What if walls could sense danger beyond cameras? A camera-free, AI-driven device called HALO says yes. From detecting vaping, distress, to aggression and threats in real-time, Motorola’s Pradeep Nair narrates everything about HALO to EFY’s Akanksha Sondhi Gaur.
Q. What is Halo, and how does it differ from conventional surveillance or IoT (Internet of Things) sensors?
A. Halo is a privacy-first, non-invasive device that integrates 16 intelligent sensing functions in a single unit. These include vaping and drug-use detection, aggression and gunshot detection, distress keyword recognition, occupancy counting, and environmental and air quality monitoring. It operates without cameras or microphones. Halo complements existing security systems, integrates with over 80 third-party platforms, and provides real-time alerts using AI (artificial intelligence) and edge computing. All analysis occurs locally at the edge, while optional cloud integration enables extended analytics and predictive insights.
Q. Can you share some typical use cases, particularly for India?
A. The sensor is so versatile that it can be deployed across multiple sectors. In education, it can help to curb vaping and detect signs of aggression or bullying through sound and keyword analysis. In healthcare, it monitors signs of distress in emergency rooms or psychiatric wards and helps to maintain optimal air quality. Government and public infrastructure, including airports, metros, transport hubs, and data centres, benefit from smoke and vaping detection, aggression detection and environmental tracking. In hospitality, it can discreetly identify unauthorised smoking or drug use in guest rooms, ensuring compliance without compromising privacy. For data centres, the device consolidates temperature, humidity, pressure, noise, and occupancy monitoring while supporting access control and compliance, reducing the need for multiple devices.
Q. Does Halo work with existing systems, and how is privacy ensured?
A. Halo complements, rather than replaces, existing systems. It integrates with building management systems (BMS), video management systems (VMS), and access control. In privacy-sensitive areas such as washrooms, VIP lounges, or boardrooms, where cameras are restricted, it provides discreet monitoring. Fully GDPR-compliant, the device detects signs of aggression or distress by identifying keywords without recording video or audio, and sends secure alerts to two-way radios, VMS, or enterprise apps, providing a balance of privacy-first and safety-first capabilities.
Q. How do AI, machine learning (ML), and edge computing enhance the sensor’s capabilities?
A. Detection is done at the sensor level for real-time alerts, which is critical for emergencies. AI algorithms improve anomaly detection and minimise false positives. For example, vaping detection has been highly accurate. Edge and cloud deployments enable both real-time alerts and long-term analytics for compliance, audits, and predictive monitoring. Halo uses edge AI for anomaly detection at the sensor level, providing instant alerts. Data is simultaneously streamed to the cloud for analytics, notifications, and six months of historical tracking. AI algorithms help deliver high accuracy for general sensing and vaping detection.
Q. Coming to India, what adoption challenges do you anticipate here?
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