Embedded Computing Design

One of the key aspects of Artificial Intelligence (AI) and Machine Learning (ML) applications is image processing and computer vision. With the rise in complexity and demand for AI and ML applications, it is important to develop efficient, cutting-edge tools for image processing and analytics of visual data.

With the massive demand for AI applications, the underlying hardware needs to be compatible with advanced software tools for optimal product development life-cycle. AndeSight V1.5 is one of the newest IDEs that enables users to efficiently develop embedded use cases for AI and much more.

With the rise of electric vehicles, there has been a demand in the industry to attain more efficient, environment-friendly technologies for EV batteries. A revolutionary platform, Sinanode meets the market requirements and provides a solution in a cost-effective way. 

Accelerating AI inference models has become an essential task as we progress towards creating more sophisticated and efficient AI applications. Flexibile and complete AI assistance are critical components for success in the fast-growing AI sector. 

In recent years, Deep Neural Networks have made significant advances in bringing the accuracy of computer vision algorithms to the next level. OpenVINO toolkit is one such example that enables the optimization of DNN models while providing high performance.

Emerging IoT technology contributes to the growth of OEMs in various sectors as it helps collect massive amounts of data from multiple sources. Although it is complex to collect, process, and analyze this load of data, the blend of AI with the help of IoT has the power to revamp the operation of industries, businesses and economies.

Working with AI models can be highly demanding in terms of computational resources — with more processing power comes greater power requirements. To solve this problem, Ceremorphic developed the ThreadArch multi-thread processor technology.

With every passing day, technical demands evolve, and so does the technology we use. Edge services and cloud computing have both improved significantly in the past few years with a wide range of functionalities. Combining both of these technologies offers great advantages. 

TP-Link recently announced a range of smart, secure home devices under the Tapo brand that includes HomeKit-enabled smart lights, plugs, smart switches, and a few more IoT-enabled consumer appliances.

IoT networks are prone to cyberattacks if not secured effectively. The QuarkLink IoT security management platform secures and enhances Macronix’s ArmorFlash Ecosystem with its most resilient and scalable IoT security approach.

The microcontroller development board is the core component of an embedded or IoT application, thus it becomes significantly important to choose the board before designing the application. As there were many launches of development boards in 2021, it may be a difficult decision to choose the one suitable for your target application. 

Amazon Web Services recently announced its IoT TwinMaker that optimizes the development of digital twins, making the complex process much faster and easier. AWS IoT allows developers to construct and use digital twins of real-world systems to monitor and optimize operations more quickly and easily.

Machine learning (ML) requires industry-standard performance benchmarks to aid in the creation and competitive assessment of the numerous ML-related software and hardware solutions.

RISC-V is known as an open-standard instruction set architecture (ISA) whose base instructions have been frozen to minimize complexity. But more recently it has added a wide range of custom extensions and enhancements that are making it increasingly popular amongst SoC designers building application-specific systems.

The progress in the field of OEM products comes at the cost of increasing complexities in the design and architecture of the systems. As the most trending feature contributing to this type of progress, Edge AI brings out the issue of compatible platforms for such dynamic development and designing. 

Radio communication is becoming extremely important for safety and emergency communication systems during situations like natural disasters and terrorist attacks. Interoperability problems are faced by military and civil safety officials as different aid agencies have radios working in different frequency bands, waveforms, and protocols. Additionally, these radios used need to be low cost, small size, portable and require low power to operate.

With the exponential rise in the popularity of embedded systems due to their compact size and efficient performance, the security of embedded systems has become a major concern.

With the development of 4G LTE networks along with the ramping up of 5G and Ethernet services, the industries are compelled to enhance the RAN transport and access architectures.

Overcoming the shortcomings of the current ethernet-based industrial networks, the CC-Link IE TSN, “Opens the Future of Connected Industries” by adding the advantages of Time-Sensitive Networking along with flexible implementation for various types of equipment.

Despite the precision in sensor technology, there is always a shortcoming associated with the performance of monitoring systems.