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Internet of Things

91 posts

The explosive growth of IoT isn’t hypothetical; it’s happening today in every sector. Digital transformation is here, and while it is changing industries in new ways, that change doesn’t always come easy. Challenges abound, and when it comes to edge computing, companies are finding some common concerns, including:

·       Latency: Cloud computing is becoming more powerful by the day, but some use cases require data to be processed within milliseconds. Sending data to a backend system, whether it’s located in a public cloud, private cloud or data center, introduces too much latency for these use cases.

·       Perishable data: Not all data is useful in the data center. Sometimes data needs to be acted upon right away with low latency. Perishable data, like the data generated by autonomous vehicles, can’t wait until tomorrow. It must be analyzed at the edge for immediate action.

·       Limited bandwidth: Bandwidth at the edge is often limited, so deciding what data to send can be difficult. Sending everything back to the data center is expensive, time consuming and inefficient. To make the best use of resources and to save time and money, it’s essential to prioritize data and send only what you need.

·       Uninteresting data: Assets and sensors generate huge volumes of data, but not all of it matters to you. You might want to know when an asset is operating outside of normal parameters, but perhaps you don’t need to capture, store, transmit, and analyze the data that’s generated when it’s operating normally. You might also want to reduce the amount of data collected to relieve the burden and overhead of data management.

·       Security: Bringing assets onto the network puts them at risk of being infected with malware. With the growth in smart assets and the fact that cyber attacks are escalating in number and sophistication, securing assets and protecting the integrity of the data and network is vital.

What are some of the other IoT Edge challenges you see in this space?

Across every industry, analytics and business intelligence are hot topics that promise greater insight, more efficiency, and a more competitive organization. And analytics can truly deliver on those promises, despite the myriad challenges that many organizations face in getting that value.

 

One of the most pervasive challenges today is siloed data. Data coming from assets may be used only at the edge, while business applications often have their own separate infrastructure, databases, and sets of information. Getting a complete picture of information across the organization is difficult—often impossible. Without the ability to bring data from disparate systems together in a way that enables fast, smart decision making, business outcomes are poor and costs are high.

 

Not only are data silos a common problem, but data generation itself can be a challenge, too. Many organizations have not been ready to take advantage of analytics capabilities, and don’t generate enough data to derive insights from. Other organizations may generate large volumes of data in the hope that they can derive some business value from it, but lack the filtering capabilities to make sense of data and put the right information in the hands of people who need it.

 

Good predictive abilities require good data gathering and filtering processes. By bringing together the right data from across the organization, whether it lives at the edge or in the data center, the results can be better business outcomes. The analytics capabilities of Lumada address these challenges and deliver fast time-to-value, so that your outcomes are better, faster.

Creating or acquiring IoT solutions can be complex and may seem daunting. Where do I start? Do I have access to all the resources and expertise that will be needed? Is there someone that can help and guide me?

 

If you’re used to buying pre-packaged solutions for specific tasks, then you are likely to discover that these can’t deliver what you want or need in IoT. It's unchartered territory for many.

 

IoT solutions most often combine the physical and digital worlds, almost by definition. They connect to your physical environment – your Operational Technology (OT) – your machines, your buildings, your sensors, etc. They also connect with your IT environment – your ERP system, your CRM system, your procurement system, etc. A successful solution creation and deployment takes expertise in multiple disciplines and deep knowledge about your OT and IT environments as well as the business challenges you’re trying to address. Very few companies have that breadth of expertise in one team or even inside one company. Hitachi does, and we’ve made it our business to help other companies with this.

 

This is where the Co-Creation methodology we use comes in. It’s a methodology we have proven in real life with customers and also inside Hitachi itself. Hitachi has both the OT and IT expertise and capabilities in the Hitachi Group. We’re not only creating IoT solutions – we have first hand experience from running factories, hospitals, transportation services, etc. So we're both a technology and solution provider as well as a user of these solutions. It's very unique to have this dual perspective.

