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Despite the industry being in a state of post-revolution following the onset and adoption of machinery, there is a batch of technologies that already define the state of technological innovation in agriculture.

 

The agricultural sector is in the middle of the data-driven transformation. Farmers and commodity traders are heading towards technological innovation in agriculture, adopting data analytics and smart farming technologies. Facing a crucial period in their history, agricultural businesses are tasked with combating the issues that will change not only their working methods but the world as we know it.

The agribusiness issues at hand

One of the greatest pain points associated with agriculture is the ability to predict the events that will achieve a given result.

Conditions play even less in the favour of farms positioned within markets that face rising production costs. The global population reaching 9.6 billion people by 2050, up from around 7 billion at present, according to forecasts from the United Nations, combined with the spread of economic prosperity are adding great pressure to the market. The UN suggests the doubling of crop production by 2050 as a countermeasure to this growth.

Some farmers simply cannot increase their land in order to grow more crops. As a result, there is a case for technology to make better use of the space available.

 

How IoT and predictive analytics can solve agriculture’s pressing problems

To become more efficient, agricultural businesses need data and plenty of it. This opens the door for technological innovation, as the size of these businesses and their plots of land prevent any kind of manual surveying.

Already we are seeing an active use of IoT devices to analyse the status of crops, capturing real-time data with sensors. For instance, with soil sensors, farmers can detect any irregular conditions such as high acidity and efficiently tackle these issues to improve their yield.

The data gathered from sensors allows to apply advanced analytics and get the insight that aid decisions around harvesting, while machine learning can transform the figures into solid predictions. Using advanced analytics, agricultural businesses can forecast yields, foresee unexpected weather conditions, predict market demand and mitigate risks, as well as better plan their capacity.

Agricultural drone is also among the key components of smart farming today. Tasked with the surveying of crop and livestock conditions from up high, their use of time lapsing within onboard cameras is helping farmers identify problems in areas like irrigation, which would otherwise go undetected.

Other members of the drone family allow for the spraying of crops at a greater accuracy than a tractor. As an added benefit, this also seeks to reduce the risk of human exposure to harmful chemicals. Back to ground level, there is potential for other robots to help out with manual duties like planting, ploughing and meat production.

The end goal in this case? A more efficient, more effective farm.

 

Conclusion

To spell things out: population growth could mean that every agricultural business will have to increase their levels of productivity over the next 30 years. That said, a review of the tech on today’s market suggests even the most specific problems can be matched with smart agribusiness solutions.

In the era of smart agriculture, IoT and predictive analytics are powering more efficient operations around the world. Combining IoT with analytics, agribusinesses get accurate predictions for crops and market conditions, allowing to increase their yields and profits. Smart application of technologies can facilitate warehouse and inventory management, help plan and execute seasonal works with the automated flow of data from the fields and agro-research labs.

Get in touch to discuss where the IoT can help futureproof your own agricultural business.

 

Originally published at eleks.com

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"One day I'm in my cubicle, Steve shows up with someone I've never met before. He asks me, 'Guy, what do you think of this company Knoware?'. I said, 'Well Steve, it is a mediocre company, mediocre product, lot of drilling practises, doesn't make full use of graphics, just basic mediocrity, nothing that strategic for us.' He says to me, 'I want you to meet the CEO of Knoware.' So that's what was like working for Steve Jobs. ‘You always have to be on the ball.

A lot of water has flowed under the bridge since then. The flow of information has also changed the way we live in today’s world.

Your mark on the world begins…

Every morning when we read a newspaper having out so much information we came to know the latest happening in the world (of course in details), yeah you are right even the internet edition also. This is just a very basic example of IoT. All our Railways, Air and even sea networks are connected with the help of IoT. We can take the example of banking. It is very easy to transact any amount of money from part of the world to other with help of e-commerce. We can purchase anything online with help of debit and credit cards. This has made our lives more and more simple. People are working on the internet without really having to go outside to their workplace. IoT has changed the whole scenario. Companies can share technologies online. Even the doctors can guide the other doctors while operating on a patient with the help of Information Technology. A whole new world is coming our way. Technology is allowing us to reimagine our future transportation system. Advances in connected automation, navigation, communication, robotics, and smart cities—coupled with a surge in transportation-related data—will dramatically change how we travel and deliver goods and services. Automation in the field of transportation is everywhere. Have we as humans become an afterthought? We order service on our smartphones, we manoeuvre around in increasingly automated vehicles, we ride in driverless transport, and we will increasingly find ourselves sharing our highways and byways with drones and other unmanned craft.

