Think Big: How Design Plus Data Will Change Your Business

Is design thinking catching your attention? It should. Data insights not available before now can transform your business models and allow you to lead in your industry when you incorporate elements such as predictive, mobile dashboards and machine learning. This wave of change is forcing data architects to re-think and re-design how programs and applications must be built. To truly innovate, design teams need to push the design thinking envelope on almost every project.

“You can have data without information, but you cannot have information without data.”
– Daniel Keys Moran, computer programmer and science fiction writer.

Since the invention of the first computer, the world has been on a digital light-speed journey – one that has seen massive change in how we interact with our world and with each other. Today, there are more than 2.5 billion[i] smart phones carried in people’s pockets – each more powerful than the ones used to run the spacecraft that landed the first men on the Moon.[ii] In particular, how we interact with and gain insight from data has gone through an incredible transformation. We have evolved from relying on simple historical reporting – from the days of simple reporting to now, where tanker.

The Way It Was

Reporting has always been a critical element for a business to thrive and we have been accustomed to seeing our reports – our data – in fairly standard and historic terms. Let’s take a straightforward quarterly sales report at a consumer retail company, for example. Simple data, like units sold, prices received, cost of goods, volume of shipments and so forth, would be gathered and stored over a three-month period and then used to generate a few charts and graphs. Conclusions would be drawn from this static data and the company would shift strategy based on the conclusions.

Perhaps the conclusions were accurate and maybe they weren’t. Regardless, that’s how it’s been done for a long time: based on the data available.

The Way It Is

Today, the capability exists to break down data into far greater detail, do it in real-time and through disciplines like machine learning and artificial intelligence, draw highly focused and accurate conclusions not at the end of a business quarter but at the end of each day, and, in many cases, as it happens.

IoT Changes Shipping Industry – Reduces Risk and Cost

A client that operates a fleet of tankers equipped with IoT sensors wanted to move beyond its basic data reports and drill deeper into the technical data gathered aboard its vessels. Optimus utilized elements from Microsoft’s IoT Suite, including Azure Data Factory, to create visually appealing reports and dashboards that contained information gathered from thousands of sensors throughout the fleet.

The results meant a far more in-depth data analysis than the company had been getting, delivering more accurate insight for more accurate business decisions. When it comes to tankers, a simple mistake can cost millions in terms of lost time, environmental disasters, financial penalties, missed deadlines and more.

Optimus solved the client’s existing problem while building a platform for continuous improvement with data analysis using Microsoft Azure tools. Because the data can be aggregated in the cloud, the client can analyze greater amounts of data over an extended period of time, thus further enhancing their shipboard operational analysis and implementing global cost saving efforts as a result.

Now, a business can make highly informed decisions immediately and adjust accordingly. Of course, it’s not simply analyzing a few traditional data points, like sales; it’s analyzing where those sales took place, in which store locations, even in which aisles or departments, at what time of day, from which shelf the customer chose a purchase, what the customer’s likely income level is– in other words, the more highly specialized the data, the more highly specialized and precise the conclusions that can be drawn.

Because it’s possible to generate highly detailed data and analyze it from so many different perspectives, every sector of the economy is making use of data analysis.

In the manufacturing sector, factory operations are being revolutionized[iii] by both big data and analytics. Sensors generate endless streams of data on the health of production line equipment, data that’s being examined by the minute for the slightest indication of a potential problem or defect. Conclusions are drawn and actions implemented immediately to avoid any breakdown and disruption in the production process. There’s a positive ripple effect to this: customers don’t experience delays and the company doesn’t experience a loss of revenue.

The virtually unlimited storage capacity in the cloud, coupled to highly sophisticated computer algorithms that can perform serious analysis in, literally, seconds, is placing tremendous demands on data architects. Programs and applications must be agile enough to allow for updates, added features and improvements without delay. This has meant developing new architecture that can not only run a program at lightning speed but can be altered or updated in the areas where it needs improvement, much like making incremental improvements to a car model but without re-designing the whole car every time.

Gone are the days of a monolithic software structure where data warehouses needed a year or more to be designed and several more months for data to be inputted. If missing data was discovered, it would mean an entire rebuilding of the program.

Microservices and Teams

Today, Optimus Information designs architecture so that updates, changes or improvements can be made to one area of a program or application without having to open up the whole program. By using microservices in our software development, Optimus has created functional teams whose responsibility is to just one area of a program. A team focuses only on its specific area and generates improvements without impacting other teams or resulting in an overhaul of an entire software product. Tremendous amounts of time are saved for our clients and the cost of updates or re-designs is driven down dramatically.

Optimus applies the same method to data gathering. By means of advanced tooling, our clients can store raw data, without pre-aggregating it, run a query on that raw data and have the answers they need in a matter of seconds. Previously, it would take weeks to get a result because the data would have to be assessed and compartmentalized as it was gathered and placed into structured environments before a query could be run. This is what we call modern data warehousing. The focus is on agility and speed.

