SAN JOSÉ, Calif., Oct. 5, 2023 /PRNewswire/ — Today, Sony Semiconductor Solutions America (SSS-A), alongside the tinyML Foundation and The City of San José, announced the final winners for the Pedestrian Safety Challenge Hackathon competition, which began in May as an effort to reduce pedestrian-involved accidents, in connection with the city’s Vision Zero initiatives.

In collaboration, the three groups joined together to encourage teams across the globe to solve for this issue, as pedestrian injuries and fatalities have become more common with issues like distracted driving, distracted walking, illegally crossing roadways, and more.

The hackathon boasted 29 participating teams from across the globe, including the United States., Germany, Lebanon, Nigeria, and Saudi Arabia, as well as teams local to the Silicon Valley and the San Francisco Bay Area (SFBA).

Mark Hanson, Vice President and Head of Marketing for System Solution Business Development at SSS-A states, “It was a pleasure to partner with tinyML and the City of San José on the important issue of pedestrian safety, especially as a native resident and with Sony Electronics’ office in the city. The groundbreaking, people-first solutions coming from these teams makes us optimistic, not just in local Vision Zero efforts, but to see these technologies be used to benefit communities around the globe.”

First place was awarded to the Leopard Imaging team, presenting a solution that features SSS’s AITRIOS platform and IMX500-enabled hardware, with the NeurOHM team as second place, team from King Abdullah University of Science and Technology (KAUST) in third place, and special Edge Impulse award going to the KAUST team.

Evgeni Gousev, Senior Director at Qualcomm, and Chair of the Board of Directors at tinyML Foundation says, “As a global non-profit organization with a mission to accelerate development and adoption of energy-efficient, sustainable machine learning technologies, we were enthusiastic for this collaboration with the City of San José, Sony, and other partner companies. We were very pleased to see a strong response from the tinyML Community, are grateful to all the teams and participants who have contributed their ideas and proposals for this real-world problem and would like to congratulate the finalists on delivering innovative-yet-practical solutions.”

Hanson continues, “It was very exciting for us that Leopard Imaging entered with an AITRIOS-built solution and won first place in the Hackathon. It shows that vision AI tools, like AITRIOS, can make these Vision Zero and pedestrian safety goals a tangible, low-cost, and scale-based platform to support these initiatives.”

“Through our partnership with Sony and tinyML, brilliant minds from across the world have generated ideas that will ultimately save lives in San José and beyond,” said San José Mayor, Matt Mahan.

To learn more about the Pedestrian Safety Challenge and its winning solutions, please visit the tinyML Foundation website, here.

About Sony Semiconductor Solutions America

Sony Semiconductor Solutions America is part of Sony Semiconductor Solutions Group, today’s global leader in image sensors. We strive to provide advanced imaging technologies that bring greater convenience and joy to people’s lives. In addition, we also work to develop and bring to market new kinds of sensing technologies with the aim of offering various solutions that will take the visual and recognition capabilities of both humans and machines to greater heights. Visit us at: https://www.sony-semicon.co.jp/e/

Corporate slogan “Sense the Wonder”: https://www.sony-semicon.co.jp/e/company/vision

The post Sony Semiconductor Solutions Concludes Pedestrian Safety Challenge, Announces Winners with tinyML Foundation and The City of San José appeared first on Edge AI and Vision Alliance.

On the software front, DeGirum continues to prioritize user experience and adaptability. The company has launched a user-friendly Python SDK and will soon launch a JavaScript SDK. The upcoming SDK promises seamless real-time operations directly from browsers, a testament to DeGirum’s commitment to enhancing accessibility and ease-of-use for developers worldwide.

In the demo, Kudryavtsev showcases DeGirum’s JavaScript SDK executing Yolo-based face detection directly from the browser using a local AI accelerator. Concurrently, he demonstrates the company’s Python SDK running Yolo-based hand detection via the cloud. Both SDKs assist with the preprocessing and postprocessing tasks, as well as improving efficiency. And both implementations utilize local camera feeds and display real-time processing.

The post DeGirum Demonstration of Streaming Edge AI Development and Deployment appeared first on Edge AI and Vision Alliance.