1) SaaS & Bring Your Own Device

Global movements such as BYOD and SaaS, where consumerisation of IT and mobility are drastically changing the capabilities of employees and their expectations of a workspace. Building your own apps is the ideal way to mitigate the risk of BYOD and SaaS. An organisation can provide those that only allow the user to access what they need. The enter-prise’s concern is the data; the employee’s concern is the device. In the IT security world, we care about both. Now that most of the organizations started adopting BYOD in some form, it is not just their personal iPads and laptops that users are bringing into the office, they are also using the consumer apps available in their personal device for work purpose which leads to the next wave in mobility. In the very near future BYOD won’t be a ‘trend’ but a norm no one would think twice about.

2) The Emergence of Big Data

 "Big data" alluringly holds out the promise of competitive advantages to companies that can use it to unlock secrets about customers, website usage and other key elements of their business operations. Big Data now stream from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. It's estimated that 43 trillion gigabytes of new data will be created by the year 2020. 

3) Cloud computing: How it's transforming the role of IT

Market conditions require significant change and many organizations are using this driver as an opportunity to simplify their applications and data through rationalization and technology innovations such as Cloud Computing. Cloud is defined as any cloud service where consumers are able to access software applications over the internet. The applications are hosted in “the cloud” and can be used for a wide range of tasks for both individuals and organisations. Google, Twitter, Facebook and Flickr are all examples of SaaS, with users able to access the services via any internet enabled device. Cloud is also the fastest growing because it keeps pace with emerging and future business models than on-premise systems, the majority of which were designed for business models of the past.

The next step, moving towards virtual workspaces, can make organisations far more agile but only if those responsible for the IT (and in effect, the productivity) of the employees understand the relationship employees have with their devices and how these change throughout the day based on their personal preference – be it a smartphone for the train, a tablet device for a client meeting or a laptop for remote working at home.

4) Millions of sensitive IT services exposed to the Internet

All the more the Internet is becoming more and more important for nearly everybody as it is one of the newest and most forward-looking media and surely "the" medium of the future. These advances—in fields such as robotics, A.I., computing, synthetic biology, 3D printing, medicine, and nanomaterials—are making it possible for small teams to do what was once possible only for governments and large corporations: solve the grand challenges in education, water, food, shelter, health, and security. Technology is, today, moving faster than ever. Advances that took decades, sometime centuries, such as the development of telephones, airplanes, and the first computers, now happen in years.

The macro trends that have changed the playing field in the past 10 years have been cloud, mobility, Big Data, and social networking. An even bigger trend ahead will be the Internet of Things that will extend information technology into every aspect of our lives. IT has become more agile and responsive to the needs of the business. While cloud was considered hype just a few years ago, the cloud in its many forms, private, public, hybrid, is transforming IT into a service model. IT leaders who embraced these changes have been able to do more with less and have proven their strategic value.

According to Steve, the iPhone was originally a tablet project. Partway through the R&D process, he said, “Hmm, we can make a phone out of this.” After the launch, many people rewrote history and said that the purpose of the iPhone was to reinvent the future of telephony.

Today, technology is, moving faster than ever. The ubiquity of network connectivity and the proliferation of smart devices (such as sensors, signs, phones, tablets, lights, and drones) have created platforms upon which every enterprise can innovate. Since the past few years we have also seen countless innovations that improve our daily lives. From Internet technology to finance to genetics and beyond - we have seen technologies such as mobile, social media, smartphones, big data, predictive analytics, and cloud, among others are fundamentally different than the preceding IT-based technologies. And advances in science and technology have changed the way we communicate, our thought processes, exchange views, understand the way we relate to one another and think about what it means to be a real Innovative change maker. Perhaps one day you too can be a part of reinventing something which is new, timely, relevant and useful.

 

Best Regards,

Raj Kosaraju

 

Raj Kosaraju specializes on Cloud Computing, Data Warehousing, Business Intelligence, Supply Chain Management, Big Data & IoT.

Read more…

 

"One day I'm in my cubicle, Steve shows up with someone I've never met before. He asks me, 'Guy, what do you think of this company Knoware?'. I said, 'Well Steve, it is a mediocre company, mediocre product, lot of drilling practises, doesn't make full use of graphics, just basic mediocrity, nothing that strategic for us.' He says to me, 'I want you to meet the CEO of Knoware.' So that's what was like working for Steve Jobs. ‘You always have to be on the ball.

A lot of water has flowed under the bridge since then. The flow of information has also changed the way we live in today’s world.

 Your mark on the world begins…

Every morning when we read a newspaper having out so much information we came to know the latest happening in the world (of course in details), yeah you are right even the internet edition also. This is just a very basic example of IoT. All our Railways, Air and even sea networks are connected with the help of IoT. We can take the example of banking. It is very easy to transact any amount of money from part of the world to other with help of e-commerce. We can purchase anything online with help of debit and credit cards. This has made our lives more and more simple. People are working on the internet without really having to go outside to their workplace. IoT has changed the whole scenario. Companies can share technologies online. Even the doctors can guide the other doctors while operating on a patient with the help of Information Technology. A whole new world is coming our way. Technology is allowing us to reimagine our future transportation system. Advances in connected automation, navigation, communication, robotics, and smart cities—coupled with a surge in transportation-related data—will dramatically change how we travel and deliver goods and services. Automation in the field of transportation is everywhere. Have we as humans become an afterthought? We order service on our smartphones, we manoeuvre around in increasingly automated vehicles, we ride in driverless transport, and we will increasingly find ourselves sharing our highways and byways with drones and other unmanned craft.

