AI on Edge Computing – Can it solve IoT Data Privacy Issues?

AI on Edge Computing: The rapid development in Artificial Intelligence, smart gadgets, and smart cities guarantees to change the way we function, live, as well as interact. Nevertheless, current scandals around the handling of customer information have motivated a wave of personal privacy issues. The smarter a city obtains, the much more it can maintain tabs on every move of its citizens. Furthermore, with connected home devices and digital assistant grabbing our everyday tasks as well as inquiries, the capacity for personal privacy violations are limitless.

Europe’s introducing General Information Personal privacy Policy (GDPR) is among several efforts by federal governments to alleviate extensive deficiencies in client information security, for both firms and also federal governments. Various other nations, as well as even US states like California, have adopted similar regulations. However, stringent data regulations do not come without their disadvantages. More policy implementations are on the horizon across the globe. Hence many worry if future data-driven technology innovations and advances are at risk.

One possible remedy is Edge computing solutions. Edge computing provides a method to integrate the expanding numbers of IoT tools in our individual, public, and professional lives with user data privacy.

AI Voice Assistants like Alexa, Siri for Smart Home

Voice aides like Alexa as well as Siri, remain to expand in appeal. In 2018, United States wise voice aide adoption expanded 40 percent, getting to 66.4 million or 26 percent of the United States adult population.

The Alexa, as well as Siri systems, might be “wise,” however the AI abilities that are required to support all the variety of inquiries do not reside on these gadgets. Instead, a regular smart device, for instance, documents what customers state, transfers it to the webserver for handling, after that beams back an outcome. In voice assistants, Natural Language Processing is used to convert speech to text for data processing and then text to speech for playback the processed results to the user.

“Alexa, can you play the most recent struck by Justin Bieber?”

This command converts the audio to text and transfers the data countless miles to data centers for processing. Then the processed data is converted from text to speech to playback on your device. Because of this process, Alexa, as well as Siri, usually, do not function offline and is also why Google Home’s offline performance is restricted.

Much of the personal privacy worry in Smart home gadgets are, in fact, not a problem with the devices themselves, but with the procedure of sending and also saving information. That is because data is most vulnerable in transit, and centralized databases of customer data serve as hotspots for cyber hackers.

One solution? A genuinely smart gadget would undoubtedly have the ability to process all required information by itself. That is at the Edge. This process would not only make the device much more functional, receptive, much faster but also a lot more protected. It would considerably help in GDPR conformity.

To understand, one can check out Amazon.com’s newest Alexa-related personal privacy error. This July, Amazon.com inadvertently sent out a guy 1,700 Alexa documents that belong to another Alexa owner. The twist: these documents were sent in response to the guy’s GDPR data ownership request.

Data processing for the devices of tomorrow in Smart Cities:

These innovations could also apply to smart technologies well beyond the home, including smart cities. Many intelligent cities and cutting-edge public safety programs urgently need to educate themselves towards new regulations. GDPR, for example, restricts how potentially identifiable information can be stored, processed, and collected not just by corporations and municipalities.

Under GDPR, user data can be used without explicit consent only if the user identity information is removed and directly contributes to approved purposes. At the same time, the performance of critical functions like scanning video for missing persons, criminal activity, or traffic violations requires substantial processing power. If the data is processed outside the device, new privacy concerns come up. However, current device processors are limited in their ability to process information, and together, these limitations curtail basic functionality.

For smart cities, most of the computing power must be driven to the edge of the network. This change means the devices and sensors will be responsible for processing decisions locally, on their own, without a remote server. There will always be at least some data sent to a server given the massive amount of information that needs to be processed. However, Edge computing guarantees that only the most relevant, digested data will be sent there. 

Summary:

AI on Edge Computing: A key solution to GDPR’s current limitations on innovation is edge computing. However, edge computing alone is not sufficient. Intuitive edge processing with AI is key to making these devices truly smart.

Footnotes:

  • AI on Edge Computing.
  • Mobodexter, Inc based in Redmond, WA builds IoT Edge solutions for enterprises applications on Kubernetes & Dockers.
  • Register now at developers.paasmer.co and enjoy free Edge trial license of Edge Intelligence software that runs on Raspberry Pi.
  • Follow our all our weekly IoT Blogs: https://api.mobodexter.com
  • Our IoT Newsletter reaches 3000+ subscribers– Subscribe Now.
  • Become our affiliate partner today.
%d bloggers like this: