I O T & A I
RAVIRAJ IT TECHNOSYS PVT LTD ®
Computers | Peripherals | Licensed Software | Servers | Storage | Networking | Biometrics | Surveillance | IOT | Trunkey Projects Etc.
AN ISO 9001:2015 CERTIFIED COMPANY
Application
Existing Projects : Hardware lab for Colleges under-
-AICTE MODROB Scheme.
Hardware lab for University under-
-RUSA Scheme.
For Universities and Colleges
Infrastructure for Colleges against Modernisation And Removal of Obsolescence (MODROB)
Infrastructure for Universities against Rastriya Uchchatar Shiksha Abhiyan, A Centrally Sponsored Programme (RUSA)
Various other Central and State sponsored programs for Colleges & Universities towards Infrastructure Development Programme
Completely upgraded, re-engineered
Faster, more powerful
You'll recognise the price along with the basic shape and size, so you can simply drop your new Raspberry Pi into your old projects for an upgrade; and as always, we've kept all our software backwards-compatible, so what you create on a Raspberry Pi 4 will work on any older models you own too.
Specifications
Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz
2GB, 4GB or 8GB LPDDR4-3200 SDRAM (depending on model)
2.4 GHz and 5.0 GHz IEEE 802.11ac wireless, Bluetooth 5.0, BLE
Gigabit Ethernet
2 USB 3.0 ports; 2 USB 2.0 ports.
Raspberry Pi standard 40 pin GPIO header (fully backwards compatible with previous boards)
2 × micro-HDMI ports (up to 4kp60 supported)
2-lane MIPI DSI display port
2-lane MIPI CSI camera port
4-pole stereo audio and composite video port
H.265 (4kp60 decode), H264 (1080p60 decode, 1080p30 encode)
OpenGL ES 3.1, Vulkan 1.0
Micro-SD card slot for loading operating system and data storage
5V DC via USB-C connector (minimum 3A*)
5V DC via GPIO header (minimum 3A*)
Power over Ethernet (PoE) enabled (requires separate PoE HAT)
Operating temperature: 0 – 50 degrees C ambient
* A good quality 2.5A power supply can be used if downstream USB peripherals consume less than 500mA in total.
Waveshare HDMI Display
10.1" HDMI LCD (B) (with case),
1280×800 IPS Display
10.1inch Capacitive Touch Screen LCD (B), With Case And Toughened Glass Cover, 1280×800, HDMI, IPS Screen, Low Power Consumption
capacitive touch panel, 6H hardness
Supports popular mini PCs such as Raspberry Pi, BB Black, as well as
general desktop computers
When works with Raspberry Pi, supports
Raspbian/Ubuntu/Kali/Retropie/WIN10 IOT, driver free
When work as a computer monitor, supports Windows 10/8.1/8/7,
ten-points touch, and driver free
HDMI interface for displaying, USB interface for touch control
Supports 5-level backlight adjustment
The case
Material : high quality black Acrylic
Comes with back holder, 45° tilt angle
Features mounting holes for Raspberry Pi 3B+/3B/2B/B+/A+/B, BB
Black, Banana Pi
Developer Kit I/Os
Jetson AGX Xavier Module Interface
PCIe - X16 x8 PCIe Gen4/x8 SLVS-EC
RJ45 - Gigabit Ethernet
USB-C - 2x USB 3.1, DP (Optional), PD (Optional) Close-System Debug and Flashing Support on 1 Port
Camera Connector - (16x) CSI-2 Lanes
M.2 Key M - NVMe
M.2 Key E - PCIe x1 + USB 2.0 + UART (for Wi-Fi/LTE) / I2S / PCM
40-Pin Header - UART + SPI + CAN + I2C + I2S + DMIC + GPIOs
HD Audio Header - High Definition Audio
eSATAp + USB3.0 Type A - SATA Through PCIe x1 Bridge (PD + Data for 2.5-inch SATA) + USB 3.0
HDMI Type A - HDMI 2.0
uSD/UFS Card Socket - SD/UFS
GPU 512-core Volta GPU with Tensor Cores
CPU 8-core ARM v8.2 64-bit CPU, 8MB L2 + 4MB L3
Memory 32GB 256-Bit LPDDR4x | 137GB/s
Storage 32GB eMMC 5.1
DL Accelerator (2x) NVDLA Engines
Vision Accelerator 7-way VLIW Vision Processor
Encoder/Decoder (2x) 4Kp60 | HEVC/(2x) 4Kp60 | 12-Bit Support
Size 105 mm x 105 mm x 65 mm
Deployment Module (Jetson AGX Xavier)
Vision AI Development Kit
ELC MS VISION 500
SOC - QUALCOM QCS603
OS - YOCTO LINUX
BATTERY - 1550 mAh
CAMERA - 8 MP /4K UHD
MEMORY - 4GB LPDDR4x
BUILT-IN STORAGE - 16GB eMMC
MICROPHONE - 4 SEPERATE
WI-FI - QUALCOM WCN3980 (1X1)
802.11b/g/n 2.4 +5GHz
This Azure IoT Starter kit is a vision AI developer kit for running artificial intelligence models on devices at the intelligent edge. It is a reference design for IoT products like home monitoring cameras, enterprise security cameras and smart home devices with built-in vision AI.