1) SaaS & Bring Your Own Device

Global movements such as BYOD and SaaS, where consumerisation of IT and mobility are drastically changing the capabilities of employees and their expectations of a workspace. Building your own apps is the ideal way to mitigate the risk of BYOD and SaaS. An organisation can provide those that only allow the user to access what they need. The enter-prise’s concern is the data; the employee’s concern is the device. In the IT security world, we care about both. Now that most of the organizations started adopting BYOD in some form, it is not just their personal iPads and laptops that users are bringing into the office, they are also using the consumer apps available in their personal device for work purpose which leads to the next wave in mobility. In the very near future BYOD won’t be a ‘trend’ but a norm no one would think twice about.

2) The Emergence of Big Data

"Big data" alluringly holds out the promise of competitive advantages to companies that can use it to unlock secrets about customers, website usage and other key elements of their business operations. Big Data now stream from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. It's estimated that 43 trillion gigabytes of new data will be created by the year 2020.

3) Cloud computing: How it's transforming the role of IT

Market conditions require significant change and many organizations are using this driver as an opportunity to simplify their applications and data through rationalization and technology innovations such as Cloud Computing. Cloud is defined as any cloud service where consumers are able to access software applications over the internet. The applications are hosted in “the cloud” and can be used for a wide range of tasks for both individuals and organisations. Google, Twitter, Facebook and Flickr are all examples of SaaS, with users able to access the services via any internet enabled device. Cloud is also the fastest growing because it keeps pace with emerging and future business models than on-premise systems, the majority of which were designed for business models of the past.
The next step, moving towards virtual workspaces, can make organisations far more agile but only if those responsible for the IT (and in effect, the productivity) of the employees understand the relationship employees have with their devices and how these change throughout the day based on their personal preference – be it a smartphone for the train, a tablet device for a client meeting or a laptop for remote working at home.

4) Millions of sensitive IT services exposed to the Internet

All the more the Internet is becoming more and more important for nearly everybody as it is one of the newest and most forward-looking media and surely "the" medium of the future. These advances—in fields such as robotics, A.I., computing, synthetic biology, 3D printing, medicine, and nanomaterials—are making it possible for small teams to do what was once possible only for governments and large corporations: solve the grand challenges in education, water, food, shelter, health, and security. Technology is, today, moving faster than ever. Advances that took decades, sometime centuries, such as the development of telephones, airplanes, and the first computers, now happen in years. 


The macro trends that have changed the playing field in the past 10 years have been cloud, mobility, Big Data, and social networking. An even bigger trend ahead will be the Internet of Things that will extend information technology into every aspect of our lives. IT has become more agile and responsive to the needs of the business. While cloud was considered hype just a few years ago, the cloud in its many forms, private, public, hybrid, is transforming IT into a service model. IT leaders who embraced these changes have been able to do more with less and have proven their strategic value.


According to Steve, the iPhone was originally a tablet project. Partway through the R&D process, he said, “Hmm, we can make a phone out of this.” After the launch, many people rewrote history and said that the purpose of the iPhone was to reinvent the future of telephony. 


Today, technology is, moving faster than ever. The ubiquity of network connectivity and the proliferation of smart devices (such as sensors, signs, phones, tablets, lights, and drones) have created platforms upon which every enterprise can innovate. Since the past few years we have also seen countless innovations that improve our daily lives. From Internet technology to finance to genetics and beyond - we have seen technologies such as mobile, social media, smartphones, big data, predictive analytics, and cloud, among others are fundamentally different than the preceding IT-based technologies. And advances in science and technology have changed the way we communicate, our thought processes, exchange views, understand the way we relate to one another and think about what it means to be a real Innovative change maker. Perhaps one day you too can be a part of reinventing something which is new, timely, relevant and useful.

Best Regards,

Raj Kosaraju

 

Raj Kosaraju specializes on Cloud Computing, Data Warehousing, Business Intelligence, Supply Chain Management, Big Data & IoT.

 
 
Read more…

Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. 

While IoT may be seen as another buzzword at the moment, companies like SAP, Cloud Sigma, Net Atlantic and Amazon Web Services are working to make sure that for businesses, IoT is a reality. It’s companies with this willingness to change, adopt and invent that will win the new economy. Mobile phones, online shopping, social networks, electronic communication, GPS and instrumented machinery all produce torrents of data as a by-product of their ordinary operations. Most companies want their platform to be the foundation of everything it does, whether it is with big data, data analytics, IoT or app development. The same  rub off phenomenon was emulated in Latin American countries  like Brazil, Argentina, Mexico and European countries like Brussels, Italy,  Germany, Denmark , Poland and Prague in recent times.

