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AI is Helping Forecast the Wind, Manage Wind Farms 

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Remote wind turbines, such as those located in the ocean, can be managed with the help of AI-powered condition management systems. (Credit: Getty Images) 

By John P. Desmond, AI Trends Editor  

Among all its many activities, Google is forecasting the wind. 

Google and its DeepMind AI subsidiary have combined weather data with power data from 700 megawatts of wind energy that Google sources in the Central US. Using machine learning, they have been able to better predict the wind, which pays off in the energy market. 

“The way a lot of power markets work is you have to schedule your assets a day ahead,” stated Michael Terrell, the head of energy market strategy at Google, in a recent account in Forbes“And you tend to get compensated higher when you do that than if you sell into the market real-time.”  

This is an example of the application of AI to wind energy and the wind energy market, an effort being tried in many regions by a range of players.   

“What we’ve been doing is working in partnership with the DeepMind team to use machine learning to take the weather data that’s available publicly, actually forecast what we think the wind production will be the next day, and bid that wind into the day-ahead markets,” Terrell stated during a recent seminar hosted virtually by the Precourt Institute for Energy of Stanford University.  

The result has been a 20% increase in revenue for wind farms, Terrell stated. Google has been on a mission to radically reduce its carbon footprint. The company recently achieved a milestone by matching its annual energy use with its annual renewable-energy procurement, Terrell stated. 

“Our hope is that this kind of machine learning approach can strengthen the business case for wind power and drive further adoption of carbon-free energy on electric grids worldwide,” stated Sam Witherspoon, a DeepMind program manager, in a blog post. He and software engineer Carl Elkin described how they boosted profits for Google’s wind farms in the Southwest Power Pool, an energy market that stretches across the plains from the Canadian border to north Texas. 

European Commitment to Wind Energy Seen in SmartWind Project  

European countries have made a big commitment to wind energy, with offshore wind farms being required to supply about 8.5% of all energy in the Netherlands and 40% of current electricity consumption by 2030, according to a recent account in Innovation Origins  

AI is expected to play a big role in this effort, helping to increase energy generation and reduce maintenance costs for wind farms. The related SmartWind project is being undertaken by a consortium of four companies and the Ruhr-University Bochum in Germany.   

Prof. Constantinos Sourkounis, Institute for Power Systems Technology, Ruhr-University Bochum

“In SmartWind we can exploit the capabilities of artificial intelligence algorithms to optimize the management of wind farms,” stated Prof. Constantinos Sourkounis of the university’s Institute for Power Systems Technology, head of the German workgroup. The team aims to build an integrated cloud platform to reduce costs and optimize revenue, based on advanced and automated functions for data analysis, fault detection, diagnosis and operation and management recommendations.   

The platform will collect data in real time from sensors and control systems, such as condition and maintenance management. Machine learning algorithms and other AI techniques form the backbone of early fault detection and diagnosis.   

Turkish wind farm operator Zorlu Enerji, a SmartWind partner, will be able to put results of the research directly into practice. “The remarkable thing about this project is the close relationship between research and direct application. We are able to first test theoretical results in our laboratory, and then in a test wind farm run by our partner Zorlu Enerji,” stated Prof. Sourkounis.  

Condition Monitoring Systems Help Manage Remote Wind Turbines  

Machine condition monitoring systems (CMSs) are being applied to wind turbines to help ensure maximum availability and production. 

Mike Hastings, Senior Application Engineer, Bruel & Kjaer Vibro

This is what we call Big Data, which includes both machine vibration and process data under all kinds of operating conditions and with all kinds of wind turbine types and components,” stated Mike Hastings, a senior application engineer with Bruel & Kjaer Vibro (B&K Vibro) of Darmstadt, Germany, writing in Wind Systems Mag. Over the past 20 years, the company has installed more than 25,000 data acquisition systems worldwide, with up to 12,000 of them being remotely monitored. As a result, “B&K Vibro has accumulated a vast database of monitoring data that includes fault data on almost every imaginable potential failure mode,” Hastings wrote.  

As the worldwide installed capacity of wind turbines increases and plays a bigger role in the energy market, so does the need to ensure maximum availability and production of these turbines. Machine condition monitoring is important in this respect and many of the new turbines delivered today already have a condition monitoring system installed as standard. For offshore wind turbines, all have such a system because of their remoteness for maintenance.  

