Making data collection flexible with OpenIOLabs: three real-life examples

OPENIOLABS TEAM | November 18, 2016

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What we often hear is that IoT and machine to machine communications hold so much potential, but the reality is that the uniqueness of each lab set up makes it hard to benefit from what it offers. Facilities are filled with legacy equipment – instruments and apparatus that were designed long before IoT was even invented. The need to introduce modern equipment is important, as it increases efficiency, but incorporating them means reinvesting in new technologies, that is until OpenIOLabs was launched.

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Artificial Intelligence Applications: Is Your Business Implementing AI Smartly?

Article | March 12, 2020

The book Design, Launch, and Scale IoT Services classifies the components of IoT services into technical modules. One of the most important of these is Artificial Intelligence (AI). This article is intended to supplement the book by providing insight into AI and its applications for IoT. After many years in the wilderness, AI is back on the hype curve and will change the world again. Or, will it? AI has always been interesting, but what has changed to justify the current hype? There are several contributing factors. The volumes of data that will be produced by many IoT services suggest that this data cannot be managed by humans with traditional analytics tools. Therefore, AI can offer opportunities for IoT services to extract maximum value from the data. IoT cloud platforms are now offering AI services via APIs and application development tools, making AI more accessible for many IoT services. Now, AI can be incorporated without requiring extensive development or excessive costs.

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Securing industrial networks: it’s a journey

Article | March 12, 2020

Trying to secure the industrial network in one go is like boiling the ocean. Better to view it as a journey. At each step in the journey, you’ll make incremental changes to people, process, and technology. Minimal security. This is the current state for most manufacturers. If you’re here, you’ve segmented the industrial network from the IT network. Traffic can’t cross from the IT network to the industrial network without clearing the DMZ. You can block malware from entering the industrial network. You can block malware from leaving the industrial network to infect the enterprise network. But if the industrial network is exposed to malicious software, you don’t have a way to contain it. That means the malware might affect multiple manufacturing cells or production lines — even multiple plants.

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For your industrial IoT deployment: A four-step guide to selecting a wireless technology

Article | March 12, 2020

Most everyone agrees that wireless technology is a key pillar of the Internet of Things. Exactly which wireless technology is a different story. Opinions may vary from enterprises, to service providers or vendors, but one size does not fit all. The best wireless technology is the one that addresses the requirements for your industrial IoT use case. How could an OT manager make sure he or she will select the most appropriate technology for his/her use case(s)? To help with the decision process, here’s a step-by-step guide defining selection criteria for wireless technology.

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THE FUTURE OF BIOMETRICS IOT

Article | March 12, 2020

In 2018 when Apple unveiled its iconic iPhone X with a feature to unlock the phone with Face ID thereby eliminating the use of the home button, it met a lot of eye-rolls. Fast forward to now, people are in love with the biometrics enabled technologies. While iPhone X had a unimodal authentication system, gadget these days have updated themselves in a better way. Let’s try to have a better understanding of the Biometrics. Biometrics are a way to measure a person’s physical characteristics to verify their identity. It can be physiological traits, like fingerprints and eyes, or behavioral traits, that define the manner an individual respond to stimuli. These characteristics are unique to the person. Once collected the data compared with the pre-existing database to find a match. Accordingly, it then produces an outcome. There are many varieties in which this data is collected. Facial and voice recognition, iris and finger scanner, signature verification, hand geometry, keystroke, gait detectors are some of the examples.

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Upstream is accelerating mobile commerce in high growth markets. Our software and infrastructure platform already enables 1.2 billion people to effortlessly receive and pay for the most relevant and affordable digital subscription services on their mobile devices...

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