Uploaded August 2026 | Updated September 2026, 1 week ago
High-performance wireless. Built for flexibility.
Highlights:
โก Tri-band Wi-Fi 6E (6 GHz, 1024-QAM, 160 MHz)
๐ Up to 3.54 Gbps UL / 3.00 Gbps DL with 2ร2 MIMO
๐ PCIe 2.1 host & SDIO 3.0 slave interfaces with cross-platform support
๐ถ Bluetooth 5.4 (Classic + LE)
๐ ๏ธ Wi-Fi CSI support
๐ฌ Which feature are you most excited to explore?
#Espressif #ESP32 #ESP32E22 #AIoT #EmbeddedSystems #Bluetooth #PCIe #WiFi6
High-performance wireless. Built for flexibility.
Highlights:
โก Tri-band Wi-Fi 6E (6 GHz, 1024-QAM, 160 MHz)
๐ Up to 3.54 Gbps UL / 3.00 Gbps DL with 2ร2 MIMO
๐ PCIe 2.1 host & SDIO 3.0 slave interfaces with cross-platform support
๐ถ Bluetooth 5.4 (Classic + LE)
๐ ๏ธ Wi-Fi CSI support
๐ฌ Which feature are you most excited to explore?
#Espressif #ESP32 #ESP32E22 #AIoT #EmbeddedSystems #Bluetooth #PCIe #WiFi6









โinto API calls needed to initialize the data model, encodes them to protobuf messages and stores it in a space-efficient format on the flash.
By design, this allows the application and the data model to be decoupled and stored independently. The repo also includes an IDF component that can read this serialized format and create the data model at runtime. However, the same format is usable across Matter implementations like Matter.js, rs-matter, Matter (CircuitPython) or Arduino Matter, eliminating the need for code generators to be developed for these languages.
The talk will provide an introduction to data models of IoT devices, how Matter approaches the data modeling problem, and how the Data Model Interpreter tools and components work. It will also cover the potential use cases.
Speakers: Dhaval Gujar and Amit Sheth DevCon25 - Runtime Data Model Interpreter for Connected Devices](https://i.ytimg.com/vi/UmZA3k8RDXU/mqdefault.jpg)
