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For quite some time, the term “machine learning” and “deep learning” seeped its way to the business language, especially when it is related to Artificial Intelligence (AI), analytics and Big Data. Frankly, the approach directed to AI which provides a great promise with regard to creating self-teaching and autonomous systems that can revolutionize various industries. 

What is Machine Learning (ML)?

One of the subfield of AL is machine learning. Here the basic principle is that machine, collect data and they learn it for themselves. No doubt, this is the most awesome tool of the business’s Artificial Intelligence kit. One of the interesting advantages of the ML is that you can easily apply the training and knowledge received from analyzing huge data set to perform various functions and excelling at them like speech recognition, facial recognition, translation, object recognition, and various other tasks.    

Compared to the hand-coding a given software tool filled with specific instructions which can be used for completing the task, the ML provides a suitable system to understand the pattern by itself and make the required predictions.

What is Deep Learning?

Frankly, a subset of the ML is called as deep learning. Here one utilizes ML techniques for solving various real-life issues, and this is possible by accessing the neural networks which easily help in stimulating the decision-making of human beings. In addition, deep learning is kind of expensive and one will need extensive data sets to train. This is because there are various number of parameters that one might need to have an understanding, possible by learning about the algorithm. Thus, this can be present at the initial stages and create various kinds of false-positives.

To have a fair understanding, let’s check how deep learning algorithm can be used for understanding how a cat looks. So, a huge amount of data set of pictures is used for underlying the basic details which separates the cat from other like panther, cheetah, fox etc.

How Machine Learning And Deep Learning Affects Job

There is a kind of hysteria of doom-and gloom surrounding the machine learning AI. The majority of it is all about how people will be out of work, as there are quite successful stories where machines were able to carry out specific job-related works and bought about extensive results in it.  

Indeed it has become a huge paranoia, but it turns out that machine learning only performs tasks, and not the job. Of course, many tasks constitute a job but ML programs are not much flexible.

However, it doesn’t mean that both machine learning and deep learning will not affect your job, as they have already done and will simply continue to do so. Most importantly, whether it will be a benefit or threat will depend on how you are going to react when you identify it.

No doubt, there are quite a lot of reasons on how white-collar jobs can be a great invitation for deep learning and other related technologies. There are various experts who feel that the professional impact which AI and deep learning along with other automated technologies can drastically affect the work force count.

Conclusion

In short, there have been certain reactions or changes with regard to how machine learning and deep learning brings. It has drastically reduced the role of various professionals who are considered as knowledge gatekeepers. Plus, there has been a positive trend towards proactive and reactive services. 

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Not far from San Francisco International Airport, San Bruno is a quaint middle-class residential suburb, yet underground in San Bruno was a gas pipeline controlled by SCADA software that used the Internet as its communications backbone. On Sept. 9, 2010, a short circuit caused the operations room to read a valve as open when it had actually closed, spiking the readings coming from pipeline pressure sensors in different parts of the system. Unbeknownst to the families returning home from ballet and soccer practice, technicians were frantically trying to isolate and fix the problem. At 6:11 pm, a corroded segment of pipe ruptured in a gas-fueled fireball.

The resulting explosion ripped apart the neighborhood. Eight people died. Seventeen homes burned down. The utility, PG&E, was hit with a $1.6 billion fine.

The accident investigation report blamed the disaster on a sub-standard segment of pipe and technical errors; there was no suggestion that the software error was intentional, no indication that malicious actors were involved. “But that’s just the point,” Joe Weiss argues. “The Internet of Things introduces new vulnerabilities even without malicious actors.”

Joe Weiss is a short, bespectacled engineer in his sixties. He has been involved in engineering and automation for four decades, including fifteen years at the respected Electric Power Research Institute. He has enough initials after his name to be a member of the House of Lords—PE, CISM, CRISC, IEEE Senior Fellow, ISA Fellow, etc., all of which speak to his expertise and qualifications as an engineer. For instance, he wrote the safety standards for the automated systems at nuclear power plants.

The problem, Weiss claims, is using the internet to control devices that it was never intended to control. Among these are industrial systems in power plants or factories, devices that manage the flow of electricity through the energy grid, medical devices in hospitals, smart-home systems, and many more.

Continue reading this article on Quartz.

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Interview: 3M's Road to IoT

When you think of 3M you immediately think of Post-It Notes or Scotch tape. If you're old school or local, maybe you know that 3M was founded as Minnesota Mining and Manufacturing Company. But have you ever thought about this company, which has $30 billion in annual sales, employs 88,000 people worldwide and produces more than 55,000 products, as an IoT company? All that material science must have an opportunity in IoT. 

For that we turned to Dr. Jennifer F. Schumacher, the technical supervisor and co-founder of the Computational Intelligence group in the Corporate Research Laboratory at 3M Company. She manages a team and portfolio of 35 new technology Introduction programs which are mechanizing, electrifying, and digitizing 3M materials. Her current initiative is to drive technology platform development in computer vision, machine learning, and deep learning

When people talk about 3M, the first thing that usually comes to mind is Post-it® Notes, and they might not think about 3M at the ready for future advances. How is a materials science company playing in the IoT space?

They say you’re never more than ten feet from a 3M product – that is a lot of potential “things” we could integrate into the IoT space. In fact, we have already digitized the simple Post-it® Notes through the Post-it® Plus App, it integrates physical and digital notes and lets you connect with others to share, for example, outputs from brainstorming sessions.  

What have been some of the roadblocks you and your team have faced in convincing people that a materials science company is also a tech and data science company? How are you working to overcome this?

The data science/machine learning group at 3M is relatively new, and as such, many of the technologies we are developing are not ready for public disclosure yet. Therefore, it is difficult to communicate externally that 3M is actually working on these things, and difficult to recruit talent in this high-demand skillset space. We are addressing this by attending key conferences and interacting more with universities, for example we are sponsoring a seminar series at the University of Wisconsin – Madison.

You have a PhD in neuroscience and an expertise in human vision. How does this apply to your work at 3M when it comes to data science and the IoT?

I initially leveraged my expertise in human vision to develop the 3M™ Display Quality Score – a metric that predicts how well a human will prefer a digital display based on its resolution, contrast, color saturation, etc. I then translated this skillset from understanding how people see, to teaching computers how to see, or ‘computer vision’. The opportunity to learn new things and adapt skillsets makes the job fun.

I believe that in a world full of data, it will be the ones that ask the right questions that have the advantage. Formal training in science has helped me hone my skills in asking the right questions so the most efficient and effective experiments can be carried out first. Much of my formal training has been multi-disciplinary, and I think this breadth of knowledge and cross pollination of ideas and concepts is the key to innovation. 3M’s approach to science is aligned to this approach of cross pollinating ideas and heavy collaboration.

