When the idea of the internet of things first started gaining traction, the wireless network technologies that existed to support it were not designed with IoT in mind. These technologies — primarily 2G, 3G, 4G and LTE cellular technologies, wireless local area network technologies such as Wi-Fi, and short-range personal area network technologies (such as Zigbee and Bluetooth) — were primarily focused on discretely connecting specific, high-data devices to voice or data networks with little thought given to the power required to transmit the data.
What designers of these network technologies did not envision was a world of millions of tiny, low-data, low-power embedded devices whose purpose was to connect previously isolated physical “things” to the internet for data exchange and control — in other words, IoT. Yet, despite not having a network technology designed specifically for it, IoT has still managed to use existing network technologies to create a massive market, with Gartner estimating that 8.4 billion connected things will be in use in 2017, and total spending on endpoints and services will reach $2 trillion this year. Imagine how big IoT could become if a wireless network technology was built that could deliver broad levels of coverage for low-cost, low-energy devices? Such a network technology would enable us to truly realize the original vision of IoT — being able to connect everything to the internet, everywhere, all the time.
Imagine no more. With the arrival of low-power, wide area (LPWA) network standards — specifically CAT-M1/LTE-M, CAT-NB1/NB-IoT, and EG-GSM — and the technology needed to support these standards, IoT finally has a set of network technologies it can truly call its own. LPWA is designed to meet the core needs of IoT applications, with market-changing step function improvements in device and service costs (50% lower than broadband LTE), current requirements (more than 100 times lower power than broadband LTE), and coverage (five-10 times better coverage than broadband LTE).
LPWA technologies significantly lower device and service costs, making it economical to embed IoT devices in a host of new things. Its exponentially lower power needs allow IoT device manufacturers to achieve battery lives of 10 years or more. Also, LPWA’s dramatically broader coverage allows IoT devices to be placed underground, in remote areas and other places where coverage issues were previously a problem. In addition, there is no need to build a new cellular wireless infrastructure from scratch to support LPWA technologies — for the most part, they can be rolled out with just software upgrades to existing infrastructure.
Moreover, unlike the proprietary LPWA solutions that have grown by fits and starts over the past few years, these widely accepted standards are supported by the major wireless carriers. This support means that IoT application providers can adopt these standardized LPWA technologies without fearing that the ecosystem and network coverage needed to enable mass adoption of their applications will fail to materialize. With the arrival of these widely adopted LPWA standards, and the rollout of LPWA by major carriers starting this year, the IoT industry finally has the low-cost, low-current, broad coverage network technologies that its application developers have been dreaming about for years.
What will this mean for IoT? It means that IoT developers will finally have the network technology they need to develop new or enhanced energy, transportation, healthcare, smart city, agricultural, consumer and other IoT applications that fully realize the original promise of the IoT — making our world more sustainable, safer and more productive.
This includes water management IoT applications that preserve water, our most important natural resource. In an era of climate change, we can use IoT to optimize water use and reduce water waste over hundreds of acres of farmland in the rural countryside or across miles of water mains and pipes in a large metropolitan area. It means energy IoT applications that allow us to continue to make our energy cleaner, cheaper and more reliable by going one step beyond smart meters to monitor and control practically any energy using device that can be ramped up or down, including pool pumps, hot water heaters, air conditioners, EV chargers and residential battery-based energy storage systems. By controlling and optimizing these and other distributed energy resources, we can balance out peaks and dips in intermittent renewable energy generation, allowing us to integrate more renewables into the grid. The rise of LPWA also means inexpensive, wearable devices that provide a constant, always-on connection to cloud services, helping hospitals make sure discharged patients are healthy and parents ensure their children are safe at home.
Of course, the applications that might be the most game-changing and exciting are the ones we have not even thought of yet. LPWA provides a platform for fostering innovation that changes the way we work and play every day — just like PC and Ethernet technologies in the ’80s and ’90s and smartphone and cellular technologies in the ’00s and ’10s.
Like these technologies, IoT has grown from small, at times clunky (remember hobby PCs and brick-like cell phones) to become an advanced, global industry that is transforming the way we live. With a new network technology — LPWA — designed specifically with it in mind, IoT will be able to take another giant step forward, with low-cost, low-power, wide-coverage applications that can connect all of our things to the internet, and in so doing allow us to build a better world.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
It’s been nearly two decades since Kevin Ashton of MIT’s Auto-ID Center coined the term “internet of things, and the technology behind it has been around and evolving for even longer. Fast forward to today, and we are amidst the rise of the ultimate “thing” in IoT: the connected car.
By 2021, more than 380 million connected cars are expected to be on the road. In the meantime, automakers face a laundry list of challenges to ensure the safety, reliability, connectivity, management, optimization and more of connected car technology. Luckily, many of the same challenges have already been overcome by enterprises in other industries as they adopted various IoT-enabled technologies and processes. If the connected car market can put the same best practices into use, automakers and their partners will have a much smoother road to unlocking IoT’s potential. Here are five lessons the connected car market can learn from enterprise IoT:
- How to secure a vast array of attack surfaces. The connected car is like a data center on wheels, collecting, transmitting and storing copious amounts of information through dozens of connections (including cellular, Wi-Fi, satellite, Bluetooth and even physical connections to the on-board diagnostics port). Securing this vast array of attack surfaces is no easy feat, but is achievable through established enterprise IoT technologies and principles. First, an Internet Protocol (IP) over Ethernet backbone can consolidate and standardize disparate in-vehicle networks, allowing for deployment of proven security technologies, like firewalls and encryption. Second, artificial intelligence can be used to detect anomalies and patterns of malicious behaviors to alert drivers of potential threats or simply indicate that maintenance is needed. Third, automated IoT connectivity management platforms can help automakers continuously monitor their vehicles to ensure they are connected to (or disconnected from) the right devices, at the right times, in the right manner.