 

We recently worked with 451 Research around research into how Co-Creation methodologies and the associated services are used in the industry. On our Hitachi Vantara web page for Co-Creation Services , we recently published both a report from 451 Research as well as several videos where Greg Knieriemen from Hitachi Vantara interviews Christian Renaud (@xianrenaud) from 451 Research and John Murphy from Hitachi Vantara about the findings in the report and what we’re seeing in our interactions with customers today.

 

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Here’s a “trailer” for the video series that opens it up with addressing the question of “What Does Co-Creation Bring toYour IoT Solutions?”

 

For more information see the web site: https://www.hitachivantara.com/en-us/services/co-creation.html

Listen in as Stacey Higginbotham interviews Hitachi Vantara CTO, Rob Tiffany to learn about the Lumada IoT Platform.

 

With software and adjacent technologies continuing to eat the world, we see the pace of digital transformation accelerating in 2018 as organizations strive to enhance their customer and operational intelligence.

 

Organizations will grapple with a variety of digital technologies and skillsets this year to become more data-driven in order to improve their agility and decision-making capabilities. As always, they’ll be looking for ways to simplify operations and get more done with less. We predict the concepts and trends listed below will light a path for organizations to show them the way forward:

 

  • Climbing the Stairway from the Edge to the Cloud

The ongoing journey to move data, apps and other digital assets from private, on-premises data centers to public clouds will continue unabated as organizations look to reduce or eliminate internal ICT functions and responsibilities. Even in the midst of cutting costs, organizations will still struggle with concerns around cloud vendor lock-in via PaaS which will benefit IaaS virtual machines, container technologies like Docker and container orchestration technologies like Kubernetes, Docker Swarm, Mesos and Marathon. Overall, Amazon AWS plus Microsoft Azure and Office365 will continue to be the biggest beneficiaries of the public cloud megatrend. Along the way, one of the stair steps that remains on-premise is something called the Fog or the Edge. If you’re familiar with how content delivery network (CDN) proxy servers around the world cache and speed the delivery of Web content to your browser, Edge gateway devices do something similar. With more and more of an organization’s compute occurring in distant, public clouds, Edge devices residing on the local network can cache, aggregate, analyze and speed up cloud content to give employees inside the office a better experience. Edge devices can also be used with the Internet of Things where they connect to machines and cache, aggregate, and analyze data locally instead of waiting for that data to be transported to a distant cloud. Since neither people nor machines are vary tolerant of too much latency, expect the adoption of Edge gateway devices and associated local storage to surge in 2018.

  • Enhanced Networking Inside and Out

As organizations reduce the number of digital assets and activities that take place in-house, the primary role of ICT departments will be to create and maintain fast, reliable connectivity via wired and wireless technologies. Wired networking will be “more of the same” as we push speeds forward with fiber optics and Gigabit Ethernet to shuttle employees out to the Internet. Wireless is where things get more interesting. Inside the office, organizations will continue rolling out 802.11ac Wi-Fi access points running in the 5 GHz band to deliver data and high-bandwidth content like HD video to any device. Outside, the 3GPP has officially signed off on the first 5G specification which promises to deliver greater bandwidth, lower latency, better coverage, lower battery consumption and a higher number of simultaneously connected devices. As you might imagine, it will take some time to roll out technology based on this spec so we will look to get more mileage out of 4G technologies like LTE Advanced. On the slower side of things, you have Low-Power, Wide-Area Network (LPWAN) technologies that are making great strides for certain Internet of Things use cases. The ability to create a large wireless network in places where no cellular coverage exits is compelling for organizations capable of managing such a system. If you have devices or machines that don’t send much data every day, require years of battery life, or need to send data over long distances, one of the many LPWAN technologies might be a good fit. Whether you’re inside or outside, looking for narrowband or broadband, there’s plenty of wireless choices for organizations in 2018.

