With the rapid increase in global air travel, airports face significant challenges in efficiently handling millions of passengers and their baggage. Traditional baggage handling systems might face the following challenges. To overcome these issues, airports are turning to AI-powered solutions that offer real-time data processing and automation to streamline baggage management.
Manual Sorting & Routing Errors: According to research, the global mishandling rate surged to 7.6 bags per thousand passengers in 2022. Traditional baggage handling relies on barcodes and manual sorting, making it prone to misrouting and loss. By integrating RFID, IoT, and Edge AI, airports can automate scanning and routing with collaborative robots (cobots), significantly reducing human error and improving accuracy.
Legacy Systems Prone to Malfunction and Limited Visibility: Transfer-related delays now account for 42% of mishandled bags, underscoring the limitations of traditional systems. Legacy infrastructure is not only exposed to malfunction but also lacks end-to-end visibility, making it difficult to track, manage, or recover baggage effectively. AI-driven solutions and RFID-enabled checkpoints provide real-time monitoring, ensuring full transparency and faster response across the baggage journey.
Labor shortage: The aviation industry has been struggling with a persistent labor shortage, particularly in physically demanding roles such as baggage handling and monitoring. This might cause longer wait times and operational inefficiency. Cobots and AMRs help bridge the gap, increasing efficiency and accuracy without relying on large workforces.
Limited Scalability and Flexibility During Peak Demand: Traditional baggage systems often fail to cope with sudden spikes in passenger or luggage volume, contributing to a 74.7% increase in baggage loss in 2022. These rigid infrastructures lack the flexibility to scale on demand. In contrast, new technologies offer dynamic load management, allowing airports to maintain performance and accuracy even during peak periods.
Cobot for Baggage Scanning and Sorting
Unlike traditional baggage sorting methods that are prone to manual errors, the baggage scanning and sorting cobot significantly improves accuracy and efficiency while reducing labor dependency. By scanning the RFID tag on each bag, the cobot automatically lifts and routes baggage to the correct destination, streamlining the process.
AIE510-ONX: High-Performance Edge-AI Platform Designed for Cobots
NVIDIA® Jetson Orin™ NX
Powered by the NVIDIA® Jetson Orin™ NX, the AIE510-ONX boasts up to 100 TOPS of computing power, enabling it to analyze vast amounts of images. It also supports the NVIDIA Isaac™ Robot Operating System (ROS) SDK to accelerate AI-enabled robot development.
Rich I/O Interface for Sensors
To support seamless integration with multiple sensors on the cobot, the AIE510-ONX is equipped with a comprehensive I/O interface, including a COM port for precise motion control. For applications requiring real-time environmental awareness, customers may opt for the GMSL version for low-latency, long-distance connectivity to cameras and sensors.
Expansions for Multiple Wireless Options
The AIE510-ONX offers versatile expansion options, including an M.2 Key E 2230 slot for Wi-Fi 6E, a full-size PCI Express Mini Card slot for Wi-Fi or LTE, an M.2 Key B 3042/3052 slot for 5G/LTE connectivity, and a Nano SIM slot. These features enable seamless, high-speed communication with cloud-based tourist data centers, ensuring real-time synchronization and accuracy.
AMR for Baggage Process
Instead of requiring staff to drive vehicles to move baggage across the airport, AMRs equipped with integrated RFID scanners can autonomously identify, verify, and route each piece of luggage to its correct destination. This automation enhances routing accuracy, reduces labor dependency, and provides end-to-end visibility across the baggage handling process.
ROBOX500: AMR Controller with M12 Connectors and GMSL Interface
12th/13th Gen Intel® Core™ & AI Module
The ROBOX500 is powered by the high-performance 12th/13th Gen Intel® Core™ i7 processors. It supports a scalable AI module with an M.2 Key M 2242 slot, making it ideal for autonomous robots. Engineered to handle intricate data processing, it excels in environment sensing and real-time decision-making.
4-ch GMSL and Rich I/O Interface
GMSL enables high-speed, low-latency, and long-distance data transmission, allowing robots to perceive real-time environmental change. The system’s comprehensive I/O ensures seamless and reliable connections to external devices such as 3D Lidar sensors, IMU, RFID reader, and emergency brakes.
Rugged Design with 9-60 VDC Input
Every detail on the ROBOX500 is engineered for heavy-duty performance, including longer and thicker cooling fins, 5G anti-vibration capability, and M12-type lockable connectors. To ensure smooth operation in outdoor areas, the ROBOX500 supports an extended operating temperature range of -40°C to +70°C. Additionally, its wide 9 to 60 VDC power input range not only makes it ideal for in-vehicle applications but also minimizes energy loss due to voltage conversion, contributing to a more efficient and sustainable power usage.
AMR Builder Package: A Full Package to Accelerate Your Time-to-Market
Our AMR Builder Package aims to accelerate time-to-market through a complete support program. It includes an AMR controller, a ROS 2 software package, sensor kits, and development support services, including reference design and design guide, allowing easy system development and deployment for our customers.
AI-Driven Baggage Conveyor Monitoring
Ongoing labor shortages make it increasingly challenging to monitor baggage conveyor systems effectively. In some airports, a single handler may oversee up to four conveyor lines, leading to slower response times and reducing operational efficiency. AI-powered monitoring systems can automatically detect issues such as baggage jams, fallen luggage, or system anomalies in real time, instantly alerting staff for quick intervention. These systems can also track passenger behavior, such as crossing the waiting line, and trigger alerts as needed.
AIE100-ONX: Palm-Sized Edge-AI Platform Powered by NVIDIA Jetson ONX
Strong AI Computing Capability
The AIE100-ONX is powered by the NVIDIA® Jetson Orin™ NX platform that features a powerful 8-core/6-core ARM® Cortex® A78AE processor delivering up to 100 TOPS of AI performance and integrates an advanced 1,024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores. This makes it a perfect choice for machine vision-related applications.
Rich I/O with Front-facing Design
To enhance the versatility of connectivity, the AIE100-ONX features a rich I/O interface for cameras and sensors, making it an ideal choice for airport baggage conveyor monitoring. Its front-facing design facilitates installation and maintenance for customers.
Compact and Reliable
The palm-sized AIE100-ONX, measuring only 148.6 mm x 129.8 mm x 34.6 mm, is perfectly suited for deployment in constrained spaces. Its fanless, rugged design—with a wide operating temperature range (-25°C to +50°C), 3 Grms vibration endurance, and IP42-rated protection, guarantees reliable and smooth operation under all conditions.