- How to manage numerous devices at once. The trend of BYOD caused quite the stir in the enterprise. IT departments struggled to manage not only company-owned machines, but also large numbers of personal devices employees began connecting to the enterprise’s network. In response, the enterprise adopted automated network management technologies, where network intelligence provides lifecycle automation, monitoring and diagnostics, continuous learning and even self-healing to hundreds or even thousands of devices at once. With the same technology, automakers and other members of the connected car ecosystem can seamlessly manage fleets of vehicles with various sensors and electronic control units (ECUs). From a single interface, it is possible to monitor the performance, security and more of every part or device, and even identify opportunities for improvement.
- How to update and configure software. Many vehicles already have more than 100 million lines of code under the hood, and the complexity of connected car software will only continue to increase. Today, most software updates are performed at the repair shop or dealership, but over-the-air updates are becoming more commonplace and convenient. Automakers can push new software and configurations to vehicles instantaneously, but how do they verify the compatibility of these updates across numerous models, personalized configurations and software versions? The answer again lies in some enterprise technologies, including an automated toolchain and a cloud-based controller. The automated toolchain allows for regression testing and assessing large numbers of variations in software packages, while the cloud-based controller simplifies the management of variations of in-vehicle network configurations. By integrating the automated toolchain and the cloud-based controller with automated network management technologies, managing the various versions of software in the vehicle is dramatically streamlined.
- How to “do more” with less. With more IoT-enabled devices and sensors on their networks, enterprises realized that they needed to make more efficient use of bandwidth, storage and computing power. The connected car is facing similar challenges with economizing resources, and thus can use the same technologies found in the enterprise. To optimize bandwidth, the connected car can harness the power of fog computing, which uses distributed compute and storage to bring the cloud to the edge of the network. With fog computing, the vehicle can intelligently filter and compress data, determining which information must be sent to the cloud immediately, versus what data it can store and forward later, which helps make the best possible use of bandwidth. Also, instead of relying on dozens of ECUs in the vehicle, the connected car can employ a centralized compute and storage device, which cuts complexity and costs by virtualizing some of the units’ common logic. The connected car can even reduce wiring weight, and therefore improve fuel efficiency, by standardizing to Ethernet for in-vehicle networking.
- How to drive faster innovation. Although the automotive industry has typically employed a longer and more predictable innovation cycle (sometimes taking up to five years to plan a major new vehicle release), that approach will not work in the era of IoT. Due to the endless possibilities IoT technologies create and often unpredictable results, rapid iteration and testing are essential, especially in the early stages of IoT solution development. This makes it easier to uncover where connected cars can provide the most business value. Again, the enterprise-proven IP over Ethernet backbone for in-vehicle networking can help — giving automakers the agility and flexibility to quickly connect new sensors and devices to the vehicle, test them, measure their value and make appropriate modifications. As a result, automakers can more rapidly roll out new services and features and shorten their innovation cycle.
As the connected car market continues to grow, automakers and their partners can find solace in knowing they do not have to look too far to find answers to their most pressing challenges. Proven enterprise technologies, including automated network management solutions, fog computing and virtualization and more are all applicable to the connected car. We will likely see even more enterprise IoT technologies and best practices come into play as the connected car progresses, allowing it to deliver a safe, convenient and rewarding driving experience.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
Back in the early 1800s, there was a shift in the English textile industry as the Industrial Revolution took hold. Machinery in the form of automated looms and knitting frames was introduced into textile plants, displacing skilled workers who were slower and more expensive than these new contraptions. A group of textile workers started destroying their employers’ machinery to slow down the rate of adoption and protest the way machines were replacing humans. This ultimately fruitless effort became known as the Luddite Movement.
Today, people are most familiar with the internet of things through consumer-facing applications such as smartphones, wearables and smart refrigerators. What they may be less aware of, however, is how quickly IoT is making its way into the enterprise market by allowing manual tasks to be replaced with network-connected sensors. I am constantly impressed with the innovative ways our customers are using IoT devices in their organizations.
What may be even less apparent to the common consumer is the rapid job destruction that could take place as the speed of development and connected devices continues to accelerate. Is the enterprise IoT industry ready for blowback that could be caused by the transition pains these connected devices are almost sure to create?
If you look at the wide variety of IoT applications, this new technology touches every corner of the enterprise economy in terms of improving efficiency. These devices have great potential to increase productivity and efficiency while also reducing the need for human labor.
One beverage distribution company installed a very impressive system that breaks down and repackages beverage cases through automation and sensors. The connected product count of its warehouse tripled while its peak volume capacity increased fourfold. In addition, its inventory accuracy went from 95% to 99.99%. The downside for employees was the elimination of 25 full-time employees. Fortunately for them, in this scenario, they were reassigned to other tasks at the company. That won’t always be the case.
