Traditional positioning terminals only support basic location data collection and upload. With the deployment of edge AI algorithms, positioning terminals are equipped with real-time data analysis and intelligent decision-making capabilities, achieving a fundamental transformation from data collection tools to intelligent sensing terminals.
The AI02 smart employee badge from WinFwd IoT is a typical application of this technology. Embedded with a lightweight AI fall detection model boasting an accuracy of over 95%, the device analyzes the wearer’s motion posture in real time. Once a fall is detected, it instantly triggers an SOS alarm and pushes location data. It also provides intelligent early warnings for abnormal loitering, prolonged off-duty behavior and other activities. All data analysis is processed locally on the terminal without relying on cloud computing power, greatly reducing data transmission costs and response latency.
The core challenge of edge AI deployment lies in balancing computing performance and power consumption. Restricted by limited battery capacity, terminal devices cannot sustain the continuous operation of high-computing AI models.
WinFwd IoT has effectively addressed this challenge through lightweight algorithm optimization and collaborative hardware design. On one hand, AI models are pruned and compressed to lower computing consumption while maintaining recognition accuracy. On the other hand, low-power chips and an intelligent sleep mechanism are adopted; the device automatically switches to low-power mode when stationary.
Ultimately, it achieves an ultra-long battery life of 7 days with a 1500mAh battery, offering a replicable solution for balancing computing power and power consumption across the industry.
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