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November 6, 2019February 15, 2024 by Ayo Ayibiowu - 4 Comments

DepthAI Brings AI plus Depth to the Raspberry Pi (Crowdfunding)

Edge computing on the Raspberry PI has been a bit of ups and downs, especially with everyone gearing for AI in everything. The Raspberry Pi, on its own, isn’t really capable of any reliable AI applications. Typical object detection on the Raspberry Pi would get you something around 1 – 2 fps depending on the nature of your model and this because all those processing is done on the CPU. To address this poor performance of AI applications on the Raspberry Pi, AI Accelerators came to the rescue. The Intel Neural Compute Stick 2 is one such accelerator capable of somewhere around 8 – 15 fps depending on your application. The NCS2, which is based on the Myriad X VPU technology, offers so much more than the compute stick delivers, and this is something that the team behind DepthAI has exploited to create a powerful AI module for edge computing […]

November 5, 2019 by Stephen Vicinanza - No Comments

AuverCare is a Predictive AI 24/7 Monitor for Patients and Elderly

Information on the Internet for Monitoring Patients and Elderly If you are in the healthcare field or caring for an elderly or disabled person, you know all about trying to keep them safe. The internet is crowded with camera and audio monitors, wearable fall alert alarms, and the emergency services connected panic button. All these devices have one problem, they only work after there is a problem. What is Predictive AI? There has been a great deal of chatter since the 2016 announcement of a future predicting AI platform. The article reported on this platform was Predicting the Future – especially use cases such as falls by the elderly. With the advances in the field of AI and object recognition and behavior that is based on data gathered from a variety of sensors, it is not really a stretch to see a predictive healthcare monitor come onto the scene. Predictive […]

November 3, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

BOOTPRINT X2 96Boards AIoT Development Kit Features Sunrise 2.0 AI Processor

Horizon Robotics BOOTPRINT X2 is an AIoT / AI computing development kit providing a complete reference solution from device to cloud integration. The board is powered by the company’s Sunrise 2.0 AI edge processor based on the second-generation BPU (“Brain Processing Unit”) architecture that delivers up to 4 TOPS at low power consumption and is said to follow 96Boards specification, although from the photo below they’ve taken some liberties with the option (e.g. added a Gigabit Ethernet port). The board has now launched yet, and we have limited information about BOOTPRINT X2 kit specifications: SoC – Horizon Sunrise 2.0 AI edge processor with 4 TOPS equivalent AI processing power (no mention of architecture) System Memory – 1GB LPDDR4 RAM Storage – 4GB eMMC flash, MicroSD card socket Connectivity – Gigabit Ethernet Camera I/F – Dual 1080p camera inputs for symmetric binocular camera, combination of infrared and visible light. Audio – […]

October 29, 2019 by Jean-Luc Aufranc (CNXSoft) - 13 Comments

Lixil AI-based Toilet Analyzes Shape & Size of Feces with Camera and LEDs

Earlier this year, we wrote about machine learning & image processing in embedded systems using pasta type classification as an example. Lixil Group, a Japanese company manufacturing housing equipment, is working on a concept using similar technology, but instead of classifying pasta, they implemented the technology into an AI-based toilet that checks the shape and size of feces of people living in elderly facilities. Lixil’s toilet was unveiled at the 46th International Home Care & Rehabilitation Exhibition (HCR 2019) in Tokyo at the end of last month. The system relies on a camera and two LED’s placed on the back of the seat, which turn on when the user sits on the seat. Once the job is done, images of the feces are taken automatically and classified into seven categories as specified by the Bristol stool chart. Classification happens within a few seconds, and results can be check by staff […]

