MiTAC’s MA1 Serves as the People-Monitoring Hub at this Year’s Paris Olympics
July 19, 2024
Blog
The Olympics have arrived in Paris. For most, that’s a cause for celebration. But if your task is to monitor the flow of people, say for transportation needs, you likely have your hands full. The authorities who run the Paris Metro believe they are up to the task of effectively controlling the flow of people in and out of each subway car during the Olympics using a people-flow monitoring system. Such a system provides real-time people flow guidance information.
Monitoring the number of people moving around the city is essential to ensure public safety, manage crowd control, and optimize all transportation systems. It helps prevent overcrowding, reducing the risk of accidents and enhancing emergency response. In addition, tracking movement supports efficient allocation of resources, such as security and medical services, and helps minimize disruptions to the city’s infrastructure. Effective monitoring also aids in maintaining the overall experience for both residents and visitors, ensuring smooth and secure operations during the large-scale event.
People monitoring in real-time is crucial for immediate response to dynamic situations. It ensures rapid identification and mitigation of safety risks, such as overcrowding or emergencies. Real-time data allows for quick adjustments in transportation and crowd management, enhancing flow and reducing congestion. It also supports real-time decision-making for resource allocation, ensuring timely deployment of security and medical personnel. Overall, real-time monitoring is vital to maintaining a safe, efficient, and enjoyable environment for attendees and residents during the large-scale event.
Complex Hardware and Software Needs
Real-time people monitoring in public transportation applications requires a sophisticated and integrated mix of hardware and software elements. For example, on the hardware side, it requires many high-resolution cameras and other various sensors, including infrared sensors and LiDAR systems to capture real-time data on passenger numbers and movement patterns.
Edge computers are needed to process data locally to reduce latency and enhance response times. A robust communications infrastructure must include some combination of Wi-Fi, 4G/5G networks, and IoT gateways to transmit data between the sensors, the Edge devices, and the central systems. Centralized servers and Cloud platforms would store and analyze the large volumes of data. That data is retained and can be used down the road.
On the software side of the ledger, the requirements would include data-processing algorithms and real-time analytics software to process the sensor data. This is needed to accurately track and predict crowd movements and densities. Machine-learning models can enhance the accuracy of predictions and provide anomaly detection. And of course, robust security is needed to ensure data privacy and protection against cyber threats.
AI to the Rescue
AI is one new, and potentially hugely effective, tool in the developer’s arsenal when it comes to people monitoring in transportation applications. In this configuration, AI would encompass a host of technologies, including computer vision, natural language processing, and machine learning algorithms.
By leveraging computer vision, AI can analyze video footage from cameras to detect and track individuals, recognize faces, and monitor activities in real-time. Natural language processing can help analyze communication patterns and detect potential threats or concerning behavior in written or spoken communication. And machine learning algorithms can identify unusual patterns or anomalies in behavior, enabling predictive analysis and proactive interventions. In addition, AI can help ensure compliance with safety protocols and regulations by monitoring and analyzing data continuously.
MiTAC’s MA1 Fits the Bill
MiTAC’s MA1 industrial and fanless Edge AI computer is well-suited for the described people-monitoring applications due to its integration with NVIDIA technology. The MA1 leverages NVIDIA's Jetson platform, which provides powerful AI capabilities on the Edge of the IoT. The NVIDIA Jetson modules are equipped with GPU-accelerated processing, enabling real-time video and image analysis. With a performance level of up to 100 TOPS/25 W, the MA1 can perform advanced computer vision tasks such as facial recognition, people counting, and behavior analysis with high accuracy and low latency. It operates just fine indoors or out, thanks to its wide operating temperature range, from -20°C to +60°C.
The MA1's use of NVIDIA's deep learning frameworks and pre-trained models enhances its ability to quickly deploy and adapt to various monitoring scenarios. The compact and energy-efficient design of the Jetson modules ensures that the MA1 can be deployed in diverse environments, from smart cities to transportation hubs, without requiring an extensive infrastructure. In addition, the robust software ecosystem provided by NVIDIA, including tools for training and deploying AI models, ensures that the MA1 remains scalable and up to date with the latest advancements in AI technology. This combination of hardware and software makes Mitac’s MA1 an effective and versatile solution for comprehensive people monitoring, including what’s needed for the Paris Olympics.
Other features of the MA1 include HDMI output for up to 4K resolution at 60 Hz, 2x RJ-45 1GbE LAN, 2x USB3.2 Gen2 Type A, 1x D-Sub9 RS-232 (four-wire), high-speed M.2 2280 PCIe x4 NVMe, and support for 5G/LTE and WiFi-6E.
While this case study highlighted the actions taking place at this year’s Olympic games, held in Paris, it’s easy to see how the same technology can be applied to myriad areas, both public and private, from malls to airports, to college campuses, and so on. Contact MiTAC to learn how the company’s embedded Edge computers can discuss your particular needs.
