Scaling AIoT Projects Through Correct Component Selection

August 03, 2020

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AIoT is the combined effort of the two technologies that have been dominating the field over the past few years (AI and IoT).

It is often said that two heads are better than one. However, in the case of IoT, the addition of a single brain has opened up the path for a game changing technology.

AIoT is the combined effort of the two technologies that have been dominating the field over the past few years (AI and IoT). IoT acts as a central nervous system, collecting massive amounts of data through a series of connected devices and their sensors. AI serves as the brain endowing IoT applications with the ability to analyze the data, and take reasonable actions based on the analysis – all with minimal human intervention.

The convergence of these two technologies is already present in the shape of edge devices. Edge devices take computational tasks away from the cloud and into the edge of IoT networks. Not only does edge computing eliminate latency issues, facilitating the instantaneous response from applications, it also allows raw data to be filtered near its source thereby reducing bandwidth needs in the process.

There is no question that AIoT and edge computing have the ability to create new and exciting possibilities for systems and devices that require immediate real time reaction. Embedding AI technology into IoT solutions opens the door to massive gains in terms of operational efficiency…gaining insights from data and overall human-machine interactions.

Despite the array of potential benefits that might come with the implementation of AIoT, businesses’ efforts for large scale deployment seem to keep falling short. Failures can be attributed to a variety of reasons, with the reasons themselves often being different depending on the stage at which the project finds itself.

While strategic factors have more relevance at the initial stages, other issues such as data governance, data security, and the day-to-day logistics related to the remote management of the applications tend to become more pertinent at later stages. In order to deal with some of the roadblocks found at later stages of deployment, a philosophy of choosing partners over components should be adopted. When it comes to suppliers for key components, quality and performance are but some of the elements to consider, extra features in the form of support and built in software have come to gain more relevance.

Remote Management Through SMART Tools

For AIoT NAND Flash storage is one of these so-called key components. Moving computational tasks away from the cloud and into the edge requires reliable, durable, and high performing storage devices capable of handling the massive influx of data. Despite all the advantages and features of modern NAND technology the process of writing data into the cell will degrade the flash overtime; NAND solutions have a given lifespan and eventually have to be replaced.

Since minimizing human interaction is one of the key objectives behind AIoT, it comes as no surprise that AIoT implementations are bound to be found in a variety of environments in which human support will range from minimum to nonexistent. Whether an AIoT solution is deployed in an indoor office space or under the harshest of outdoor settings, reducing downtimes will be one of the major challenges adopters will have to face. Preventive maintenance initiatives will take the lead role, while the components utilized will start featuring a range of software analysis tools capable of providing meaningful real-time insights regarding their health and status.

Silicon Power Industrial offers a complete line of SMART software analysis tools. These tools contribute in monitoring the health status of the storage device at all times. By collecting relevant information related to the status of the device and making it available in intuitive dashboards, owners of these devices can take fully informed decisions regarding their management, maintenance or renewal. SP SMART embedded, for example, ensures the seamless integration of the tools with edge devices, whereas SP SMART IoT Sphere provides a comprehensive cloud based set-up and fully responsive alarm notification system for effective data management. 

Preventing Unauthorized Reuse and Duplication Of Data

As in most cases in which huge volumes of data are involved, concerns regarding privacy and security are a given. Edge computing is no exception to the rule, transferring computational tasks away from the cloud and into the edge, does not eliminate security concerns it just transforms them into something different.

With the greatest percentage of data being processed directly at the edge, either in an SSD or memory card, the possibilities of these storages devices being removed, copied, stolen or reused in unintended ways grow significantly. AIoT adopters have to make sure that the storage solutions they are using possess reliable features that help keeping their sensible data safe and away from misuse. 

The Host Lock feature offered by Silicon Power Industrial is a clear example of a plausible way to fight this type of vulnerabilities. SP Host Lock can help prevent users without the proper credentials from reading, writing to, or erasing data from the given device. SP Host Lock provides a reliable way to protect data from being copied and used for illegal purposes.

Beyond Quality And Performance, Support, and Features

Despite all the benefits behind AIoT implementation, projects hardly go pass the proof of concept stage. There are infinite reasons why the scaling of projects often fails, most of them attributable to strategic and conceptual elements. However, beating these initial roadblocks is often not enough; a new set of obstacles often arises at later stages. A philosophy of partners over components can help surpass some of these obstacles. Suppliers of components that play a key role in edge devices, such as the storage, can contribute to AIoT deployment ensuring that beyond high quality and performance adopters can also find great support and features. 

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