In the recent ten years, the Internet of Things has shown itself as a breakthrough solution for delivering more informed business strategies, improving customers’ experience, managing assets, automating processes, performing predictive maintenance, and so on. A large role here was played by embedded solutions – hardware and software systems which contribute to the high performance of the whole IoT ecosystem. However, there is no universal method of organizing and deploying the embedded IoT system to guarantee its complete success. On a case-by-case basis, embedded IIoT solutions providers, manufacturers, developers, and business owners have to decide which “things” to equip, how to customize solutions, and how to save without causing harm. However, the future seems to belong to the IoT embedded. 

As McKinsey reports, by 2030, total revenue for 5G IoT embedded modules will increase more than 50 times! This is partly due to deep learning processors and neural processors contributing to exponential growth in performance and energy efficiency of embedded computing systems. However, to make it real, manufacturers of the ready-made solutions have to study deeply the demand to produce off-the-shelf modules for customers’ specific needs. Despite there being an abundance of ready-made embedded systems on the market today, they are not always in strict adherence to customers’ business goals. At some point, the question might arise of reducing the cost of a solution in mass production and of a unique form factor or minimizing the dimensions of the devices. All these factors reinforce the need for custom embedded hardware and software development. This article focuses on the main points to consider while designing an embedded system within IIoT solutions to make it capable of improving business.

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