Explain how machine learning can be applied to 3M products?

Machine learning thrives on data. 3M products are, or could be, producing data. We can then leverage the insights from the algorithms to enhance the product itself (for example, the Victory Series™ buccal tubes, which were optimized for fit) or to create an entirely new solution (we have several in the pipeline, so stay tuned!)

What can 3M do to adapt to the current digital economy and help your customers adapt?

There is a global trend of greater economic opportunity in service-based business models rather than product-based. I think 3M will need to start adapting some of these service-based models to adapt to the current digital economy, and we can do so by providing complete solutions (products + services) to our customers.

What do you think the most pressing challenges are when it comes to IoT? How is 3M working to solve these?

The most pressing challenge I see is finding the most impactful applications – there are plenty of ‘cool’ factor solutions or products, but what are the sustainable solutions, the ones that significantly improve the quality of life or enable new capabilities? 3M’s vision statement concludes with ‘3M Innovation Improving Every Life’, so I think we align our research goals with significant global technology trends and sustainability issues that would have this broad impact.

 What excites you most about the future of IoT?

The more trivial decisions that a smart system can take care of, the more time I can spend dreaming and implementing what the next technology to improve lives will be.

 

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Not all Devices are IoT or IIoT

Introduction

Business opportunities created by Internet of Things (IoT) and the Industrial IoT (IIoT) are among the most
debated topics, as these are designed to function in a broad range of consumer and industrial applications.
Manufacturers of IoT components believe in this new trend, but many of them still not understand the essence
of the IoT concept. In reality, not every controlled device is an IoT nor IIoT.

The IoT/IIoT concept is a communication-based eco-system in which control devices, CCTV cameras and
industrial sensors communicate via the Internet with cloud-based computer systems and data sources, and
the result of this process is displayed on a computer screen, smartphone or used for optimal activation of a
process. Through an IoT/IIoT ecosystem you may boost productivity and achieve unique benefits. Examples
of IoT/IIoT include applications such as; remote operation of home appliances, medical devices, check on
availability of a product in a store, warnings of unusual conditions and malfunctions and more.

Leading market research firms already estimate that by 2020 there will be over 20 billion devices worldwide,
defined as part of IoT/IIoT systems. Although the forecasted number is growing every year, it is not clear
whether these figures correctly refer to what can be and what cannot be considered IoT or IIoT. It is strongly
recommended that decision factors such as outlined below shall be taken into consideration.

Devices not considered as IoT/IIoT

In reality not all devices can be accepted to the “IoT/IIoT Club”. Through the following three examples I will
try to clarify the main considerations referring to this topic.
a) You purchased a home air conditioner activated by a smartphone or a web based application. If the
packing label shows “Wi-Fi-Ready”, you can do that, but it will not necessarily make it an IoT, since remote
activation by itself is not a sufficient condition to call it an IoT.
b) You consider to add a vibration sensor to a large water pump or gas turbine to diagnose a malfunction.
This is not an IIoT, as the vibration sensor device is reporting to a special PLC and an ICS computer
which control the operation of that machinery and may stop it if a fault is detected.
c) You purchased a CCTV camera, which is connected to a home computer or a VCR for security
surveillance. This is also not an IoT, because 24/7 loop recording system does not require additional data
available from cloud based resources and not require cloud based computing.

Devices considered as IoT/IIoT

Here are three commercial, consumer oriented and industrial examples, that according to listed explanations
are considered appropriate for being considered as IoT/IIoT ecosystem.
a) Computerized control of a washing machine. The IoT ecosystem using the built-in controller which
support the decision related to optimal starting of the washing process. Consequently, the IoT controller
device communicates with cloud based data sources related to the following considerations:
• Is there a report from the electric company on unusually high loading of the power grid at the
neighborhood? If yes, the washing process is delayed.
• Is it forbidden to cause unusual noise in a residential area such as may be caused by the washing
machine? If yes, the washing process is delayed
• Is there sufficient amount of hot water from the sun-roof boiler as required for the washing? If not, the
activation is delayed until electric heating of the water is completed.

The operation of a solar power plant can be controlled by an IIoT process. After the power plant receives
a request to start supplying power, the IIoT ecosystem system checks the following conditions:
• Is the forecasted intensity of sun-rays during the next few hours adequate to generate the required
energy to the grid? If not, the power plant activation is canceled.
• Are there alternative electric power resources that are more suitable to generate electricity for the
requested period? If yes, the power plant activation is rejected.
• If there are no other alternatives, the solar power plant will be activated with limiting conditions, and
the power grid operator will be advised accordingly.
c) An order is received to purchase a certain type meat for home use. Following this requirement, the
customer can start and IoT-based search using his smartphone:
• In which food chain is this item available, and what is the ticket price
• Which stores are active during the hours when the purchase is required
• The outcome of that process shall be a list of options sent to the customer
From the three examples listed above you may learn that the IoT/IIoT concept is applicable when it is
impossible to perform a simple interaction between the requesting entity and the device which provides the
service. IoT/IIoT systems allow such interactive process through cloud-based data resources.

Is there a reason for concerns?

Definitely yes, because huge amounts of cheap IoT components without professional configuration and
without cyber security measures will flood the internet network and allow cyber-attacks from all directions and
for any purpose. Can ordinary home owners properly configure these devices, replace the default password
and detect DDoS-type security breach? Of course not, and that's the problem.
Today, as a result of strong expectations towards IoT market, none wants to remember the early 2000’s and
the dot.com bubble. Then, well-known and professional companies invested billions of dollars in products
that did not provide benefits for which users were willing to pay. The benefits came only years later, and then
more resources were required to create new business models in order to recover their losses.

Summary

We all hope for huge IoT/IIoT deployments in the future, as this is good for users, vendors and also for
innovation. But…., anyone considering to develop a new IoT/IIoT ecosystem, shall focus on finding a real
need and properly design a cloud-data based solution that delivers significant benefits.
Cyber protection for any IT and ICS architecture consists of three essential elements that are achievable: a)
the use of security technologies, b) strict adherence to policies, and c) careful user behavior. This is also true
for IoT/IIoT ecosystems. Innovative technologies, components and architectures that will include cyber
protection as part of the IoT/IIoT ecosystem at no extra cost, will definitely drive the success.

Photo credit Martin Košáň via Flickr.

