Everything About TinyML – Basics, Courses, Projects & More!
Updated on Feb 6th, 2024 TinyML is one of the hottest trends in the embedded
An edge native architecture provides efficient computing, storage and control close to data inputs or users of Internet of Things(IoT) scenarios.
Seeed is dedicated to providing reliable Edge Computing solutions to system integrators and service providers. From human machine interface to edge computing server, our goal is to develop and provide the best-in-class products and services to empower like Industry 4.0, Infrastructure, Smart City, Smart Agriculture and others with edge computing capability.
In the edge computing based IoT architecture, latency of communication between sensors and servers is greatly reduced. Local data is been stored and processed in the edge center, which reduces the risk of privacy data leakage. Edge native center provides large bandwidth for the local network.
Data is processed and stored on edge computing devices. Only data analysis results are transmitted to the cloud. This will physically prevent private data from being exposed to the public network. And it complies with data security regulations in some regions.
Edge computing devices are closer to data input, reducing the number of network nodes. This significantly reduces connection latency and provides the possibility of real-time computing for some delay-sensitive applications.
Connecting a large number of sensors requires the support of large bandwidth, which will increase the connection load of the public network and operating costs. Edge computing can provide large-bandwidth connections for a large number of devices at a lower cost.
Even when it is disconnected from the cloud server, edge computing devices can still support the operation of local applications. This ensures the stability of the service and reduces the loss caused by network connection problems.
AI modules can be integrated into edge computing devices. They provide local AI acceleration for applications and optimize model training for local scenarios. This reduces the difficulty of local AI compatibility.
reServer is based on an ODYSSEY X86 v2 board and powered by Intel® Core™ 11th Gen and Intel® Iris Xe Graphics, which delivers high CPU and AI performance for various applications. It has two high-speed 2.5-Gigabit Ethernet ports and supports hybrid connectivity including 5G, LoRa, BLE and WiFi. reServer is of compact design to work efficiently in almost any scenario. The neat structure of reServer also makes it simple to access to the hard drives, memory and PCIe slots which allows easy installation, upgrades and maintenance.
We not only provide standard devices but also provide manufacturing and customization services. Our manufacturing services include prototype and mass production and customization services cover hardware, software, mechanical and certification, etc.
Updated on Feb 6th, 2024 TinyML is one of the hottest trends in the embedded
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