Down the Road from Microsoft by Design

Optimus specializes in working with IT departments of companies that don’t or can’t spend the time and money to develop the cloud-based software architecture needed today. Optimus uses a suite of leading edge services, on the Microsoft Azure platform, that allow us to select exactly the right components to solve a client’s problem. We are physically located close to Microsoft’s Vancouver and Redmond development centres

Optimus is a Microsoft Gold Partner and, in that role, we work very closely with Microsoft on new product previews and trials that are in development, giving feedback that improves our customer’s end product. Optimus employees have often already kicked the tires on new Azure features before they are released. This keeps us at the forefront of rapidly changing technology but let’s us give feedback as enhancements are designed.

If you want to enhance and sharpen the results of your data analysis, we invite you to contact us. We are happy to explore some “what-if” scenarios with you to help propel your data insights – and your business – forward exponentially. Reach out and schedule a virtual coffee anytime.

Top 10 Most Innovative IoT Companies

The IoT ecosystem has come a long way in recent years with multiple big players coming into the field. We take a brief look at the top companies investing heavily in IoT including industrial giants, semiconductor manufacturers, cloud providers and key players in the consumer and retail sectors.


Samsung’s goal is to have 100 percent of their products IoT-ready by 2020. They are concentrating their IoT efforts on smart, compact, energy-sipping sensors and their embedded package on package technology known as ePOP. ePOP and their Bio-Processor are made to fit in the expanding market for wearable and other small portable devices. They support an open developer community that is growing their IoT influence across a wide variety of industries.

General Electric

GE’s Predix platform has been designed specifically for IoT applications that integrate machine-generated data flows with cloud computing platforms. In other words, they are right in the thick of things when it comes to leveraging big data. Among the areas where they are helping leverage IoT technology are electric grid management, transportation fuel optimization and hospital operations.


Intel is a leader in supplying IoT components and platforms. Each year, they increase their commitment to IoT and already have an impressive portfolio of products such as intelligent network gateways and new low-power processors like Intel® Quark™ and a new Intel® Atom™ processor family. They have put together a complete IoT reference model to work with third-party IoT solutions also.


Cisco is positioning itself as the answer to one of IoT’s most vexing problems: security. They hope to be the leader in IoT security certifications. They are working on providing their own IoT analytics platform as evidenced by their recent acquisitions of Jasper, OpenDNS and Parstream. Overall, they are stimulating IoT growth via open standards, while moving the industry to an integrated end-to-end architecture that spans the space between devices and the cloud.


IBM has built a significant portfolio around IoT data analytics and cognitive computing platforms. Their Watson IoT platform brings cognitive computing into the IoT mix, which is their answer to the difficulties of using conventional programming methodologies across millions of connected sensors, devices and systems. They have chartered an entire workforce of nearly 1,500 employees running on$3 billion of investment over five years dedicated to IoT.


Microsoft has been criticized for coming to the IoT party late, but they recently announced new Azure Cloud services targeted specifically at processing data from embedded devices to support IoT big data analytics. Additionally, they have released a version of Windows that supports Intel’s Arduino-based, x86 development board named Intel® Galileo. They hope to insert Windows into IoT applications in the health care, retail, manufacturing and automotive sectors.


Google promotes the idea of a single language network of interoperable IoT devices. They offer the Google IoT Cloud Platform, which enables IoT device applications to take advantage of their fast global network and powerful data analytics tools. They are also backing the Thread Group’s project to enable disparate IoT devices to communicate with one another. Google’s cross-platform micro-OS, named Brillo, is aimed at IoT devices based on ARM, Intel x86 and MIPS hardware.


Aside from the many IoT products Amazon sells on its retail site, Amazon is developing a number of consumer level embedded microcontroller products such as a portable, intelligent button used for automatic restocking of household products. They recently acquired 2lemetry, which focuses on enterprise platforms to manage IP-addressable machines and devices. Like Google, their AWS division also offers specialized IoT-enabling cloud services.


San Francisco-based, cloud computing services company Salesforce is another entrant in the IoT-enabling cloud services market sector. Its IoT Cloud is powered by a real-time, scalable processing engine called Thunder. This is an open source platform built from four collaborating technologies including distributed, real-time processing aimed at big data analytics. The thrust of the technology is to gather and analyze data at IoT scale and condense it into meaningful interpretations at the Salesforce UI.


AT&T is partnering with several companies via its IoT business unit to supply network infrastructure and its own brand of IoT-scale data analytics. They have already chartered several AT&T Foundries to stimulate innovation with regard to IoT. These Foundries bring together VCs, developers and startup companies to propose new ideas to which AT&T could contribute. It is a fast-paced way to deliver pitches to decision makers. Via Foundries and their employee TIP program, they are funding IoT solutions in a wide variety of areas including Smart Cities, Connected Health, Connected Business and Connected Home.


A huge, virtual IoT community is quickly forming that is being fueled by some of the biggest technology companies on the planet. Already, IoT platforms, the networks to connect them, cloud-based analytics and hordes of innovative solutions are being born and coming together across multiple industries around the globe.

IoT Challenges and Opportunities

The Internet of Things is poised to exponentially expand from the millions of devices and services available today to billions of components in the coming years. It is difficult to envisage all the ramifications that follow its full-on manifestation not unlike when the Internet took off in the 1980s.

Despite a lack of prediction precision, however, we know that IoT will induce tremendous impacts on standards, security, business models and individual lifestyles. The obstacles to its adoption are enormous, but so will be the opportunities that ensue.

