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Detail photo of a stick figure created by the prototype of the PrivacyLens in the Interactive Sensing and Computing Lab at the Bob and Betty Beyster Building on Tuesday, July 9, 2024. The camera begins by recording an image of a person, but only sends out a stick figure. These key point stick figures protect privacy while allowing devices to track the location and movement of people.
This phototype camera, called PrivacyLens, was designed by Yasha Iravantchi, a doctoral student of computer science and engineering, and Alanson Sample, an associate professor of computer science and engineering, to protect people's privacy in devices that use cameras for sensing. Such devices, including roombas, automated vehicles, and home assistant technologies, such as Alexa, use cameras to avoid collisions or monitor health, fitness, and activity in the home. Those same cameras increase the risk of sensitive, personal information leaking on the internet. PrivacyLens replaces humans with stick figures in the recorded images, so that the devices can register that people are present without putting an individual's privacy at risk.
Photo: Brenda Ahearn/University of Michigan, College of Engineering, Communications and Marketing
Detail photo of a stick figure created by the prototype of the PrivacyLens in the Interactive Sensing and Computing Lab at the Bob and Betty Beyster Building on Tuesday, July 9, 2024. The camera begins by recording an image of a person, but only sends out a stick figure. These key point stick figures protect privacy while allowing devices to track the location and movement of people.
This phototype camera, called PrivacyLens, was designed by Yasha Iravantchi, a doctoral student of computer science and engineering, and Alanson Sample, an associate professor of computer science and engineering, to protect people's privacy in devices that use cameras for sensing. Such devices, including roombas, automated vehicles, and home assistant technologies, such as Alexa, use cameras to avoid collisions or monitor health, fitness, and activity in the home. Those same cameras increase the risk of sensitive, personal information leaking on the internet. PrivacyLens replaces humans with stick figures in the recorded images, so that the devices can register that people are present without putting an individual's privacy at risk.
Photo: Brenda Ahearn/University of Michigan, College of Engineering, Communications and Marketing
Yasha Iravantchi, a PhD student in Computer Science and Engineering, holds the cover of the PrivacyLens prototype as he explains how the system works. In the background fellow PhD student Yang-Hsi Su is testing the system by making exaggerated movements to see how well the PrivacyLens adapts to his motions.
This phototype camera, called PrivacyLens, was designed by Yasha Iravantchi, a doctoral student of computer science and engineering, and Alanson Sample, an associate professor of computer science and engineering, to protect people's privacy in devices that use cameras for sensing. Such devices, including roombas, automated vehicles, and home assistant technologies, such as Alexa, use cameras to avoid collisions or monitor health, fitness, and activity in the home. Those same cameras increase the risk of sensitive, personal information leaking on the internet. PrivacyLens replaces humans with stick figures in the recorded images, so that the devices can register that people are present without putting an individual's privacy at risk.
Photo: Brenda Ahearn/University of Michigan, College of Engineering, Communications and Marketing
The number of digital purchasers grows every year as internet availability and usage snowballs worldwide. As a result, the demand for online services increases, and the requirement for warehouses and logistics grows exponentially.
Furthermore, numerous warehouses and order fulfillment centers rush to deliver items promptly due to the high volume of online purchases resulting in rising storage prices that force warehouse owners to look for innovative ways to make the most of their valuable real estate. Simultaneously, dimensional weight (DIM) pricing pushes the same businesses to cut package sizes and shipping costs.
Understanding this, VisAI Labs has built a vMeasure range of AI-led automated dimensioning solutions to calibrate the dimensional information of small, medium, and large-sized parcels and packages in a jiff with high-level precision.
Click here to know more about vMeasure automated dimensioners: vmeasure.ai/