“Big data fits very well into data-driven artificial intelligence (AI) and machine learning (ML) development and implementation,”  Hastings wrote. AI and ML could be implemented for the following condition-monitoring tasks: fault detection optimization, automatic fault identification and prognosis for failure. 

For fault detection, descriptors are configured by specialists, and detection of those is done automatically by the SMA. The individual descriptors and their configuration for fault detection have been optimized to a high level of reliability by diagnostics specialists with many years of experience. “One of the inherent benefits of AI is its ability to sift through vast quantities of CMS data to find patterns,” he wrote. Hidden diagnostics can be found in historical data as well.  

For fault detection before potential failures, the AI can present the results as a listing of several potential failure modes, each with a probability of certainty. “B&K Vibro has in development neural-network automatic fault diagnostic products in the past, and this remains an area of interest for future refinement,” Hastings wrote.  

Read the source articles in ForbesInnovation Origins and Wind Systems Mag. 

Source: https://www.aitrends.com/energy/ai-is-helping-forecast-the-wind-manage-wind-farms/

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Digital ID Verification Service IDnow Acquires identity Trust Management AG, a Global Provider of ID Software from Germany

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IDnow, a provider of identity verification-as-a-service solutions, will be acquiring identity Trust Management, a global provider of digital and offline ID verification software from Germany.

IDnow confirmed that it would continue to maintain identity Trust Management’s Düsseldorf location and will retain its employees as well.

The acquisition of Identity Trust Management should help IDnow with further expanding into new verticals while offering its services to a larger and potentially more diverse client base in Germany and other areas.

The combined product portfolio will aim to provide comprehensive ID verification methods, ranging from automated to human-assisted and from being purely online to point-of-sale. All these ID verification methods will be accessible through the IDnow platform.

Identity Trust Management has established its operations in Germany’s identity industry during the past 10 years, with a solid reputation and portfolio of clients focused on telecommunications and insurance services.

Andreas Bodczek, CEO at IDnow, stated:

“Identity Trust Management AG has built an impressive company both in terms of product portfolio and client relationships. We have known the leadership team for years and have established a partnership rooted in deep loyalty and mutual understanding. We are excited to welcome identity Trust Management AG’s talented team to the IDnow family and look forward to combining the strengths of both companies to create a unified, market-leading brand.”

Uwe Stelzig, CEO at identity Trust Management AG, remarked:

“This combination unites the power of IDnow’s innovative technology with identity Trust Management AG’s diverse set of capabilities to create a differentiated identity verification platform. Together, we will be well-positioned to achieve our joint vision of providing clients with a unique, one-stop solution for identity verification.”

This is reportedly IDnow’s second acquisition in just the past 6 months following that of Wirecard Communication Services in September of last year.

As covered in December 2020, the European Investment Bank (EIB) had decided to provide €15 million of growth funding to Germany-based identity verification platform, IDnow. Founded in 2014, IDnow covers a wide range of use cases both in regulated sectors in Europe and for completely new digital business models worldwide.

The platform allows the identity flow to be adapted to different regional, legal, and business requirements on a per-use case basis.

As explained by the IDnow team:

“IDnow uses Artificial Intelligence to check all security features on ID documents and can therefore reliably identify forged documents. Potentially, the identities of more than 7 billion customers from 193 different countries can be verified in real-time. In addition to safety, the focus is also on an uncomplicated application for the customer. Achieving five out of five stars on the Trustpilot customer rating portal, IDnow technology is particularly user-friendly.”

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Source: https://www.crowdfundinsider.com/2021/03/172910-digital-id-verification-service-idnow-acquires-identity-trust-management-ag-a-global-provider-of-id-software-from-germany/

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China five-year plan aims for supremacy in AI, quantum computing

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China’s tech industry has been hit hard by US trade battles and the economic uncertainties of the pandemic, but it’s eager to bounce back in the relatively near future. According to the Wall Street Journal, the country used its annual party meeting to outline a five-year plan for advancing technology that aids “national security and overall development.” It will create labs, foster educational programs and otherwise boost research in fields like AI, biotech, semiconductors and quantum computing.

The Chinese government added that it would increase spending on basic research (that is, studies of potential breakthroughs) by 10.6 percent in 2021, and would create a 10-year research strategy.

China has a number of technological advantages, such as its 5G availability and the sheer volume of AI research it produces. This is one of the few countries where completely driverless taxis are serving real customers. In that light, the country is really cementing some of its strong points.

