Digital displays and signs are all around you. You may have seen them cropping up at shopping centers and doctors’ offices. From video walls, to AR fitting mirrors, to ordering menus, digital signs are pervasive and are becoming a part of everyday shopping experience.
It is common wisdom that in order to understand complicated things, we need to break them down into smaller parts. If you want to understand complex security systems, you first need to have a good grasp on the basic security concepts, so let's begin from the start...
Digital displays and signs are all around you. You may have seen them cropping up at shopping centers and doctors’ offices. From video walls, to AR fitting mirrors, to ordering menus, digital signs are pervasive and are becoming a part of everyday shopping experience.
It is common wisdom that in order to understand complicated things, we need to break them down into smaller parts. If you want to understand complex security systems, you first need to have a good grasp on the basic security concepts, so let's begin from the start...
Digital displays and signs are all around you. You may have seen them cropping up at shopping centers and doctors’ offices. From video walls, to AR fitting mirrors, to ordering menus, digital signs are pervasive and are becoming a part of everyday shopping experience.
It is common wisdom that in order to understand complicated things, we need to break them down into smaller parts. If you want to understand complex security systems, you first need to have a good grasp on the basic security concepts, so let's begin from the start...
This article takes a look at a variety of tools available from Intel: Intel® Movidius™ Neural Compute Stick, Intel® Python Distribution for Python™, Intel® Math Kernel DNN Library, Intel® Data Analytics Acceleration Library, Intel Distribution of OpenVINO™ Toolkit
This paper introduces Intel software tools recently made available to accelerate deep learning inference in edge devices (such as smart cameras, robotics, autonomous vehicles, etc.) incorporating Intel® Processor Graphics solutions across the spectrum of Intel SOCs.
In this blog post, we highlight one particular class of low precision networks named binarized neural networks (BNNs), the fundamental concepts underlying this class, and introduce a Neon CPU and GPU implementation.
This access control system application is part of a series of how-to Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit and a compatible Intel-based platform, cloud platforms, APIs, and other technologies.
This access control system application is part of a series of how-to Intel® Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
This air quality monitor application is part of a series of how-to Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
We cover feature comparison, design considerations and then a comparison of the Intel® Joule™ Developer Kit with the latest IoT developer kit from Intel (UP Squared Grove Development Kit).
This article presents one approach to increase the quality of rotation information gathered from different sensor sources using a simple sensor fusion algorithm, specifically on an Android device.
In this article, we'll demonstrate building an Arm NN-based application for an IoT device that can perform automatic trash sorting through image analysis.
This tutorial shows you how to use the Qsys system integration tool to create a custom Field Programmable Gate Array (FPGA) hardware design using IP available in the Intel® FPGA IP library.
This paper demonstrates a special version of Caffe — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Data from the Terasic DE10-Nano's built-in 3-axis accelerometer is measured on ALL 3 axes to show when the board is in motion. The raw output of the accelerometer is converted to g-force values by a sensor library and then sent to graphing software for data visualization and interpretation.
This close-call fleet driving reporter application is part of a series of how-to Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
Are you excited to get your Myo armband from Thalmic Labs? If you're a C# developer, then check out this open source library to help you control your Myo! The post appeared first on http://www.DevLeader.ca.
The main objective of this project is to develop an Android Application that uses a built-in camera to capture the objects on a road and use a Machine Learning model to get the prediction and location of the respective objects.
The main objective of this project is to develop a Machine Learning model that detects the objects on the road like pedestrians, cars, motorbikes, bicycles, buses, etc.
This tutorial shows you how to use the System Console debugging tool to program a compiled FPGA design into an FPGA device, then access the hardware modules (i.e. peripherals) that are instantiated in that FPGA design.
In this article we’re going to build a fully functional MNIST handwriting recognition app using TensorFlow Lite to run our AI inference on a low-power STMicroelectronics microcontroller using an Arm Cortex M7-based processor
Diamanti’s plug-and-play, high-performance bare-metal platform makes it seamless to deploy and upgrade your containerized applications on a Kubernetes cluster. This article shows how quickly you can use Diamanti to deploy a WordPress application powered by MariaDB and Kubernetes.
This article will go over setting up an Intel Distribution of OpenVINO toolkit module in Azure and explore the considerations for running multiple modules on CPU and GPU on the IEI Tank AIoT Developer Kit.
This paper will go over some of the features and capabilities of Intel® AMT as well as an overview of the configuration and manageability tools available.
In this article, our focus will be installing Actian Zen Edge Server for IoT on an ARM-based Raspberry Pi running the Windows IoT Core operating system, capturing some simple time series data, writing it to the Zen database and retrieving data from the database.
This article describes how to use the .NET System.Management WMI (Windows Management Instrumentation) wrappers to enumerate and describe USB disk drives. It also includes a non-Interop solution for detecting drive state changes as they come online or go offline.
This tutorial will discuss four different methods for controlling the LEDs using the command line, memory mapped IO, schematic, and Verilog HDL to the field-programmable gate array of the Cyclone V device.
By using the Firebase ML Kit, developers save small companies and individuals massive amounts of time and money that would otherwise be spent on making their own ML Model.
