The recent car explosion near Delhi's historic Red Fort has triggered nationwide concerns about security vulnerabilities in crowded public spaces. Security agencies are now intensifying their technological capabilities to detect anomalies and prevent similar incidents.
The Security Challenge in Crowded Public Spaces
On November 10, 2025, an improvised explosive device detonated in a vehicle parked in the heart of New Delhi, highlighting critical gaps in public safety monitoring. The explosive mixture contained ammonium nitrate, car fuel, and triacetone triperoxide (TATP) - a highly unstable chemical compound that can evade conventional detection systems.
According to Atul Rai, CEO of Staqu Technologies, the fundamental challenge lies in detecting substances like TATP that pass undetected through standard metal detectors and object scanning platforms currently deployed across security checkpoints.
Current Security Monitoring Technologies
Police forces across Delhi, Haryana, Uttar Pradesh, Punjab, and Maharashtra have integrated artificial intelligence into their security operations. These systems primarily utilize facial recognition and object detection technologies to identify individuals on watchlists and monitor suspicious activities.
Law enforcement agencies actively track multiple threat indicators including suspicious loitering patterns, mismatched vehicle license plates, and unusual object shapes. While much monitoring remains reactive to intelligence inputs, proactive surveillance is gradually expanding.
The Parking Lot Vulnerability
Unorganized public parking spaces represent one of the most significant security challenges. Unlike secured facilities in malls and hotels that employ handheld or floor-operated metal detectors, open parking areas lack systematic scanning mechanisms.
This makes it exceptionally difficult for security personnel to examine vehicle contents in crowded, unstructured environments. The absence of hybrid object scanners in these spaces creates substantial security blind spots that threat actors can exploit.
How AI Platforms Enhance Threat Detection
Technology firms like Staqu are collaborating with law enforcement through platforms such as Jarvis, which contributes to approximately 30% of the company's annual revenue. These systems leverage machine learning algorithms trained on extensive databases of suspicious objects, including open-source intelligence.
The platforms analyze object shapes, colors, and various metrics to identify potential threats. Importantly, these tools operate through law enforcement data centers, keeping sensitive information within government control and outside the scope of the Digital Personal Data Protection Act, 2023.
The Path Forward for Public Safety
A senior law enforcement official, speaking anonymously, confirmed that investigation agencies continue to collaborate with AI developers to enhance detection capabilities. The focus includes advanced image recognition, pattern analysis, and real-time video monitoring.
Security agencies maintain a globally-shared database of suspicious objects that undergoes constant updates. However, achieving complete public safety remains challenging, as security experts acknowledge the perpetual "cat-and-mouse game" between safety measures and threat actors.
Authorities emphasize the critical role of citizen vigilance, urging public reporting of suspicious activities in unorganized spaces to enable prompt intervention by security forces.