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Top 6 Skillsets Required for IoT

IOT is a system of interrelated ‘things’ that are connected over a network and can send and receive data over it. A ‘thing’ in IOT can be thought of any man made or natural thing that can be assigned an IP address, for example, a man have a heart monitor implant or a car having sensors to alert the driver of any abnormal condition.

What do I need to have?

According to a survey, as of now we just have 300,000 IOT experts, but we might need as much as 4.5 million IT people having IOT expertise in future. IOT in a midst of explosion, but the problem is the lack of talent regarding this field. If you will have the following skill sets of IOT will surely benefit you in future.

  1. Machine Learning- expertise in this field will take you a long way. Machine learning algorithms make the machines smarter by giving them the ability to predict by recognizing the data patterns. According to an IT expert this skill is 220% more in demand in the market because employers want to harvest the large amount of information using the machines and their sensors.
  2. AutoCAD- this is software that enables you to engineer appliances and have a very strong growth as the complexity of the machinery related to IOT goes on increasing. Smart and connected things often require a whole new set of thinking principles and hence there can be a change in the design at the very last moment. AutoCAD helps in making any change even at the last moment quite efficiently and expertise in this field is said to have a weightage of 108% when compared to other skills.
  3. Security infrastructure- with the presence of such sensitive information over a network the apex concern of any employer has to be its security. Due to the complexity of the IOT devices the endpoint security gives a lot of attention. Everything that is available on a network is prone to theft and a risk of information leak, hence having a skill around security comes as a critical factor for your success in it.
  4. Data management (Big Data) - IOT has an enormous amount of data revolving and every day there is an addition to it. Companies need to collect all the data and also filter the repetitive one. The data needs to be so managed that it gives an accurate estimation of the business so that ways to growth can be taken out of that. Using artificial intelligence along with big data can help the companies get the results faster and more efficiently.
  5. Electrical engineering- the future needs an apt team up of software engineers and electrical engineers. Electrical engineers are needed to help with embedded device development for mobile applications and for radio frequency in order to get a smooth and effective mode of communication.
  6. Circuit design- connected devices are forcing the companies to adjust and adapt chip design to meet their requirements. For example- systems that require power for a longer span of time are required to have a chip that takes care of their power consumption and keep it optimized.

Conclusion

IOT is a revolution in IT that will certainly increase the number of jobs that are available in this sector. Moving with time and learning new things is the only way to proceed and become succeed.

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There is an ongoing transition from a world where having an internet connection was sufficient, to a world where ubiquitous connectivity is quickly becoming the norm. The ability to gather and transport data at high speeds from anywhere is leading to increased automation, smart-everything (vehicles, homes, appliances – you name it), and a standardization of languages and protocols that make the possibilities nearly endless.

Recently, IEEE and Eclipse Foundation completed surveys that provided a snapshot on tools, platforms and solutions being used by engineers and programmers alike to build the Internet of Things. According to Joe McKendrick for RTInsights.com, there were several notable conclusions to be drawn from the results, including the revelation that, of the 713 tech professionals surveyed, nearly 42 percent said their companies currently deploy an IoT solution, and 32 percent said they will be deploying/working with an IoT solution over the next 18 months. Additionally, RT Insights writes:

“In terms of areas of concentration, 42% report they are working with IoT-ready middleware, while 41% are concentrating on home automation solutions. Another 36% are working with industrial automation as part of their IoT efforts. One-third are working on IoT for smart cities, and the same number are building smart energy solutions.”

An interesting note from those conclusions is that 36 percent are working with industrial automation as part of their IoT efforts. Earlier this year, we predicted that Industrial IoT (IIoT) app development would outpace consumer IoT apps, and although this sample size is somewhat limited, it still bodes well for the development of the IIoT sector that is just starting to come into its own.

Among IoT developers, there has been a bit of debate over the programming languages that best suit IoT apps. There are situationally appropriate uses for the main languages, but currently, the majority of developers prefer Java and the C language. For developers, being able to build out IoT apps that can work across platforms is a giant step toward standardization. Specifically, in the Industrial IoT, being able to build apps that can function at the Edge to enable smart data collection is a becoming an unofficial mandate for any companies hoping to transition legacy OT operations into the IT/OT convergence movement taking place across critical industries.

Of course, building apps is a meaningless task if the hardware being deployed can’t host those apps, a finding that was demonstrated by the survey:

Hardware associated with IoT implementations include sensors, used at 87% of sites, along with actuators (51%), gateways and hub devices (50%), and edge node devices (36%).

This Edge functionality and sensor deployment are two pieces that are driving the adaption of IoT technology across industries that have traditionally relied on data as the main tool for decision making. However, with smarter hardware, these industries now have the opportunity to improve the efficiency of that decision making – a transformative capability in the industrial realm.

Join FreeWave’s ZumLink IPR Pilot Program!

IIoT App Development with Java, Python and C++ languagesWhat if you could…..

  • Collect, analyze and react to data in real-time at the sensor edge?
  • Reduce BIG DATA that clogs data pipelines?
  • Minimize the cost of expensive PLCs?
  • Control your sensor at the closest touchpoint?

The ZumLink IPR App Server Radio combines 900 MHz wireless telemetry with the ability to program and host 3rd party Apps for intelligent control and automation of remote sensors and devices. To participate in the pilot program, visit: http://www.freewave.com/zumlink-ipr-pilot-program/.

Pilot Program participants:

  • Receive a complimentary hardware/software Dev Kit
  • Get support from FreeWave software engineers
  • Should have App developer’s skills

Let’s discuss:

  • Use cases that would help you or your organization solve a problem
  • Problems you would like to solve
  • Developers that could build this App
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Antarctica inhabits a unique place in the human exploration mythos. The vast expanse of uninhabitable land twice the size of Australia has birthed legendary stories of human perseverance and cautionary tales about the indomitable force of nature. However, since those early years, Antarctica has become a rich research center for all different kinds of data collection – from climate change, to biology, to seismic and more. And although today there are many organizations with field stations running this data collection, the nature of its, well, nature still presents daily challenges that technology has had a hand in helping address.

Can You Send Data Through Snow?

British Antarctic Survey (BAS) – of recent Boaty McBoatface fame – has been entrenched in this brutal region for over 60 years, the BAS endeavors to gather data on the polar environment and search for indicators of global change. Its studies of sediments, ice cores, meteorites, the polar atmosphere and ever-changing ice shelves are vitally important and help predict the global climate of the future. Indeed, the BAS is one of the most essential research institutions in the world.