However, this may also be a matter of survival. US trade restrictions have hobbled companies like Huawei and ZTE, in part due to a lack of cutting-edge chip manufacturing. The US also leads in overall research, and the Biden administration is boosting spending on advancements for 5G, AI and electric cars. As experienced as China is in some areas, it risks slipping behind if it doesn’t counter the latest American efforts.

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Source: https://www.engadget.com/china-five-year-plan-for-technology-225618577.html

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How Machine Learning is Being Applied to Software Development

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When Elon Musk proposed the idea of autonomous vehicles, everyone assumed it to be a hypothetical dream and never took it seriously. However, the same vehicles are now on the roads, being one of the top-selling cars in the United States.

The applications of artificial intelligence and machine learning are visible in all areas, from Google Photos in your smartphone to Amazon’s Alexa at your home, and software development is no exception. AI has already changed the way iOS and Android app developers work.

Machine learning can enhance the way a traditional software development cycle works. It allows a computer to learn and improve from the experiences without the need for programming. The sole purpose of AI and ML is to allow computers to learn automatically.

Moreover, being a software developer, you might need to specify minute details to let your computer know what it has to do. Developing software integrated with machine learning can help you make a significant difference in your developing experience.

Machine Intelligence is the last invention that humanity will ever need to make!

When it comes to how machine learning and AI help developers, only the sky’s the limit. Taking it even broader, AI has always transformed every industry it has ever entered. Here’s a quick rundown of stats that convey the same:

As the figures stated, artificial intelligence and machine learning are surely transforming the world, and the development industry is no exception. Let’s have a look at how it can help you write flawless code, deploy, and rectify bugs.

AI and ML in Development – How Does This Benefit Software Developers?

Whether you’re a person working as an android app developer or someone who writes codes for a living, you might have wondered what AI has in it for you. Here’s how developers can harness the capabilities of machine learning and AI:

1. Controlled Deployment of Code

AI and machine learning technologies help in enhancing the efficiency of code deployment activities required in development. In the development spectrum, the deployment mechanisms include a development phase where you need to upgrade your programs and applications to a newer version.

However, if you fail to execute the process properly, you need to face several risks including corruption of the software or application. With the help of AI, you can easily prevent such vulnerabilities and upgrade your code with ease.

2. Bugs and Error Identification

With the advancements in Artificial intelligence, the coding experience is getting even better and improved. It allows developers to easily spot bugs in their code and fix them instantly. They don’t have to read their code, again and again, to find potential flaws in their code anymore.

Several machine learning algorithms can automatically test your software and suggest changes.

AI-powered testing tools are certainly saving a plethora of time to developers and help them deliver their projects faster.

3. Secure Data Storage

With the ever-growing transfer of data from numerous networks, cybersecurity experts often find it complex and overwhelming to monitor every activity going on in the network. Due to this, there might be a threat or breach that may go away unnoticed, without producing any alerts.

However, with the capabilities of artificial intelligence, you can avoid issues such as delayed warnings and get notified about bugs in your code as soon as possible. These tools gradually lessen the time it takes a company to get notified about a breach.

4. Strategic Decision Making and Prototyping 

It’s a habit for a developer to go through a hefty and endless list of what needs to be included in a project or code they’re making. However, technological solutions driven by machine learning and AI are capable of analyzing and evaluating the performance of existing applications.æ

With the help of this technology, both business leaders and engineers can work on a solution that cuts down the risk and maximizes the impact. By using natural language and visual interfaces, technical domain experts can develop technologies faster.

5. Skill Enhancement

To keep evolving with the upcoming technology, you need to evolve with the advancement in technology. For the freshers and young developers, AI-based tools help them to collaborate on various software programs and share insights with fellow team members and seniors to learn more about the programming language and software.

Parting Words

While machine learning and AI simplify numerous tasks and activities related to software development, it doesn’t mean that testers and developers are going to lose their jobs. A hired android app developer will still write codes in a faster, better, and more efficient environment, supported by AI and machine learning.

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Future of Mobile Apps: Here’s Everything that’s Worth the Wait

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@devansh-khetrapalDevansh Khetrapal

Devansh writes all about tech. He mainly talks about AI, Machine Learning and Software Development.

This year has been really rough on everyone and I guess we’ve seen enough of that already, but what we’ve also seen during this period are some amazing technological inventions. With phones, however, it’s kinda gotten boring. 

