Prototipe Alat Survey Kondisi Jalan Otomatis

Summary

Fadil Hidayat, a researcher at ITB and expert in smart city innovations, developed an AI-powered and cost-effective road condition survey system in collaboration with the West Java Public Works Department. The system uses dashboard camera footage to detect road damage and an IoT device for precise location tracking. It helps generate accurate Pavement Condition Index (PCI) reports, enabling predictive road maintenance. This innovative solution reduces costs compared to existing systems like Hokai, making frequent surveys more feasible and improving road infrastructure management with real-time, updated data.

Takeaways

• 😀 The project was initiated in 2020 with a collaboration between Fadil Hidayat's team and the Public Works and Spatial Planning Department of West Java to develop a smart platform for road and bridge monitoring.
• 😀 The main problem faced was outdated road database due to long intervals between manual surveys, which were costly and labor-intensive.
• 😀 A current system in use, called 'Hope', is an automated tool installed on vehicles but is expensive and limited in availability throughout Indonesia.
• 😀 To improve the process, Fadil’s team developed a semi-automated application named SKPJ (Survey of Road Pavement Condition) to assist in road condition surveys.
• 😀 SKPJ processes video footage from dashboard cameras of survey vehicles to detect and classify various road damages, including potholes, crocodile skin cracks, and other unknown cracks.
• 😀 The application also extracts GPS data from the camera to automatically calculate the Pavement Condition Index (PCI) and generate PCI reports.
• 😀 Despite its benefits, SKPJ was still inefficient, prompting the team to integrate AI for more accurate damage classification and identification from video recordings.
• 😀 The AI system initially focuses on detecting three types of road damage: crocodile skin cracks, potholes, and unspecified cracks.
• 😀 GPS data from the dashboard camera was found to be insufficient for accurately pinpointing the location of road damage, leading to the development of an IoT-based tool for better accuracy.
• 😀 The IoT tool, attached to a survey vehicle’s wheel, uses two sensors—an odometer for tracking vehicle movement and a gyroscope for measuring vibrations. This data helps update the location of the road damage with better precision.
• 😀 The IoT-based tool allows for more frequent and cost-effective surveys, ultimately helping to keep the road database up to date. The project aims to provide predictive analysis for road maintenance and repair schedules.

Q & A

What is the main problem addressed by the innovation described in the script?

The main problem is the inefficiency and high cost of manual road surveys. Existing tools, like 'hokai,' are expensive and few in number, leading to outdated road condition data.

What is the name of the application developed to help with road condition surveys?

The application developed is called SKPJ, which stands for 'Survei Kondisi Perkerasan Jalan' (Road Condition Survey).

How does the SKPJ application work to improve road condition surveys?

SKPJ works by processing video footage from dashboard cameras of survey vehicles. The app uses AI to identify and classify types of road damage, such as potholes, crocodile skin cracks, and other types of cracks, and extracts GPS data to locate the damage.

Why is the SKPJ application described as semi-automatic?

SKPJ is semi-automatic because it requires manual input of video footage, but it automates the identification and classification of road damage and the calculation of the road condition index (IKP).

What issue was found with the GPS data used by the SKPJ application?

The GPS data from the dashboard camera was not sufficiently accurate to pinpoint the exact locations of road damage.

What solution was developed to address the GPS accuracy issue?

An IoT-based device was developed to improve GPS accuracy. This device records vehicle movement using an odometer and measures vibrations using a gyroscope to update the precise location of road damage.

How does the IoT device help in improving the road survey process?

The IoT device helps by providing more accurate data about the vehicle's movement and vibrations, which allows for better location tracking of road damage when integrated with the camera footage.

What are the key sensors used in the IoT device, and what do they do?

The IoT device uses two key sensors: an odometer to track vehicle movement and a gyroscope to measure vibrations. These sensors help improve the accuracy of road damage location data.

Why is the system described as cost-effective compared to existing technologies?

The system is cost-effective because it is much cheaper to develop than the expensive 'hokai' equipment, making it more accessible for widespread use. This enables more frequent surveys and better maintenance of roads.

What long-term benefit can the updated road condition database offer?

The updated database can facilitate predictive analysis of road life cycles, allowing for more accurate predictions of when road repairs should be carried out, ultimately leading to better resource management and reduced maintenance costs.