Elevating Cloud Video Surveillance with ASUS IoT
Video surveillance has evolved from standalone analog systems to sophisticated Cloud-based solutions. The first such systems appeared in the 1940s, used primarily for military purposes. Fast forward to the 1990s, when digital video recording came into play, a technology that improved storage efficiency and retrieval. However, it relied on local hardware for implementation.
Next came IP cameras, enabling direct network connectivity, which allowed scalable, higher-resolution storage. However, these systems required significant infrastructure and on-premises management.
Cloud-based solutions now leverage the latest technologies, including broadband communications and the immense amounts of compute power available in the Cloud. Video can now be streamed, stored, and processed remotely, reducing on-site infrastructure needs. Advanced AI-driven analytics, real-time remote access, and integrations with industrial IoT (IIoT) ecosystems have revolutionized surveillance.
The bottom line is that Cloud solutions enable scalable, secure, and cost-efficient deployments, with edge computing optimizing bandwidth usage. The latest systems combine on-premise edge processing with cloud storage for resilience, integrating AI for incidents detection/classification, access control, forensic investigations, and business intelligence. The shift towards Cloud-native and hybrid models continues to redefine surveillance—delivering smarter security and improved operational efficiency.
Advantages of Cloud-Based Video Surveillance
The advantages of a Cloud-based video surveillance are many, including scalability, flexibility, and cost efficiency compared to traditional on-premises systems. To be specific, Cloud-based video surveillance can remove hardware limitations, allowing organizations to scale cameras and storage capacity as needed without significant upfront investments. And users can monitor live and recorded footage from any device with an Internet connection, enabling real-time oversight across multiple locations.
In terms of cost, the Cloud solutions reduce the need for expensive on-site hardware, as well as the maintenance and IT infrastructure that it requires. Cloud providers typically handle software updates, security patches, and feature enhancements, ensuring an always up-to-date system with minimal user intervention. What’s more, Security is enhanced because data is encrypted, stored redundantly across multiple locations, and protected from physical damage, theft, or tampering.
Furthermore, Cloud platforms can leverage AI-driven analytics for real-time alerts, facial recognition, and object and anomaly detection. For example, AI-powered analytics can detect anomalies, such as unauthorized access, loitering, or abandoned objects, triggering instant alerts. It also enables advanced biometric authentication and object classification, improving access control and forensic investigations. The AI engine can filter out irrelevant motion (likes swaying trees, animals, cars driving by) and distinguishes genuine security threats, reducing false alerts.
Combining with machine-learning models and historical data, the system can identify patterns, enabling proactive security measures before incidents occur. AI-powered indexing lets users quickly locate specific events, individuals, or objects within vast video archives. Also, AI-driven analytics can provide business intelligence, such as customer behavior tracking, occupancy monitoring, and workflow optimization
Inherent Development Challenges
Despite all the above advantages, the Cloud-based surveillance system requires several key hardware components to ensure efficient video capture, processing, storage, and network connectivity, which can still be a challenge in development. Each component plays a crucial role in ensuring seamless surveillance, high-quality video streaming, and secure data transmission in a cloud environment.
Those components would obviously include the cameras. In most cases, it would be IP-based cameras with integrated processors and encoders for direct Cloud streaming. They could also be specialized cameras, such as those incorporating thermal, night vision, and motion-detecting, based on the specific needs of the application.
In terms of networking equipment, a high-speed reliable network infrastructure is needed to transmit video feeds, including routers and switches. A Cloud gateway would act as an intermediary between the array of cameras and the Cloud, enabling local processing and buffering for bandwidth optimization. And firewalls and security appliances would protect against cyber threats and unauthorized access. Limited local storage is needed for redundancy and failover. In addition, an uninterruptable power supply (UPS) ensures system uptime during outages.
AI Can Be Complex
For the AI portion of the platform, you obviously need a GPU. The choice of that GPU is very application dependent. It would also be based on the software that’s being deployed, because it can be cumbersome to rewrite code to fit a specific GPU if it’s already been deployed for another.
One example that developers can learn from is the Eagle Eye Cloud Video Management System, developed by Eagle Eye Networks. It’s an open, Cloud-based platform with AI that was deployed at a US location recently. The system helps improve daily operations by detecting trends and patterns, as well as analyzing activity and reporting findings. A system like the Eagle Eye platform allows less time to be spent managing the actual video findings by making use of powerful analytics, providing users with actionable information, such as uncovering employee training gaps, alerting of potential safety liabilities, providing necessary audit trails, and simplifying compliance reporting.
Sometimes It Takes a Village
Many hands were involved in the design of the Eagle Eye system, with an assist from both Contec and ASUS IoT. Contec is a global electronics manufacturer and systems integrator that specializes in embedded computing, industrial automation, and M2M/IoT communication technologies. Its products are used in a host of applications, including factory automation, transportation, medical and life sciences, robotics, security, energy, government, and beyond. When Eagle Eye sought a hardware solution provider capable of delivering robust, long-lifecycle industrial motherboards—along with industry expertise in hardware integration and flexible customization—ASUS IoT emerged as the ideal partner. A sub-brand of the world’s leading motherboard manufacturer, ASUS, ASUS IoT has long been dedicated to developing cutting-edge AI and IoT solutions.
To meet the specific needs of the Eagle Eye system, Contec, as the systems integrator, selected the ASUS Q670EM-IM-A Micro-ATX industrial motherboard. Some customizations were required, including modifications to the I/O ports and a customized BIOS to align with Eagle Eye's operational requirements. ASUS IoT’s ability to provide tailored solutions ensured seamless integration within the system.
Eagle Eye did not require the most demanding CPU capabilities, so a slightly scaled-back processor was sufficient. The motherboard’s Micro-ATX form factor allowed Contec to design a compact enclosure while maintaining performance efficiency. With years of design expertise, global R&D services, and advanced manufacturing capabilities, ASUS IoT was able to work seamlessly with Contec to swiftly handle the necessary customizations.
As for the product itself, the Q670EM-IM-A features rich I/O capabilities and advanced connectivity, including legacy options for industrial applications, multiple COM ports, and three LAN ports. Expandability is enhanced through a PCIe slot, an M.2 E key, and an M.2 M key, allowing for flexible integration with various peripherals. Built with durable, industrial-grade components, the Q670EM-IM-A is engineered for 24/7 operation in harsh conditions, making it an ideal solution for a wide range of vertical markets.
From a cost-efficiency standpoint, the Q670EM-IM-A supports Intel 14th/13th/12th Gen processors, with power requirements of up to 125W. It features dual PCIe x16 slots, four U-DIMM slots supporting up to 128GB of 4.4GHz DDR5 memory, and four DisplayPort interfaces. With an operating temperature range of 0°C to +60°C, the motherboard is built for durability. ASUS IoT has committed to supporting this product for at least seven years, ensuring long-term availability and reducing total cost of ownership (TCO) for Eagle Eye Networks.
Together, ASUS IoT, Contec and Eagle Eye Networks, work together to drive success in Cloud-based video surveillance, enabling digital transformation ahead of its time. Reach out to ASUS IoT to learn more about the Industrial Motherboard and more product line, connect with Contec for more system integration requirements, and contact Eagle Eye Networks for its software solutions.