It is important to realize that technology is exploding before our very eyes, generating unprecedented opportunities. With easy access to cheap cloud services, smarter people came up with these platforms, and it has fundamentally changed businesses and created new ways of working. Mobile cannot be an afterthought. It needs to be integrated in everything you do and positioned at the forefront of your strategy. You have no valid reason to avoid migrating to the cloud. Cloud provides a ubiquitous, on-demand, broad network with elastic resource pooling. It’s a self-configurable, cost-effective computing and measured service. On the application side, cloud computing helps in adopting new capabilities, meeting the costs to deploy, employing viable software, and maintaining and training people on enterprise software. If enterprises want to keep pace, they need to emulate the architectures, processes and practices of these exemplary cloud providers.

One of the main factors of contributing value additions is the concept of a Smart City which is described as one that uses digital technologies or information and communication technologies to enhance the quality and performance of urban services, to reduce costs and resource consumption and to engage more effectively and actively with its citizens. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other.The idea is to embed the advances in technology and data collection which are making the Internet of Things (IoT) a reality into the infrastructures of the environments where we live. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other. Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. The current model adopted for IoT is to attract businesses to develop software and hardware applications in this domain. The model also encourages businesses to put their creativity to use for the greater good, making cities safer, smarter and more sustainable.

A few years ago like many others  I predicted  that Business models will be shaped by analytics, data and the cloud. Moreover, the IoT is deeply tied in with data, analytics and cloud to enable them and to improve solutions. The key goal is to ensure there is value to both customers and businesses. You can effectively put this strategy into action and build a modern data ecosystem that will transform your data into actionable insights.  

Till we meet next time...

Best,

Raj Kosaraju

CIO 

 

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Can the Public Internet Secure Our Digital Assets?

There is a lot of talk, and, indeed, hype, these days about the internet of things. But what is often overlooked is that the internet of things is also an internet of shared services and shared data. What’s more, we are becoming too heavily reliant on public internet connectivity to underpin innovative new services.

Take this as an example. Back in April, Ford Motor Company, Starbucks and Amazon announced and demonstrated an alliance that would allow a consumer to use Alexa to order and pay for their usual coffee selection from their car. Simply saying, “Alexa: ask Starbucks to start my order,” would trigger the sequence of events required to enable you to drive to the pickup point and collect your already-paid-for coffee with no waiting in line.

Making that transaction happen behind the scenes involves a complex integration of the business processes of all the companies involved. Let’s be clear: this is about data protection. For this series of transactions to be successfully handled, they must be able to share customer payment data, manage identity and authentication, and match personal accounts to customer profiles.

Because all of that critical data can be manipulated, changed or stolen, cyberattacks pose significant data protection risks for nearly any entity anywhere. The ambition of some of these consumer innovations makes an assumption that the “secure” network underpinning this ecosystem for the transfer of all that valuable personal data is the public internet. And that’s the point – it’s not secure.

As we’ve talked about previously on Syniverse's blog Synergy, the public internet poses a systemic risk to businesses and to confidential data. In short, when we are dealing on a large scale with highly sensitive data, the level of protection available today for data that, at any point, touches the public internet is substantially inadequate.

And this alliance between Ford and Starbucks is just one example of the type of innovation, across many different industry and consumer sectors, that we can expect to see a lot of in the very near future. These services will connect organizations that are sharing data and information about businesses and about consumers – about their purchase history, their preferences and requirements, and also about their likely future needs. This is potentially a very convenient and desired service from a consumer’s point of view, but at what cost?

We need security of connectivity, security from outside interference and the security of encrypted transfer and protection for our personal and financial data. And we need to be able to verify the protection of that data at all times by ensuring attribution and identity – both concepts we’ll explore more deeply in an upcoming blog post. And that’s a level of security that the public internet simply cannot provide.

Last month, an internet-based global ransomware attack took down systems and services all over the world – affecting sensitive personal healthcare data in the U.K. in particular.

Whether it is personal health records, financial records, data about the movement of freight in a supply chain, or variations in energy production and consumption, these are digital assets. Businesses, institutions and government bodies all over the world have billions of digital assets that must be constantly sent to and from different parties. And those assets require the type of high-level data protection that is not currently possible because of the systemic risk posed by the insecure public internet.

As mentioned in my last blog post on Synergy, there is an alternative. Some companies using private IP networks were able to carry on regardless throughout the high-profile cyberattacks that have been capturing headlines in the last year. That’s because those companies were not reliant on the public internet. Instead, they were all using what we are beginning to term “Triple-A” networks on which you can specify the speed and capacity of your Access to the network while guaranteeing the Availability of your connection. What’s more, on a Triple-A network, Attribution is securely controlled, so you know who and what is accessing your network and the level of authority granted both to the device accessing the network and to its user.

