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What is an IoT-Ready PC?

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Can your PC or laptop handle IoT applications? This means it should have the ruggedness and extra connectivity support for IoT devices such as Arduino or Raspberry Pi, while supporting OS such as Windows 10 IoT Core.

At the same time, nothing should stop an IoT-ready PC from working as a normal computer to handle regular browsing, gaming, and Office applications. While a regular PC or laptop can handle the same things, the main difference lies in the fact that IoT-ready PCs have been certified for IoT use, and might give you an extra edge in your IoT development work.

How is an IoT-ready PC Different from a Regular PC?

From a look at existing IoT-ready desktop PC models, it does not appear that there is a huge difference. “There isn’t any unique feature” of such an IoT PC that you wouldn’t find in a late-model laptop or an All-in-one desktop. However, a few things are definitely common.

  • Small form factor: the few IoT PCs currently available in the market are built on an M2. NVMe design which happens to be the smallest form factor at the moment. This compactness is not surprising given that they may need to be transported more frequently.
  • Fanless design: are you not a fan of cooling fans in a computer? Well the IoT-ready PCs are bracing for the future with their concepts of fanless designs which keep the thermals in check. Lenovo’s M90N IoT PC is a great example of such a fanless concept. It looks solid as a brick with no moving components.
Iot Ready Fanless Lenovo M90n Iot 1
Lenovo M90N IoT PC (fanless design)
  • Factory, rugged design: the IoT-ready PCs have a rugged design more suited for industrial applications. This means it works on a low power processor (you can’t let too much heat to be generated.) Intel Atom and Celerons are common. They should be able to handle temperatures in the range of 50 degrees celsius and above. Dell’s Embedded Box PCs of the 3000 and 5000 series address this industrial PC market. It has been designed for a thermal shock of –40°C to 65°C, 150 cycles at around 20°C per minute ramp.
Iot Readu Dell 3000 5000 Embedded Box 1
  • Support as IoT Hub: an IoT-ready PC should work as a hub for any IoT device used in your project. Whether you use Arduino, Raspberry Pi, ESP32, or other boards, or fit your PC with a smart home consumer appliance, the IoT-ready PC is in a position to serve your needs.

Both Dell Embedded Box PC and Lenovo’s M90N IoT PC have a large number of ports and connecting points than you find in a regular PC: USB 2.0, USB 3.1, dual Gigabit Ethernet x RJ-45 (hook them up with Raspberry Pi), serial interfaces and more.

  • Operating systems/Cloud certifications support: Lenovo’s IoT-ready model as well as Dell Embedded Box PC has been certified by Microsoft Azure IoT Edge, Amazon IoT Greengrass, Windows 10 IoT, etc. They can also work with Ubuntu Desktop.

Any Takers for IoT-Ready PC?

IoT-ready PC are a very new phenomenon and are mainly used by industrial PC applications on a premise. However, IoT developers can work with them as well as they are custom-built for such tasks..

Will you buy an IoT-ready PC for your use? Do let us know in the comments.

Source: https://www.iottechtrends.com/what-is-iot-ready-pc/

Big Data

Top 10 Big Data trends of 2020

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Top 10 Big Data trends of 2020

By Priya Dialani

During the last few decades, Big Data has become an insightful idea in all the significant technical terms. Additionally, the accessibility of wireless connections and different advances have facilitated the analysis of large data sets. Organizations and huge companies are picking up strength consistently by improving their data analytics and platforms.

2019 was a major year over the big data landscape. In the wake of beginning the year with the Cloudera and Hortonworks merger, we’ve seen huge upticks in Big Data use across the world, with organizations running to embrace the significance of data operations and orchestration to their business success. The big data industry is presently worth $189 Billion, an expansion of $20 Billion more than 2018, and is set to proceed with its rapid growth and reach $247 Billion by 2022.

It’s the ideal opportunity for us to look at Big Data trends for 2020.

Chief Data Officers (CDOs) will be the Center of Attraction

The positions of Data Scientists and Chief Data Officers (CDOs) are modestly new, anyway, the prerequisite for these experts on the work is currently high. As the volume of data continues developing, the requirement for data professionals additionally arrives at a specific limit of business requirements.

