Born in the ‘80s, the CAN bus helps in carrying reliable electronic communication within your vehicles. This article delves into the basic principles, architecture, protocols, applications, and limitations of the CAN bus.
Tagged with
embedded systems
Latest Posts
Audio event detection functions can listen for distinct sounds or patterns embedded within an audio stream. It uses advanced signal processing and machine learning algorithms to accurately identify and classify sound events in real-time, with no internet connectivity required.
Sensor fusion enables the seamless integration of data from multiple sensors, paving the way for advanced Edge AI implementations that optimize real-time processing, enhance decision-making, and boost system responsiveness in dynamic environments.
A Comprehensive Introduction to Flying Probe Test, its Essential Components, Advantages, Limitations, and Application Cases
In the rapidly evolving landscape of IoT, battery life is paramount for device sustainability. We dissect the challenges and strategies for battery longevity of LPWAN IoT devices. Explore battery profiling and optimization for extended device life and reduced costs.
Low-power computer vision provides a new opportunity to gain a practical understanding of the world through data collection and vision in remote areas.
In the ever-evolving world of processor architectures, the showdown between RISC-V and ARM sparks fervent competition. With their distinct histories, these two giants are redefining computing power and igniting discussions on openness, customization, and innovation in microprocessors.
Article #4 of Spotlight on Innovations in Edge Computing and Machine Learning: Discover the integration of TinyML and wearable tech as we delve into a project that detects falls in real-time, potentially saving lives in our aging population.
Article #3 of Spotlight on Innovations in Edge Computing and Machine Learning: A computer vision system that detects and localizes the surface cracks in concrete structures for predictive maintenance.
16 minutes read
Article 6 of Bringing Intelligence to the Edge Series: The utilization of edge AI facilitates advanced system optimization, predictive maintenance, and improved anomaly detection, greatly advancing technological capabilities across varied fields.
Article 5 of Bringing Intelligence to the Edge Series: Integrating voice user interface technology into microcontroller units for offline, edge-based voice recognition is set to redefine the landscape of home automation and smart industrial applications.
Article 4 of Bringing Intelligence to the Edge Series: AI is proving to be a more precise and time-efficient tool in processing the big data crunch by recognizing patterns and noticing inconsistencies in real-time.
Article 3 of Bringing Intelligence to the Edge Series: Balancing the critical metrics of accuracy, power consumption, latency, and memory requirements is key to unlocking the potential of Tiny Machine Learning (TinyML) in low-power microcontrollers and edge computing.
Article 2 of Bringing Intelligence to the Edge Series: Advancements in AI and embedded vision technologies are revolutionizing various industries, enabling real-time decision-making, enhancing security, and facilitating automation in various applications.
Article 1 of Bringing Intelligence to the Edge Series: With the introduction of AI, IoT devices can become more intelligent and less reliant on external systems— but not without trade-offs in performance and cost. Understanding how to make that decision is key.