The public internet cannot provide or compete with a Triple-A level of security, and nor should we expect it to. It cannot live up to the stringent data protection requirements necessary for today’s critical digital assets. We cannot remain content that so much infrastructure, from banking, to transport and to power supplies, relies on a network with so many known vulnerabilities. And we must consider whether we want to carry on developing an industrial internet of things and consumer services on a public network.

We will continue to explore these issues on this blog, to highlight different approaches, and examine the requirements of the secure networks of the future. And in the process, we’ll take a look at the work being done to build more networks with a Triple-A approach.

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How Can You Cope With The Rise Of Dark Data

At this point, everyone has heard about what big data analytics can do for marketing, research, and internal productivity. However, the data only about 20% of all data created is collected and analyzed. The other 80% is known as dark data, or data that collected but not analyzed or made to be searchable. So, what is the purpose of this data, and why is it taking up terabytes worth of storage space on servers around the world?

Examples of Dark Data

  • Media: Audio, video and image files oftentimes will not be indexed, making them difficult to gain insights from. Contents of these media files, such as the people in the recording or dialogue within a video, will remain locked within the file itself.

  • Social Data: Social media analytics have improved drastically over the last few years. However, data can only be gathered from a user’s point of entry to their exit point. If a potential customer follows a link on Facebook, then send the visited website to five friends in a group chat, the firm will not realize their advertisement had 6 touchpoints, not just the one.

  • Search Histories: For many companies, especially in the financial service, healthcare, and energy industries, regulations are a constant concern. As legal compliance standards change, firms worry that they will end up deleting something valuable.

As analytics and automation improve, more dark data is beginning to be dragged out into the light. AI, for example, is getting far better at speech recognition. This allows media files to be automatically tagged with metadata and audio files to be transcribed in real time. Social data is also starting to be tracked with far better accuracy. In doing so, companies will be able to better understand their customers, their interests, and their buying habits. This will allow marketers to create limited, targeted ads based on a customers location that bring in more revenue while reducing cost.

The explosion of data we are currently seeing is only the tip of the big data iceberg. As IoT and wearable devices continue their integration into our daily lives, the amount of data we produce will only grow. Companies are looking to get ahead of the curve and ensure they can gain as much insight from this data as possible. If these firms do not have a plan to create actionable insights from this currently dark data, they ultimately could fall behind and lose out to competitors with a bigger focus on analytics.

The original story was published on ELEKS Trends Blog, visit to get more insights. 

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An Open and Dangerous Place

Let’s just say it: The public internet is great, but it’s an unfit, wide-open place to try to conduct confidential business.

More and more, the public nature of the internet is causing business and government leaders to lose sleep. The global ransomware attacks this year that crippled infrastructure and businesses across Europe clearly shows the concern is not only justified but also growing.

As a result, internet and privacy regulations, like GDPR and PSD2, are front and center as governments around the world increasingly look at the web and how it’s being used. This is creating competing and contradictory objectives.

On the one hand, governments want to protect consumer privacy and data; on the other, they want to be able to monitor what certain folks are up to on the internet. And in both cases, they can at least claim to be looking to protect people.

Regardless of the difficulty of the task, there is no doubt the big governments are circling and considering their options.

Speaking in Mexico in June, Germany Chancellor Angela Merkel touted the need for global digital rules, like those that exist for financial markets, and that those rules need to be enforceable through bodies like the World Trade Organization.

From a business perspective, I can applaud the ambition, but it does seem a little like trying to control the uncontrollable. The truth is that the public internet has come to resemble the old Wild West. It is an increasingly dangerous place to do business, with more than its fair share of rustlers, hustlers, and bandits to keep at bay.

The public internet connects the world and nearly all its citizens. When it comes to connecting businesses, national infrastructures, and governments themselves, trying to regulate the Wild West of the public internet simply isn’t an option. Instead, it’s time to take a step back and look for something different.

We believe organizations that want to conduct business, transfer data, monitor equipment and control operations globally – with certainty, security and privacy – should not be relying on the public internet. The sheer number of access points and endpoints creates an attack surface that is simply too wide to protect, especially with the increased trending of fog and edge networks that we’ve discussed on previous Syniverse blog posts.

Just last week, the online gaming store CEX was hacked. In an instant, around two million customers found their personal information and financial data had been exposed. Consumers in America, the U.K. and Australia are among those affected. As I said, the public internet presents an ever-widening attack surface.

Recently on the Syniverse blog, we’ve been talking about the need to develop private, closed networks where businesses, national utilities and governments can truly control not just access, but activity. Networks that are always on and ones where the owners always know who is on them and what they are doing. Networks that are private and built for an exact purpose, not public and adaptable.

Trying to apply or bolt on rules, regulations and security processes after the fact is never the best approach.  Especially if you are trying to apply them to a service that is omnipresent and open to anybody 24/7.

