June 2020
eInfochips collaborates with EchoNous Inc. to develop the recently FDA-cleared KOSMOS platform
The collaboration has enabled the creation of the world’s first AI-on-the-Edge ultrasound-based tool combined with deep learning for clinical assessment of the heart, lungs and abdomen. The eInfochips team has leveraged Qualcomm and Microsoft partnerships to create this integrated device-to-cloud solution. Read More
Case Study: Handheld Imaging Laser Scanner
A European client wanted to develop a lightweight handheld imaging laser scanner that recreates spaces in 3D. It was based on SLAM (Simultaneous Localization and Mapping) technology which is a combination of high-speed dual axis LiDAR, multi-camera vision system, and an inertial measurement unit. eInfochips, leveraging its strong experience on latest Qualcomm® Snapdragon™ platforms and SDKs, proposed a solution based on Snapdragon™ 820 with complete ownership of hardware design, firmware development of the product. Read More
5G Drones – Eye In The Sky – Helping To Fight Against COVID-19
For ‘Drone-as-a-Service’ companies, COVID-19 has presented unprecedented use cases, to showcase what autonomous drones are capable of, especially to meet the needs of medical supply and food deliveries. Let’s see how 5G technology and virus-fighting drones have helped to keep the lights on when they’re the needed most. Read More
eInfochips extends Eragon portfolio - Eragon 865 HDK is now available for Order.
Based on Qualcomm® Snapdragon™ 865 processor, the HDK offers intelligent on-device AI, 2-gigapixel-per-second camera speeds, and high-end graphics at low power consumption. This feature-rich Android 10 development platform is an ideal starting point to kick-start development of embedded devices for Gaming, AR/VR, infotainment, 4K cameras as well as automation solutions. The kit features Qualcomm® Snapdragon Elite Gaming™, Qualcomm® Sensing Hub Qualcomm® Artificial Intelligence Engine, Qualcomm® aptX™ Adaptive Audio and Qualcomm Aqstic™ Audio Technologies. Read More
Case Study: Handheld Auto-Checkout Device for the Retail Industry
The client, one of the top retailers based in the United States, wanted to develop a second generation of their portable scanner with advanced features like Zigbee, audio, and touchscreen display. eInfochips took the ownership from design to GMS certification and came up with Qualcomm® Snapdragon™ 660-based solution package to reduce the checkout time. Read More
COVID19 – Social Distancing Monitoring with Artificial Intelligence on NVIDIA Jetson based IoT Gateway & Microsoft Azure
In today’s era of a global pandemic, businesses, customers, and governments are determined to take the necessary measures to reduce the risk of COVID-19. The only way to go back to normal is by religiously following the rules of social distancing. This blog discusses how artificial intelligence on NVIDIA Jetson based IoT gateway and Microsoft Azure can help in social distancing monitoring. Read More
eInfochips Exhibited and Presented at Design & Reuse IP-SoC Silicon Valley 2020
The penetration of service robots has been growing rapidly across industry segments including healthcare, cleaning, inspection & maintenance, agriculture, retail, logistics, manufacturing, & so on. Need for automation, rise in funding for robots & AI, high labor costs are some of the key drivers for the growth of service robots. Read More
Building a Secure Edge in Manufacturing
Transforming legacy industrial manufacturing assets to digitally enabled connected assets requires a holistic, flexible solution that supports a complex edge configuration. The complexity manifests in service level and application platform configurations, field device communication standards and hardware rooted secure access to data and resources across architecture components. Managing these complexities at scale, at low cost, and with seamless enterprise application integration drives the business case for enterprise wide implementation of asset technology. Read More
NLP Text Pre-Processing: Text Vectorization
For Natural Language Processing (NLP) to work, it always requires to transform natural language (text and audio) into numerical form. Text vectorization techniques namely Bag of Words and tf-idf vectorization, which are very popular choices for traditional machine learning algorithms can help in converting text to numeric feature vectors. Read More
