7 months ago
India's AI Surveillance Shift to Real-Time Intelligence
India is quickly adding many surveillance cameras in cities and public places.
Right now, these cameras mostly record videos that are watched later if something happens.
But now, experts say using AI can help watch and understand what's happening in real-time.
This means cameras can do more than just record; they can help make decisions quickly, like managing traffic or catching crimes earlier.
To keep this safe, the AI should work directly on the cameras or nearby computers, not sending sensitive videos over the internet.
This makes the system more secure.
However, there's a need for clear rules on how to use these AI cameras in public places to ensure they are used properly and fairly.
India is expanding surveillance camera networks under smart city and public safety programs.
Current systems mostly record footage for later review, not real-time monitoring.
AI-enabled real-time intelligence is becoming essential for proactive decision-making.
Edge-based processing allows AI to work directly on cameras or local servers, enhancing security.
Clear standards are needed for the acceptable use of AI in public surveillance to build trust and ensure proper governance.
- Who
- Urban local bodies, police departments, transport agencies, Qualcomm Technologies, CP Plus
- What
- India's shift from passive surveillance to real-time AI-based intelligence
- Where
- Across roads, transit hubs, and public facilities in India
- When
- Currently and in the future
- Why
- To enhance security, governance, and proactive public infrastructure management
Key facts
- Primary Category
- TECHNOLOGY
- Secondary Category
- AI
- Tertiary Category
- Surveillance
- Quaternary Category
- Real-Time Intelligence
- Key Stakeholders
- Urban local bodies, police departments, transport agencies, Qualcomm Technologies, CP Plus
- Current Surveillance Mode
- Record-and-review
- Future Surveillance Mode
- Real-time monitoring and response
- Key Technology
- Edge-based processing
- Security Benefit
- On-device AI for secure recognition systems
- Governance Need
- Clear standards for acceptable AI use in public spaces
Quotes
Nakul Duggal
EVP and Group GM for automotive, industrial, and embedded IoT and robotics at Qualcomm Technologies
“Authentication and decision-making at the edge make systems more resilient. Edge processing helps identify spoofing attempts before data leaves the device and ensures that sensitive video does not travel across networks for analysis.”
financialexpress.com
“Our job is to assist them by providing platforms that are built for operational sovereignty, privacy-aware processing, and secure on-device intelligence.”
financialexpress.com
Aditya Khemka
MD, CP Plus
“Current legal frameworks provide general data protection provisions but do not sufficiently address how visual AI systems should be governed in real-world environments. The introduction of well-defined standards for the use of camera AI in public and semi-public spaces will help in the maturation of India’s surveillance ecosystem, and such guidelines would help align authorities, technology providers and citizens.”
financialexpress.com
“By running AI models directly in cameras or edge hardware, recognition processes are shielded from external networks, reducing the risk of cyber manipulation, signal interception, or synthetic spoofing.”
financialexpress.com
Sources
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