BIAL rolls out smart airside safety system to prevent accidents at Kempegowda International Airport

Bengaluru: Bangalore International Airport Limited (BIAL) has introduced an integrated Smart Airside Safety System at Kempegowda International Airport in Bengaluru, aimed at improving real-time surveillance, reducing collision risks and strengthening operational safety in critical airside zones.

The system has been deployed at Cross Service Roads, where aircraft and ground vehicle movements intersect and where precise coordination is essential for safe airport operations.

BIAL said the new setup combines AI-based computer vision, intelligent automation and centralised monitoring to manage right-of-way more efficiently.

According to the airport sources, Cross Service Roads are among the most sensitive points in airside operations. Until now, right-of-way protection at these intersections depended largely on manual or semi-manual activation of inset lights, a process that involved human intervention and could lead to delays or operational gaps.

The new system uses real-time situational intelligence to detect vehicle movement, assess risk and automate signalling. AI-enabled cameras monitor CSR intersections, identify potential conflicts, detect non-compliant movement and confirm zone clearance in real time. Based on these inputs, the system automatically activates inset lights to protect aircraft movement and restores normal signalling once the intersection is clear.

BIAL said the platform also maintains a digital record of all events through a centralised analytics system, improving governance, compliance and operational control. By reducing dependence on manual intervention, the system is expected to lower the chances of human error, especially during night operations and low-visibility conditions.

The airport source said the automation would also improve traffic flow, reduce unnecessary stoppages and help quicken the turnaround time for aircraft and ground vehicles. In addition, the system is expected to create a foundation for predictive safety analytics, including trend analysis, peak-hour optimisation and risk forecasting.