This smart fire alarm application is part of a series of how-to Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
This section describes implementation of FaaS inference samples (based on Python 2.7) using Amazon Web Services (AWS) Greengrass and AWS Lambda software.
In this part, I will discuss some more concrete examples about how we apply simulation to enable small batches, early adjustment, and better efficiency in hardware and system design.
Use a Microsoft Kinect to control the home automation in the house. Lights can be turned on an off from speech recognition or from pointing at them and waving your other hand one way to turn on and the other way to turn off.
Several open source projects that are being integrated into open source Lustre are designed to improve reliability, flexibility, and performance, align the enterprise-grade features built into ZFS with Lustre, and enhance functionality that eases Lustre deployments on ZFS.
This tutorial shows you how to incorporate a digital signature algorithm (DSA) and key agreement protocol (KAP) into the programmable FPGA fabric and HPS of the Cyclone® V SoC FPGA device on a DE10-Nano board.
This article provides a list of industrial sensors currently supported by the UPM library, as well as information about supported communications protocols.
Traditioanlly, Roofline charts have been built by hand, but Intel Advisor will build these charts for you. Roofline charts show you where your bottlenecks are, and why those bottlenecks are happening.
In this article, we can see how to debug and check the exception error in Android Linux Kernel in Intel ® Architecture-based system with Intel ® JTAG Debugger which is a part of tool Intel System Studio ® Ultimate Edition
The Intel® Computer Vision SDK is a new software development package for development and optimization of computer vision and image processing pipelines for Intel System-on-Chips (SoCs).
This tutorial shows you how to create the hardware equivalent of “Hello World”: a blinking LED. This is a simple exercise to get you started using the Intel® Quartus® Prime Software Lite edition software for FPGA development.
In this use case tutorial we'll use an Intel® NUC and Intel® IoT Gateway Developer Hub to interface an industrial fluid/gas pressure sensor to AWS IoT running in the Amazon Web Services Cloud.
This blog will go through the high level features of the Intel® Atom™ x3 platform, especially the features which mobile app developers are interested in.
The Face Access Control application is one of a series of IoT reference implementations aimed at instructing users on how to develop a working solution for a particular problem.
A graph is a good way to represent a set of objects and the relations between them. Graph analytics is the set of techniques to extract information from connections between entities.
The new Intel® Xeon Phi™ processor (code-named Knights Landing, or KNL) is Intel’s first processor to deliver the performance of an accelerator with the benefits you’ve come to expect from a standard CPU
Novosibirsk State University boosts a simulation tool’s performance by 3X with Intel® Parallel Studio, Intel® Advisor, and Intel® Trace Analyzer and Collector
Nervana is currently developing the Nervana Engine, an application specific integrated circuit (ASIC) that is custom-designed and optimized for deep learning.
Fast image inversion forms a good basis for optimizing pixel wise operations. We will discuss the ways to achieve the best speed on this inversion operator.
The Intel® Computer Vision SDK is an Intel-optimized and accelerated computer vision software development kit based on the OpenVX standard. The SDK integrates pre-built OpenCV with deep learning support using an included Deep Learning (DL) Deployment toolkit.
Here we utilize the OpenCV libraries and apply the Histograms of Oriented Gradients (HOG) algorithm to create a computer vision application for people detection/counting.
This automatic plant lighting system monitor application is part of a series of how-tos for Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
This Plant Lighting System application is part of a series of how-to Intel® Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
Where as public cloud is amorphous with nigh-limitless resource pools, private cloud is more like slapping a perfectly formed organizer on your resources.
Explore performance analysis options provided by the Intel® VTune Amplifier for Python applications to identify the most time-consuming code sections and critical call paths.
This paper provides introductory information, links and resources for operating an IEI Tank with the Intel® Distribution of OpenVINO™ toolkit for Linux with FPGA support.
This article is for developers who’d like to learn more about the Terasic self-balancing robot, understand how it was designed, and explore some of the architectural decisions that were made.
This is a simple application for creating the serial number based on HDD hardware code. It has 3 necessary part of serial number application(Request Code, Getting Serial Number and Confirming that)
This smart stove top application is part of a series of how-tos for Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, Intel® IoT Gateway, cloud platforms, APIs, and other technologies.
This storage unit flood detector application is part of a series of how-to Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit and a compatible Intel-based platform, cloud platforms, APIs, and other technologies.
TotalView includes a set of tools that provide scientific and academic developers with controlover processes and thread execution, along with deep visibility into program states and data.
This blog covers some Tips and Tricks on memory optimization and working with textures and was compiled by Steve Hughes who works as an Applications Engineer for Visual Computing at Intel.
This article presents a commercial-grade cross-platform Harel UML StateChart Open-Source application framework named StateWizard for concurrent, distributed, and real-time reactive system development with simplicity, efficiency, and scalability.
With edge computing, you can avoid transferring raw data by carrying out data cleaning, aggregation and analysis on the device itself, and then send the insights gained to the cloud.
The Alibaba Cloud advantage is not simply confined to one or two features. It's there for your developers across the full range of Alibaba Cloud's products, starting with Alibaba Elastic Compute Service (ECS) itself, and including database, storage, Big Data, and multimedia services.