October 24, 2019 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

Orange Pi AI Stick Lite $20 Neural Compute Stick Ships with Free Training Tools

Shenzhen Xunlong Software launched Orange Pi AI Stick 2801 neural compute stick last year for $69. It was interesting as an alternative to Intel Neural Compute Stick. But once the documentation and SDK were released a few days later we discovered you could only run demos with the stick for that price, and the training tools would cost an extra $149. The excellent news is that the company has now launched an updated, yet similar Orange Pi AI Stick Lite for just $19.99, and best of all the PLAI training tools are now entirely free. Orange Pi AI Stick Lite specifications: ASIC – Gyrfalcon SPR2801S Lightspeeur series processor with 2-dimensional Matrix Processing Engine (MPE) with AI Processing in Memory (APiM) delivering up to 2.8TOPS @ 300mW, 5.6 TOPS @ 100 MHz (peak performance) Storage – eMMC 4.5 flash with 68 MB/s read, 84.69 MB/s write Host interface – USB 3.0/2.0 […]

October 23, 2019October 23, 2019 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Arm Introduces Ethos NPU Family, Mali-G57 GPU, and Mali-D37 Display Processor

Arm Ethos NPU: Ethos-M37, Ethos-N57 & Ethos-N77

Arm has just announced four new IP solutions with the most interesting being Ethos NPU (Neural Processing Unit) family with both Ethos-N57 and Ethos-N37 NPUs for mainstream devices, but the company also announced the new Arm Mali-G57, the first mainstream Valhall GPU, as well as Arm Mali-D37 DPU (Display Processing Unit) for full HD and 2K resolution. Arm Ethos NPU Family There are three members of the new Ethos family, and if you’ve never heard about Ethos-N77 previously, that’s because it was known as Arm ML processor. The three NPU’s cater to different AI workloads / price-point from 1 TOPS to 4 TOPS: Ethos-N37 Optimized for 1 TOP/s ML performance range 512 8×8 MAC/cycle 512KB internal memory Small footprint (<1mm2) For smart cameras, entry smartphones, DTV Ethos-N57 Optimized for 2 TOP/s ML performance range 1024 8×8 MAC/cycle 512KB internal memory For mainstream smartphones, smart home hubs Ethos-N77 Up to 4 […]

October 21, 2019September 2, 2020 by Stephen Vicinanza - No Comments

AAEON M.2 and mPCIe Cards for AIoT Acceleration Run Kneron KL520 AI SoC

The AAEON announcement of its AI Acceleration M.2 and mini-PCIe cards AAEON uses Kneron KL520 AI SoC dual Cortex-M4 on a series of new modules that are accelerating AI edge computing and that only need 0.5 Watt of power. The modules are M.2 and mini-PCIe AI acceleration cards, that offer a new way to come at AI acceleration. What AI Features are Enhanced The cards are meant to enhance and accelerate AI functions, like gesture detection, facial and object recognition, driver behavior in such AIoT areas as access control, automation, and security. History of the AAEON Development Previously AAEON has been offering the M.2 and mini-PCIe AI core modules for the Boxer computers that are based on the Intel Movidius Myriad 2 and Myriad X Vision Processing Units (VPU). Reporting was done on these previous releases in the articles on the UP AI core mini-PCIe card and the AI Core […]

October 11, 2019October 11, 2019 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Intrinsyc Unveils Open-Q 845 µSOM and Snapdragon 845 Mini-ITX Development Kit

Intrinsyc introduced the first Qualcomm Snapdragon 845 hardware development platform last year with its Open-Q 845 HDK designed for OEMs and device makers. But the company has now just announced a solution for embedded systems and Internet of Things (IoT) products with Open-Q 845 micro system-on-module (µSOM) powered by the Snapdragon 845 octa-core processor, as well as a complete development kit featuring the module and a Mini-ITX baseboard. Open-Q845 µSOM Specifications: SoC – Qualcomm Snapdragon SDA845 octa-core processor with 4x Kryo 385 Gold cores @ 2.649GHz + 4x Kryo 385 Silver low-power cores @ 1.766GHz cores, Hexagon 685 DSP, Adreno 630 GPU with OpenGL ES 3.2 + AEP (Android Extension Pack), DX next, Vulkan 2, OpenCL 2.0 full profile System Memory – 4GB or 6GB dual-channel high-speed LPDDR4X SDRAM at 1866MHz Storage – 32GB or 64GB UFS Flash Storage Connectivity Wi-Fi 5 802.11a/b/g/n/ac 2.4/5Ghz 2×2 MU-MIMO (WCN3990) with 5 GHz […]