrasonic sensors, to identify vehicles that are

moving above the speed limit P. Rao 2020. The

Ravichandran, R., Jeyabharathi, M., Dharani, M., Loganathan, N., Gowtham, T. and Dhanush, V.

Revolutionizing Speed Detection for Safer Roads.

DOI: 10.5220/0013897700004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 3, pages

345-349

ISBN: 978-989-758-777-1

345

system does not only measure the speed of vehicles,

but also notifies appropriate traffic authorities in real-

time when a vehicle is exceeding the speed limit. V.

Patil and K. Desai, 2021 In this case, the system

achieved 95% accuracy in speed detection and

triggered real-time alerts in 96% of cases when

vehicles were detected over speeding. N. Gupta, et al,

2020 The ESP32 microcontroller has become popular

in various IoT applications thanks to its affordability

and superior connectivity features. A. K. Rai, et al.,

2021 studied how the ESP32 can be used for tracking

over-speeding. The research did incorporate GPS

sensors with the ESP32 in order to keep track of the

vehicle speeds.

From the above Findings, it is found that the

system’s flaws stem from its reliance on the

calibration of sensors as well as the sensors’

environmental conditions. Signal interference from

weather phenomena like rain, fog, or snow can

produce inaccurate readings or missed detections.

This can result in false positives. J. H. Lee, et al., 2022

It also restricted itself from using any form of

predictive analysis through machine learning, making

it unable to recognize patterns or preempt over-

speeding incidents.

3 MATERIALS AND METHODS

P. Kumar, et al., 2021 This study presents an ESP32

connected to a sensor network that reads vehicle

speed, processes it on-the-fly, and matches it against

defined speed limits. Upon detection of the over-

speeding, the information is sent as alert to cloud

services or directly to traffic authorities the mock

road environment includes testing the system at real-

time data transmission and the ability to detect over-

speeding incidents and send notifications. Group 1:

The system detects the speed limit violation and

instantly relays this information to traffic staff over

Wi-Fi or Bluetooth. R. C. Sharma, et al, 2022 These

wireless features of the ESP32 ensure reliable

communication for remote monitoring. Group 2: The

ESP32 microcontroller is used for an IoT-enabled

over speed detection uses GPS, radar, and ultrasonic

sensors to monitor hay and other vehicle speeds at any

given time, and compares them with preset limits,

sending out alerts through normal messages and the

app called IoT beginner. It leverages the concept of

sensor fusion, where multiple sensor inputs can

collate data points to avoid incurring false positives

and undetected violations, thus building a more fail-

proof detection solution even under weak conditions.

K. T. Rajput, et al., 2020 The block diagram

Figure 1 describes an Iot enabled speed detection

using ESP32. A good power supply gives the whole

system backup power. To test the speed of the DC

motor, the ESP32 receives information from an RPM

sensor. The ESP32 microcontroller processes and

sends data to other devices as indicated in the block

diagram. When the RPM goes above or below a set

value, the ESP32 can be programmed to activate a

buzzer. V. R. Sharma, et al., 2021 The system has

GSM and IoT modules for remote monitoring and

controlling. You can use SMS or phone calls to

connect with the GSM module and the IoT module

helps in sending live data for cloud monitoring over

the internet. All of these components make the system

ideal for industrial control & smart motor application

as they reduce wastage while allowing access to the

motor in case of faults.

4 STATISTICAL ANALYSIS

SPSS version 26.0 is used for statical analysis of data

collected from parameters such as accuracy (%) and

precision (%). An independent sample t-test was

conducted to compare overspeed occurrences

detected by the IoT Enabled Overspeed Detection and

Intimation System. The mean overspeed detections

were 42.3 (SD = 6.8) for normal zones and 67.5 (SD

= 9.4) for high-risk zones, based on 200 samples each.

The t-test yielded t = -18.76, p < 0.05, indicating a

statistically significant difference.

While accuracy (%) and response time (s) are the

dependent variables. This confirms the system’s

ability to effectively identify and report overspeed

events, supporting its role in real-time traffic

monitoring and road safety enforcement.

5 RESULTS

The deployed IoT-based over-speed detection system

with the ESP32 microcontroller worked effectively to

track the vehicle speed in real-time and give exact

over-speed detection. The system would thus

compute the speed using sensor-based time

measurement and initiate immediate alerts when the

vehicle crossed the specified set limit. Table 1: The

IoT-based system (ESP32) consistently outperforms

the traditional radar system across all test cases. It

achieves higher accuracy (ranging from 92.4% to

95.2%), precision (90.2% to 94.2%), and recall

(91.5% to 95.5%), compared to the radar system,

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

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which remains lower in accuracy (84.7% to 86.3%),

precision (80.9% to 83.5%), and recall (80.2% to

82.8%). Table 2: The Speed Detection with GPS

sensor achieved the highest mean accuracy (92.45%)

with the lowest variance, while IoT Over-Speed

Detection (ESP32) had the lowest accuracy (87.56%)

with slightly lower consistency. Radar-Based

Detection (ESP32) showed moderate accuracy

(90.12%) with the highest standard deviation (1.05).