CDO is a C-level authority at risk for data availability, integrity, and security in a company. As more businessmen comprehend the noteworthiness of this job, enlisting a CDO is transforming into the norm. The prerequisite for these experts will stay to be in big data trends for quite a long time.

Investment in Big Data Analytics

Analytics gives an upper hand to organizations. Gartner is foreseeing that organizations that aren’t putting intensely in analytics by the end of 2020 may not be ready to go in 2021. (It is expected that private ventures, for example, self-employed handymen, gardeners, and many artists, are excluded from this forecast.)

The real-time speech analytics market has seen its previously sustained adoption cycle beginning in 2019. The idea of customer journey analytics is anticipated to grow consistently, with the objective of improving enterprise productivity and the client experience. Real-time speech analytics and customer journey analytics will increase its popularity in 2020.

Multi-cloud and Hybrid are Setting Deep Roots

As cloud-based advances keep on developing, organizations are progressively liable to want a spot in the cloud. Notwithstanding, the process of moving your data integration and preparation from an on-premises solution to the cloud is more confounded and tedious than most care to concede. Additionally, to relocate huge amounts of existing data, organizations should match up to their data sources and platforms for a little while to months before the shift is complete.

In 2020, we hope to see later adopters arrive at a conclusion of having multi-cloud deployment, bringing the hybrid and multi-cloud philosophy to the front line of data ecosystem strategies.

Actionable Data will Grow

Another development concerning big data trends 2020 recognized to be actionable data for faster processing. This data indicates the missing connection between business prepositions and big data. As it was referred before, big data in itself is futile without assessment since it is unreasonably stunning, multi-organized, and voluminous. As opposed to big data patterns, ordinarily relying upon Hadoop and NoSQL databases to look at data in the clump mode, speedy data mulls over planning continuous streams.

Because of this data stream handling, data can be separated immediately, within a brief period in only a single millisecond. This conveys more value to companies that can make business decisions and start processes all the more immediately when data is cleaned up.

Continuous Intelligence

Continuous Intelligence is a framework that has integrated real-time analytics with business operations. It measures recorded and current data to give decision-making automation or decision-making support. Continuous intelligence uses several technologies such as optimization, business rule management, event stream processing, augmented analytics, and machine learning. It suggests activities dependent on both historical and real-time data.

Gartner predicts more than 50% of new business systems will utilize continuous intelligence by 2022. This move has begun, and numerous companies will fuse continuous intelligence during 2020 to pick up or keep up a serious edge.

Machine Learning will Continue to be in Focus

Being a significant innovation in big data trends 2020, machine learning (ML) is another development expected to affect our future fundamentally. ML is a rapidly developing advancement that used to expand regular activities and business processes

ML projects have gotten the most investments in 2019, stood out from all other AI systems joined. Automated ML tools help in making pieces of knowledge that would be difficult to separate by various methods, even by expert analysts. This big data innovation stack gives faster results and lifts both general productivity and response times.

Abandon Hadoop for Spark and Databricks

Since showing up in the market, Hadoop has been criticized by numerous individuals in the network for its multifaceted nature. Spark and managed Spark solutions like Databricks are the “new and glossy” player and have accordingly been picking up a foothold as data science workers consider them to be as an answer to all that they disdain about Hadoop.

However, running a Spark or Databricks work in data science sandbox and then promoting it into full production will keep on facing challenges. Data engineers will keep on requiring more fit and finish for Spark with regards to enterprise-class data operations and orchestration. Most importantly there are a ton of options to consider between the two platforms, and companies will benefit themselves from that decision for favored abilities and economic worth.

In-Memory Computing

In-memory computing has the additional advantage of helping business clients (counting banks, retailers, and utilities) to identify patterns rapidly and break down huge amounts of data without any problem. The dropping of costs for memory is a major factor in the growing enthusiasm for in-memory computing innovation.

In-memory innovation is utilized to perform complex data analyses in real time. It permits its clients to work with huge data sets with a lot more prominent agility. In 2020, in-memory computing will pick up fame because of the decreases in expenses of memory.

IoT and Big Data

There are such enormous numbers of advancements that expect to change the current business situations in 2020. It is hard to be aware of all that, however, IoT and digital gadgets are required to get a balance in big data trends 2020.