Take that one example and start multiplying it around the country or world. Connected cars are making huge strides in their capabilities, yet one in seven jobs is still tied to transportation in the U.S. Between newer companies, like Uber, Tesla and Otto, and traditional manufacturers, like Ford, Toyota and Mercedes, the race for self-driving technologies has already started.
It is estimated that 38% of jobs in the U.S. are at high risk for being automated and replaced by 2030. The jobs most likely to be automated and replaced include those in transportation and storage (56%), manufacturing (46%) and retail (44%). Fortunately, of those jobs that have already been lost, nearly 80% have been replaced and upgraded, which is great for young employees and those capable of learning new skills. Technology has created exciting workforce opportunities that were unimaginable just a few years ago.
But what happens if we reach a tipping point where the number of jobs destroyed exceeds the number of jobs created (or the jobs created cannot be filled by the individuals whose jobs were destroyed)? Things may become problematic.
How would continued job destruction lead to limitations for IoT development? A few examples of Luddite-like activity as a result of job losses that could impede progress or acceptance of IoT include:
- Security — The lack of standards and Wild West environment of IoT today could be used by social hackers to bring down job-destroying devices. Disabling every connected meter means humans must go out and check them instead.
- Regulation — Will gains in efficiencies be reduced by government regulation that only has one goal in mind: preventing job losses? Will automated trucks require a human operator to drive on public roads, completely negating the technology’s cost benefits?
- Employee revolt — Could full-on resistance toward connected devices by employees who feel their jobs may be threatened impact the success of future IoT projects?
I am certainly not arguing that technology is a bad thing. Connected devices can perform repetitive tasks with more accuracy and much cheaper than manual labor, often replacing jobs that are undesirable and hard to fill in the first place. We implement connected devices and automations to help make ourselves more efficient and scalable. Even so, it’s good to be aware of any potential long-term impacts your company could experience as the world continues to become more automated and connected.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
U.S. cities of all sizes are experiencing an influx of new residents, and it’s a trend that shows no signs of slowing. According to the U.S. Census Bureau, all but one of the nation’s 20 largest cities in 2015 saw their populations grow at an average rate that was almost double that of the previous decade. This is driving a parallel growth in the demand from residents and businesses for “smarter” cities. They expect municipal officials to leverage technologies that constantly collect and analyze volumes of data to improve the delivery of services, save energy, reduce traffic congestion, provide a boost to businesses and improve the overall quality of life. This requires making the modernization of the networks supporting their transportation infrastructure a top priority.
These aging networks were built decades ago and based on proprietary solutions. They are expensive to operate, difficult to maintain and create unacceptable levels of risk for citizens and first responders in the event of an emergency.
The technology exists today to turn train stations, bus stops, airports and even parking spaces and streetlights into an open, high-speed connected communications network that enables government agencies, local businesses and residents to interact and share information in real-time. Converting these “dumb” resources into interactive points enables residents and visitors to receive hyper-contextualized, proximity-based, relevant notifications tied to proximity services and businesses, tourist and cultural information on their mobile devices.
According to a new report by Deloitte, the financial leaders at the federal, state and local levels of government need to embark on some smarter thinking about how to get these projects underway. Partnering with the private sector is critical:
As a first step, this includes supporting policies such as fiscal incentives (including tax abatements), public-private partnerships (PPPs), and qualified infrastructure bonds specifically focused on smart city requirements. The public sector should encourage private-sector investment in new smart city partnership models that will reduce the near-term cost of investment in technology-enabled infrastructure (in an era of public resource constraints), while ensuring any risk and reward considerations are appropriately balanced.
In other words, without PPPs, a smart city plan will most likely remain stuck on the drawing board. If the results of the U.S. Department of Transportation’s “2016 Smart City Challenge” are any indication, it appears the private sector in the U.S. is ready to help build smart cities.
Seventy-seven cities submitted entries to the DoT’s $50 million contest that detailed their plans to leverage new and developing technologies to solve their transportation problems. Columbus, Ohio, won the contest and will receive $40 million from the federal government and another $10 million from Seattle-based Vulcan, owned by Microsoft co-founder Paul Allen. The city will also reap an additional $90 million in matching funds from local companies, governments and nonprofits.
Private companies and nonprofits have committed funding and their expertise to help not only Columbus, but also the cities that didn’t win (or even enter) the DOT’s contest. These companies represent sectors such as cloud computing, telecommunications, electric vehicle charging infrastructure systems and wireless transmitters for vehicles and infrastructure. The DOT reported 150 companies and nonprofit groups have pledged as much as $500 million worth of support.
This statement from the Deloitte report underscores the urgency with which government agencies and the private sector need to place on modernizing transportation infrastructure:
Not only is the safety and security of our citizens and businesses at risk as infrastructure assets age and fall into disrepair, but so too is the broader economic well-being and global competitiveness of our cities and our country. Undertaking a broad-based smart city reinvestment and modernization program will help reduce costs, maximize revenue potential, and improve citizen well-being through the deployment of cutting-edge, technology-enabled infrastructure that is more environmentally friendly and resilient.