Fundamental Drivers of IoT

IoT’s key technological enabler is the proliferation of rapidly shrinking, low-power sensors and embedded IP-addressable devices. These find their way into applications in manufacturing, the health care sector, consumer products and public infrastructure. Everyday things such as kitchen appliances, automobiles and parking meters – not previously considered “computers” – are now active IoT participants.

These devices generate, gather and act upon “micro-data” that in the aggregate will trivialize the scale of today’s Big Data streams. These data are in demand by increasingly sophisticated analytics services that improve IoT-enabled product performance. They also super-charge a blossoming analytics segment feeding automated enterprise decision-making systems.

Barriers to Adoption

Security and Privacy

The sheer scale of a full-blown IoT approaching a hundred billion devices has a potential to pose unimaginable problems, the first of which are likely to be around privacy and security. IoT offers an enormous attack surface for malware. It adds layers to the software/hardware stacks employed today, which also creates new security risks.

IoT’s data flood being shared across its infrastructure creates the certainty of privacy breaches. Even though single data burst may not contain personally identifiable information, those with criminal intent have an opportunity to create hundreds or thousands of associations that may yield something useful to them. Furthermore, all such data that is stored is subject to attack as well.

Lack of Widespread Standards

Clearly, IoT is well ahead of new standards that would mitigate its inherent complexity. Look forward to a mix of competing standards and proprietary solutions that create a heavy friction for device manufacturers, developers and testers, even though the success of IoT demands a high level of collaboration if it is to reach full promise.

Although in theory IoT presents a rich platform for experimentation, especially for aggregator services layered over it, a lot of junk apps and services will surely crop up. These will muddy value propositions and ROI evaluations for many businesses, especially startups that have worthwhile IoT concepts. At the least, this creates a perceptual drag on IoT.

Opportunities Abound

Despite the obstacles to IoT, it appears it will not fall off a cliff anytime soon. One estimate of its economic potential comes from the McKinsey Global Institute, which estimates it to generate value from $4 trillion to $11 trillion by 2025 in consumer and business applications. IoT participating technology companies producing hardware, software, services and integration are all likely beneficiaries.

Semiconductor Giants as Solution Providers

Already, semiconductor companies are seizing the IoT moment. At the core of every IoT device is silicon of course. However, the most nimble and forward-looking semiconductor companies realize that providing packaged solutions in the form of micro- or pico-sized IoT devices represent a new revenue stream. They will be able to skirt obstacles such as security by keeping these a closed system.

Wearable Health Care and Smart Homes

Already, a huge investment is being made in the healthcare sector in IoT-capable wearable health monitoring devices and supporting technology. Another growing sector is smart home monitors and security systems that rely on a multitude of sensors and actuators that send and receive data and commands remotely. These alone are projected to generate revenue of half a billion dollars in the next few years.

Unimagined Innovation

The application for IoT sensors seems only limited by human imagination. Farmers are already using them to monitor crops and livestock and automating adjustments in food, fertilizer and pesticides. Retailers are utilizing IoT devices to monitor inventory, learn more about their customers and provide them with personalized information and offers. Cities are using IoT to monitor traffic and pedestrian flows, which they optimize via traffic signals or lane sharing.


IoT is at the cusp of transforming our daily lives and society as a whole in ways that go beyond the onset of the Internet. Although IoT faces significant headwinds as it gains speed, especially in areas such as security, privacy and testability, these will be overcome eventually.

Major companies such as Google, Cisco, Microsoft, Intel and many others are already contributing to IoT’s growth, but that does not mean there is not plenty of room for as yet unheard of startups to profit from recognizing both the challenges and opportunities of this new technology wave.

IoT Goes Open Source With the Linux Foundation’s Zephyr Project

Linux is well-known for being the OS of choice by adept PC users. It is also widely deployed in Internet servers and industrial control systems due to its small footprint, operating efficiency and open-source legacy. Attributes such as these also make it a natural choice to be a driving technology in the nascent Internet of Things or IoT.

The Linux Foundation recently announced the Zephyr Project, which is squarely aimed at bringing the best of Linux to IoT devices in the form of a small-scale real-time OS or RTOS. The project is being supported by some big IoT market players including UbiquiOS, Synopsys, NXP Semiconductors and Intel.

Zephyr as an IoT Accelerant

One of the many obstacles hindering IoT growth is the lack of interoperability standards that can be utilized by IoT device manufacturers. Zephyr could be the answer to that as a single, unifying, highly customizable, scalable and secure OS if the project is successful at meeting the extremely tight constraints required of IoT devices.

Linux already has many “micro” distributions that are used in a variety of applications as a reliable RTOS that uses a minimal memory footprint. Zephyr proposes to take these features to their limit in the nano-OS world of IoT.

The fact that Linux is open source, i.e. free, is an additional incentive to its use. Its adoption could go a long way toward realizing full value from IoT as it drops device costs and communication barriers between products from disparate vendors. Furthermore, being open source enhances the security of Linux, since code is open for scrutiny by security experts. Security is one of the biggest concerns around IoT, which is why Zephyr will include a dedicated security group.