The function of IoT in healthcare can be seen today, likewise, the innovation joining with gig data is pushing companies to get better outcomes. It is expected that 42% of companies that have IoT solutions in progress or IoT creation in progress are expecting to use digitized portables within the following three years.

Digital Transformation Will Be a Key Component

Digital transformation goes together with the Internet of Things (IoT), artificial intelligence (AI), machine learning and big data. With IoT connected devices expected to arrive at a stunning 75 billion devices in 2025 from 26.7 billion presently, it’s easy to see where that big data is originating from. Digital transformation as IoT, IaaS, AI and machine learning is taking care of big data and pushing it to regions inconceivable in mankind’s history.

Source: https://www.fintechnews.org/top-10-big-data-trends-of-2020/

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Fintech

Sberbank’s Pay with QR and Take&Go offerings recognized among world’s best

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Sberbank’s Pay with QR and Take&Go offerings recognized among world’s best

Sberbank has won Future Digital Awards in two categories, securing gold accolades for the innovativeness and user-friendliness of its Pay with QR (Best QR Code Payment Offering) and Take&Go (Best In-Store Technology) services.

Pay with QR is an innovative cashless method of accepting payments for products or services, which is available to Sberbank customers, as well as to clients of other banks who use Sberbank’s QR Platform. To make a payment, you only need to show your personal QR code generated by the mobile application or scan the code posted at the outlet. For businesses, this type of payment is much more affordable than merchant acquiring, with the fee being only 0.6% to 1.5%. On top of that, outlets don’t need any special equipment to use the service.

Take&Go is a revolutionary computer vision technology to make purchases at stores. The first store without checkouts in Russia was opened at Azbuka Vkusa. To make a purchase, you just need to scan a QR code using the Take&Go mobile app, take the groceries you need off the shelf and leave. The money will be debitedautomatically.

Dmitry Malykh, Acquiring and Bank Cards Director, Sberbank:

“Sberbank constantly develops and introduces innovative payment solutions that become an integral part of our customers’ lives over time. They pay for their purchases every day in the most convenient and secure ways. The Pay with QR and Take&Go offerings are already very popular among our individual customers while opening up new opportunities for businesses of any size. The international experts’ recognition once again proves that we are moving in the right direction.”

Future Digital Awards is an international award, founded in 2008. Its participants are companies that operate in fintech and payment, digital service provision, technology and innovation such as smart devices, cities and houses, IoT, etc. Juniper Research analytical group assesses applications, draws up short lists of potential winners based on criteria such as product innovation, its peculiar features and advantages, product partnerships, certification and compliance, and future business outlooks. Amazon, Visa, Google, Microsoft, Apple, Mastercard, IBM and other globally recognized tech companies won the award in 2016–2019.

Source: https://www.fintechnews.org/sberbanks-pay-with-qr-and-takego-offerings-recognized-among-worlds-best/

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How Artificial Intelligence is Changing the eLearning Environment

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Illustration: © IoT For All

Artificial intelligence (AI) is everywhere these days, making inanimate objects increasingly smart. It’s designed by humans for humans, to enrich and facilitate our everyday lives. As a matter of fact, AI is now the brain behind your smartphone, car, music streaming service, banking app, freezer, and travel agency. It’s not only omnipresent, it’s omniscient as well. 

If the main keyword for AI is “smart”, then how come we don’t talk more about this burgeoning technology in the context of knowledge, learning, and education? AI has everything we need to revolutionize the industry, enrich and facilitate the learning experience of students and adult learners, and boost the knowledge retention rates across the board.

It’s a whole new chapter in the history of the classroom. The change has already begun, with AI reshaping eLearning as we know it. Find out how.

AI Makes Personalized Learning a Child’s Play

Every student is different. Educators have known this for a long time, but it wasn’t until LMS software solutions that they were able to actually accommodate the various needs of different types of learners.

The introduction of technology to the traditional classroom established a framework for blended learning, which is now the dominant model for educating modern-day students. Essentially, blended learning allows students to choose how they access educational content, and how they acquire knowledge in terms of learning styles and speed. But AI brings personalization to a whole new level. 