IoT in healthcare represents an exciting new frontier for the wider tech community; it’s a landscape that is packed with opportunity and potential. But it’s also a sector which is strewn with challenges and requires more sensitivity, commitment and innovation than most. Lead strategist at Future Platforms, Olivier Legris, shares his insight on how innovators can conquer the IoT complexities of this frontier.
An aging demographic, shrinking budgets and increased demands are driving the urgent need for solutions across the healthcare sector. While running headfirst into innovation may be tempting, the healthcare sector presents a series of challenges, meaning that IoT developers need to take a slow-and-steady-wins-the-race approach if they are to achieve results that are as futureproofed as possible; their solutions could become a matter of life and death.
An obligation to change
While it’s difficult to say if IoT will guarantee a marked improvement in service, there is at least an obligation to change because of the potential benefits it could bring to hospitals, with optimization topping the chart. With the right tech, shift-work can be optimized, for example, thus determining a more efficient way of working, pushing costs down and returning the focus to the provision of quality patient care.
There are savings to be made too, and according to analysts at Goldman Sachs, a major spending reduction is not far away, thanks to IoT. In a recent report, they predicted that there is “opportunity for $305 billion in savings from [U.S.] digital healthcare, with as much as $200 billion coming from chronic disease management [CDM] [such as heart disease, asthma and diabetes],” which currently accounts for a third of U.S. healthcare spending. Enabling remote patient monitoring for CDM through IoT and its connected devices could therefore be integral to cost savings in this sector. Although, according to the report, “seismic shifts like this will take time to materialize.”
As with budget pressures, an aging demographic presents a challenge too — but one that can be overcome. Japan provides a good example: in spite of an aging population and reduced investment into healthcare, this technologically advanced country has embraced innovations in the fields of automation and robotics to answer its healthcare problems — with Toyota’s Human Support Robot being a flagship development. And with a notion that there will come a point when robots will be able to undertake 90% of human tasks, these solutions are real stepping stones towards achieving this future vision.
If countries like Japan can get it right, why are others falling down on the road towards a fully-fledged IoT experience? There are multiple reasons, including regulation constraints and social adoption, but largely it hinges on cost.
Many devices being used are not in mainstream production yet, and so costs — taking sensors as an example — are still high. In relation to sensors specifically, IBM urges that “to truly achieve cost-effectiveness, the whole system cost has to be optimized — focusing on cost optimization of a single component may not result in the lowest overall system cost over the product’s intended lifespan.”
The shift from mainstream is set to change, however, as there has been an explosion of smart, connected sensors across the board. And healthcare is one industry that is poised to lead this charge.
MarketResearch.com shared its projections that the healthcare IoT market segment is set to hit $117 billion by 2020, and so it’s unsurprising that a number of initiatives are being rolled out with the aim of making it easier to connect devices to the internet. Companies leading this revolution, such as Temboo — which provides the software stack for developing IoT applications — will be first to capture a piece of this $117 billion pie.
There are a number of good examples of IoT in healthcare that are engendering this revolution, and across a variety of device types too, including connected inhalers, activity trackers for use during cancer treatment, ingestible sensors and even connected contact lenses.
Both heavy investment and time is needed before new innovations such as these will fill the IoT space in healthcare; you cannot simply throw a prototype into the space as there are many constraints surrounding regulations, the ecosystem and social adoption. It will take five to 10 years before devices in healthcare are in a good enough position to become mainstream.
Scale up with caution
Innovation and investment aside, data and its role in healthcare will be critical in the IoT game plan. The amount of data being processed in this sector is almost unparalleled, and it is likely to continue climbing. Therefore, the efficient and sensitive handling of this data — a massive task in itself — will need addressing in a new way.
IoT’s capacity to leverage a series of connected devices to deliver data more efficiently makes investment in this arena a must — a conclusion that is further strengthened by recent reports from Gartner that the total number of connected devices is forecast to reach 20.4 billion worldwide by 2020, with healthcare and retail leading the charge. However, while the collection of data is important, the analysis of it is even more crucial.
In terms of research, a major shift is starting to occur whereby studies that have been traditionally small scale and consisting of a minimal sample of patients are now growing. Google’s health spin-off, Verily, recently launched Project Baseline in an ambitious attempt to gather health data from 10,000 U.S.-based volunteers. Having scaled-up results will have an important impact on the future of healthcare as it will help professionals gain a deeper understanding of health and the transition to disease.
There’s more hesitancy surrounding the data debate in healthcare than in other industries due to its personal nature. Because of this tension, anything related to health needs to be scaled up cautiously as any backlash could be potentially devastating; the misuse of data in this sector could trigger fatal consequences.
As hackers take advantage of poor security on embedded devices, the call to protect data and patients is urgent; imagine the impact of a hacked insulin pump that can administer a fatal dose — there’s potentially a life-or-death scenario, as noted by Ed Cabrera, chief cybersecurity office at threat research company, Trend Micro.
Looking at the solutions emerging in this space, ownership and responsibility of data are therefore important issues.
A recent report by Berkley Research Group underscored the significance of data and its impact on healthcare’s IoT landscape, indicating that ultimately it’s all about information management. The report urged businesses to:
- Know your data
- Map your data
- Classify your data
- Protect your data
- Enforce regulatory controls
To stimulate greater acceptance or readiness to share information, solution providers must keep security as a top priority, because if it goes wrong, it’s going to happen on a massive scale.