How Low Can You Go?

There are at least a dozen small footprint Linux distributions made for PC users. One of the smallest is Tiny Core Linux [] with a six megabyte image that runs from removable media such as a USB pen drive. It even includes a GUI desktop. Others have taken Linux “distros” down to 200KB of RAM for storage and one megabyte of flash for OS execution.

Such a minimal footprint is not small enough for IoT devices controlled by relatively simple microcontrollers that use no more than 10KB to 100KB of memory for storage and OS. Furthermore, in that sparse space, an IoT device is expected to operate in real-time. These constraints are formidable obstacles. The highly collaborative, community-based effort of Zephyr is an ideal approach to solving such problems.

Zephyr Goals

Zephyr is dedicated to producing both micro-kernel and nano-kernel versions. These are initially to be based on the contribution from Wind River Systems of its Rocket RTOS kernel. The nano-kernel project aims to run in no more than 10KB of RAM using a 32-bit processor.

More specific goals are stated for Zephyr as well:

  • It will be independent of CPU architecture, although it initially supports only x86, ARM and ARC.
  • Supported platforms include Arduino 101, Arduino Due, Intel Galileo Gen 2, MinnowBoard MAX, Quark D2000, Quark SE and the NXP FRDM-K64F Freedom board.
  • It will be modular, scalable and highly secure.
  • Connectivity support includes Bluetooth, Bluetooth LE, IEEE 802.15.4, CoAP, IPV6, and NFC.
  • Powerful development tools are part of the package with the kernel and select components open source under the Apache v2.0 License.

Long-term Impact of Zephyr on IoT Development

Despite IoT’s small-scale granularity, extreme scalability and potential for millions of new apps, its lack of standards and plethora of proprietary solutions have posed a significant hindrance to it being a hotbed for innovation. Diminishing such barriers, therefore, may be the Zephyr project’s greatest contribution to the growth of IoT.

By definition, open source platforms enable thousands of developers worldwide to invent new use cases, new apps and unique solutions. If the platform is inadequate for them to implement their solutions, they are free to modify the platform itself. This aspect will provide an enormous stimulant to IoT expansion. Zephyr’s primary goals to create an OS that is extremely flexible and scalable fits hand-in-hand with the open source development paradigm.


The Zephyr project will be seen in hindsight as a major inflection point in the progress of IoT. It is a boon to developers, enterprises and ultimately for consumers who will enjoy a much higher degree of interoperability, reliability and security among the IoT devices that inhabit their daily lives. Given that open source Linux is already utilized in a majority of enterprise networks and computational infrastructure, Zephyr adoption should be relatively smooth sailing as compared to a fragmented world of one-off OS solutions.

Internet of Things (IoT) Predictions for 2016

This year, nearly every major intelligence gatherer/analyst is jumping on the IoT bandwagon making forecasts about where IoT is heading in 2016 including Gartner, IDC, Forrester, WEF and Machina Research. We did the same thing to bring to you what we think are the best-of-the-best predictions for IoT trends on 2016.

IoT Enterprise Adoption Reaches a Tipping Point

The major thrust for IoT continues to come from the enterprise side versus the consumer side of the markets. According to Forrester, over half of businesses are already utilizing IoT or will within the coming year. Most of these enterprises are leveraging IoT to optimize use of company assets or as part of a transition from discrete products to product-based services. Further accelerating this trend will be the emergence this year of end-to-end IoT platforms that will go a long way to reducing the potential complexity of creating IoT apps and services.

Consumer Awareness Is on the Rise

On the other hand, 2016 is a marker year in IoT consumer awareness as most customers are now explicitly inquiring about the number and types of sensor/communication technologies that are embedded in new products from kitchen appliances to home security systems to automobiles. Companies this year are more than ever touting their products’ “connectedness” and home insurers are offering discounts to smart house homeowners.

Semiconductor Companies Are Jumping In

Intel especially has come to recognize that IoT is a hugely expanding market for them that could offset their shrinking sales in the PC market. IoT was a major consideration in their acquisition of semiconductor company Altera last year. This year they are developing complete IoT devices including sensors, embedded CPUs and communications. They are putting strong focus on applying their newly-found IoT expertise in the retail sector as evidenced by recent partnerships with SATO and RetailNext.

IoT Player Consolidation

Other big-tech companies are positioning themselves for IoT growth by acquiring smaller players, and that will accelerate in 2016. Cisco bought out IoT analytics company Parstream in late 2015. More recently, they acquired the largest IoT platform provider in the world, Jasper. Sony is acquiring chip company Altair Semiconductors, which is a leader in modern chip processes and cellular technology.

Keep your eye out for several rumored acquisitions coming this year including FireEye, Proofpoint, Fortinet and CyberArk.

The Numbers Continue to Astound

If the previous predictions seem a disputable, here are some hard numbers predicted by Gartner for the coming year:

  • 2016 will see 6.4B “things” connected worldwide
  • Over 5 million of these “things” will be connected every single day
  • Between consumers and enterprises, IoT hardware spending will exceed $1.4B
  • IoT service spending will be 22 percent higher than last year and total $235B
  • The downers are that there will be a multi-billion black market spawned that sells fake IoT data, personal privacy breaches will increase and the vast majority of IoT projects will take far longer than planned.