When we look at the public internet, we see fake actors, state actors, hackers and fraudsters roaming relatively freely. We see an environment where the efforts to police that state might raise as many issues as they solve.

Instead, it’s time for global businesses to build a new world. It’s time to leave the old Wild West and settle somewhere safer. It’s time to circle the wagons around a network built for purpose. That is the future.

Read more…

Why Edge Computing Is an IIoT Requirement

How edge computing is poised to jump-start the next industrial revolution.

From travel to fitness to entertainment, we now have killer apps for many things we never knew we needed. Over the past decade, we’ve witnessed tremendous improvements in terms of democratizing data and productivity across the consumer world.

Building on that, we’re entering a new era of software-defined machines that will transform productivity, products and services in the industrial world. This is the critical link which will drive new scenarios at even faster rates of innovation. By 2020, the Industrial Internet of Things (IIoT) is expected to be a $225 billion market.

To jump-start the productivity engine of IIoT, real-time response is needed at the machine-level at scale and that requires an edge-plus-cloud architecture designed specifically for the Industrial Internet. From Google maps to weather apps, we’ve been experiencing the benefits of cloud and edge computing working together in our daily lives for quite some time.

But, what is edge? Edge is the physical location that allows computing closer to the source of data. Edge computing enables data analytics to occur and resulting insights to be gleaned closer to the machines. While edge computing isn’t new, it’s beginning to take hold in the industrial sector – and the opportunity is far greater than anything we’ve seen in the consumer sector, and here’s why:

Real-time data in a real-time world: The edge is not merely a way to collect data for transmission to the cloud. We are now able to process, analyze and act upon the collected data at the edge within milliseconds. It is the gateway for optimizing industrial data. And when millions of dollars and human lives are on the line, edge computing is essential for optimizing industrial data at every aspect of an operation.

Take windfarms for example. If wind direction changes, the edge software onsite would collect and analyze this data in real-time and then communicate to the wind turbine to adjust appropriately using an edge device, such as a field agent and connected control system, and successfully capture more kinetic energy. Because the data is not sent to the cloud, the processing time is significantly faster. This increases wind turbines’ production, and ultimately distributes more clean energy to our cities, increasing the value of the renewable energy space.

Big data, big trade-offs: The harsh and remote conditions of many industrial sites make it challenging to connect and cost-effectively transmit large quantities of data in real-time. We are now able to add intelligence to machines at the edge of the network, in the plant or field. Through edge computing on the device, we’re bringing analytics capabilities closer to the machine and providing a less expensive option for optimizing asset performance.

Consider the thousands of terabytes of data from a gas turbine. Sending this data to the cloud to run advanced analytics maybe technologically possible, but certainly too cost prohibitive to do a daily basis. Through edge computing, we can capture streaming data from a turbine and use this data in real-time to prevent unplanned downtime and optimize production to extend the life of the machine.

What’s Next

Today, only 3% of data from industrial assets is useable. Connecting machines from the cloud to the edge will dramatically increase useable data by providing greater access to high powered, cost effective computing and analytics tools at the machine and plant level.

Consider the fact that for years traditional control systems were designed to keep a machine running the same way day in and day out for the lifecycle of the machine. At GE Energy Connections, we recently debuted the Industrial Internet Control System (IICS), which successfully allows machines to see, think and do and will enable machine learning at scale. To take IICS to the next level, we’re creating an ecosystem of edge offerings to accelerate widespread adoption across the industrial sector. We’re advancing this ecosystem and empowering app developers who want to play a role in driving the new industrial era. 

Currently, to add value to a software system, a developer writes the code, ports it into the legacy software stack, shuts down the devices and finally, updates it. That’s all going to change. We are working on creating an opportunity for any developer to create value-added edge applications. Customers will be able port the necessary apps to their machine without having to shut it down, just like we do on our phones today. Companies will be able to download apps for their needs and update frequently to ensure their business is running smoothly. While no one likes to run out of battery on their smart phone, an outage for a powerplant is far more costly, so the ability to port apps without shutting down devices and being able to detect issues before it occurs will be a game changer.

From wind turbines to autonomous cars, edge computing is poised to completely revolutionize our world. It’s forcing change in the way information is sent, stored and analyzed.  And there’s no sign of slowing down.

Read more…

How Customer Analytics has evolved...