Unlike teachers, artificial intelligence can recognize students’ learning needs, interests, preferences, habits, and capacities automatically and in real-time, by analyzing their performance. This powerful insight helps create highly personalized learning environments and paths where every aspect – from content type to delivery method – is adjusted to the students’ individual needs.

The result? Optimum performance of every learner.

AI is at Learners’ Disposal Anytime, Anywhere

In combination with personalized learning paths, unlimited connectivity makes it possible for students to access educational content from anywhere and at any given moment. 

Adaptive learning environments enable and encourage self-paced learning, thus allowing students to make the best out of their peak productivity hours. But what happens if one learner’s productivity peaks in the middle of the night, when there’s no one around to help solve a dilemma or address points of confusion?

Since blended learning is a combination of instructor-led training and online courses, tutors should remain available 24/7, whenever students may need their guidance. This may not be possible with human tutors, but it is with digital assistants.

Thanks to machine learning and natural language processing, AI assistants can learn to provide necessary guidance to students, answer their questions, and solve their problems. And since machines never sleep, this digital mentorship is available 24/7.

Digital Mentorship Can Encourage Engagement

Usually, AI assistants work with students individually. Extending the concept of student-centered education, smart technology caters not only to different learning styles but also to different personalities and temperaments. This is significant to introverted students, who usually don’t feel comfortable expressing themselves in front of their peers in the traditional classroom environment.

Faceless AI is a saving grace for such learners as it allows them to voice their dilemmas without the fear of being judged, while the eLearning environment itself encourages them to participate in social learning. Of course, AI has the potential to motivate and engage all students, be they introverts or extroverts, visual learners or auditory learners.

Higher engagement is a natural consequence of personalization – by facilitating the learning path, AI makes knowledge acquisition easier, thus eliminating all frustration from the process. All students thrive in such a learning and development (L&D) environment when they are motivated by their own achievements.

AI Allows Continual Real-Time Improvement

Thanks to cutting-edge software technology and authoring tools, everyone can learn to create an online course that encourages engagement and equips students for success.

It’s maintaining this eLearning environment that’s hard, especially in today’s fast-paced world. Technology is a powerful knowledge acquisition tool – the more potent it becomes, the more we understand about the world we live in. The human race is learning on a daily basis.

The road from tacit to explicit knowledge was a long one in the pre-digital age. At times, students had to wait years before new findings were added to their old textbooks. Today, we have the Internet – the biggest and fastest knowledge base in history.

With AI, we can now comb through this knowledge base in matters of minutes, update our online courses with cutting-edge information in real time, and keep educational content relevant. Having said that, up-to-date content is not enough to ensure a rich learning experience. Educators and online course creators must learn from their students as there are always challenges that need to be addressed. Because of this, student feedback is precious.

Real-Life Examples of AI in Learning

Let’s now see a few companies who are working behind the scenes to bring the benefits of AI-powered technologies to people.

Nuance

Massachusetts-based software technology company, Nuance builds speech recognition software. The technology can transcribe a maximum of 160 words per minute. It is useful especially to learners with mobility challenges, including writing. Instructors too can rely on it to dictate classroom lectures and expedite repetitive tasks such as emails.

Carnegie Learning

As a provider of quality math education, Carnegie Learning brings together artificial intelligence and machine learning to its platform. It puts emphasis on personalized learning experiences to turn learners into critical thinkers, creative problem solvers, and lifelong learners. By combining cognitive and learning science with research and practical instructions, CL helps students gain a deeper understanding of what they are learning.

Century

Century is a provider of an AI-based teaching and learning platform located in London. It provides adaptive learning solutions for learners according to their strengths and weaknesses, while helping instructors simplify their routine tasks such as grading. For this, it combines AI, neuroscience, and data analytics.

Artificial intelligence is already making waves in the eLearning industry by unlocking exciting new opportunities for educators and students alike. But deep personalization, 24/7 availability, increased engagement, and real-time improvement are only a fragment of what AI may mean for the future of education. Experts predict that the use of this smart technology will grow by 47.5% in the next two years. We can only imagine the possibilities.

Source: https://www.iotforall.com/how-artificial-intelligence-is-changing-the-elearning-environment

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