  • Mobility for People and IoT for Machines

While the mobile device revolution has been the biggest megatrend of this new century, the torch has now been passed to the Internet of Things. When you think about it, they’re not terribly different from each other except for the endpoints. Mobile device endpoints are proxies for people and Thing endpoints refer to machines (intelligent or otherwise). They’re both sending data about themselves and other topics of interest over a network. Both interact with apps, analytics and other on-prem or cloud data sources to derive value and business intelligence. In order to regain a level of simplicity and perhaps sanity, organizations will push back against the use of multiple enterprise platforms for Mobile people and IoT machines. Additionally, many organizations will wring their hands of having to understand an alphabet soup of protocols and myriad IoT standards and revert to using the same Web and Internet standards they already understand. Just like they currently do with Mobile and the Web, organizations will insist that IoT sends and receives JSON data to and from URLs over HTTP/REST while being displayed via HTML5, secured with TLS and brought to life with JavaScript. This use of familiar, widely-used, “good enough” Web technologies will win the day over the more advanced but esoteric technologies currently employed by IoT platforms. This move to simplicity and familiarity will reduce friction and help the Internet of Things deliver value and fulfill its promise the way the Mobile, Web and the Cloud have. Expect big changes in IoT for 2018 along with a big shakeout of the hundreds of Internet of Things platform companies.

  • Digital Twins make Everything Digital

The rise of Digital Twins will give every organization the starting point they’re looking for to begin their Digital Transformation. A Digital Twin is essentially a digital representation of a physical object. It can be a machine, a person, a complex mechanical subsystem, a collection of machines working together on an assembly line, or even a process. These twins have attributes or properties that describe them like a person’s heart rate or a motor’s temperature or current revolutions per minute (RPM). Organizations can assign key performance indicators (KPIs) to the current values of these properties. A red heart rate KPI might be 200 whereas a green motor temperature KPI might be 200 degrees Fahrenheit. Digital Twins can exhibit behavior by executing programming language and/or analytics code against the combination of their current property values and associated KPIs. Not only does this bring everything in an organization to life, it also facilitates the running of simulations to see how things will behave when different types of data points are fed to these Digital Twins. This is definitely the most promising and exciting technology for 2018.

  • Security, Privacy and GDPR cause Organizations to Stumble

Unrelenting cyberattacks keep organizations in a defensive posture rather than moving forward with important digital initiatives and deployments. While we won’t cover the myriad security steps every organization must follow in order to stay ahead of individual and state-sponsored hackers, this is one of the most important functions of an ICT department. Organizational leaders who don’t take this seriously by not funding the appropriate security technology or staffing the appropriate security employee headcount do so at their own peril. Needless to say, organizations must prioritize the privacy and protection of data, people (employees and customers), and systems if they want to remain viable. To turn up the heat a bit, the European Union’s General Data Protection Regulation (GDPR) becomes enforceable on May, 25 2018. This regulation gives control back to EU citizens and residents over their personal data by strengthening data protections for all individuals within the  European Union as well as the export of personal data outside the EU. Quite a few companies operating in countries across the globe play it fast-and-loose with the security and privacy of individual data without user consent. This comes to an end in May when companies can be fined  up to €20 million or 4% of their global annual revenue, whichever is greater, for violating this regulation. Any company operating in the EU must obtain explicit consent for all data collected from an individual as well as reason/purpose of using and processing that data. Additionally, that user consent may be withdrawn. Many companies around the world haven’t made the necessary changes to their digital systems to be compliant with GDPR and will be in for a rude awakening in 2018. Data privacy and security matters in a big way.

