Vehicle Detection Monitoring System using Internet of Things
| Autor: | Nurhadryani, Yani, Wulandari, Wulandari, Mastika, Muhammad Naufal Farras |
|---|---|
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi); Vol 6 No 5 (2022): October 2022; 749-760 Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi); Vol 6 No 5 (2022): Oktober 2022; 749-760 |
| ISSN: | 2580-0760 |
| DOI: | 10.29207/resti.v6i5.4082 |
| Popis: | The overcapacity of vehicle numbers is one of the significant causes of the traffic congestion problem on Indonesia roadways. The government applies a One-way system (SSA) as one proposed solution to unravel the congestion. However, several congestion points are still found during the SSA implementation. Thus, this research offers an alternative method to detect congestion using IoT technology. The system automatically enumerates the number, classifies the type, and computes the speed averages of vehicles to identify the severity of congestion based on the Indonesian Highway Capacity Manual (IHCM) published by the Ministry of Public Works 2014. We utilize ultrasonic sensors to detect the vehicles and send the data to the server in real time. The research successfully develops an IoT system for traffic congestion detection. Communication between nodes and API can be done well. Data exchange involving encryption and decryption with AES-256 is successfully done. The website application developed in this research successfully show the severity level of the congestion and their vehicle numbers. The average accuracy of the system is 78,97%. The system detected more vehicles than actual numbers due to the misreading value of the sensors. The overcapacity of vehicle numbers is one of the significant causes of the traffic congestion problem on Indonesia roadway. The government applies a One-way system (SSA) as one proposed solution to unravel the congestion. However, several congestion points are still found during the SSA implementation. Thus, this research offers an alternative method to detect congestion using IoT technology. The system automatically enumerates the number, classifies the type, and computes the speed averages of vehicles to identify the severity of congestion based on the Indonesian Highway Capacity Manual (IHCM) published by the Ministry of Public Works 2014. We utilize ultrasonic sensors to detect the vehicles and send the data to the server in real-time. The research successfully develops an IoT system for traffic congestion detection. Communication between nodes and API can be done well. Data exchange involving encryption and decryption with AES-256 is successfully done. Website application developed in this research is successfully show the severity level of the congestion and their vehicle numbers. The average accuracy of the system is 78,97%. The system detected more vehicles than actual numbers due to the misreading value of the sensors. |
| Databáze: | OpenAIRE |
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