In addition to two research ships, five aircraft and five research stations, the BAS relies on state of the art data gathering equipment to complete its mission. From GPS equipment to motion and atmospheric sensors, the BAS deploys only the most precise and reliable equipment available to generate data. Reliable equipment is vital because of the exceedingly high cost of shipping and repair in such a remote place.

To collect this data, BAS required a network that could reliably transmit it in what could be considered one of the harshest environments on the planet. This means deploying GPS equipment, motion and atmospheric sensors, radios and more that could stand up to the daily tests.

In order to collect and transport the data in this harsh environment, BAS needed a ruggedized solution that could handle both the freezing temperatures (-58 degrees F in the winer), strong winds and snow accumulation. Additionally, the solution needed to be low power due to the region’s lack of power infrastructure.

 The Application

Halley VI Research Station is a highly advanced platform for global earth, atmospheric and space weather observation. Built on a floating ice shelf in the Weddell Sea, Halley VI is the world’s first re-locatable research facility. It provides scientists with state-of-the-art laboratories and living accommodation, enabling them to study pressing global problems from climate change and sea-level rise to space weather and the ozone hole (Source: BAS website).

The BAS monitors the movement of Brunt Ice Shelf around Halley VI using highly accurate remote field site GPS installations. It employs FreeWave radios at these locations to transmit data from the field sites back to a collection point on the base.

Once there, the data undergoes postprocessing and is sent back to Cambridge, England for analysis. Below are Google Maps representation of the location of the Halley VI Research Station and a satellite image (from 2011) shows the first 9 of the remote GPS systems in relation to Halley VI.

The Problem

Data transport and collection at Halley VI requires highly ruggedized, yet precise and reliable wireless communication systems to be successful. Antarctica is the highest, driest, windiest and coldest region on earth and environmental condition are extremely harsh year round. Temperatures can drop below -50°C (-58 °F) during the winter months.

Winds are predominantly from the east. Strong winds usually pick up the dusty surface snow, reducing visibility to a few meters. Approximately 1.2 meters of snow accumulates each year on the Brunt Ice Shelf and buildings on the surface become covered and eventually crushed by snow.

This part of the ice shelf is also moving westward by approximately 700 meters per year. There is 24-hour darkness for 105 days per year when Halley VI is completely isolated from the outside world by the surrounding sea ice (Source: BAS Website).

Additionally, the components of the wireless ecosystem need to be low power due to the region’s obvious lack of power infrastructure. These field site systems have been designed from ‘off the shelf’ available parts that have been integrated and ‘winterized’ by BAS for Antarctic deployment.

The Solution

The BAS turned to wireless data radios from FreeWave that ensure uptime and that can transport data over ice – typically a hindrance to RF communications. Currently, the network consists of 19 FreeWave 900 MHz radios, each connected to a remote GPS station containing sensors that track the movement of the Brunt Ice Shelf near the Halley VI Research Station.

The highly advanced GPS sensors accurately determine the Shelf’s position and dynamics, before reporting this back to a base station at Halley VI. Throughput consists of a 200 kilobit file over 12 minutes, and the longest range between a field site and the research station is approximately 30 kilometers.

Deployment of the GPS field site is done by teams of 3-4 staff using a combination of sledges and skidoo, or Twin Otter aircraft, depending on the distance and the abundance of ice features such as crevassing. As such, wireless equipment needed to be lightweight and easy to install and configure because of obvious human and material resource constraints.

In addition, the solution has to revolve around low power consumption. FreeWave radios have more than two decades of military application and many of the technical advancements made in collaboration with its military partners have led to innovations around low power consumption and improved field performance. The below image shows an example of a BAS remote GPS site, powered by a combination of batteries, a solar panel and a wind turbine (penguin not included).

FreeWave Technologies has been a supplier to the BAS for nearly a decade and has provided a reliable wireless IoT network in spite of nearly year-round brutal weather conditions. To learn more, visit: http://www.freewave.com/technology/.

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5 Blockchain Technologies To Watch For In 2017

For a couple of years, Blockchain which is the underlying technology of Bitcoin is gaining a huge amount of popularity. As there are various DAPPs and mind-blowing technologies written each week, somewhat you can say that there are huge amount of new aspects to lookout for.

For any individual who is simply starting with blockchain technology or any kind of development related to it. They will have numerous choices to select from. So, let’s check some of them.

Interesting Blockchain Technologies

1) Bitcoin

Introduced first by Satoshi Nakamoto in the year 2008 and written in his white paper, it simply caught the attention of the mainstream media. This so called Britcoin’s blockchain utilizes UTXOs (Unspent Transaction Outputs) mechanism. Here the major components related to the Bitcoin technology is Descriptions, Transaction ID, Inputs and Outputs and Meta data. Each transaction that you receive will have certain inputs and it will even create some outputs too. In addition, you can even embed certain data in such transactions. 

2) Ethereum

The brainchild of Vitalik Buterin, Etheruem’s first public implementation is called as Frontier. This was released somewhat in the mid-2015. There is a Turing-whole virtual kind of machine called EVM. Do you know the major improvement with regard to the Bitcoin blockchain? It is the basic ability to develop Smart Contracts.

There are various languages present in the Ethereum such as Solidity, LLL, Serpent, etc which the common supported languages present in this community are.  There has been a growing interest for the Ethereum from various industries and communities. One of the major innovations present in the Ethereum is the easily and basic simplicity of using smart contacts to develop tokens. This can represent certain physical assets like Gold, Fiat currency, computational hours, company shares, and the list goes on.

3) Hyperledger

The Hyperledger is one of the incubation project utilized for DLT (Distributed Ledger Technologies) by the Linux Foundation. There are three major incubation projects related to the Hyperledger which are Sawtooth, Fabric, and even Corda.

Even though the Fabric is the implementation of the IBM, still the Sawtooth is created by the Corda and Intel. Here, the Fabric is quite necessary as a private version of the blockchain, where the nodes of the network will work and form a private chain and even help in sharing data.   

4) Ripple

One of the blockchain technologies which simply focus on financial applications and settlement is the Ripple. This is created from the ground up, making it easy for you integrate with the existing infrastructure of the banking sector without distributing the integration of the overhead.

For few years, Ripple, the private firm has been developing this so called protocol and they have seen some good results from customers in terms of financial institutions and banks. Here the basic protocol is ILP (Interledger Protocol) and this simply helps the banks to make payment through various ledgers and networks all around the world.

5) Zcash

Here the latest shiny thing present in the land of the Bitcoin and blockchain is the Zcash. The best and easiest followers of the Zero-Knowledge proof are the Zcash. There have certain criticisms of this technology by users in terms of the public nature of transactions.

