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Author: Kelly Kao

What is AIoT

Artificial Intelligence of Things (AIoT) is the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT). IoT enables devices to collect and transmit data through sensors and networks, while AI provides analytical and decision-making capabilities. When combined, AIoT not only allows devices to perceive their environment and exchange information but also enables real-time inference and automated actions at the cloud or edge. This makes AIoT the backbone of next-generation infrastructure, driving the development of smart cities, industrial automation, and public safety.

Differences between IoT and AIoT

• IoT: Its primary function is “sensing and transmission.” Devices collect data via sensors and send it to the cloud or data centers for analysis and decision-making. Its role is primarily that of an information collector.
   
• AIoT: Builds on IoT by integrating artificial intelligence, enabling devices to make real-time judgments and automated decisions. These judgments can occur in the cloud or directly at the edge. AIoT has evolved from being a collector to becoming an intelligent actor.
   

AIoT-Driven Transformation of Security Monitoring

1. From Passive Recording to Intelligent Decision-Making

Traditional security monitoring systems are mostly limited to “passive recording” and “post-event review.” Different subsystems lack integration, requiring manual comparison and judgment, resulting in delayed responses. AIoT removes this limitation. For example, when an access control system detects abnormal entry, AI-powered video recognition can instantly cross-check camera footage, automatically tag suspicious images, notify administrators, and simultaneously trigger alarms and lockdown procedures. This automation compresses response time from minutes to seconds, greatly improving emergency handling efficiency.

2. Edge Computing: The Key to Real-Time Monitoring

In traditional IoT architectures, massive amounts of data must be sent to the cloud for processing, which not only creates bandwidth pressure but also fails to meet real-time requirements. AIoT integrates edge computing, allowing cameras and gateways to perform local AI inference and achieve on-site real-time video recognition and anomaly detection. This is particularly critical for traffic management and public safety, where millisecond-level responses often determine the effectiveness of incident response. Moreover, edge intelligence reduces data uploads, lowering the risk of data leakage.

3. Secure-by-Design: The New Foundation of Security Monitoring

The concept of “Secure-by-Design” originated in IoT and cybersecurity, emphasizing that security must be embedded during the design phase rather than added afterward. With the rise of AIoT, this principle has become even more important.

In the AIoT environment, challenges extend beyond traditional IoT device vulnerabilities and network attacks. New threats include tampering with AI training data, adversarial attacks that mislead models, and malicious control of edge devices. Without security and resilience built in from the start, these risks can directly undermine the accuracy of real-time judgments and automated decisions.

Therefore, Secure-by-Design for AIoT must include:

• End-to-end encryption: Ensuring that data transmission cannot be intercepted or altered.
• Identity authentication and access control: Preventing unauthorized devices or users from entering the system.
• AI model and data protection: Reducing risks of adversarial attacks and model theft.
• Compliance with international standards: Such as ISO/IEC 27001 and IEC 62443, to ensure long-term system resilience.
   

Transformational Benefits of AIoT

The adoption of AIoT in security monitoring is driving change across three key dimensions:

1. More immediate response: AI models running on edge devices can make instant judgments. For example, when a camera detects suspicious behavior, the system can trigger an alarm within seconds without waiting for manual video review.
    
2. Greater efficiency: AI automatically filters out vast amounts of “no-event” footage, reducing false alarms and manual workload, allowing security personnel to focus on real threats.
    
3. Stronger protection: Platforms built with Secure-by-Design integrate end-to-end encryption and access control, ensuring that even under cyberattacks, video and data remain secure and available.
    

These changes transform monitoring from being a passive recording tool into an intelligent protection network, enhancing both public safety and enterprise asset security.

Conclusion

AIoT is shifting security monitoring from “mere recording” to “intelligent protection.” By combining real-time analytics, edge intelligence, and security-by-design principles, monitoring systems gain higher speed, efficiency, and resilience. For enterprises and public agencies, this means achieving stronger protection at lower costs. For investors, it signals that AIoT security solutions are becoming one of the most promising areas within smart cities and digital infrastructure.

Disclaimer

The content of this article is provided for reference and informational purposes only. It aims to explore the impact of Artificial Intelligence of Things (AIoT) on security system deployment, including industry trends, technical applications, and policy developments. The information herein is compiled from publicly available data, professional reports, and general industry understanding. The analyses and inferences are based on currently available information and the author’s interpretation.

However, the accuracy and completeness may vary as sources are updated or market conditions change. Readers should verify original sources and assess applicability based on their own needs and professional judgment before citing or applying this information. This article does not constitute technical commitments or product endorsements.

Reference

AIoT-Enhanced SSD Solutions for Surveillance Systems

The evolution of edge computing in security

AIoT will be concentrated in certain IoT use cases

Secure IoT by design

How should companies choose an AIoT platform that complies with cybersecurity standards?

Exploring the Impact of AIoT on Security