According to May Wang, chief technology officer at ZingBox, “Over the last three years, the healthcare sector has been hacked more than the financial sector. And more hacking incidents are targeting medical devices.”
At last year’s IoT hacking contest, hackers found 47 new vulnerabilities in 23 IoT devices at the DEF CON security conference. From thermostats to wheelchairs, the hackers flagged vulnerabilities which included poor design decisions and coding flaws. In spite of efforts to draft security guides and standards for IoT vendors, it seems the rush to bring new devices to the IoT marketplace means some security best practices are being ignored by device manufacturers.
To ensure best security practices are being met, Berkley Research Group’s report highlighted a number of recommendations, including:
- Take a risk-based approach
- Incorporate security language into procurement contracts
- Engage stakeholders
- Follow the data flow
- Conduct security testing
- Go for the low hanging fruit
The invisible touch
The decentralization of hospitals will also be paramount when evolving IoT in healthcare. At a base level, patients are admitted to hospitals so they can be assessed, monitored and treated.
The growing cost of running these facilities is exponential. To be able to have more people treated in their own homes will not only encourage a more comfortable recuperation for them within a familiar environment, but will also spur massive savings as the cost of treatment falls.
There is also the notion of accessibility and technology can work to improve the lives of those with disabilities. But it’s more than just designing user-friendly interfaces, it’s about social acceptance. For this to be achieved, developers need to consider how to create solutions which are, effectively, invisible. From pacemakers to hearing aids and mobile ECGs, there is a growing need for connected health and medical devices to become less conspicuous.
Healthcare deals with private issues that relate to personal feelings. Technological developments need to factor in this human element and the notion of acceptance of these tools at a human level. The more we succeed in making these tech tools invisible then the more successful the initiative will be.
A matter of priority
When considering the digital transformation of a sector such as healthcare, it’s important to remember that we are at the beginning of the process. There’s a lot of expectation around how and when IoT can make a positive impact, yet it’s still very early days. While we start to lay down the building blocks that will form a foundation for the future of the industry, there are a few key points that developers and innovators need to keep close to mind:
- Be responsible: If you don’t run a project with empathy or human care, you will fail.
- Think long term: Most innovators develop projects with longevity in mind, but it’s wise to remember that healthcare requires more commitment than most.
- Be safe: Cybersecurity is already a massive threat to healthcare, and with the rollout of new connected devices, it is only going to increase. The good news is that many IoT vendors are already investing in keeping their systems up to date and IoT management platforms are working hard to ensure threats are kept to a minimum.
While we focus on the potential downsides, we should not forget the upside, which is that this is an exciting time for tech in healthcare — think of how artificial intelligence (AI) will identify tumors more precisely than its human specialist counterparts; think of the remote surgery concept and its impressive arrangement; think of how virtual reality (VR) can be used to reduce pain levels, aid mental health issues such as claustrophobia, or entertain patients to provide them have better experiences.
While AI, machine learning and VR will potentially drive exciting and positive changes to the industry, mobile will still play an integral role, becoming the real brain behind the IoT operation.
To yield optimum results from the full implementation of IoT, the healthcare sector and its tech leaders need to be bold in their pursuit of technological innovation and adoption. It will not happen overnight, but early adopters will reap the benefits of getting a head start.
After Red Hat Summit, I traveled up to Maine for a vacation with my family. The area was cool, quiet and beautiful. The rugged coastline was remarkable. I found myself particularly entranced by the natural glacial lakes of New England, so different from the man-made creations we have in Georgia. You see, lakes here are engineered by constructing dams and diverting water from ponds, rivers and swamps. The water released downstream is regulated according to water use, including power generation, navigation, recreation and agricultural irrigation. It got me to thinking about the difference between siloed data stores — sometimes referred to as data swamps — and the natural data lakes which seem better suited for IoT implementations.
Natural versus engineered
If you think about it, data warehouses are similar to Georgia’s ponds, rivers and swamps. These are separate, but important, ecosystems that could be architected to work as one — if you apply a whole bunch of engineering to it. They are great for giving you a real-time picture of the state of a business. But you must remember that they only provide subsets of data. This data can be biased based on the selection criteria of your search. Like our southern reservoirs, they are very regulated, and you pretty much know exactly what kind of fish you’re going to get if you decide to throw in a line.
Data lakes are a different type of data store that grow organically. They can help you find correlations and patterns you may not have seen before to assist with decision-making processes. When you go fishing for information here, you’re more likely to catch a keeper. Casting off in these waters will often reveal correlations and patterns you may not have seen before.
The basic differences between a data warehouse and a data lake are summarized in the table below found in Tamara Dull’s blog, “Data Lake vs. Data Warehouse: Key Differences.”
Finding your prize in a lake full of data
In an IoT architecture, we are faced with thousands of sensors collecting masses of unstructured data, from sound to video to clicks. And everything is streaming down quickly into the raw data pool. Yet much of this data isn’t being used. A study by McKinsey & Company in 2015 on the energy industry found that less than 1% of the data gathered by sensors on offshore oil rigs was used for decision-making. A recent survey Cisco conducted indicated that up to 60% of IoT projects either stalled or failed due to businesses not being well-enough prepared to reap the benefits of their data, as well as the lack of quality of the data collected.
