by Farhad Fallahlalehzari, Applications Engineer, Aldec
As the deployment of Industrial IoT systems continues to proliferate, the streams of data transferred to the cloud skyrockets, drastically increasing the cost for cloud computing.
To solve this, many systems designers are adopting edge computing, in which data processing is done close to the source (e.g. sensors) in a bid to reduce data transfer, storage and processing costs, plus address a few other concerns over Cloud Computing, in particular security.
Big Data is a broad label for the growing amount of data generated by IoT devices and smart systems. For instance, some aircraft engines have more than 5,000 elements that are monitored at relatively high sample rates. Most of the data is transferred to a ground station for the real-time monitoring of the engine and for future R&D work. But this is only part of a growing trend. Most ‘smart’ systems produce vast amounts of data which needs to be processed immediately or be stored for subsequent processing
To store Big Data, huge datacentres are required. These are often costly, need a spacious climate-controlled environment and require regular maintenance. The alternative is Cloud Computing, the on-demand delivery of compute power, applications and other IT resources, and cloud providers - such as Amazon with its web service (AWS) - provide a simple way to access their servers, databases, processing and platforms and storage devices
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