The Vision AI Development Kit is certified to run with Microsoft Azure IoT, and is built around the Qualcomm Vision Intelligence 300 Platform and includes camera processing software, hardware-accelerated inferencing of AI models, and SDKs for machine learning and computer vision. Developers can use the kit to prototype products in applications like industrial safety, manufacturing, logistics, retail, and home and enterprise security.
Inside the kit, the Microsoft Azure IoT Edge runtime and the Qualcomm Neural Processing SDK for AI make it easy to take models trained in the cloud and run hardware-accelerated inference at the intelligent edge. The kit runs models built using Microsoft Azure Machine Learning (AML). It also runs other Azure services like Azure Stream Analytics, Azure Functions, Azure Cognitive Services and Azure SQL Server for edge analytics and AI processing.
With the Vision AI Development Kit, you can easily combine the Azure Machine Learning service from Microsoft and the edge computing power of the Vision Intelligence Platform from Qualcomm Technologies.
Qualcomm Vision Intelligence Platform + Microsoft Azure bring edge AI solution
This Azure IoT Starter kit is a vision AI developer kit for running artificial intelligence models on devices at the intelligent edge. It is a reference design for IoT products like home monitoring cameras, enterprise security cameras and smart home devices with built-in vision AI.
The Vision AI Development Kit is certified to run with Microsoft Azure IoT, and is built around the Qualcomm Vision Intelligence 300 Platform and includes camera processing software, hardware-accelerated inferencing of AI models, and SDKs for machine learning and computer vision. Developers can use the kit to prototype products in applications like industrial safety, manufacturing, logistics, retail, and home and enterprise security.
Inside the kit, the Microsoft Azure IoT Edge runtime and the Qualcomm Neural Processing SDK for AI make it easy to take models trained in the cloud and run hardware-accelerated inference at the intelligent edge. The kit runs models built using Microsoft Azure Machine Learning (AML). It also runs other Azure services like Azure Stream Analytics, Azure Functions, Azure Cognitive Services and Azure SQL Server for edge analytics and AI processing.
With the Vision AI Development Kit, you can easily combine the Azure Machine Learning service from Microsoft and the edge computing power of the Vision Intelligence Platform from Qualcomm Technologies.
Edge AI benefits for the IoT ecosystem
The Vision Intelligence Platform developer kit that includes both hardware and software, helps customers and developers innovate by unlocking the benefits of AI at the edge:
Low latency
Superior robustness
Privacy
Efficient utilization of network bandwidth
Efficient utilization of cloud resources
Azure benefits for the IoT ecosystem
Azure IoT Edge along with Azure ML will provide services for managing edge devices and allow developers to build ML solutions with access to pretrained models and customization of AI models
Cloud storage
Cloud processing
Enhanced security
Enhance device provisioning and management
Integrated environment to build, train, validate and deploy AI models on edge devices
Device telemetry and analytics
In particular, Qualcomm Technologies and Microsoft will be working in parallel to make sure the Snapdragon NPE interoperates with Azure services, so customers and developers can convert their models and deploy them to the Azure IoT Edge running on the Qualcomm Vision Intelligence Platform.