In 2020, SenSen reconnected with DiGiCOR, a long-standing partner, to support their cutting-edge smart city project. SenSen required Jetson AGX Xavier devices embedded with NVIDIA GPUs to meet the rigorous demands of their initiatives.

SenSen’s smart city project demanded high-performance hardware to support complex tasks such as real-time number plate recognition, parking management, and driving distraction detection. In order to fulfill our client's specifications, a thorough analysis of their requirements was needed. This facilitated a comprehensive understanding of their needs, enabling us to deliver a tailored solution that precisely aligned with SenSen's business objectives.

To achieve this, Jetson AGX Xavier devices with the following specifications were needed:

• 32 GB RAM and diverse storage capacities for heavy data loads.
• Gigabit Ethernet for maintaining high frame rates and superior network performance.
• NVIDIA GPUs for rapid video processing and real-time analytics, critical for roadside number plate recognition. 

Each system needed to efficiently handle data from six to eight cameras while delivering reliable, real-time performance to meet the project's goals.

DiGiCOR supplied SenSen with 15 ADLINK RQX-580, an expandable ROS 2 robotic controller powered by NVIDIA® Jetson™ AGX Xavier series module. tailored to their specific requirements:

• Each device was equipped with NVIDIA GPUs to process video at 24 frames per second, enabling rapid data analysis and real-time number plate recognition.
• The robust configuration of 32 GB RAM and Gigabit Ethernet ensured seamless performance even under demanding conditions.

These systems played a pivotal role in several aspects of SenSen’s smart city project:

• Energy Conservation: Integrating streetlight sensors to reduce energy usage.
• Smart Traffic Management: Collaborating with government services to detect and penalise distracted drivers.
• Heavy Vehicle Monitoring: Supporting the National Heavy Vehicle Regulator with speed and number plate recognition.

The integration of ADLINK RQX-580 led to several significant achievements for SenSen's smart city project:

• Real-Time Efficiency: The systems enabled cameras to capture and process number plates in mere seconds, vastly improving operational speed and accuracy.
• Network Reliability: The hardware configuration maintained superior network thresholds, ensuring seamless performance for tasks like parking management and detecting driving distractions.
• Impactful Applications: Key contributions included energy conservation via streetlight sensors, enhanced traffic management in collaboration with government services, and advanced heavy vehicle monitoring for regulatory purposes.

SenSen was highly satisfied with DiGiCOR's support and praised the tailored solutions provided, reinforcing their long-standing partnership.

DiGiCOR's delivery of ADLINK RQX-580 devices equipped with NVIDIA GPUs was instrumental in the success of SenSen's smart city initiatives. By meeting the technical demands of real-time data processing and network performance, these systems enabled SenSen to effectively execute their project objectives. This collaboration not only strengthened the trust between SenSen and DiGiCOR but also highlighted DiGiCOR's commitment to delivering innovative, high-performance solutions aligned with client needs.

Founded in Melbourne, Australia, SenSen has evolved from a small company into an international enterprise over the past 15 years, employing over 200 people across Malaysia, Singapore, Canada, North America, and New Zealand. Their mission is to revolutionize the world using video technology and analytics, focusing on three core business areas:

• Casino Solutions: delivering large-scale data insights, including facial recognition for bet tracking and loyalty programs.
• Drive-Off Solutions: Preventing theft at petrol stations by identifying offenders.
• Smart City Initiatives: Managing parking operations, recognizing number plates, detecting driving distractions, and enhancing various retail services.