Public Sector IoT Accelerates

Smart Cities, Smart Grids, Smart Buildings are all areas that are accelerating this year, especially in Germany and Scandinavia. Finland, for example, uses trash can sensors to reduce the costs of garbage pickup by 30 percent. Although the trend in public sector IoT began in Europe, it is accelerating in the Asia/Pacific region as well as in North America.

This year governments across the globe are starting to implement IoT rather than just talk about it. They are connecting motion sensors to streetlight to save energy, distributing smart parking apps that monitor when spaces free up and are employing IoT to optimize the use of and to share public services assets such as road equipment and transportation.


Underlying mega-trends continue to pump juice into IoT, such as cheaper sensors, processors, bandwidth, the long-awaited move to IPV6 and various types of wireless coverage in every nook and cranny.

A few holdouts still see IoT as nothing more than an already flat fad given that the IoT equivalent of “flying cars” is still not on the horizon. However, in the face of the numbers and moves by some of the biggest tech companies, it is hard to take these critics too seriously.

So far, the reports of IoT’s demise are supremely exaggerated and many past predictions have been exceeded already. IoT will surely experience bumps and jolts along the way to the prediction by IDC that IoT spending will surpass $1.7 trillion by 2020, but for this year and beyond it appears to be an unstoppable wave that is far from cresting.

How IoT Impacts Your Organization

Increasingly, companies across all business sectors are realizing they need to adopt an Internet of Things mentality, or Internet of Everything as some put it, in order to keep their business expanding in the right direction. In many cases, IoT is only understood as a newly coined buzzword without a full comprehension of how it will impact the business from inside and outside. We look at a few of the most important ramifications for your business to become IoT-ready.

The Prerequisites for IoT Participation

If your business has even a hint of being behind in terms of technology, one of the first orders of business should be a full evaluation of your current machinery, network and computational capabilities. The main question you have to ask is how well-connected your current infrastructure is to the Internet, and does your business’ infrastructure have the capability to communicate with itself and internal business processes.

Upgrading your technology capability for IoT might be done piecemeal, but it is more likely to require a full overhaul over the next few years. The basic rule of thumb here is to make sure that any new equipment and its software is designed to connect to the Internet.

Get on the Cloud Now

As part of your technology capability evaluation, think about how your activities, processes and machinery can be moved to the cloud. Not only can use of cloud infrastructure and cloud-based services reduce capital costs, it is an ideal way to make sure your company keeps up with IoT developments and other technology improvements. It also enables the business to scale up and down seasonally or permanently as the business grows or new markets are entered.

Invest in Your Employees

Even if you personally are not fully conversant in IoT and its value relative to your business, it is time to start educating your employees. You may find they already know a lot more about the topic than you do. They probably will provide a wealth of ideas about improving the business’ IoT readiness. This is especially true of Millennial employees as they are more than likely to already “get it” with regards to IoT.

Brainstorm Taking Advantage of IoT

Once you and your employees understand the business is adopting an IoT-centric viewpoint, it is time to imagine ways to leverage it to increase sales and profits:

  • Look for ways to reduce operating costs with IoT. This can be done by using IoT products to reduce electricity or fuel consumption, improve asset management, perform more efficient machinery maintenance, increase operating uptime or make employee life-work balance more effective.
  • Seek out ways to use IoT to improve your customers’ experience. This is especially applicable to retail outlets, which can utilize closed wireless networks in stores plus downloadable apps that provide customers a higher level of connection to products and offers. Done correctly, this connectivity acquires data pertaining to customer preferences and buying habits.
  • Invent new, connected customer-centric services by leveraging the plethora of sophisticated, but easy-to-use, IoT development platforms available these days. These are new products or promotional collateral that will keep customers connected to your business throughout their daily activities.
  • Ask how to make your existing products more IoT-friendly. IoT-capable appliances, tools, electronic devices and other products are increasingly including IP-addressable components that allow them to be monitored or controlled remotely by customers or maintenance services. The majority of customers now expect to find such capabilities in all manner of products. If your products lack them, they may be at a competitive disadvantage.

Readiness to Handle Big Data Flows

Larger businesses, especially those with a broad portfolio of IoT-enabled products, need to prepare for an onslaught of data flowing from an expanding deployment of IoT products that growing at a 30+ percent rate per year.

Regardless of whether your enterprise is moving to a cloud infrastructure or not, these data flows require upfront planning, ongoing monitoring and resource allocation. Especially if your business is planning to take advantage of real-time data analytics from thousands or millions of IoT components, you probably need to invest in higher performance hardware, software and expert training.


The Internet of Things is no longer a future concept. It is happening right now and accelerating at a phenomenal pace. Every business, whether in the technology sector or not, needs to educate themselves regarding the prerequisites to participate in IoT, and what it means to their business operations, to their customers and their product portfolios.

IoT might require a complete re-thinking of your organization’s structure or it could be approached in smaller steps, but the time to start thinking about how IoT impacts the business is today.