It seems to me that we need better fishing tools. What if I went fishing in this data lake with the right application as bait? I could start to see patterns from what I was pulling in. Imagine a business setting where I wanted to identify the conditions for failure on my equipment. I can look at the conditions and note that, when it hits a particular temperature, the humidity is over a certain percentage and the machinery has been in use for a specific number of hours, there’s a failure. Once I’ve identified a replicable pattern, I can take appropriate actions. I could work to reduce the temperature and humidity and possibly modify the maintenance schedule. That’s one type of fish I could catch.
At the same time, I’ve noticed that the machinery deployed before 2012 is having repeated failures not related to these conditions. Noticing that the machinery is from different manufacturers, I can tell that the older machinery should probably be replaced. Once again, I’ve hauled in another prize catch.
Use the right fishing pole and avoid the swamps
Georgia’s reservoirs remind me more of a data store where you are pulling together several swamps filled with databases, file systems and Hadoop clusters containing a bunch of siloed data with no efficient way to find, prepare and analyze it unless the engineers managed to build something connecting it all. It takes a whole lot of engineering to create those lakes.
With analytics applications like those provided by our open source partner, Cloudera, you can use its Hadoop engine and machine learning to sift through patterns and correlations in data lakes. Its application in IoT environments, with the scalability, security and flexibility of its Hadoop platform, is a natural fit; as natural as the glacial lakes I found in Maine. Analytics solutions like these can help you take advantage of complete lakes of data to optimize your IoT implementation. They can help you find the nuggets that are hidden within. If you use a data store architecture more suited to IoT implementations, you can show a greater ROI on your IoT investment and start fishing where they’re biting.
Security and privacy are always hot topics when it comes to discussions about the internet. And with the emerging internet of things, security and privacy questions are becoming even more prevalent.
It’s one thing to safeguard your passwords or to carefully designate who can view your online photos. But connecting your home to the internet? That could be dangerous — or just plain unnerving. Imagine someone hacks your house and can turn lights on and off, or open the front door at will. So it’s no surprise that many companies are spending a lot of money and engineering hours on making smart home systems safe and secure.
At the same time, a new generation of products is getting popular. Take Alexa (and her cousins): a microphone in the middle of the room where you call and she answers whatever your question may be. The weather in Rome. The news in Atlanta. The business hours of a nearby store. It’s essentially a browser you can talk to that understands what you are asking and, most of the time, provides solid answers.
This technology is a big step forward, both in technology and as a new way of connecting and interacting with the internet. The screen and keyboard are now a microphone and speaker. Technology prognosticators are already predicting that this method of computer interaction will soon become dominant.
So, back to security and privacy. Product manufacturers let us install passwords, and they implement encryption — along with a host of other security features — so that our secrets stay secret. But we suddenly fall in love with Alexa, believing that Alexa only listens if we say, “Hi Alexa,” before asking a question. Right? Just like we believe that our smartphone only listens if we say, “Hey Siri.” Right? Or that our voice-enabled remote control only listens if we push the voice button… (Right?)
Recently I met someone who had placed a sticker over the camera on his laptop. I asked him why, and the answer was not terribly surprising: “I want to make sure that I am not being watched.” But what about being listened to? Which is potentially more damaging — someone looking at your face while you are at your computer or someone able to listen to what you are saying anytime you are near the computer?
In addition to a sticker over the camera, should there be earbuds on the microphone? And what about cell phones? Is your cell phone listening to your conversations when you’re not using it? Well, probably not, at least not so far. But with this promising new user interface, replacing the keyboard and screen with a microphone and speaker is becoming mainstream.
Now, think about introducing this concept in every piece of equipment in our homes. We could talk to the washing machine, dishwasher, refrigerator, television and so forth, but all these appliances and electronics would be permanently listening. What we say could be sent over the internet to an “interpreter” that translates words into code that can be executed, as if we had typed it into a browser. The result is either sent back over the internet as an action to “do something” (for example, turn on off the lights, start the dishwasher), or it is sent back as a voice stream that comes out of the speaker.
So, yes, we care about security and we heed the warnings to pay attention to privacy. But on the other hand, we all now walk around with cameras and microphones that 007 (the Sean Connery version, at least) could only dream of. How do we balance installing microphones in every room in our house with paranoia?
Product developers and manufacturers should put security and privacy first in building technology for voice-enabled wireless equipment like remote controls. Do not develop technology that listens to anything not intentionally shared — and, by the way, the remote batteries would die quickly without the option to turn the microphone on and off. But we cannot control who uses our technology, in what kinds of products and with what intent.
Put security and privacy first, not because there may be “a little man” in your TV listening to conversations in your living room, but because this next generation of technology is rolling out quickly and skyrocketing in popularity. Without putting security first, will there ever be a legal framework protecting the consumer and defining responsibilities? Who will be responsible if a third party hacks or otherwise abuses the technology capabilities?
Headline-making cyberattacks on big companies and their customers’ passwords, credit card numbers and email addresses are just the beginning. With the arrival of IoT and technology advancements in our homes and in our lives, security and privacy are becoming more important than ever.
