Lenovo announced yesterday at the Embedded World 2021 DIGITAL virtual exhibition that it will introduce an updated edge IoT embedded mini PC portfolio including the ThinkEdge SE30 and SE50 models. These new models are small, fanless and rugged, yet powerful enough to provide enterprise-level data processing, security and scalability at the edge through the addition of Intel Tiger Lake CPUs. Shipping dates are set for some time in mid-2021, although pricing is to be determined.
The ThinkEdge SE30 model is designed for embedded applications like kiosks and ATMs for smart retail, automated production lines in manufacturing, and medical device monitoring in healthcare. More than half of the fanless case measuring 7.04 x 3.46 x 2.03 inches (179 x 88 x 51.5 mm) and weighing up to 2.2 lbs is allocated for the heatsink fins. It can be powered by Core i3-1115GRE or i5-1145GRE vPro processors, which can be coupled with up to 16 GB of DDR4 RAM and up to 1 TB NVMe SSD storage. The port selection is quite robust, offering 2x COM connectors, 3x USB-A 3.1 Gen2, 1x USB-A 3.1, 1x USB-C 3.1 Gen2 with display, 1x Thunderbolt 4 with display and power delivery, 1x DP (i5 SKU), 1x HDMI (i3 SKU), 2x GbE jacks and a combo audio jack. This model will support 4G :LTE connectivity by default, and Lenovo will offer a 5G upgrade later on. It also features 2x M.2 2280 slots for storage upgrades and an M.2 2230 for a Wi-Fi / Bluetooth module. Lenovo guarantees that this model is able to operate between -20 and 60 degrees Celssius and also features proofing for humidity, vibrations and shocks.
There is no detailed spec list for the SE50 model as of yet, but Lenovo mentions that it will feature up to an i7 processor, up to 32 GB of RAM, up to 2 TB (SSD + HDD combo) and possibly more ports (at least 4x GbE jacks mentioned). This model will feature a bigger 2-liter case with operating temperatures ranging between 0 and 50 degrees Celssius and it is recommended for versatile applications that require higher analytics and data processing at the edge so it can be deployed to aggregate and analyze real-time data from distributed IoT devices.
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