All the basic transaction can be easily traced to the original address and this simply leads to a huge issue, like revealing the amount of assets one has.  However, as it is built on the Britcoin Core’s codebase there is less chance for your personal information getting revealed.

Conclusion

In short, it is simply clear that such technology i.e blockchain is only attractive to certain tech companies but there are certain major players like IBM and Microsoft who have been taking notice of it.  So, let’s wait and watch how this works. 

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From wind turbines to your washing machine, the IoT is all the rage, and everyone wants their piece of the pie. Monetization and creating business value, not to mention profits, is the holy grail for the IoT. But who is really making money on the IoT and where are the most lucrative opportunities?  For that we turned to Mike Fallon, Senior Advisor of the IoT Transformation Advisory Practice at PTC. Mike is responsible for delivering frameworks to companies that address the how of IoT monetization – specifically for CIOs and other C-suite executives.

How can organizations profit from the IoT? 

Today, we are seeing two primary areas of opportunity for monetizing the IoT: operational efficiencies and new revenue generation. Operational efficiencies are of interest because of how the IoT allows you to organize and use data. In manufacturing, for example, the IoT can help to prevent unplanned downtime, capture real-time insights regarding production and operation, and integrate data across an extended supply chain.

Of even greater interest, right now, is new revenue generation, particularly for hardware companies that see opportunities to introduce digital services into their product offerings. Since the economy has rebounded from the recession, C-level executives and shareholders are very focused on growth. With so many digital transformations happening right now, traditional manufacturers and hardware companies are looking to these digital services as a way to generate new revenue and bring value to those transformations that are underway.

Why is it so hard to monetize the Internet of Things? 

We see a handful of common challenges as we talk to companies about monetizing their IoT strategies. One of the main challenges is developing a strategy and achieving alignment across key stakeholders in the organization. This often carries over to another challenge that we see – companies taking an inside-out approach that prioritizes the provider’s goals over what the end customer needs. Many companies aren’t asking themselves important questions about their strategies, such as, “How do we ensure that the customer or user cares enough about our service to want to pay for it?” The most successful companies are the ones that prioritize the user’s needs and the user experience.

Further, this idea of forming the right strategy can extend to the company’s go-to-market execution. This can be particularly challenging for companies that traditionally sell hardware and are trying to introduce digital services to their customers as part of new offerings. Whenever new offerings or services are introduced, the challenge of how to best market them typically follows.


There is no neat one-size-fits-all monetization model for the IoT, not least because the needs of different companies vary hugely. What are some of the successful models that you have seen, both in consumer and industrial sectors of IoT?

If we look at new revenue monetization, the key question that a company needs to answer as it shapes its business model is, “What is my customer or user willing to pay and how would they like to buy?” Many companies get trapped in what we could describe as more traditional thinking, often asking themselves, “How do I want to bill the customer?” along with other internal-oriented perspectives. These factors won’t be ignored, but the best business models are the ones that customers adopt rapidly because it’s clear to the customer how the software or service helps them do their job easier, enables them to do more than they could previously, and helps them achieve their own goals and objectives.

If companies stick to an inside-out approach that prioritizes their own needs over those of the customer, they’re potentially setting themselves up for failure because they likely aren’t doing all that they can to achieve the customer adoption needed to be successful.

As our publication name suggests, we focus on the Internet of Things, specifically the Industrial IoT. How do you plan to roll your product out for IoT devices? Can you provide examples?  

Right now, the IoT space is being defined by the platform. More and more companies are adopting IoT platforms, like the ThingWorx Industrial IoT platform from PTC, for their IoT initiatives. The best platforms provide companies with the capabilities that they need to be successful with their IoT strategies, such as application enablement, machine learning, industrial connectivity, and, increasingly, augmented reality.

Platforms allow companies to rapidly iterate as they build new IoT applications and solutions. This is crucial right now, as the IoT space is still maturing and companies are determining what works and what is needed in the market. Platforms also help companies future-proof their IoT strategies, as the best platforms will continue to add new capabilities and features to match the evolution and maturity of the market.

PTC makes ThingWorx available to partner companies and solution builders, which, in turn, use the platform to develop new solutions and applications that they sell to end customers. These solution builders can be system integrators, hardware companies, or other software companies. PTC has developed a robust ThingWorx partner ecosystem that offers companies multiple ways to take advantage of the platform and its many benefits.

Additionally, PTC uses ThingWorx for its own internal development of new connected solutions that are sold through its well-known solutions business, focused primarily on computer-aided design (CAD) and product lifecycle management (PLM). An example is the Navigate application from PTC – a PLM-focused solution that has emerged as one of the best-selling solutions in PTC history.

Talk to us about pricing models. What are they, which are the most popular and which ones do you see has having the longest and greatest run?   

The IoT Transformation Advisory Practice at PTC spends a lot of time looking at pricing and business models. One of the things that we most often emphasize to our customers is, once the strategy around deciding what to connect and what data you can collect is set, do not try to copy and paste business models. There is rarely a one-size-fits-all approach when it comes to IoT business models, primarily because each customer could have a different set of needs and/or objectives. At a higher level, this is where companies tend to struggle with generating new revenue through IoT. The pricing models that work start with understanding the needs and aspirations of the user of the service. The company needs to understand what the user is willing to pay for and the specifications that are included.

In today’s world, opting in and out of digital services is commonplace – it could be something as simple as cancelling a Spotify account or it could reach the level of an Industrial IoT service. The pricing models with the greatest and most sustained adoption will fit the evolving needs and expectations of the customer. Because the companies providing the new services will likely have insights into their customers’ operations, they’ll have the opportunity to have access to changing behaviors and shifts in their customers’ business.

As we’ve seen our customers’ journeys evolve, we’ve started to see innovation possibilities in the context of outcome-based design as well. Outcome-based design will continue to be important because it helps to align the design and engineering teams and more closely connects them to user insights that drive more targeted innovation and a faster time-to-market, all in the context of the customer experience.

Who in the organization plays the most important role creating an IoT monetization strategy?

It seems that there’s a common misconception that there’s one person who is most crucial to the development of an IoT monetization strategy. To be successful with a monetization strategy, it can’t fall solely on the shoulders of the CIO, CMO, CTO, etc. There needs to be a cross-functional team that provides input from each member’s respective discipline. IT, marketing, and finance can all play important roles in the development of the strategy, and it’s important that there’s a balance between these perspectives. When I work with customers, establishing a cross-functional view is a critical first step that I help them with.