The field service profession is undergoing an unparalleled tech transformation as advances in IoT, application integration and mobility redefine what can be accomplished by a mobile workforce and millions of geographically dispersed assets. The one-two punch of low-cost sensors and open connectivity give companies a competitive edge in their ability to equip employees with the best processes to keep customers happy while creating new revenue channels and services. As tech trends including IoT, cloud computing and real-time mobile communications converge, consumers and field reps are gaining a new perception of what the future of customer service looks like: It needs to be seamless and predictive. To create the preventative customer service today’s buyers demand, organizations need to take smart steps to put an IoT-enabled integration strategy in place.
Field service reps bring it all together
Field technicians have always served as a critical hub for many businesses because they need to coordinate communications, technology and logistics with many different departments, partners and customers. Serving as a hub for different departments means field teams need to do a lot of heavy lifting to work with a multitude of traditional, siloed business systems. There is an enormous amount of manual follow-up required to get account and customer data, place orders and manage inventory, enable field repairs and execute billing, which leads to long resolution times, a major no-no for customer service.
With the rise of millions of connected devices, many of these manual processes can be totally automated, freeing up field technicians to radically streamline their work. As every vehicle, worker and piece of machinery in the field is sensor-enabled, we will see a massive shift from manufacturing-centric businesses to a service-based economy. Companies like GE no longer sell aircraft engines. Instead it will sell “guaranteed time in the air,” including identifying and fixing any issue or mechanical problems before they ever happen.
But IoT-enabled devices alone won’t unlock the power of connectivity. It’s imperative that the various systems are linked across a cloud-based integration platform to ensure that field service workers, devices and assets have access to information wherever they are — whether they’re on-site with a customer or at the local field office. They need the ability to make updates, place orders and process transactions on the go, in real time. Only then can the full benefits of IoT be funneled back to businesses and their customers.
Although an integrated field service experience is within reach for every business, many leaders are unsure which paths to take to make it a reality and, as a result, their integration efforts fall short. Findings from a recent Gartner Magic Quadrant for field service management reflect this shortfall, stating that through 2020, 80% of organizations with more than 75 field technicians will miss more than 20% of planned efficiency gains due to incomplete integration or deployment.
The key is to leverage modern integration platforms to expose data from legacy on-premises business systems, new cloud-based solutions and mobile endpoints, and to make it available for field technicians from any device or location. This strategy frees companies from the burden of manual processes and provides quick access to data across a wide range of systems, from inventory and pricing to orders and asset management. With this approach, all businesses should be able to sidestep the pitfalls of siloed systems and realize enormous efficiencies through connected field service.
Here are a few ways field service benefits by implementing smart, integrated devices:
- Be more proactive. Simply being able to read the status of a sensor on an IoT-enabled device doesn’t add much value for field service reps. They need devices to be smarter and communicate issues before they happen. For instance, embedded sensors in connected devices and equipment enable the devices to send alerts when they need regular maintenance or when a pattern is identified that indicates they are about to fail. Smart sensors don’t simply improve the company’s ability to provide effective service; they can actually prevent equipment problems before they arise.
- Fix common problems faster. Sensors provide massive amounts of data which can be analyzed in real time and in aggregate to learn from broader trends, which can help field technicians be more proactive in handling common problems. Moreover, connected devices have the ability to not only request service, but also provide details to explain why they need attention so field service teams can address root causes, not just the surface issues that come up. For instance, if batteries keep failing, data collected from the devices can uncover trends around weather or electricity supplies, for example, that could lead to a product upgrade rather than continually replacing non-functioning batteries.
- Make better use of team time. Time is money, and digitizing field service gives time back to busy field services teams. Digital field service operations automatically accept service requests, dispatch technicians and track results without requiring manual data entry. Integrated systems also allow technicians to minimize drive time between sites by grouping nearby appointments together and ultimately reducing the length and number of different trips. These time savings can also extend beyond the field service teams to the other departments that support them, such as inventory management or accounting.
We’ve only just begun
Integration of IoT-enabled devices and data promises to transform the way field technicians work in the coming year. Field services can now move beyond making fixes after an issue arises to actually preempting problems and anticipating customer demands. Companies that take a holistic approach to connectivity by integrating the wide range of solutions that have been brought online in recent years will make those technologies much more powerful by linking them together. Field service teams have the opportunity to set the standard for seamless connectivity across departments to deliver a better customer experience at a lower cost.
Today, every business is a digital business. More and more CEOs are seeking opportunities to implement or leverage IoT technologies to reap the benefits of the data economy. The implementation of IoT and its associated connectivity, services and revenue potential signifies the tremendous cusp of business change, liabilities and requirements before us.
IoT expands the information supply chain 360 degrees. As customer solutions, data transfers, vendor and supplier communications, and data resale capabilities arise, new security standards, compliance requirements, and fiduciary and financial liabilities emerge as well. For entities operating in highly regulated industries such as government, healthcare and transportation, comprehensive information security practices must integrate or transition to meet updated standards such as European Union General Data Protection Regulation (EU-GDPR) (Regulation 2016/679), personally identifiable information (PII) and controlled unclassified information (CUI) requirements within both the centralized and edge computing practices of IoT. The result? The data economy of IoT requires greater agility, customer level adaptability and ongoing security updates.
