選單
Technically, the project utilizes edge computing applications. LILIN cameras are equipped with high-performance AI chips, allowing image recognition and data analysis to be processed directly on the device. This technology delivers several tangible benefits:
Real-time Response
Anomaly detection occurs without the need to transmit data back to a back-end host, reducing latency.
Reduced Hardware Costs
The system operates without extra PCs or high-end servers, saving server room space and lowering power consumption.
Simplified Maintenance
The minimalist architecture reduces the risk of hardware and software failure, lowering long-term operational and maintenance expenses.
Given the high volume of vehicle traffic in the underground parking lot, a highly integrated License Plate Recognition (LPR) system is essential. The system accurately captures plate information under various lighting conditions to ensure complete access logs, and automatically triggers alarms if an unauthorized vehicle is detected. For residents, this automated experience eliminates the need to fumble for access cards, as the system identifies their identity to open gates, optimizing traffic flow during peak hours.
In energy-saving areas like stairwells where light is dim, traditional surveillance often struggles with blurry or monochrome footage. This project utilizes LILIN’s low-light cameras, which maintain clear, full-color imagery even in near-total darkness. This allows security personnel to accurately identify clothing features and scene details during emergencies while allowing the community to maintain its energy-saving lighting policies without compromising security quality.
The success of Zhonghe Youth Social Housing demonstrates the substantial contribution of technology to living quality. Through edge computing, LPR, full-color low-light imaging, and virtual fencing, Merit LILIN has seamlessly integrated security into the fabric of community management.
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