IoT and Enterprise Security Risks

In one sense, the Internet of Things has been around since the early days of the Internet. The geekiest of early Internet users found that it was child’s play, for instance, to discover and interact with – unauthorized of course – thousands of unprotected Windows PCs and their peripherals. The IP addresses of these devices were easy to find on public hack lists.

The State of Today’s IoT Security

Unfortunately, for much of what constitutes the IoT today, security is hardly better. In fact, there is a website, Shodan, that lets anyone search for networked devices, many of which are unsecured, across the globe. The majority of these are webcams, but there are many scanners, printers, control devices, routers, ftp sites and more that are exposed.

Clearly, if IoT is to meet growth expectations and survive a series of inevitable high-profile hacker attacks along the way, it needs to start looking a lot less like a sitting duck.

Steps to Improve Enterprise IoT Security Now

The current paucity of IoT security means that enterprises must augment IoT vendor security with some common sense precautions. The first step is for IT to use the network management system to scan for all exposed IP addresses and set alerts when new ones are detected.

Additionally, it is good practice to verify that each device is actually what its network profile says it is and determine if it should be network accessible at all. Its authorization protocol should be evaluated for sufficiency compared to the asset being protected. It is common, for instance, for network device username/password pairs to have never been changed from their defaults.

Imagine the Problem Scaled Out Exponentially

A quick survey of enterprise IoT devices may cover dozens, hundreds or even thousands of devices. Now, imagine this task at the scale of the 10s of billion connected IoT devices expected to be in place by 2020.

To extract additional value from IoT, there will be layering apps that aggregate data and control streams from a large diversity of such devices to look for patterns that might legitimately be useful for predicting, say, the weather or the velocity of a particular market sector. Illegitimate uses of such data that violate the privacy of individuals and groups of individuals in this manner are not difficult to imagine however.

Such a scenario is bad enough, but it gets worse. Future IoT edge devices will collaborate among themselves through data sharing and behavior modification of fellow edge devices, which may come from different manufacturers. Robust communication and API standards will make this possible and it is generally a good thing. However, such inter-device activity makes an already humungous hacker attack surface exponentially bigger.

Approaches to a Secure IoT

Best practices, standards and technology with regard to security are already in place for the computational, storage and networking resources in the Internet, but these will need serious upgrades in the context of IoT. One hundred percent security will never be achieved, but applying risk management techniques will mitigate the potential for catastrophe.

As IoT matures, manufacturers of edge device packages, network providers, middleware vendors and analytics software producers all must contribute expertise and tools:

  • Privacy and security measures must be built into all layers from sensors to dashboards. Since IoT devices are essentially nano-computers, more security must be built into the hardware. A full-stack approach will provide defense-in-depth that could contain attacks within any single tier.
  • Analytics must take into account security risks in addition to business algorithms. This additional functionality should be aimed at detecting unexpected or suspicious network behavior. This ability could, for instance, detect malicious traffic indicative of a distributed denial-of-service attack.
  • In much the same way that lost or stolen devices in an enterprise BYOD environment are handled, IoT endpoints that have “gone rogue” should be disabled. Of course, a disablement interface must be managed as a security risk also.
  • End users at both the edge and the analytics tier must be thoroughly educated in how to protect their privacy, which behaviors to avoid and the signs to watch out for that may indicate a security or privacy breach.


As with any new technology, there are benefits and there are risks. In the case of IoT, it seems that both sides of the coin are equally gargantuan. Until IoT security standards and practices catch up to the impending explosion of networked edge devices now being deployed, individuals and organizations have to be the first line of defense in ensuring reasonable security and privacy through the use of IoT.

IT security teams need to review their own security best practices and update them to account for the new world of millions or even billions of independent, connected, smart devices that are able to communicate with one another and are delivering torrents of unstructured data back to the enterprise.

How to Develop Apps for the Internet of Things

Analysts are generally in agreement that the Internet of Things will generate an enormous amount of economic value. They only disagree on how big the wave will be. Indications are that 10s of billions of IoT edge devices will be in place over the next few years and that over half of homes in developed countries will have IoT incorporated into their daily lives via their cars, home automation, appliances and wearable technology.

One of the key enabling pieces for IoT expansion is the growing presence of IoT-ready development platforms coming online. Some are offered by tech giants such as SAP, Microsoft and IBM, but many smaller players exist that offer all the tools a company needs to develop their own IoT contributions rapidly and cheaply.

The Three IoT Development Tiers

Edge Devices

The endpoints of IoT are as diverse as they are plentiful. They mostly consist of sensors packaged with a low-power microcontroller, real-time OS and wireless networking capability that outputs its data via an Internet gateway. The majority of IoT hardware platforms have no screen, but provide an HTTP or other common protocol interface through which they are managed.

The types and classes of IoT sensors are virtually endless including thermometers, light meters, tachometers, manometers, cameras, GPS receivers and more. The applications built on top of these sensors are equally numerous. Most are engaged in monitoring activities in health care, farming, manufacturing management or keeping track of more mundane things such as your refrigerator’s efficiency.

Data Ingestion Tier

IoT device data are sent to a second middleware tier of software and server infrastructure that provides an in-house or public cloud processing service. This tier provides IoT edge device vendors or users a way monitor and update devices en masse. It also aggregates, organizes and pre-processes the relatively unstructured data streaming in from the edge.

