High-speed networking enables fast data transfer in industrial computing, crucial for real-time operations, efficiency, safety, and predictive maintenance, evolving significantly over the past 30 years.
High Performance Embedded Computing (HPEC) integrates high-performance computing with embedded systems for real-time processing in rugged environments, enhancing industries like defense, aerospace, and medical imaging.
BVM ensures 24/7 reliability in mission-critical systems through rigorous testing, including burn-in, thermal, vibration, and power cycling evaluations, tailored to specific application needs.
This article compares Pelicase PCs and rugged laptops, highlighting their distinct features, performance capabilities, and suitable applications for demanding field conditions and operational needs.
Industrial computing demands reliability through rugged design and certified components. This guide outlines crucial features, standards, and technologies essential for efficient, secure industrial systems.
Industrial computers face common failure points, including cooling systems, hard drives, power supplies, environmental exposure, aging components, connectors, and software instability. Preventative maintenance is essential.
MTBF, or Mean Time Between Failures, indicates the reliability of industrial systems, influencing purchasing decisions by reducing downtime, maintenance costs, and enhancing durability in critical environments.
The article compares virtual machines and multiple physical systems for industrial applications, highlighting their advantages, disadvantages, and real-world use cases across various sectors.
M2M communication is crucial for IoT, enabling autonomous device interaction. Time-Sensitive Networking (TSN) ensures timely data delivery, enhancing industrial automation and real-time performance in systems.
Intel TCC technology enhances edge computing by enabling real-time performance through determinism and precision, essential for industries like aviation, healthcare, and automation.
The article compares NVIDIA’s RTX, Jetson AGX, and DGX platforms for AI applications, highlighting their distinct strengths, weaknesses, and ideal industrial use cases.
This guide details selecting industrial motherboards and SBC form factors, emphasizing reliability, I/O requirements, environmental resilience, and application-specific constraints for optimal system design.
Generative AI and LLMs are set to enhance embedded systems, transforming them into smart, adaptive devices while addressing challenges in resource constraints, power consumption, and real-time needs.
AI is transforming DNA sequencing, enhancing speed and accuracy. GPUs are preferred for AI applications due to their efficiency in processing genetic data compared to CPUs.
Time-Sensitive Networking (TSN) enhances Ethernet for real-time communication, offering benefits like determinism and interoperability across industries.
