AI Inferencing Solutions for Smart City Environments
Proven performance in Smart City Environments
The most progressive industrial companies in the world are implementing AI inferencing technologies to deploy large-scale initiatives. GPU-accelerated computing enables AI at industrial scale, letting you take advantage of unprecedented amounts of sensor and operational data to optimise operations, improve time-to-insight, and reduce costs.
Faster Response Time
The ability to process and analyse data in real time provides the opportunity to improve operational efficiency, resource allocation and disaster response.
Secure Deployment and Scalability
Deploy AI from the edge to the cloud with a scalable range of appliances from the NVIDIA range handling a city’s traffic cameras to a network of servers comprising a micro datacentre.
Using AI powered video analytics from sensors across a city-wide landscape it is possible to capture and classify objects such as vehicles, cyclists and pedestrians, and identify interactions in near real time, providing city officials with a 24/7 data stream of everything from illegal turns on red lights to pedestrian movement outside of designated crosswalks to parking space metrics. The ability to identify speeding vehicles, cyclist movements and pattern and times at which these occur, it can be used for predictive analytics in order to make busy traffic junctions safer, plan where new cycle lanes or pedestrian crossings are needed.
Industrial areas on the outskirts of large cities often contribute volumes of traffic entering already crowded streets. Using AI analytics allows far greater insight into freight tracking and route optimisation through an urban area to the motorways. This not only provides data on potential fuel cost savings and delivery delays, but may also help forecast risk mitigation by understanding where lorries are parked overnight or left unattended.
Sensors at all entry points into a city environment offer the opportunity to optimise traffic light timing to keep traffic running better with less chance of gridlock and bottlenecks forming. Furthermore, the better a city’s bus services run not only leads to efficiency and cost savings, but also increases the likelihood of residents opting to use them instead of cars – reducing environmental impact and leading to quieter roads.
AI Inferencing Solutions
Scan has partnered with Advantech and NVIDIA to bring to market a range of AI Edge Solutions for inferencing – the MIC series. Powered by the NVIDIA Jetson GPU series, these provide the performance of a GPU workstation in an embedded module. Featuring strict validation ensure thermal, mechanical, and electrical compatibility, plus industrial-grade anti-vibration, high temperature operation capabilities, and modular, compact-sized design, these are the perfect hardware platforms for medical imaging, microscope analysis and automated diagnostic applications.
The range includes various models designed for specific environments and tailored for particular inferencing workloads. Many are modular allowing expansion through the i-Module expansion chassis or the i-Door interface to add PCI slots, extra connectivity or control modules.
Network Video Recording (NVR) Solutions
NVIDIA Jetson Xavier NanoLearn more
NVIDIA Jetson Xavier NXLearn more
NVIDIA Jetson Xavier AGXLearn more
Edge AI Solutions
Learn more about the usage of AI and computer technologies to enhance IT infrastructure in this presentation by CEO of Scan Computers, Elan Raja, at the Advantech IIoT Virtual Summit. Skip to 1:01:28 in the video to view Elans presentation