Top 10 Things To Know About Retail and IoT In 2017

| February 28, 2018

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Retailers are apparently still confused about which technologies constitute IoT and which do not. It’s no wonder Senior Management is slow to support IoT.

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Icon Labs provides unique and specialized security software for IoT devices and embedded systems. These products are modular security solutions tailored for use with embedded Linux and real-time operating systems. For embedded OEMs, software products must be integrated into the end-user application.

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Which IoT Applications will Benefit Most from Edge Computing?

Article | March 2, 2020

Edge computing refers to information being processed at the edge of the network, rather than being sent to a central cloud server. The benefits of edge computing include reduced latency, reduced costs, increased security and increased business efficiency. Transferring data from the edge of a network takes time, particularly if the data is being collected in a remote location. While the transfer may usually take less than a second, glitches in the network or an unreliable connection may increase the time required. For some IoT applications, for example, self-driving cars, even a second may be too long. Imagine a security camera that’s monitoring an empty hallway. There’s no need to send hours of large video files of an empty hallway to a cloud server (where you will need to pay to store them). With edge computing, the video could be sent to the cloud only if there is movement detected in the hallway.

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LIVING IN A SMARTER WORLD: WHY USE AI-ENABLED IOT IN HEALTHCARE

Article | March 12, 2020

Artificial Intelligence and Internet of things are hot topics now, as a consequence, integrating AI into IoT is becoming a common practice. The healthcare system is everybody’s business, so finding one's way around is equally important for all. Yet, keeping all the details in mind is no easy task. There are limits to human mental and physical performance. Thus going beyond one’s maximum has to be relegated to such technologies as the Internet of things and Artificial Intelligence. The implementation of innovative solutions in healthcare is always a good idea and IoT together with AI are strong drivers of the digital transformation regardless of what field the technologies are applied in. Municipal infrastructure, smart homes, retailing, manufacturing, supply chain, education, healthcare and life sciences — the entire digital ecosystem, an IoT ecosystem of connected devices, has been created and is growing stronger with each passing day. Empowered with Artificial Intelligence and Machine Learning, among other things, IoT is used as a means of equipping people with intelligent assistance. Gradually, it is taking over both minor and major processes in a number of industries. Healthcare is no exception.

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Building a Cold Chain Management IoT Solution

Article | February 27, 2020

Artificial intelligence (AI) has existed in the public consciousness for decades. The (mostly) sentient machines playing the villains in Hollywood movies have never been realistic depictions of the technology, but they have left an impression, nonetheless. AI has proved as exciting to the layman as it is to the expert. Usually based in remote data centers, AI is capable of collecting and examining immense volumes of data, generating insights based on analytical algorithms. With varying degrees of autonomy, these capabilities have been put to use streamlining decision-making processes. While AI is often thought of as a product in its own right, it is increasingly intersecting with other parallel trends. Chief among these is the Internet of things (IoT), which enables previously isolated machines to “talk” to one another and, at the same time, generate data that makes new modes of operation a possibility.

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How Will the Emergence of 5G Affect Federated Learning?

Article | April 10, 2020

As development teams race to build out AI tools, it is becoming increasingly common to train algorithms on edge devices. Federated learning, a subset of distributed machine learning, is a relatively new approach that allows companies to improve their AI tools without explicitly accessing raw user data. Conceived by Google in 2017, federated learning is a decentralized learning model through which algorithms are trained on edge devices. In regard to Google’s “on-device machine learning” approach, the search giant pushed their predictive text algorithm to Android devices, aggregated the data and sent a summary of the new knowledge back to a central server. To protect the integrity of the user data, this data was either delivered via homomorphic encryption or differential privacy, which is the practice of adding noise to the data in order to obfuscate the results.

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Icon Labs

Icon Labs provides unique and specialized security software for IoT devices and embedded systems. These products are modular security solutions tailored for use with embedded Linux and real-time operating systems. For embedded OEMs, software products must be integrated into the end-user application.

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