Many logistics fleets are installing AI surveillance systems in their trucks to ensure successful goods delivery and driver safety. As some vehicle surveillance systems lack continuous learning capabilities; they typically base their judgements on predetermined contingencies, resulting in misjudgments. ZH-AOI, an expert AI solution provider, built hundreds of sets of AI Fleet Management Systems for an e-commerce fleet last year. These systems are divisible into four subsystems — Advanced Driver Assistance Systems (ADAS), Driver Monitoring Systems (DMS), Blind Spot Detection (BSD) systems, and Tire Pressure Monitoring Systems (TPMS). These AI Fleet Management Systems have comprehensive functions and the ability to learn. Aken Lee, the CEO of ZH-AOI, explained the situation using DMS as the example, “The same truck may be driven by different drivers. As a result, misjudgments can occur during monitoring due to the height of a driver’s seat. However, ZH-AOI’s system can enhance prediction system accuracy using big data learning based on AI.” This can reduce the rate of misjudgment incidents and the misinterpretation of driver behavior.
Aken Lee added that the recording functions found in presently available vehicle surveillance systems suffer from issues related to missing key images. He explained, “These problems are usually caused by poor system power management and inadequate streaming techniques.” ZH-AOI addressed this problem using continuous hard disk write-in and file recovery techniques following power outages. Such techniques enable the user to access images from before and after abnormal events. Indeed, users are granted a clearer event picture and don’t need to worry about key image loss.
Aken Lee also emphasized the importance of customization, adding, “Currently, there are many fleet management platforms available for aftermarket installation products (retrofits made after the vehicles leave factories); however, these options may not be able to satisfy the needs of fleets in different industries. If suppliers lack customization abilities, users may have no choice but to use inefficient fleet management platforms.”
ZH-AOI supports image analysis techniques and system integration, enabling users to deliver excellent customization services. This is in line with ZH-AOIs record of accomplishments. Indeed, they built AI Fleet Management Systems for more than three thousand trucks used in logistics transportation, cold-chain transportation, and gas-transportation fleets in one year.
AI platforms were essential in ZH-AOI’s AI Fleet Management Systems. Analogously, ZH-AOI selects products based on their cost effectiveness, I/O interfaces, convenience of installation, anti-vibration features, form factor, and wide temperature & voltage support. To this end, ZH-AOI chose the Advantech MIC-710AIL AI Inference System (Lite), the YUAN High-Tech DVP-7036HE image capture card, and QCAP SDK, for secondary AI system development.
The Advantech MIC-710AIL is a high-performance AI inference system that supports a variety of AI models and delivers superior AI computing capabilities. MIC-710AIL is used in four major subsystems to create a safe driving environment. Indeed, when applied in trucks alongside 8 x cameras, the MIC-710AIL can process a huge amount of image capture data simultaneously for smooth AI analyses.
MIC-710AIL undergoes strict temperature and vibration testing at Advantech before leaving the factory. This low-power consumption product features an excellent design structure that optimizes its heat dissipation. Aken Lee explained, “Heat dissipation problems and high-power consumption are common challenges in vehicle systems. Other companies’ products often crash. In contrast, we have been using Advantech’s products for several months and their products are comparatively stable.”
Moreover, MIC-710AIL also provides iDoor technology to engender high flexibility. iDoor technology enables SI to quickly develop applications using modular appliances.
E-commerce companies are striving to improve customer loyalty by ensuring timely delivery. Despite their efforts, ensuring timely, safe product delivery remains difficult. AI Fleet Management Systems enable close driver management in logistics fleets, and are useful for liability reasons following accidents.
ZH-AOI collaborated with Advantech and YUAN High-Tech to create this AI Fleet Management System. It ensures safe driving, allows remote management, takes images, and enables the use of reward systems for desirable behavior.
AI System (Lite) Based on NVIDIA Jetson Nano