If the CIO or another executive is in the lead role, he or she should reach across the hall and ensure that team members that spend all day thinking about customers and have direct engagement with customers are part of the team. This could be someone as high up as the CMO or it would be a more focused product marketing manager or director. Marketing will need to be a part of the solution to help guide the go-to-market strategy and execution.

So if a company wants to begin monetizing IoT, what’s the go-to-market approach they should take?

I work with companies that, for centuries, have been successful building their businesses with business models largely driven by the sale of physical products. While aftermarket services have also been a source of value (spare parts, component upgrades, warranty services, etc.), the strategy by the naming associated with “after” has been just that.

My background is working with companies that produce physical products. Now that I am in software, I have gained an appreciation for the importance of communicating in advance the availability of new services. This comes back to the critical role that marketing plays. Traditional and forward-thinking marketing efforts, along with the use of insights that you have from the customer and user are vital to connecting with your market.

As we think about how these new services will be sold, it’s important to consider that most sales executives could be used to getting paid in a certain way for selling a physical product. If the new service that is introduced requires a new selling strategy – perhaps one that requires more support from marketing, inside sales, or aftermarket services – both the learning curve and overall motivation for the sales executive needs to be considered.

If your strategy is to drive rapid adoption of the new service from your customers, at least at the initial launch of the offering, having a team that is dedicated to service with a focused understanding of the offering and a focused incentive or rewards system will typically drive adoption more rapidly and will have access to learnings that you may want to incorporate into the service as you iterate. Remember that your customer’s and user’s needs are in constant evolution and continuing to meet and anticipate those needs is critical to the overall strategy.

Anything else you’d like to add?

To summarize, there are six main components to think about when developing an IoT monetization strategy:

  • Strategy – Understand the objective in terms of a broad adoption strategy versus a more selective, premium offering for selective customers.
  • User-Centric – Approach the strategy from a user-focused perspective and build your design for revenue off of this.
  • What to Charge – Leverage learnings from user-engagement and feedback to understand pricing models.
  • How to Charge – Put a focus on making the service easy to adopt or test out.
  • Go-to-Market – Remember that this is a team game, driven by the cross-functional group that has developed the overall strategy. Tell a user-centric story and consider who sells and how to keep incentive and reward systems from being barriers.
  • Technology – Ideally, the technology that’s offered will have robust capabilities, allow for secure, rapid iteration and scaling, and allow for integration to other business and enterprise systems.
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Top 5 uses of Internet of Things!!

While many organizations are creating tremendous value from the IoT, some organizations are still struggling to get started.  It has now become one of the key element of Digital Transformation that is driving the world in many respects.
It is really a time to look beyond the hype and get real about Internet of Things.
Just putting IoT in place may not help organizations but applyinganalytics is extremely essential for the success of IoT systems for better decision making.
Here are top 5 areas where IoT is making the disruption:
1.     Wellness - IoT helps continuously monitor the patients and symptoms to early detection, diagnosis & accelerate breakthrough drug development. Wearables like Fitbit, Apple watch, and Samsung have all created new revenue streams from giving their users workout analytics and the ability to set daily health goals. Mobile apps around wellness have been around for years now to track your sleep, weight, nutrition, and more. 
2.     Safety and Security – Sensor based monitoring of elevators, escalators improves travelers safety at airports.  Sensors, which are much cheaper these days, can let you know whether or not your water pipes are leaking or are about to burst. The droneswill allow the handful of rangers to quickly investigate reports of fires, than traveling into remote parts of the jungle over unpaved roads. Connected cars allows vehicle diagnostics and real time intervention from technicians for better safety.
3.     Marketing – with use of IoT, businesses can reach to right customer at at right time using geofencing. It is a virtual field in which apps are capable of sending alerts depending on your entrance or exit from a vicinity. With geofencing, your shopping experience can be more hyper-personalized to what you’re looking for. 1-800-Flowers covered the area around jewelry stores that were close to their flower shops to encourage customers to buy flowers with jewelry. Amazon Go is Amazon’s store concept without a check-out line. 
4.     Smart Cities & Smart Infrastructure – IoT is helping build the infrastructure which is really smart in quick response and improves the life of residents. Real time weather response systems, better traffic management, waste management, and optimal utilities management helps governments around the world.  Smart Homes helps people more peaceful life.
5.     Energy, Aviation & Manufacturing – Using IoT to do predictive maintenance can reduce downtime up to 50%. Companies like GE have put up 100s of sensors across the plant that provide round-the-clock monitoring and diagnostics of existing hardware. IoT enabled engines consume almost 15% less fuel than average jet engines, and also have reduced emissions and noise.  Smart grids helps in increasing the reliability and efficiency of grid, avoid thefts.
In future IoT will continue to enhance our lives more and more by tracking our needs in real time giving opportunity to businesses to react accordingly and immediately.
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As businesses are trying to leverage every opportunity regarding IoT by trying to find ways to partner with top universities and research centers, here is a list of the Top 20 co-occurring topics of the Top 500 Internet of Things Authors in the academic field. This gives an idea of research frontiers of the leaders.
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Sounds similar to jargons from the movie ‘Back to Future (1985)?

Hold yourself together. A part of the world has already started using it.

If you have a light memory turning off switches or managing home appliances, these IoT technologies are going to be your guardian angels.

Let’s find how the above ‘jargons’ will become a part of your life. Also, for the geek in you, their modus operandi is also described.

#1 Adaptive Lighting

IoT can make your home lighting system smart enough to adjust its brightness or to switch off automatically by sensing its surroundings. With IoT adaptive lighting your, indoor lighting systems will turn themselves off when there is no one in the house, or adjust the brightness according to external lighting conditions to give minimized energy consumption.

Companies like LG are taking it to forward to manufacture lighting systems that will turn on by default along with alarm clocks or to flicker when there is a telephone call or movement is sensed. Adaptive lighting relies on motion sensors and optical sensors to gather metrics about its immediate surroundings based on which the lighting systems function.

#2 Responsive Thermostats

Thermostats that auto adjust the temperature and power consumption according to external climatic conditions is a boon for any household. Smarter thermostats can learn the usage pattern of family members and alter its functions accordingly. Going a step ahead, these responsive thermostats can even connect to the Internet to receive updates about family members and change the power consumption and internal temperature control.

For instance, if you are away from your home for a very long time, the thermostat will reduce the power consumption to a bare minimum, or send alerts when the equipment malfunctions. Amazon Nest is a classic example of responsive thermostats. They use heat and climate sensors to decide at what optimum temperature the thermostat must run for best performance.

