Transjakarta, Jakarta’s public transportation operator, is developing three AI technologies to enhance its services and operations.

This initiative is part of the company’s digital transformation strategy.

Director of information technology systems and services at Transjakarta Raditya Maulana Rusdi announced the development of an AI Agent, AI Vision, and a recommendation engine.

These technologies aim to create a more efficient public transport system.

The AI Agent will use generative AI to facilitate natural interactions with customers through chatbots and text-to-speech features.

It will provide real-time assistance, including route updates and bus arrival times. Additionally, it will help with lost items.

AI Vision will apply computer vision technology to analyze CCTV data. It will monitor passenger density at bus stops and track fleet movements to improve operational efficiency.

Transjakarta has also introduced a Driver Monitoring System (DMS) to evaluate driver behavior in real-time, ensuring safety.

The recommendation engine will study service data and travel patterns. It will generate recommendations for new routes, adjustments to fleet frequency, and potential partnerships based on data insights.

🔗 Source: Liputan6.com

🧠 Food for thought

1️⃣ AI adoption in transit mirrors global success patterns with measurable returns

Transjakarta’s AI initiatives follow proven implementations from major transit agencies worldwide, where similar technologies have already delivered substantial benefits.

The New York MTA successfully used AI to detect 92% of track defects before human inspectors could identify them, significantly enhancing safety and maintenance efficiency 1.

In Shanghai, AI-powered on-demand bus service adjusts routes based on real-time passenger requests, demonstrating how smart routing systems like Transjakarta’s planned recommendation engine can improve service flexibility 1.

Transportation AI applications globally have shown the ability to reduce maintenance costs by 10-20% through predictive systems, while smart traffic management can decrease congestion by up to 25% 2.