  • Making Sense of an Avalanche of Data with Advanced Analytics

While data and analytics systems have been around for decades, the amount of data collected for analysis by organizations has increased exponentially. With a 50x growth rate from machines alone, the Internet of Things has become the newest data source for organizations to analyze. Lots of little data integrated from people, machines and business systems adds up to an overwhelming amount of Big Data to make sense of. Luckily, there are an increasing number of streaming and batch analytics systems and tools to tackle this job. Making this trend better is that most of these technologies are open source and free which helps level the playing field between small, mid-sized and large organizations with varying amounts of money to spend. Head over to Apache.org. Another interesting trend in data science is how Python has surpassed R as the most popular language for Machine Learning. An increase on online courseware, an abundance of scientific libraries, and the fact that Python is one of the easiest programming languages to learn, means you don’t always have to be a PhD in Statistics to get the job done. Virtually every organization in the world is looking for Machine Learning/Deep Learning expertise, so this trend should help the supply side of this equation. The last analytics trend that is coming on strong in 2018 has to do with where data is analyzed. It will no longer be the exclusive domain of the cloud or large clusters of servers. The need to answer questions and make decisions more quickly is driving analytics of all types out to the Edge. Thanks to Moore’s Law and the need to eliminate latency, more and more edge gateway devices will be performing IFTTT and even Machine Learning predictions (with models trained in the cloud). There’s no shortage of important trends that are simplifying advanced analytics for organizations in 2018.

Clearly, 2018 is going to be a transformational year where properly-equipped decision-makers and leaders can shift their organization into the next gear to accelerate their digital transformation.

Hold on tight.

-Rob

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares that a Digital Twin is a digital representation of a physical object -- at Hitachi we call these Asset Avatars.  Asset Avatars are comprised of two components, an Avatar Type which defines the attributes and behaviors of a physical object and the other is the Avatar itself which collects and acts on sensor data.  You can think of the Avatar Type as the asset's DNA and the Avatar itself as the brain.

 

Justin Ruiz

A Failure to Launch?

Posted by Justin Ruiz Jan 1, 2018

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains what is preventing the $11 Trillion Internet of Things business from launching into the stratosphere.  It needs to be easier to develop, deploy and use. It needs to work with existing machines and devices, not just the latest and greatest. Projects need to be geared toward getting quick wins rather than multi-year efforts to boil the ocean. The combined costs of all the IoT components must be lower to ensure an ROI for customers. Lastly, every component of an IoT solution must be secured from hackers or no one's going to deploy this technology.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares his experiences from his participation in the creation of numerous Internet of Things (IoT), Mobile Device Management (MDM) and Mobile Enterprise Application Platforms (MEAP) over the course of his career.  These software platforms share many valuable concepts and technologies that can help drive digital transformation when combined together.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares that despite the great promise of IoT to improve business and society, many think it's being held back due to complexity and the associated lack of required skills to make it a success. Is it possible that the antidote to this complexity and skill shortage problem lies in the existing open standards and technologies that comprise the World Wide Web?

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains how you can streamline your processes and cut costs by putting your supply chain on autopilot.  An IoT platform can make B2B connections to vendors and suppliers to automatically reorder products based on inventory levels and customer preferences so you never run out of stock and always deliver the products customers want.

 

Justin Ruiz

The Collaborative Edge

Posted by Justin Ruiz Jan 1, 2018

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains that when retail machines talk to each other directly or collaborate through edge gateways, customers are more likely to find what they're looking for. Why lose a sale due to a lack of inventory when a customer can be redirected to a nearby location where their product preferences can be met.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains that in the same way Uber matches the drivers of cars with people who need a ride, smart connected products can be matched with people looking for those products. Mashing-up products, proximity, preferences and people can lead to sales.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares that by capturing real time inventory data from vending machines, smart shelves and other instrumented sources of retail data, you can identify customer preferences which let you quickly manipulate a product mix to increase sales.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains that the Internet of Inventory is all about remote monitoring use cases where sensors send telemetry over wireless networks to tell us current inventory so we can make intelligent decisions about what to stock.

 

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he uses the example of "meter reading" to describe the evolution of remote monitoring.  Remote monitoring started as a very manual process with people capturing meter data on paper and later transcribing it into a computer system back at the office. The mobile revolution sped things up, reduced errors and used the magic of wireless to transmit data from the meter reader's smartphone to a computer system back at the office. With the Internet of Things you put a sensor on the meter along with a SIM card to automatically stream readings back to the office computer system.