#3 Autonomous Security Systems

IoT will foster a breed of homes and offices where physical keys, access cards or even tokens will never be needed. Sensor based security systems can be programmed for allowing entry, locking or alerts in case of a break in. Advanced IoT applications also allow integrate your home security system for communicating with your smartphones. These autonomous security systems will work based on movement sensors or proximity sensors.

#4 Connected Appliances

How many times have you missed turning off the oven? Or the washing machine? Or the coffee machine and the endless list of other home appliances? With the oncoming wave of IoT, connected appliances will empower homeowners to control their entire suite of home appliances using their smartphone or remote controls.

Two of the classic examples of connected appliances are: Smarter’s WiFi coffee machine that brews fresh coffee even when you are lazing around or the Electrolux CombiSteam Oven that can be controlled anywhere using your smartphone.

#5 Surface Remote Controls

Surface remote controls can turn any surface (like a desk, wall, floor, etc.) into a remote control. Surface remote controls allow users to control several domestic settings like lighting, control connected appliances, open/close doors, switch on/off TV, wifi, music system, etc.

Image source: knocki

These devices are equipped with programmed sensors which can communicate with other IoT devices to do desired actions. Surface remote controls can bring about a revolutionary level of comfort not just in homes, but also offices, factory floors and public spaces. Knocki is one such device that can turn any surface into a remote control.

That brings us to the conclusion. Be informed that this is just a tip of the iceberg. IoT is an ocean of opportunities and these five hints at how homes of the future will look and function like.

Contus, the digital transformations company is creating a whole new breed of IoT connected systems under its ambit of services titled Contus Connect.

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Cybersecurity in Digital age

You must have heard about the global cyberattack of WannaCry ransomware in over 200 countries. It encrypted all the files on the machine and asked for payment. Ransomware, which demands payment after launching a cyber-attack, has become a rising trend among hackers looking for a quick payout.
Every day it seems another news breaks about cyber-criminals hacking in and stealing data, & information. Private companies, government agencies, hospitals…no one is immune. Cybersecurity is no longer buried in the tech section of organizations, newspapers and websites - its front-page news.
With the penetration of the digital movement, cyber-attacks have also doubled year over year, making businesses and government sites more vulnerable.
In simple terms cybersecurity is use of digital technologies to protect company networks, computers and programs from unauthorized access and subsequent damage.
In recent times, every organization has launched a “go-digital” initiative. This has led to explosion of connected environments.
The growing mobility trend has sparked a rapid growth of endpoints that must be secured, and bring-your-own-device (BYOD) programs mean that employees could be accessing sensitive data on unsecured devices.
The prevalence of cloud based services and third party data storing has opened up new areas of risk.
As businesses adopt the new technologies like Big Data, Analytics, IoT & Mobility, the focus must be on how to safeguard the data spread across devices and cloud.
Cybersecurity must be a key factor during your journey to digitally transforming your business, just as you would ensure that your offices, brick-and-mortar store has locks and security systems of the highest quality, your digital storefront must have the same levels of security. If consumers do not trust these digital storefront with their data, or if that trust is broken because of a data breach, the cost to rebuild that trust is incredibly high.
The best way to protect yourself is to be suspicious of unsolicited emails and always type out web addresses yourself rather than clicking on links.
There are different types of attacks we have seen so far:
·        Hackers target the software vulnerabilities that are yet to be discovered  and patched
·        Attack on mobile devices: malwares designed specifically for smartphones to steal data
·        Data leakage: hackers steal the data by interrupting the traffic between organization and cloud environments
·        Programming: hackers use malicious code on any server that gets replicated and allow them to delete, steal data
There are multiple ways to combat these cyber-attacks:
·        Network defense: detect unwarranted traffic e.g. someone communicating with malicious host, malware entry into the network, unauthorized data transfer
·        Detect user access violations: misuse of user access within the system, ensure proper authentications, use of antivirus, malware to prevent steal user information
·        Mobile device protection: detect unauthorized devices or prevent hackers from compromising individual devices.
·        Protect data in motion & rest: ensure data transfers protected within various environments
·        Investment in securing IoT devices – today with everything is connected it is extremely important to secure all access points.
Today with machine learning organizations are in a very good position to know what users are doing that can affect the network and increase risk. Artificial Intelligence is used to constantly learn new malware behaviors and recognize how viruses may mutate to try and get around security systems.
Traditional IT security practices like network monitoring and segmentation will become even more critical as businesses and governments deploy IoT devices.

Recent events have highlighted the growing need for enhanced cybersecurity.

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18 Big Data tools you need to know!!

In today’s digital transformation, big data has given organization an edge to analyze the customer behavior & hyper-personalize every interaction which results into cross-sell, improved customer experience and obviously more revenues.
The market for Big Data has grown up steadily as more and more enterprises have implemented a data-driven strategy. While Apache Hadoop is the most well-established tool for analyzing big data, there are thousands of big data tools out there. All of them promising to save you time, money and help you uncover never-before-seen business insights.
I have selected few to get you going….
Avro: It was developed by Doug Cutting & used for data serialization for encoding the schema of Hadoop files.
 
Cassandra: is a distributed and Open Source database. Designed to handle large amounts of distributed data across commodity servers while providing a highly available service. It is a NoSQL solution that was initially developed by Facebook. It is used by many organizations like Netflix, Cisco, Twitter.
 
Drill: An open source distributed system for performing interactive analysis on large-scale datasets. It is similar to Google’s Dremel, and is managed by Apache.
 
Elasticsearch: An open source search engine built on Apache Lucene. It is developed on Java, can power extremely fast searches that support your data discovery applications.
 
Flume: is a framework for populating Hadoop with data from web servers, application servers and mobile devices. It is the plumbing between sources and Hadoop.
 
HCatalog: is a centralized metadata management and sharing service for Apache Hadoop. It allows for a unified view of all data in Hadoop clusters and allows diverse tools, including Pig and Hive, to process any data elements without needing to know physically where in the cluster the data is stored.
 
Impala: provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS or HBase using the same metadata, SQL syntax (Hive SQL), ODBC driver and user interface (Hue Beeswax) as Apache Hive. This provides a familiar and unified platform for batch-oriented or real-time queries.
 
JSON: Many of today’s NoSQL databases store data in the JSON (JavaScript Object Notation) format that’s become popular with Web developers
 
Kafka: is a distributed publish-subscribe messaging system that offers a solution capable of handling all data flow activity and processing these data on a consumer website. This type of data (page views, searches, and other user actions) are a key ingredient in the current social web.
 
MongoDB: is a NoSQL database oriented to documents, developed under the open source concept. This comes with full index support and the flexibility to index any attribute and scale horizontally without affecting functionality.
 