Customer analytics has been one of hottest buzzwords for years. Few years back it was only  marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza.
SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services.
In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics.
By the late 2000s, Facebook, Twitter and all the other  socialchannels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant.
With the  digital age things have changed drastically. Customer is superman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience.
This tsunami of data has changed the customer analytics forever.
Today customer analytics is not only restricted to marketing for churn and retention but more focus is going on how to improve the customer experience and is done by every department of the organization.
A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating  customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics.
From the technology perspective, the biggest change is the introduction of  big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation.
Then came  Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure.
Predictive models of customer churn, Retention,  Cross-Sell do exist today as well, but they run against more data than ever before.
Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical.
There are various ways customer analytics is carried out:
·       Acquiring all the customer data
·       Understanding the customer journey
·       Applying big data concepts to customer relationships
·       Finding high propensity prospects
·       Upselling by identifying related products and interests
·       Generating customer loyalty by discovering response patterns
·       Predicting customer lifetime value (CLV)
·       Identifying dissatisfied customers & churn patterns
·       Applying predictive analytics
·       Implementing continuous improvement
Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time
Now via  Cognitive computing and  Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their  deep learning neural network algorithms provide a game changing aspect.
Tomorrow there may not be just plain simple customer  sentiment analyticsbased on feedbacks or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time.
There’s no doubt that customer analytics is absolutely essential for brand  survival.
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The digital revolution has created significant opportunities and threats for every industry. Companies that cannot or do not make significant changes faster to their business model in response to a disruption are unlikely to  survive
It is extremely important to do digital maturity assessment before embarking on  digital transformation.
Digital leaders must respond to the clear and present threat of digital disruption by transforming their businesses. They must embed digital capabilities into the very heart of their business, making digital a core competency, not a bolt-on. Creating lasting transformative digital capabilities requires you to build a  customer-centric culture within your organization.
This requires new capabilities that organizations need to acquire and develop which include disruptive technologies like  Big Data, AnalyticsInternet of Things, newer business models.
Digital maturity model measures readiness of the organization to attain higher value in digital  customer engagement, digital operations or digital services. It helps in incremental adoption of digital technologies and processes to drive competitive strategies, greater operationally agility and respond to rapidly changing market conditions.
Business can use the maturity model to define the roadmap, measuring progress on the milestones.
The levels of maturity can be defined as per multiple reports available and

adopt the ones which makes more sense to your business.

·     Level 1 : Project based solutions are developed for a particular problem, no integration to home grown systems, unaware of risks and opportunities
·     Level 2 : Departmentalized projects but still not known to organization, little integration
·     Level 3 : Solutions are shared between the departments for a common business problem, better integration
·     Level 4 : Organization wide efforts of digital, highly integrated, adaptive culture for  fail fast  and improve
·     Level 5 : Driven by CXOs, customer centric and complete transformation changes happen to organization
Here are the 7 categories on which business should ask questions to all the stakeholders to gauge the maturity of Digital Transformation and identify the improvement and priorities.
1.   Strategy & Roadmap - how the business operates or transforms to increase its competitive advantage through digital initiatives which are embedded within the overall business strategy
2.   Customer – Are you providing experience to customers on their preferred channels, online, offline, anytime on any device
3.   Technology – Relevant tools and technologies to make data available across all the systems
4.   Culture – Do you have the organization structure and culture to drive the digital top down
5.   Operations – Digitizing & automating the processes to enhance business efficiency and effectiveness.
6.   Partners – Are you utilizing right partners to augment your expertise
7.   Innovation – How employees are encouraged to bring the continuous innovation to how they serve the customers
Finally you know when you are digital transformed?
·             When there is nobody having “Digital” in their title
·             There is no marketing focused on digital within the organization
·             There is no separate digital strategy than company’s business strategy
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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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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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The IoT needs to be distinguished from the Internet. The Internet, of course, represents a globally connected number of network, irrespective of a wired or wireless interconnection. IoT, on the other hand, specifically draws your attention to the ability of a ‘device’ to be tracked or identified within an IP structure according to the original supposition.
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Today we are into  digital age, every business is using  big data and machine learning to effectively target users with messaging in a language they really understand and push offers, deals and ads that appeal to them across a range of channels.
With exponential growth in data from people and &  internet of things, a key to survival is to use machine learning & make that data more meaningful, more relevant to enrich customer experience.
Machine Learning can also wreak havoc on a business if improperly implemented. Before embracing this technology, enterprises should be aware of the ways machine learning can fall flat. Data scientists have to take extreme care while developing these machine learning models so that it generate right insights to be consumed by business.
Here are 5 ways to improve the accuracy & predictive ability of machine learning model and ensure it produces better results.
·       Ensure that you have variety of data that covers almost all the scenarios and not biased to any situation. There was a news in early pokemon go days that it was showing only white neighborhoods. It’s because the creators of the algorithms failed to provide a diverse training set, and didn't spend time in these neighborhoods. Instead of working on a limited data, ask for more data. That will improve the accuracy of the model.
·       Several times the data received has missing values. Data scientists have to treat outliers and missing values properly to increase the accuracy. There are multiple methods to do that – impute mean, median or mode values in case of continuous variables and for categorical variables use a class. For outliers either delete them or perform some transformations.
·       Finding the right variables or features which will have maximum impact on the outcome is one of the key aspect. This will come from better domain knowledge, visualizations. It’s imperative to consider as many relevant variables and potential outcomes as possible prior to deploying a machine learning algorithm.
·        Ensemble models is combining multiple models to improve the accuracy using bagging, boosting. This ensembling can improve the predictive performance more than any single model. Random forests are used many times for ensembling.
·       Re-validate the model at proper time frequency. It is necessary to score the model with new data every day, every week or month based on changes in the data. If required rebuild the models periodically with different techniques to challenge the model present in the production.
There are some more ways but the ones mentioned above are foundational steps to ensure model accuracy.
Machine learning gives the super power in the hands of organization but as mentioned in the Spider Man movie – “With great power comes the great responsibility” so use it properly.
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Smart IoT - Generate Greatest Value

