Vehicle Detection and Speed Estimation for Automated Traffic Surveillance Systems at Nighttime

doi:10.17559/tv-20170827091448

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…To test the feasibility of using the traffic mobility information data for delinquency detection, the delinquency detection model uses Artificial Neural Networks [54]. The test dataset is further divided into two subsets T1 and T2., In our implementation only some of the values in the following attributes have been falsified making it difficult for the detection model to distinguish between truth data and falsified data [55]. This is due to the evasion approach that attackers use to carry out advanced and sophisticated bad-behavior attacks, which make it difficult for these machine learning algorithms to distinguish between normal and bad-behaved nodes [56].…”

Section: Research Resultsmentioning

confidence: 99%

Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept

Dewi¹

2021

IJEM

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The background of this research raises the problem of the development of smart transportation in terms of monitoring and enforcement of traffic on the highway, with the proposed system that will help many parties such as the police and the government. The system that is running is to develop a system using CCTV that is placed on every corner of the capital city to replace the police in carrying out road surveillance and law enforcement against lawbreakers, especially in the traffic sector. The method used in this research is by using literature review of many previous research journals, by reading many journals will be able to add knowledge and can deepen ongoing research. The problem raised in this research is finding solutions to problems in the transportation sector, especially smart transportation, using smart transportation will be able to connect all systems that have been made. This research produces a system proposal that can be used in further research and can be applied in terms of the development of smart cities, especially smart transportation.

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Section: Research Resultsmentioning

confidence: 99%

Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept

Dewi¹

2021

IJEM

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“…Pemberian ROI dan penentuan nilai faktor skala yang tepat dalam proses klasifikasi menjadi solusi untuk memperkecil kesalahan deteksi, mendapatkan hasil yang akurat dan kinerja yang baik. [17], [18], [19], [20] 4. KESIMPULAN DAN SARAN Penelitian ini merancang sistem klasifikasi, deteksi dan perhitungan kecepatan dari berbagai jenis kendaraan tertentu.…”

Section: Gambar 10 Batasan Area Deteksi (Roi)unclassified

Deteksi dan Estimasi Kecepatan Kendaraan dalam Sistem Pengawasan Lalu Lintas Menggunakan Pengolahan Citra

Zulfikri

Hairani

Ahmad

et al. 2021

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Deteksi objek berbasis pengolahan citra digital pada kendaraan sangat penting untuk diterapkan dalam membangun sistem pengawasan atau sebagai metode alternatif dalam mengumpulkan data statistik untuk pengambilan keputusan rekaya lalu lintas yang efisien. Pada penilitian ini, dibuat sistem deteksi kendaraan berbasis video lalu lintas untuk jenis kendaraan tertentu dengan menggunakan Haar Cascade Classifier dan estimasi kecepatan kendaraan dilakukan dengan menghitung perbedaan waktu pada Region of Interest (ROI) yang telah ditentukan dan hasilnya akan ditampilkan pada Radar Speed Design. Pengujian dilakukan dengan 5 video pengujian. Hasil yang didapatkan dari deteksi kendaraan yaitu nilai rata-rata recall 0.988 dan presisi 0.97 dan dari perhitungan kecepatan didapatkan nilai Mean Squared Error (MSE) yaitu 0,6.

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“…In the development of intelligent transportation drivers are an important part of the transportation system, with good drivers the system will run smoothly and the occurrence of road errors will be reduced [50], therefore drivers must be surveyed to get results, the types of good drivers must be explained and described for the development of smart transportation in a large and developing city [51].…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Greedy Algorithm on Traffic Violation Enforcement

Dewi¹,

Putra²

2021

IJEME

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The background of this research is how the application of the algorithm in traffic control systems, with the Greedy algorithm, the system will decide what action and what punishment will be given to traffic offenders on the highway, with the Greedy algorithm, the decisions taken will be based on data and facts. based on existing laws, so decisions made based on law and the human side cannot influence the decisions to be taken by the system based on the application of the Greedy algorithm. The research method used in this study uses literature reviews by reading many previous research journals, it will be able to add knowledge and deepen the research we are doing this time, with the literature review method, we will be able to find new problems and can be used as new research because The literature review is very helpful for our research this time. The system that is being used is using CCTV and can determine what decisions and punishments will be given to traffic offenders, through evidence based on images taken by cameras placed at red lights or corners of the capital's highway, the system this has been active effectively but with the implementation of the algorithm will increase. This research will produce a system proposal and be able to find out whether the application of the Greedy algorithm is correct and can help the current system by implementing the algorithm, so the existing system is more perfect. The main contribution of this research is that the use of the Greedy algorithm can help control the traffic system to enforce the law.

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Vehicle Detection and Speed Estimation for Automated Traffic Surveillance Systems at Nighttime

Cited by 5 publications

References 12 publications

Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept

Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept

Deteksi dan Estimasi Kecepatan Kendaraan dalam Sistem Pengawasan Lalu Lintas Menggunakan Pengolahan Citra

Application of Greedy Algorithm on Traffic Violation Enforcement

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