Threshold Based Efficient Road Monitoring System Using Crowdsourcing Approach

Sabir, Naveed; Memon, Anzal Ali; Shaikh, Faisal Karim

doi:10.1007/s11277-019-06324-y

Cited by 17 publications

(6 citation statements)

References 24 publications

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“…Sabir et al [42] proposed a driver-friendly interface system that can monitor the speed breakers and potholes by monitoring the roads. Crowdsourcing approach was used to design and develop the system.…”

Section: Related Workmentioning

confidence: 99%

A Blockchain Based Cloud Integrated IoT Architecture Using a Hybrid Design

Rupa

Srivastava

Gadekallu

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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The Internet of Things (IoT) and its applications are gaining popularity in recent years due to features like ease of use and increased availability of the Internet. We can enhance the efficiency of IoT based systems by adding other advanced technologies like cloud infrastructure and blockchain technology. Through these enhancements IoT applications can be accessed at any time from any place. However, a database is required for storing the information of the application. Cloud infrastructure is an ideal solution for storing IoT based applications as it provides remote services such as storage, computation, and analysis. The major drawback of these applications are their inability to provide security and privacy for data. Blockchain technology helps in overcoming these drawbacks with features like immutability, transparency, and distributed structure. In this paper, a blockchain based cloud integrated IoT application is proposed that can assist to identify intruders through virtual monitoring. The main advantage of this application is that it can operate in areas where manual monitoring is challenging and data is stored in a blockchain-based tamper-free environment.

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Section: Related Workmentioning

confidence: 99%

A Blockchain Based Cloud Integrated IoT Architecture Using a Hybrid Design

Rupa

Srivastava

Gadekallu

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…The threshold and sliding window size were changed for the tuning of each algorithm for pothole detection, and the best true positive rate achieved was 90%. A system named TERM [ 15 ] is a road monitoring system using dynamic thresholds and crowdsourcing methods. In this algorithm, a potential pothole is detected when the acceleration values of the X - (lateral) and Z -axes (vertical) exceed the specified threshold, and a speed bump is detected when the acceleration values of the Y - (longitudinal) and Z -axes exceed the specified threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data

Wang

et al. 2020

Sensors

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Road surface monitoring and maintenance are essential for driving comfort, transport safety and preserving infrastructure integrity. Traditional road condition monitoring is regularly conducted by specially designed instrumented vehicles, which requires time and money and is only able to cover a limited proportion of the road network. In light of the ubiquitous use of smartphones, this paper proposes an automatic pothole detection system utilizing the built-in vibration sensors and global positioning system receivers in smartphones. We collected road condition data in a city using dedicated vehicles and smartphones with a purpose-built mobile application designed for this study. A series of processing methods were applied to the collected data, and features from different frequency domains were extracted, along with various machine-learning classifiers. The results indicated that features from the time and frequency domains outperformed other features for identifying potholes. Among the classifiers tested, the Random Forest method exhibited the best classification performance for potholes, with a precision of 88.5% and recall of 75%. Finally, we validated the proposed method using datasets generated from different road types and examined its universality and robustness.

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“…Then, the crowd sensed potholes within a 10-meter radius were aggregated into one pothole through a simple averaging procedure. Sabir et al [26] conducted a similar study to enhance the accuracy of the detected road anomalies. In their study, the public reported potholes within a 5-meter radius were clustered to eliminate duplicated reports.…”

Section: Related Studiesmentioning

confidence: 99%

Embracing Crowdsensing: An Enhanced Mobile Sensing Solution for Road Anomaly Detection

Huo

Goldberg

et al. 2019

IJGI

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Road anomaly detection is essential in road maintenance and management; however, continuously monitoring road anomalies (such as bumps and potholes) with a low-cost and high-efficiency solution remains a challenging research question. In this study, we put forward an enhanced mobile sensing solution to detect road anomalies using mobile sensed data. We first create a smartphone app to detect irregular vehicle vibrations that usually imply road anomalies. Then, the mobile sensed signals are analyzed through continuous wavelet transform to identify road anomalies and estimate their sizes. Next, we innovatively utilize a spatial clustering method to group multiple driving tests’ results into clusters based on their spatial density patterns. Finally, the optimized detection results are obtained by synthesizing each cluster’s member points. Results demonstrate that our proposed solution can accurately detect road surface anomalies (94.44%) with a high positioning accuracy (within 3.29 meters in average) and an acceptable size estimation error (with a mean error of 14 cm). This study suggests that implementing a crowdsensing solution could substantially improve the effectiveness of traditional road monitoring systems.

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Threshold Based Efficient Road Monitoring System Using Crowdsourcing Approach

Cited by 17 publications

References 24 publications

A Blockchain Based Cloud Integrated IoT Architecture Using a Hybrid Design

A Blockchain Based Cloud Integrated IoT Architecture Using a Hybrid Design

An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data

Embracing Crowdsensing: An Enhanced Mobile Sensing Solution for Road Anomaly Detection

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