The challenge: Supply chain bottlenecks impacting our daily lives
A record number of container shipments are entering US ports as consumption continues to grow. U.S. ports, notably the Port of Los Angeles & Long Beach which accounts for 31% of all containerized international waterborne trade in the U.S., have faced several challenges in order to keep up with demand.
The ramifications of this have been a near unprecedented bottleneck at our ports, resulting in more than a 10x increase in the cost of shipping a container from China into Los Angeles, and the transit time growing from roughly seventy days pre-pandemic to well over a hundred.
The recently passed infrastructure bill will provide $17B to help modernize our port infrastructure. Deploying this capital on technology that will make an immediate impact, however, is challenging. Like any new technology, modernization efforts need to be interoperable with existing systems and processes.
Much of the incremental workload is falling upon two critical roles at the port: longshoremen and truck drivers. According to the California Maritime Association, it can take up to 8,000 trucks to unload a cargo ship.
With a record number of containers at ports, ensuring trucks and containers are at the right place at the right time for crane operators to quickly unload and load is critical. As traffic increases, the resulting port congestion creates an environment with higher risk of safety incidents, and makes it more difficult for ports to achieve their goals of reducing CO2 emissions.
A key part of the solution: Optimizing truck turnaround times and port crane operations
Using artificial intelligence (AI) and analytics to optimize the turnaround time of trucks being unloaded and loaded presents one of the best opportunities to improve the throughput of ports and implement enhanced worker safety insights required due to increased port congestion.
However, today’s ports run sophisticated processes and have substantial brownfield or legacy infrastructure. All digital transformation requires technologies that run both existing and new applications to be successful.
Both software and hardware infrastructure are critical to deploy in brownfield environments. By using a recent technology innovation from Microsoft called Azure IoT Edge for Linux on Windows (EFLOW), ports can keep both existing applications written primarily in Windows running and new AI services in Linux. This allows developers to run existing Windows applications with modern Linux and AI-based solutions.
Intel has contributed technology to enable developers to get access to integrated GPU hardware acceleration in EFLOW. This allows developers to use Intel® NUC Kits with 11th Generation Intel® Core™ processors to run multiple AI models and camera feeds by using an Intel® Video AI Box powered by the Intel® Distribution of OpenVINO™ Toolkit along with existing infrastructure.
With EFLOW and the Intel® Video AI Box, developers can now fast track deployment of AI models that calculate the turnaround time of trucks and rubber-tired gantry (RTG) cranes. Developers can also deploy models to enhance worker safety through trip wire sensor detection zones that notifying operators if workers are safely away from the crane to proceed with unloading.
By streaming that edge data to the cloud, developers can add advanced analytics in the Splunk Cloud Platform to look at turnaround times and track safety incidents across operators and terminals. Plus, users can calculate CO2 emissions from fuel consumption to allow port fleet managers to prioritize hybrid crane deployment.
The team: Arrow Electronics, Microsoft, Intel, Splunk, Strategic Maintenance Solutions, Scalers AI, and you
Deploying edge to cloud solutions on critical lines of business infrastructure requires a collaborative ecosystem. Without the innovations from Microsoft, Intel, Arrow Electronics, Splunk and Scalers AI, deploying the necessary technology today would not be possible due to previous cross-platform limitations.
Splunk’s Senior Director of Business Development Lerry Wilson, who is guiding the integration of these technologies says, "Ports are a critical part of our supply chain challenges today and we must offer secure digital solutions to modernize ports. With OpenVINO for AI and Splunk for analytics, we can enhance port efficiency, improve safety, and monitor and improve CO2 emissions."
Equally important is the knowhow to deploy leading edge technology in line of business. "Strategic Maintenance Solutions is thrilled to pair its deep industry knowledge and deployment capability with Intel, Splunk, and Scalers AI solutions to enhance the operational efficiency, increase worker safety insights, and track emissions from port operations", says Jason Oney President at Strategic Maintenance Solutions.
“System Integrators and OEMs want AI application platforms and support to deliver faster value. We are excited to support these solutions with the Microsoft EFLOW and Intel Distribution of OpenVINO Toolkit. Our global expertise in embedded software and hardware helps guide AI application innovation,” says Roland Ducote Supplier Programs Director at Arrow Electronics.
How to move forward: code and training at the Intel Vision Summit
Democratizing the technology for developers to deploy AI at the edge and transform industries is incredibly important to our mission. We are making the reference solution code available at the Intel Vision Summit, including training on how to scale this technology across public safety, retail, and industrial applications. This training and solution code will save hundreds of hours of development and fast track deployment of this critical technology.
Learn more about our edge and computer vision developer tools.
Joe Mayberry
GM, Intel IoTG