Digital Transformation

We have now entered an era with a new virtual revolution, particularly, the Internet of things (IoT). The virtual revolution marks the starting of information age. We use the Internet almost every day. The net has turned out to be one of established ways for us to work together, to share our lives with others, to shop, to teach, to research, and to learn. However  the next wave of the Internet isn't about people. it's far about things, honestly?

All about IoT

IoT is defined as the network of physical objects that can be accessed through the Internet. These objects contain embedded various technology to interact with internal states or the external environment.

IoT is characterized as "the figuring frameworks of sensors and actuators associated by systems, where the processing frameworks can screen or deal with the status and actions of connected objects and machines, and the connected sensors can likewise screen the characteristic world, individuals, and creatures." The center of IoT is not just about interfacing things to the Internet. It is about how to generate and use the big data from the things to make new values for individuals, and about how we empower new trades of significant worth between them. In other words, when objects can sense and communicate, IoT has its knowledge to change how and where choices are made, and who makes them, and to pick up a superior esteem, solution or service.

Smart IoT

Fundamental to the estimation of IoT is in actuality the Internet of smart things (smart IoT). Supported by intelligent optimization, smart IoT can increase productivity of work and enhance quality of lives for people. Let us take “cities” — the engines of global economic growth — as an example. Smart cities have the potential to dramatically improve the lives of everyone. In intelligent transportation systems (ITS), smart IoT can not only monitor the status of the transportation, but also optimize traffic signal controls to solve traffic congestion and provide the travelers with better routes and appropriate transportation information, etc. Combining IoT and machine learning (ML) can also make our roads safer. Profits by smart IoT have been shown also in health-care, logistics, environment, smart home, in the aspects of better quality, energy conservation, efficiency increase, and so on.

Smart IoT remains in its infancy now in terms of the technology  development and the effect on our global economy system and our daily lives. Maximum IoT statistics aren't used presently within the era of big data. Maximum IoT has no intelligence inside the generation of artificial intelligence (AI).  IoT which might be used these days are on the whole for anomaly detection and control, as opposed to optimization and prediction. Given the brilliant anticipated increase of the Internet over the following 10 years, it is considered one of vital challenges and possibilities for us to invent and practice in real-global programs on a way to make the IoT smarter to generate the greatest value.

 

 

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Internet of Things (IoT) began as an emerging trend and has now become one of the key element of Digital Transformationthat is driving the world in many respects.
If your thermostat or refrigerator is connected to the Internet, then it is part of the consumer IoT.  If your factory equipment have sensors connected to internet, then it is part of  Industrial  IoT(IIoT).
IoT has an impact on end consumers, while IIoT has an impact on industries like Manufacturing, Aviation, Utility, Agriculture, Oil & Gas, Transportation, Energy and Healthcare.
IoT refers to the use of "smart" objects, which are everyday things from cars and home appliances to athletic shoes and light switches that can connect to the Internet, transmitting and receiving data and connecting the physical world to the digital world.
IoT is mostly about human interaction with objects. Devices can alert users when certain events or situations occur or monitor activities:
·       Google Nest sends an alert when temperature in the house dropped below 68 degrees
·       Garage door sensors alert when open
·       Turn up the heat and turn on the driveway lights a half hour before you arrive at your home
·       Meeting room that turns off lights when no one is using it
·       A/C switch off when windows are open
IIoT on the other hand, focus more workers safety, productivity & monitors activities and conditions with remote control functions ability:
·        Drones to monitor oil pipelines
·       Sensors to monitor Chemical factories, drilling equipment, excavators, earth movers
·       Tractors and sprayers in agriculture
·        Smart cities might be a mix of commercial and IIoT.
IoT is important but not critical while IIoT failure often results in life-threatening or other emergency situations.
IIoT provides an unprecedented level of visibility throughout the supply chain. Individual items, cases, pallets, containers and vehicles can be equipped with auto identification tags and tied to GPS-enabled connections to continuously update location and movement.
IoT generates medium or high volume of data while IIoT generates very huge amounts of data (A single turbine compressor blade can generate more than 500GB of data per day) so includes  Big Data, Cloud computingmachine learning as necessary computing requirements.
In future, IoT will continue to enhance our lives as consumers while IIoT will enable efficient management of entire supply chain.
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