Edge AI
Edge AI brings artificial intelligence to the point where data is generated: sensors, cameras, machines and mobile devices. Local processing reduces latency and data transmission while enabling intelligent functions without a permanent cloud connection. Explore embedded AI, TinyML, AI processors, edge computing platforms and intelligent sensor systems.
Articles on this topic
Embedded AI: When Artificial Intelligence Becomes Part of the Device
What is embedded AI? Embedded AI is the integration of artificial intelligence into a dedicated electronic device or embedded system. Instead of using AI only as external software or a centralized cloud service, the intelligence becomes part of the product itself. An embedded AI device may capture…
Wearables with Sensors and AI: From Data Trackers to Intelligent Assistance Systems
Wearable devices have evolved significantly in recent years. Simple step counters have become connected systems capable of continuously collecting, processing and, in some cases, interpreting data related to the human body. This development is driven by the combination of advanced sensors…
TinyML Explained: Machine Learning on Microcontrollers and Sensors
TinyML brings machine learning to small, energy-efficient devices. Instead of continuously sending sensor data to the cloud or a powerful server, data can be analyzed directly on microcontrollers, sensor platforms and compact embedded systems. This allows devices to detect patterns, classify events…
Embedded AI in Sensors: How Artificial Intelligence Operates Directly Inside Sensors
Sensors measure physical quantities such as temperature, pressure, motion, sound, light and force. Conventional sensing systems transmit these measurements to a controller, edge computer or cloud platform for further processing. Embedded AI changes this approach. Algorithms and machine-learning…
Edge AI Explained: Intelligence Directly at the Sensor and Device
Edge AI refers to the execution of artificial intelligence directly where data is generated: on machines, cameras, sensors, vehicles or other devices. Instead of transferring all data to a data centre or cloud platform first, it is processed locally. This approach is particularly relevant for…