Many CEOs are jumping on the IoT train because they realize the benefits of gaining information, connectivity and new capabilities from a variety of known and unknown data sources. However, deriving business ROI from IoT requires the application of the DevOps mindset in planning, design, integration and across the cybersecurity and regulatory compliance spectrum.
Often, many businesses that are new to IoT are challenged to implement automated system-of-system security capabilities and practices to manage the protection of CUI, EU-GDPR, PII and other regulatory and due diligence risk mitigation. IoT delivers rapid information flow and the potential for rapid response at the edge of connectivity exactly where these exchanges are at the highest risks for data leaks and breaches. In this context, maturing information protection practices, workflows and independent assessments of risk exposure are key to achieving and maintaining compliance and cybersecurity regulations.
How the DevOps mindset may establish IoT security practices
IoT will fundamentally change how companies are collecting, producing and sharing data internally and with their (likely) global supply chain. As the velocity and volume of these data-rich transactions continue to increase, traditional security and compliance practices may become inconsistent with the implementation and use of IoT. Businesses that understand IoT will likely leverage the DevOps mindset in order to apply security-by-design and in context.
Essential to success is using the DevOps mindset for cyber and compliance as a means of achieving reliable data privacy and protections. This focus of constant evolution will evolve further as implementation of CUI for government contractors under the FAR and DFARS clauses are fully implemented and enforced. Additionally, as rules such as GDPR continue to take precedent, companies will need to think about their practices to secure the code, the environment of IoT and the transactions of the IoT customers.
Organizations that are integrating IoT into their business should equally prepare for a deep digital transformation in their cyber and compliance practices. Rethinking device connectivity and enterprise IT needs translates into adopting a new mindset that captures the forces of cloud, revenue-generating IoT, and automated cyber and compliance protections for the applications, customers, and the underlying intellectual property.
Because IoT projects tend to start small and scale fast once a use case is proven, the ability to seamlessly scale in size and geographic reach is critical — especially for global deployment.
With 85% of global organizations considering an IoT strategy, businesses need to build on a foundation that supports long-term growth. This starts by choosing the right IoT platform to deliver business value today — and in the future.
You can think of an IoT platform like the heart of the IoT solution. The IoT technology stack consists of multiple layers, including device hardware, connectivity, data management, applications, analytics and security. IoT platforms facilitate and orchestrate key interactions between each of these layers as well as with other back-end systems in a business. This provides the most efficient and scalable way for customers to realize business value from IoT solutions.
So how do you choose the right IoT platform? I recommend conducting a thorough technology review against your needs today, while thinking ahead to anticipate future growth and opportunities. Here are six potential needs to consider in your IoT platform selection:
Support multinetwork connectivity. Today, there are many network technology options to connect IoT devices. Your best network choice will depend on how and where it will be used, as well as the type of service level required. For this reason, a comprehensive IoT platform should provide connectivity support across all major IoT network types — from satellite to LTE-M — to offer the greatest flexibility for current and future projects.
Include convenient tools to manage IoT devices and connections. IoT platforms should provide you with access to user-controlled software tools to manage the devices and connections that are part of an IoT solution. Convenient, on-demand hosted service management functionality enables you to take control of your IoT network — allowing you to add, move, remove or change your IoT device reporting functions.
Enhance, transform and augment a high volume of data. Most IoT solutions use a variety of sensors that can generate a high volume of data over time. In many cases, this data may need to be combined with existing data or data from other sources to create business insights. An IoT platform provides the ability to enhance, transform and augment data from this diverse mix of IoT endpoints. It can receive streams of data coming in from multiple sources and break them down, so that the data can be easily processed, used or reacted to.
Provide a full suite of data analytics capabilities. The ultimate goal of data gathering is to fuel better business outcomes through increased visibility and insight. An IoT platform should facilitate data analytics capabilities that can extract value and keep businesses from drowning in information. This will include analytics built into the IoT platform as well as the ability to utilize specialized third-party analytics software as securely as possible via APIs and services.
Account for security at every level. Security is a major concern for any business in IoT. Each individual device may not represent a major threat on its own, but when you put millions of them together, it can become a more significant issue. Also, security has to be comprehensive across all layers of the stack. Following core security principles and practices will help reduce the risks and maximize the benefits of incorporating new types of connected devices into the ecosystem.
Offer flexibility for the future. Flexibility allows businesses to experiment and scale their solutions using multiple devices, network types, applications, APIs and cloud environments without redesigning the core IoT platform or updating device firmware every time a change occurs or as technology evolves. It also means accounting for technology trends that will continue for many years to come, including the rise of edge computing.
As IoT connected devices and sensors proliferate within an enterprise, managing, sifting through and analyzing so much data can be a massive challenge. In an edge computing model, sensors and connected devices transmit data to a nearby edge computing device that processes or analyzes the data, instead of sending it back to the cloud or to a remote data center. An IoT platform that includes tools to push data processing and independent applications to run at the edge of a solution is important to planning ahead.
The internet of things is revolutionizing businesses and life as we know it. And it’s not slowing down. Prepare your business to keep pace by investing in a foundation that’s fit for the future. Make your business a success story by building it on the right platform.