End-User App Tier

The topmost tier in a typical IoT hierarchy applies sophisticated analytics capable of providing real-time insights into how an enterprise’s products are performing and being used. This software feeds directly into automated business decision processes that, for instance, regulate supply chains. It often provides real-time, interactive dashboards with several tabs of graphical and customizable data displays.

Leveraging IoT Platforms

Assuming that your organization is software focused and is leaving the innovation and manufacturer of edge devices to hardware companies, your activity will be concentrated in the ingestion and end-user tiers. Leave it up to the big manufacturers to continue pumping out increasingly cheaper and more able IoT edge devices.

Rather than taking a painstaking, do-it-yourself approach to creating the software in the top tiers, there are plenty of ready-made IoT development platforms of which you can take advantage. Many of these, such as SAP, Oracle and others, provide a complete end-to-end IoT platform that includes middleware and analytic APIs to which you add your customized app layer. There are also a number of startups whose products can spin up your IoT development in a hurry.


ThingWorx is a highly flexible IoT development platform that can even be used by non-coders. Their Composer™ tool models all three tiers, which simulates a complete mockup of your IoT app including program logic, storage, security and visualization.

Their drag-and-drop Codeless Mashup Builder pulls together apps, dashboards, and mobile interfaces without any code to create a complete solution. Bringing on a new sensor type is simply a matter of writing a JavaScript connector to incorporate it with the ThingWorx platform.

ThingWorx also provides device management utilities that monitor and interact with all the connected things in your app. Their Business Process Manager enables analysts to create live process flows from single or multiple edge device inputs.


Xively apps are written in whichever development language your developers want. Apps integrate with their IoT API, via HTTPS or other communication protocols. Companies typically get their first IoT app prototype up and running in a week.

Their cloud platform includes everything needed for rapid IoT app development:

  • Secure handling of consumer and operational data
  • Real-time, secure messaging and routing protocols
  • The ability to customize permissions based on group or object properties
  • User and device management via a sophisticated Web interface
  • Storage for data streams and archiving
  • The ability to build analyst dashboards, predictive analytics and automated business decision-making processes without coding

Xively’s APIs support data transfer and control via almost any protocol you wish including REST, HTTP, HTTPS, MQTT and more. They provide connector libraries that are installed on edge devices that pre-packages data of interest and transports it to Xively’s cloud platform.


Besides the myriad IoT development platforms already available, there is a growing body of code examples showing up in places such as GitHub and IoT forums. It is a dynamic environment, however, and lacking substantial standards, so it is probably a good idea to assign your IoT app development to your most innovative programmers. Alternatively, you could wait until the field is more fully developed, but then you risk falling behind what might be the biggest tech wave since the Internet.

Testing the Internet of Things

The precise definition of the Internet of Things varies according to the beholder, but in general constitutes a broad array of sensors, actuators, devices that communicate with their creators, users and other devices. More technically, any IP-addressable thing with a digital brain qualifies, although the smartest devices, i.e. PCs and smartphones, are typically not considered members of the IoT club on par with smart home devices, smart kitchen appliances, smart cars, smart cities, etc. Your kid’s teddy bear should be joining the IoT shortly, however.

Why IoT Testing is Different

Testers embedded in the world of PCs, servers and mobile apps will readily detect a substantial difference in IoT’s input/output model. Keyboards, displays, touchscreens and audio are decidedly minimal for IoT devices, if they exist at all. These devices might interact via motion or thermal detectors, cameras, and by monitoring and recording our behaviors such as when we open and close the refrigerator door. In fact, many IoT devices never interact directly with humans, which requires that their “correctness” is evaluated indirectly based on interactions within a system context that may include other IoT devices.

Less complex I/O and compute power of embedded devices reduces the number of functional and non-functional test cases when they are sitting on the workbench. However, a core concept of IoT is extreme connectivity, with interactions among a web of devices. This introduces a brittleness that may be outside the realm of many testers’ experiences.

Conformance, Interop and Security Testing Is Critical

To even come close to the heightened expectations for IoT, well-developed standards for interoperability and communication are vital. Otherwise, for example, communications protocol breakdowns between even a few IoT device types could create an enormous ripple effect depending on the roles of those devices and to how many other devices they are connected. Conformance and security testing in the IoT world is even more crucial than it is in the mobile device world today.

IoT Brings UX Testing to a New Level

The user experience for IoT-based services is potentially broad, subtle and complex. UI testing for a single device may be inconsequential, but IoT UX testing must encompass a larger context of intuitiveness, interactions, effects, expectations and satisfaction regarding the service in which the single device may play a small, but integral part. Today’s UX testing for PCs and mobile devices could appear trivial in comparison.

It is not difficult to imagine other non-critical side effects that are possible, even likely, when dealing with highly distributed interacting “things” with limited compute/storage/power resources, subject to asynchronous configuration changes or data delays going in or out of the device. Not the least of these are the possibilities for hacks and the release of private data.

For example, Philips IoT-enabled, LED lighting API allows Netflix to dynamically change ambient lighting in response to the brightness and color of an in-progress movie. Depending on a home’s layout, what other occupants are engaged in, etc., automatic lighting adjustments could be annoying or even disruptive. Such side-effect situations are within the domain of IoT UX testing.