The first demonstration is of people detection and tracking, performed on MediaTek’s Genio 500 SoC. As part of the demo, the camera captures an image and a person is detected using an objection detection AI network, followed by an OpenPose network which in realtime is able to overlay a skeletal representation of the person’s pose. The AI computation required for this demo is performed on MediaTek’s integrated APU (AI Processing Unit), which is comprised of 2x Tensilica Vision P6 DSPs. Additionally, a servo controlled articulating arm moves the camera to actively track the person’s movement.

The second demonstration is of a large image language model in an industrial camera, provided by Labforge.ca. Unlike typical LLM demos, this demo takes images and text prompts as input and provides a confidence level that the prompts match the captured image in realtime. The “Bottlenose” camera system features an SoC by Toshiba that integrates 4x Tensilica Vision P6 DSPs to help assist and accelerate the performance of today’s generative AI models. The Vision P6 DSP handles pre/post-processing, various CV/imaging algorithms, and multiple layers of the neural network.

The post Cadence Demonstrations of Generative AI and People Tracking at the Edge appeared first on Edge AI and Vision Alliance.

NXP’s new MCX N MCU, which includes the NXP-developed eIQ Neutron NPU, delivers an approximately 40x inference performance improvement when running a face detection demo NPU-accelerated versus solely on the CPU. Huereca then demonstrates a complete smart human-machine interface (HMI) solution based on the i.MX RT117H crossover MCU. This second demo showcases both facial recognition and voice detection running at the edge on a single device.

The post NXP Demonstration of AI Functions Implemented on Low-power MCX and RT Microcontrollers appeared first on Edge AI and Vision Alliance.

This latest processor from NXP Semiconductors, continuing the company’s long legacy of i.MX applications processors, features the Arm Ethos U65 NPU, which is showcased in a driver monitoring system demo. Pontikes demonstrates various facial recognition features, showing how the i.MX 93 SoC and its NPU can do complex classification tasks in real time.

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Offering a comprehensive solution for video infrastructure, this platform makes efficient use of small processors, thus making it an ideal edge-to-cloud tool. As embedded computing and artificial intelligence continue to reshape the industry, Odom explores in this demo how Network Optix is contributing to these pivotal developments in video technology. To find out more, visit www.networkoptix.com.

The post Network Optix Demonstration of Its Solution for Navigating the Video Infrastructure in the Era of AI appeared first on Edge AI and Vision Alliance.

Glance is powered by several computer vision algorithms, runs on Lattice Semiconductor FPGAs and SoCs, and targets smart edge devices. The AI-based computer vision algorithms enable use experiences around attention sensing, wellness, collaboration and human-machine interfaces (HMI). Glance is a production solution currently shipping in over 40 million devices.

The post Lattice Semiconductor Demonstration of Its Glance Software appeared first on Edge AI and Vision Alliance.

Driver monitoring systems are enabling safer cars and roads, and saving lives. Lattice Semiconductor has developed a state-of-the-art DMS system leveraging an IR sensor, which can be deployed on an FPGA, CPU, GPU or accelerator. The solution can detect parameters such as driver gaze, eye and mouth opening to infer distraction and fatigue.

The post Lattice Semiconductor Demonstration of an Advanced Driver Monitoring System appeared first on Edge AI and Vision Alliance.

The VMS leverages the Samurai Detect video analytics application developed by Hailo’s software partner, Art Of Logic, integrated with the NxWitness VMS platform from Hailo partner and fellow Edge AI and Vision Alliance Member company Network Optix, all running on a small, fanless RCS101 platform developed by Hailo’s hardware partner, Axiomtek. For more information, visit http://hailo.ai.

The post Hailo Demonstration of Art of Logic’s Video Management System appeared first on Edge AI and Vision Alliance.

Chilappagari demonstrates PYSDK’s ability to pipeline multiple machine learning models by showcasing a use case in which the output of one machine learning model is used to determine the input to the second machine learning model. The first model is a YOLOv5s-based person detection model which identifies all the people in each frame. The bounding boxes of people are then cropped and sent to a pose detection model which identifies multiple key points. DeGirum’s PySDK then combines all the information and renders the output.

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