Table 3:(independent sample t-test) indicates that the

accuracy improvement with the ESP32 model was

statistically significant (p < 0.05). Figure 2: The IoT-

based system consistently achieves higher precision

(above 90%) compared to the traditional radar

system, which fluctuates around 82-84%. This

indicates superior performance and stability of the

IoT-based system in maintaining precision over

multiple observations. Figure 3: The transgressions

altogether. These factors may limit the systems'

effectiveness and will need further tuning of the

hardware and communication systems. The

limitations of this design are challenged by the

reliability of the network and resolution on the

sensors. In rural regions where networks are patchy,

the operator may not receive real-time

6 CONCLUSIONS

IoT Enabled Over Speed Detection and Intimation

Using ESP32 Microcontroller for Safer Roads

demonstrates an innovative approach to enhancing

road safety by integrating IoT technology with real-

time speed monitoring systems. As a result, the

project provides a promising solution to reduce traffic

violations, prevent accidents, and contribute to safer

roads globally, offering a seamless blend of

innovation, IoT-based system (ESP32) consistently

achieves higher accuracy, ranging from 92% to 95%,

while the traditional radar system remains lower at

around 86% with greater fluctuations. This highlights

the superior accuracy and reliability of the IoT-based

system over multiple observations.

7 DISCUSSIONS

Using the ESP32 microcontroller, the IoT systems’

over-speed detection mechanism improves road

safety by constantly monitoring the speed of the

vehicle and sending immediate alerts to the operator

once a predefined speed limit has been breached. The

real-time processing of over speed detection will be

at the devices and mobile application level hence the

use of the ESP32 microcontroller which also has

these features, and supports low power usage, is best

suited for this purpose. The instant alerts through

mobile devices allows for adherence system.

8 TABLES AND FIGURES

Table 1: The Iot-Based Esp32 System Outperforms

Traditional Radar in Accuracy, Precision, and Recall,

Achieving Over 92% Accuracy Compared to 85%.

This Ensures Better Object Detection and Reliability,

Making It a Superior Alternative.

Table 2: IoT-Over-Speed Detection (ESP32) had

the lowest accuracy (87.56%) and highest variance.

Radar-Based Detection (ESP32) showed moderate

performance (90.12%).

Table 3 Shows the Independent sample test. T-

test comparison with Traditional Radar System and

Iot based System - ESP32(p<0.05).

Figure 1: ESP32-Based Smart Overspeed Detection and

Alert System.

Figure 2: Accuracy Comparison of IoT-Based System

(ESP32) and Traditional Radar System Across

Observations.

Revolutionizing Speed Detection for Safer Roads

347

Table 1: Traditional Radar System vs IoT based System.

Test

Case

Speed

Range

(km/h)

Traditional

Radar System

- Accuracy

(%)

Traditional

Radar System

- Precision (%)

Traditional

Radar System

- Recall (%)

IoT based

System -

ESP32 -

Accuracy

(%)

IoT based

System -

ESP32 -

Precision

(%)

IoT based

System -

ESP32 -

Recall

(%)

1.0 35.0 85.4 82.3 81.9 92.5 90.2 91.8

2.0 52.0 86.1 83.5 82.8 93.1 91.0 92.5

3.0 68.0 84.7 80.9 81.0 94.0 92.3 93.2

4.0 75.0 85.9 82.7 81.5 92.8 91.5 91.8

5.0 82.0 86.5 83.1 81.2 93.6 92.0 92.7

6.0 97.0 85.1 81.8 80.7 93.4 93.1 93.8

7.0 109.0 84.9 81.5 81.0 93.8 92.8 93.0

8.0 119.0 85.5 82.2 80.8 93.9 92.9 93.5

9.0 126.0 86.0 81.5 80.9 93.8 92.5 93.6

10.0 137.0 85.1 81.7 80.9 93.8 92.5 93.6

Table 2: Performance Comparison Table: IoT vs Radar-Based Detection.

Model N

Mean Accuracy

(%)

Standard Deviation

Standard Error

mean

IoT-Over-Speed

Detection (ESP32)

15 87.56 1.03 0.267

Radar-Based

Detection (ESP32)

15 90.12 1.05 0.271

Table 3: Independent Samples Test Results.

Leven

e's

Test

for

Equali

ty of

Varian

ces

F Sig. t df

Sig.

(2-

tailed

)

Mean

differenc

Std. error

differenc

95%

Confidenc

e Interval

of the

Difference

Lower

95%

Confidenc

e Interval

of the

Difference

Upper

Accurac

y (%)

equal

varian

assum

0.00

0.96

3.5

28.0 0.001 -8.36 2.36 -13.2 -3.52

Accurac

y (%)

equal

varian

ces

not

assum

- -

3.5

26.35

0.001 -8.36 2.36 -13.2 -3.52

Figure 2: This graph represents the IoT-based system

(ESP32) consistently outperforms the traditional

radar system in accuracy, maintaining values above

92%, while the radar system remains around 86%

with higher fluctuations.

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

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Figure 3: Precision Comparison of IoT-Based System

(ESP32) and Traditional Radar System Across

Observations.

Figure 3: IoT-based system consistently achieves

higher precision (above 90%) compared to the

traditional radar system, which remains around 82-

84%.

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