In recent years, the IoT devices and next-generation manufacturing industry has seen a significant surge in industrial automation. The ecosystem's multiplicity of key stakeholders has led to a competitive and diverse IoT adoption in the manufacturing market.

Laird Connectivity has announced the new Lyra Series of Bluetooth Low Energy (BLE) Modules that is based on the Silicon Labs EFR32BG22 SoC and p

Loko from Dronee is an open source, battery operated GPS tracker that sends navigation data to its receiver via peer-to-peer LoRa radio and also works anywhere, even if there is no 2G/ 3G/LTE coverage.

The IoT device and data management company, Friendly Technologies has released an open-source LwM2M client to support at-scale management of IoT devices globally.

Taoglas has recently launched its System-on-Module (SoM) portfolio for rapid IoT deployment.

U-blox has released NEO-M9L-20A, NEO-M9L-01A modules, and the M9140-KA-DR chip that are specially designed for first-mount automotive solutions. Suitable for integration on the roof, behind the windscreen, or inside hot electronics control units (ECUs), these new automo

Audio front-end (AFE) algorithms play an important role in building a sensitive voice-user interface (VUI). With the aim to enhance the performance of the voice user interface, AI Labs of Espressif Systems has developed new

With the aim to advance the deployment of 5G in the IoT vertical industries and expand the new market opportunities of 5G technology in the IoT sector, Fibocom has introduced two new 5G wireless modules FG130 and FM130.

Fujitsu Components has introduced a line of the embedded FWM7BLZ20W mesh network and multi-sensor units with built-in Wirepas Massive network connectivity for real-time locating systems and smart industrial IoT applications.

New Versal AI Edge adaptive compute acceleration platforms (ACAPs) from Xilinx is designed to enable AI innovation from edge to the endpoint in automotive, robotics, healthcare, and aerospace applications. These ACAPs offer 4 times higher AI performance