Every year the mobile users are excited because of the new Snapdragon processors and other bleeding-edge specs that these devices are pumping so they can insanely outperform the previous generation smartphones, but are the mobile apps in these phones evolving as congruently?

From the most interactive social media and messaging apps like Facebook, Instagram, WhatsApp, etc, it seems like there isn’t anything beyond that. So what’s next? Well, that’s exactly what we’re going to talk about.

Here’s the Future of Mobile Apps

When we say future of mobile apps, we don’t completely mean that these technologies aren’t already here. In fact, several of these are being incorporated right now. It’s just that these are in their primitive stages of development.

Here they are:

IoT (Internet of Things)

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It’s projected that by 2023, the global spending on IoT technology will be $1.1 trillion. Through Machine Learning and integrated Artificial Intelligence (AI), it has the potential to not just enable billions of devices simultaneously but also leverage the huge volumes of actionable data that can automate diverse business processes.

What does this entail for the future of mobile apps? Well, get ready to be able to control your car, thermostats, and kitchen appliances through your mobile devices. The IoT is being presently used in Manufacturing, Transportation, Healthcare, Energy, and many other industries.

Artificial Intelligence

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AI will single handedly change the future of mobile app design.

Mobile apps are coded to operate within the constraints of certain parameters, the implications of which have to be predefined. Simply put, if you’re browsing for a homestay on Airbnb, the results you see are based on predetermined parameters like your location, your size, and amenity requirements.

Those predetermined parameters, with the assistance of AI, can evolve to a point where you’ll be able to get results based on your preferences that it learned along the way, such as the kind of accommodation you usually prefer, the kind of facilities you need, and may even suggest you buy a place because your favourite restaurant is nearby. 

Augmented Reality (AR) / Virtual Reality (VR)

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AR and VR are attracting a high amount of investments and are forecasted to reach $72.8 billion by 2024. We can already see their success in the gaming and entertainment industry with Pokemon Go, Sky Siege, Google Cardboard, iOnRoad, and Samsung Gear VR.

Brands like Jaguar Land Rover and BMW have already started using VR to conduct design and engineering evaluation sessions to finalize their visual design before they spend any money on manufacturing the parts physically.

Gradually, you’ll be able to make more immersive simulations that can revolutionize any form of architecture involved in it.

Cross-Platform Development

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The future of mobile apps will definitely make native app development obsolete. Currently, React Native offers exceptional flexibility while developing Android and iOS apps. This will save tons of time since you won’t have to develop 2 separate apps.

More importantly, cross-platform app development will eliminate the downside of having to compromise on certain nuanced features. All of this will gradually make the app development process a lot cheaper, simpler, and time-saving.

5G

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Imagine if you could download an entire Netflix series in about 10 seconds. That’s how great the potential of 5G is. Theoretically, it has the potential to reach speeds of 10 Gigabits per second and not just high speeds, but low latency. Even in its infancy, we can witness 5-6 Gigabits per second on our smartphones in the US.

Speaking of the future of mobile apps, well, fast internet would mean faster download and upload speeds, which changes everything from Augmented and Virtual Reality, IoT, supply chain, transportation, smart cities, because everything can happen in real-time because of the latency of merely 2 – 20 milliseconds.

Blockchain

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Blockchain is a term being thrown around a lot lately. Well, it’s a technology that allows data to be stored globally on thousands of servers. Now because it’s decentralized, completely transparent, and immutable, it becomes difficult for one user to gain control over the network.

This means that it’s almost impossible for anyone to hack into blockchain and make changes. The future of app development depends highly on blockchain technology because of its ability to deliver highly secure mobile apps.

Wearable Devices

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You see wearables, or “smartwatches”, being popularly used as fitness bands these days. They’re smart in the sense that they’re able to tell you your heart rate, blood oxygen, count steps, are able to notify you in case of irregular heart rhythms. And of course, it does tell time.

The tech, when combined with IoT, opens up so many doors. Be it checking appointments, making calls, sending messages, getting reminders, it’s just scratching the surface. This tech has a huge potential to evolve and can eventually eliminate the need to use a smartphone. 

Wrapping Up

It’s pretty assuring that the future of mobile apps is ridiculously exciting. We can only imagine how the user experience is going to unfold. 

Be it data visualization with the help of VR and AR, or maximization of convenience with the help of wearables, they’re all going to bring about a massive change in the mobile app development trends. Hopefully, we’ve helped you scratch that itch of curiosity and you got to learn about how our interaction with the world is about to change.

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