Neo4j: is a graph database & boasts performance improvements of up to 1000x or more when in comparison with relational databases.
Oozie: is a workflow processing system that lets users define a series of jobs written in multiple languages – such as Map Reduce, Pig and Hive. It further intelligently links them to one another. Oozie allows users to specify dependancies.
 
Pig: is a Hadoop-based language developed by Yahoo. It is relatively easy to learn and is adept at very deep, very long data pipelines.
 
Storm: is a system of real-time distributed computing, open source and free.  Storm makes it easy to reliably process unstructured data flows in the field of real-time processing. Storm is fault-tolerant and works with nearly all programming languages, though typically Java is used. Descending from the Apache family, Storm is now owned by Twitter.
 
Tableau: is a data visualization tool with a primary focus on business intelligence. You can create maps, bar charts, scatter plots and more without the need for programming. They recently released a web connector that allows you to connect to a database or API thus giving you the ability to get live data in a visualization.
 
ZooKeeper: is a service that provides centralized configuration and open code name registration for large distributed systems. 
 
Everyday many more tools are getting added the big data technology stack and its extremely difficult to cope up with each and every tool. Select few which you can master and continue upgrading your knowledge.
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What are common features of IIoT and SCADA/HMI and differences between them? And what advantages do Internet of Things Platforms have over SCADA systems? Find out answers in our new presentation.

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IoT meets Augmented Reality

Many years ago there was an entertaining television commercial in the USA where a company, I think it was Wendy's, explained how much care and effort they put into making a perfect meal for their customers. Each and every focal point that showed the extra care and effort they took was followed by some lame guy saying "Boy, you sure make a lot of work for yourselves!!" At the time I didn't realise how many truisms this commercial contained, but the implied message of "Good things take extra effort" didn't escape me and with time I learned to appreciate how much work really goes into making extraordinary things.

PTC also seems to have taken this philosophy to heart. While it is very easy to find large software products that are complex, difficult to use, and bug-ridden, it is a rare treat to find a powerful tool that does a great deal of heavy lifting for you in an elegant and reliable manner. For my dime, PTC has done just that with their ThingWorx ensemble. They have made a lot of work for themselves, so that you and I don't have to.

Although there are numerous vendors offering IoT solutions, ThingWorx is the only one I have found that focuses on developing IoT interfaces with a minimum of coding skills required and has an Augmented Reality design interface. Considering the time and effort that has gone into the development of ThingWorx Studio, I expect it will be a quite some time before any IoT competitors match or exceed the ThingWorx platform capabilities.

ThingWorx is more of a concept than an application suite. It works very diligently to create an ecosystem for IoT devices to be created, deployed and maintained with a minimum of effort and a maximum of consistency and reliability. Whereas in the "old world" vendors would create proprietary solutions, forcing you to live within the boundaries of their technology, ThingWorx opens the world of IoT to allow companies to pick and choose Best-of-Breed solutions for the specific needs that they have. No longer should you be locked into proprietary technology, tying your fate and fortune to that of your supplier.

This article (http://www.ar-intelligence.info/2017/05/product-review-thingworx-studio/#Jump) is an abbreviated review of the ThingWorx Studio and its surrounding concepts.

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We've updated our IoT platform presentation to tell you more about it, derived products and solutions.

Pleasant viewing!

                           

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Our software offers fully functional monitoring solutions for healthcare organizations. Fast deployment, easy integration, and great usability guarantee quick troubleshooting to your healthcare IT teams.

AggreGate IoT Platform enables centralized monitoring and data aggregation for various wearable medical devices and mobile e-health applications. Intelligent Big Data processing algorithms allow detecting negative trends proactively, providing a strong foundation for building customized predictive medicine solutions.

In addition, choosing AggreGate solutions for your medical infrastructure monitoring, you get all types of industry-specific management.

Find out what AggreGate can offer for your health, medical devices, and facilities in IoT Solutions for Healthcare and Social Institutions website section.

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Top 7 Virtual Reality Industry use cases

Today Digital Transformation has entered our life and we have subconsciously using it also in day to day life.
Virtual Reality technology has evolved dramatically in the past few years the costs of VR devices has gone down so it is all set to hit mainstream markets soon. While gaming applications like Pokemon Go have attracted most of the attention, there are many other use cases that could have a much larger impact on our lives.
Google Cardboard is a super low-cost headset ($15) to which a compatible, VR enabled mobile phone is attached to deliver the VR experience.
Other commercial product is Oculus Rift gear which has becomeextremely popular in gaming & business equally.
Here are some great VR use cases:
1.     VR for Tourism: do you want to sit on your couch and climb up the Eiffel tower? Or walk on the glass horse shoe at grand canyon? Wild Within is VR app available for experience of travel through rain forest in Canada. Travelers around the world are able to experience a helicopter flight around New York City or a boat ride around the Statue of Liberty.
2.     VR for Education: Over last decade eLearning had picked up very much. But it could not deliver hands on experience which is now possible with VR technology. Technicians can actually learn the real life examples and do their bit to solve the problems on the shop floor. Medical students can actually perform surgeries allowing them to make mistakes without any impact on actual patients.
3.     VR for Sales: Traditionally automakers have the showroom to show the cars to the customers and explain their features and sometimes a test drive is also possible. But customization of how the interior will look as per their choice was not possible which now can be done via VR.  Audi is experimenting this in London, where customer can configure their Audi with accessories as they want and drive virtually in real time.
4.     VR in Gaming: who does not know the excitement Pokemon Go had created and reached 50 million users in record time of 22 days.  Using AR/VR technology games have changed the life of seniors as well as teens. Game of Thrones has capitalized on VR and gone viral in various countries.
5.     VR in Designing: product designing is tedious task and changes to products based on the competition or customization is time consuming. This is where VR helps designers. They can now create the products easily, configure all the features and test them out. It is more popular in construction of buildings to see how the interior will look like.
6.     VR in Marketing: With Digital Marketing ads are becoming more intrusive. The best marketing campaigns use VR to create successful campaigns as users get completely immersed into the content, and create memorable experiences. Coca Cola created a virtual reality sleigh ride. New York times releases multiple immersive documentaries in their app. Finnair is showing their Airbus 350 via VR to attract more customers.
7.     VR in Sports coaching: The potential for VR in sports in endless. You get all the benefits of real-world interaction, but in a controlled environment. Showing is so much more effective than explaining, and experiencing something first-hand is that much more powerful again. Football, Cricket.

Virtual reality technology holds enormous potential to change the future for a number of fields, from medicine, business, and architecture to manufacturing. We are on the roller coaster ride !!
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