Reolink Argus PT Ultra review – A solar powered 4K WiFi Pan-and-Tilt smart security camera

Reolink Argus PT Ultra Solar Panel Instllation

Nearly four years ago, I reviewed the solar-powered Reolink Argus PT pan-and-tilt security camera. The device worked (and still works) mostly fine, but it was at a time when security cameras did not implement AI features like people and vehicle detection just yet relying only on PIR motion sensors so I’d get plenty of false positives. The WiFi connection is not overly reliable either especially when I tried to access the camera from outside my house, something that does not happen with the PoE and 4G LTE models from the company. Reolink asked me whether I wanted to review the new Reolink Argus PT Ultra security camera with higher 4K resolution, dual-band WiFi support, as well as people, vehicle, and pet detection, and most of the same other features found on the older Argus PT. So I took up on the offer and I’ve used it for about one month […]

SunFounder PiCar-X 2.0 review – A Raspberry Pi 4 AI robot car programmable with Blockly or Python

SunFounder PICAR-X Robot review

SunFounder PiCar-X 2.0 is an AI-powered self-driving robot car using the Raspberry Pi 3/4 as the main processing board. It is equipped with a camera module that can be moved by a 2-axis servo motor, allowing the camera to pan or tilt, an ultrasonic module for detecting distant objects, and a line detection module. The PiCar-X robot can also perform computer vision tasks such as color detection, face detection, traffic signs detection, automatic obstacle avoidance, and automatic line tracking. The PiCar-X can be programmed with two computer languages: Blockly-based Ezblock Studio drag-and-drop program and Python, and the robot works with OpenCV computer vision library and TensorFlow for AI workloads. Finally, you can also control the robot through the SunFounder controller application on your mobile phone. The company sent us a sample of the Picar-X 2.0 for review, so let’s get started. SunFounder PiCar-X 2.0 robot overview The PiCar-X robot kit […]

AMD Ryzen Embedded 7000 Zen 4 SoC integrates Radeon RDNA 2 graphics, up to 28 lanes of PCIe 5 connectivity

AMD Ryzen Embedded 7000

AMD Ryzen Embedded 7000 Series is a new “Zen 4” processor with integrated Radeon RDNA 2 graphics designed for high-performance embedded systems targetting industrial automation, machine vision, robotics, and edge servers. The last two Ryzen Embedded families from AMD, namely the Ryzen Embedded V3000 and Ryzen Embedded 5000, mostly targeted headless networking and storage applications since the processors lacked any 3D GPU. But the new Ryzen Embedded 7000 processors bring back graphics with a Radeon RDNA 2 GPU clocked at up to 2.2 GHz and also come with up to 12 Zen4 cores clocked at up to 5.4 GHz, and feature up to 28 lanes of PCIe 5 connectivity. Ryzen Embedded 7000 Series specifications: CPU – Up to 12-core/24-thread “Zen 4” processor GPU – Radeon RDNA 2 graphics 1WGP @ 2.2GHz max with support for AV1/VP9 decode, H.264/HEVC decode/cncode Cache – Up to 1MB L2 cache/Core, up to 32MB L3 […]

TRACEPaw sensorized paw helps legged robots “feel the floor” with Arduino Nicla Vision

TRACEPaw

Our four-legged friends don’t walk on tarmac the same way as they do on ice or sand as they can see and feel the floor with their eyes and nerve endings and adapt accordingly. The TRACEPaw open-source project, which stands for “Terrain Recognition And Contact force Estimation through Sensorized Legged Robot Paw“, aims to bring the same capabilities to legged robots. Autonomous Robots Lab achieves this through the Arduino Nicla Vision board leveraging its camera and microphone to run machine learning models on the STM32H7 Cortex-M7 microcontroller in order to determine the type of terrain and estimate the force exercized on the leg. But the camera is apparently not used to look at the terrain, but instead, at the deformation of the silicone hemisphere – made of “Dragon Skin” – at the end of the leg to estimate 3D force vectors, while the microphone is used to recognize terrain types […]

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