It is easy to envision an in-home, elderly care medical monitoring service composed of IoT devices from disparate manufacturers, such as the Proteus ingestible pill sensor, a Metria™ wearable health monitor and a SmartThings home automation system going awry because one or more components silently failed an update or a communication protocol was subtly modified. Consequently, unintentional alerts to doctors or family members could disturb doctors and family and generate significant expense.

The Evolution of IoT Testing

Today’s IoT devices are easier to test due to their singularity of purpose, minimal connectivity and tentative expectations from human users. That situation is changing rapidly, however. IoT stakeholders, including test professionals, must raise awareness of the critical importance of standards and conformance if an IoT network effect is ever to get off the ground. In parallel, innovation in testing methodologies and tools must also sustain a sharp pace.

Fortunately, this is not altogether unfamiliar territory. Such complexity challenges have faced testers at every technology inflection point. The Internet evolved from static data repositories to an extremely dynamic, highly distributed, asynchronous system upon which “mashups” of complex services reside today. Improved standards, better tools, sophisticated testing methodologies and roll-up-your-sleeves innovation enabled test teams to keep up.

Highly connected, embedded IoT devices are consuming and generating data at an enormous rate. Harnessing and acting upon this information will create an array of new services heretofore unimaginable. To maintain the pace, test/QA teams must match this IoT innovation wave, especially with regard to evaluating human experiences in a context of services built upon countless devices with unprecedented connectivity.

How IoT Will Drive Big Data Adoption

According to Internet of Things true believers, the time is just around the corner when our cars, homes, appliances, TVs, PCs, phones and any other electronic or mechanical device in our lives will be spewing out data in all directions. That makes some sense, since IoT devices – at least those now envisaged – are designed for data spewing as they have minimal compute capacity presently.

Cisco estimates that already nearly 15 million connected devices comprise the nascent IoT, which will grow to 50 million by 2020. That sounds impressive until you realize it is less than 3 percent of the “things” on our planet potentially able to participate in IoT. Unfamiliar numerical terms such as zettabytes must enter our lexicon to describe the volume of data to be generated, consumed and analyzed.

What the IoT Data Wave Means for Big Data

The processing of the rivers of big data coming from today’s embedded sensors, telemetry, RFID chips, PCs, mobile devices, wearables, etc. already leaves 90 percent of these data in the dustbin. That is primarily because current big data hardware and software stacks are inadequate to manipulate it all let alone comprehend it.

Big data compute, storage and networking capabilities improve daily. However, even those enterprises on big data’s bleeding edge are today ill-equipped to handle the expected data flood gushing from the IoT let alone the larger Internet of Everything that Cisco tracks.

Even if IoT is realized in twice or thrice the time of most projections, then big data enterprises are going to be perennially behind the curve for the foreseeable future. The constant running to catch up will be the prime driver of the big data ecosystem beyond the next decade. If that does not kill big data, it will only make it stronger. Enterprises large and small will join the data mining gold rush if real-time analytics improve and a big data meta-architecture, as hinted at by Hadoop, emerges.

The Obstacles to a Happy Marriage between IoT and Big Data

Lack of Standards

Having to figuratively invent the wheel over and over again is the bane of any competitive industry. Without standards, IoT will struggle to reach escape velocity due to technology fragmentation. Standards must be in place for efficient access to “things”, consistent API interfaces, machine-to-machine communication, addressing privacy and security issues and lowering entry barriers to smaller, innovated players.

Closed or Inefficient Architectures

IoT is a game changer for big data architecture. All stakeholders are just now starting to recognize that dealing with IoT will require as much collaboration as competition.

The sheer magnitude of IoT data volumes dictate a layered hardware/software stack that is too gigantic, geographically dispersed and complex for a single enterprise or cloud providers. It begs for an ultra-distributed meta-architecture that step by step digests, absorbs and disperses unstructured data as it is collected, cleaned, normalized, correlated with other data, stored when necessary, deeply analyzed and presented. Along the way, vendors who today specialize in each of these processing layers will contribute via enormous arrays of small-scale data centers.

Analytics Capability Growth Rate

Above all else, business intelligence processing is the critical bottleneck to realizing the full potential of big data. The rate at which supporting analytics can improve is questionable without significant breakthroughs, but the search for data gold represents an immeasurable incentive. The deluge of IoT real-time data headed down the analytic pipeline will create even more pressure but is likely to engender even more opportunities for value extraction.


The Internet of Things is not an invention but a logical consequence of highly available, low-power, low-cost sensor technology and improvements in wireless connectivity penetration. Related technology improvements and cost-reductions in compute, storage and network hardware will complement the growth of IoT and make it something useful and valuable. And, finally, IPV6 is going to receive the appreciation it justly deserves.

All this power to generate, gather and process new, real-time micro-data is for naught, however, if it must be set aside awaiting analysis capabilities to catch up. Fortunately, although big data infrastructure and software are likely to be overwhelmed initially, that and analytic capabilities seem to have a bit of a head start. Increased collaboration among stakeholders, an effective, shared processing architecture and the inevitable analytical breakthroughs may just carry the day in the end.