Real-Time Visual Monitoring — using VisionBot AI devices
In today’s world of intelligent video monitoring, high computing servers working in tandem with advanced deep learning models have dramatically improved how CCTV camera video feeds are interpreted. By utilizing specialized neural networks—Convolutional Neural Networks (CNNs) for spatial analysis and Recurrent Neural Networks (RNNs) for temporal tracking—systems can not only identify but also follow objects with precision across numerous camera feeds. Visionbot.com exemplifies these innovations, delivering practical and scalable solutions for real-world environments.
The surge in CCTV deployment has generated enormous volumes of video data. Manual monitoring of these feeds is both inefficient and prone to errors. To automate the process, Visionbot.com and similar platforms employ artificial intelligence models that detect and track objects such as people, vehicles, and packages, enabling smarter security, safety, and operational insights.
GPU servers are essential for handling the computational intensity of deep learning models. Their parallel processing capabilities allow for real-time analysis of high-resolution video streams, making them ideal for large-scale monitoring operations. Visionbot.com leverages GPU-powered infrastructure to deliver seamless, rapid object detection and tracking, even across hundreds or thousands of video streams.
VisionBot’s innovative approach to infrastructure cost optimization centers on harnessing the power of modern multi-core CPUs as an alternative to traditionally expensive GPU servers. By designing and deploying deep neural network architectures that are finely tuned for parallel execution on CPU clusters, VisionBot delivers scalable AI-powered video analysis without the substantial capital and operational expenses associated with high-end GPUs. This strategy not only reduces hardware costs but also lowers energy consumption and streamlines maintenance, ensuring that advanced visual intelligence becomes accessible and sustainable for a broader range of organizations. The result: robust, real-time deep learning performance for monitoring and analytics—delivered at a fraction of the conventional cost.
VisionBot addresses the challenges of latency and computational demand in visual AI for object and event detection by processing data directly on-premise. By deploying AI models locally—either on dedicated GPU servers or optimized multi-core CPU clusters—VisionBot eliminates the delays inherent in transmitting video feeds to remote data centers or cloud platforms. This local processing ensures real-time responsiveness, which is critical for applications where immediate detection and action are required, such as security breaches or operational incidents. Furthermore, VisionBot’s efficient deep learning architectures are tailored to make the most of available hardware, achieving high-throughput analysis without sacrificing accuracy or speed. This on-premise approach not only enhances privacy and data security but also empowers organizations to scale their visual intelligence capabilities while maintaining tight control over performance and infrastructure costs.
VB-05AS A16
VisionBot’s High Performance Visual AI Server comes pre-installed with a robust Visual AI platform, offering full configuration, real-time viewing and marking, event generation, and alert annunciation. Designed to eliminate hardware bottlenecks, the system supports a wide range of applications, including smart city solutions, security and surveillance, construction site monitoring, manufacturing shopfloor oversight, logistics loss prevention, retail customer monitoring, and hospitality hygiene management.
VB-05AS M08
VisionBot’s High Performance Visual AI Server comes pre-installed with a robust Visual AI platform, offering full configuration, real-time viewing and marking, event generation, and alert annunciation. Designed to eliminate hardware bottlenecks, the system supports a wide range of applications, including smart city solutions, security and surveillance, construction site monitoring, manufacturing shopfloor oversight, logistics loss prevention, retail customer monitoring, and hospitality hygiene management.
VB-05AS B04
Visionbot’s entry level Visual AI device with multi camera aupport , available in compact rail or wall-mounted formats for industrial-grade use, is designed to eliminate hardware limitations and support advanced applications across diverse sectors. It powers smart city initiatives, enhances security and surveillance, and enables comprehensive monitoring for construction, manufacturing, logistics, retail, and hospitality environments.
On premise Visual AI server Network connections:
Cloud / On premise Visual AI Application
The VisionBot visual AI dashboard, seamlessly integrated aboard the dedicated visual AI server, empowers users with comprehensive analytics for both object and event identification. Through an intuitive interface, the dashboard presents real-time insights into detected people, vehicles, and packages, mapping activity patterns and flagging anomalies with precision. Advanced filtering and search tools allow users to review specific incidents, generate reports, and visualize trends across multiple video streams. This centralized application not only streamlines monitoring workflows but also enhances decision-making by providing actionable intelligence at a glance—unlocking the full potential of AI-driven surveillance for security, safety, and operational excellence.
Feature comparison chart
| Category | Features | A16 | M08 | B04 |
|---|---|---|---|---|
| Video Stream | ||||
| Input stream encoding | H264 | H264 | H264 | |
| Input FPS (Optional) ** | 10 FPS | 4 FPS | NO | |
| Camera Stream Live View | YES | YES | YES | |
| Stream snapshot resolution (Standard) ** | 1280×720 | 1280×720 | 640×480 | |
| Camera Input protocol | RTSP | RTSP | RTSP | |
| Minimum Camera capability | 2 MP | 4 MP | 4 MP | |
| AI | ||||
| Object recognition Accuracy level | High | Medium | Medium | |
| Detection FPS shareable across streams | 22 | 12 | 4 | |
| Max detection FPS per stream | 4 | 4 | 1 | |
| Configuration | ||||
| Visionbot Analytics Platform | Local | Local | Cloud | |
| Internet connectivity required *** | NO | NO | YES | |
| Max number of cameras | 16 | 8 | 4 | |
| Max simultaneous platform users | 2 | 2 | 1 | |
| Retention period of frames** | 15 days | 15 days | 10 days | |
| Option to extend retention period? ** | Yes | Yes | No | |
| Retention period of Analytics Data | 3 months | 3 months | 1 month | |
| Custom training option | Yes | Yes | No | |
| Custom event option | Yes | Yes | No | |
| Max events per customer | 32 | 32 | 12 | |
| Max events per camera per customer | 4 | 4 | 2 | |
| Max alerts per customer | 48 | 24 | 8 | |
| Max alerts per hour for one stream | 4 | 2 | 1 | |
| Alert Digital Output | Yes | Yes | No | |
| General | ||||
| Physical dimensions | 32 (L) x 36 (B) x 28(H) inches | 32 (L) x 36 (B) x 28(H) inches | 10.8 (L) x 8.5 (B) x 4.9 (H) inches | |
| Weight (Kg) | 17 | 17 | 1.5 | |
| External Interface | ||||
| Power input | 200-240VAC | 200-240VAC | 5VDC USB PD | |
| Network Interface | Gigabit Ethernet | Gigabit Ethernet | Gigabit Ethernet | |