It seems like everyone these days is talking about the internet of things and how connected devices and wearables have and will continue to impact our lives. From wrist watches to smart appliances, we can already see this trend come to fruition.
However, it is in the industrial internet of things where the real societal impacts will manifest in the years ahead. As a confluence of factors make IIoT more available, affordable and realistic, the way factories and facilities work will inevitably change. As a technology innovator in the space and with skin in the IoT-game, here are a few ways I predict IIoT playing out in the months ahead:
1. The year of ‘smart’ decisions
As mentioned, we are at a turning point in terms of affordability and availability of IIoT. This will be a continuous driving factor. Where companies previously may have excluded IIoT technologies from their toolset because connectivity wasn’t up to par or the components were too expensive, the months ahead will witness a surge in facilities making the move to the cloud as prices drop and capabilities increase. More devices will be set up for edge processing, with revised IT policies to allow for fog computing and new SaaS offerings to bring about quick and accurate data-driven decisions.
In many facilities today, there remains a gap between operational efficiencies and decisions at the top. This gap will begin to narrow as machine-to-machine communication via sensors provides the bridge between legacy equipment and modern methods of data analysis and interaction. This is where we will see the biggest change as real-time and historical machine data will become the basis for decisions, rather than simply past experience or gut instinct.
2. Cloud adoption by factories and facilities will become imperative
Along these same lines, the thinking around on-premises versus in-the-cloud data processing will need to change. No longer can facilities sit idly by, slowly developing their policies around cloud adoption as the world passes them by. Packaged software and on-premises systems, as opposed to cloud-based SaaS, will become increasingly obsolete as the scale of data grows beyond their on-premises capabilities.
Instead, the future lies in a mix of cloud and fog computing, where some computing happens at the edge on devices in the field and some occurs in the cloud. Initial data will be processed in the field, anomalies and change data will be sent to the cloud for analysis, and on-site systems will provide continuous insight on system health to highlight potential areas for improvement.
3. Risk awareness and security will evolve alongside connected industry
By virtue of simply being a new technology, IIoT presents a new attack surface, but it’s not that IIoT is inherently riskier. Instead, the problem exists in the fact that IIoT presents an entirely different type of risk that requires a new way of thinking and awareness to address.
Last year, witnessed a raise in creative cyberattacks and our best protection for the future is to join forces to stop cybercrimes. With cloud computing, you get the best line of defense as your application is always up to date. Cybersecurity experts that are constantly searching for vulnerabilities, and fixing them instantly is a part of the best practices used by third-party cloud applications.
Both sides — the developers of these new IIoT technologies and those facilities putting them to use — will need to change their thinking to examine security protocols around sensor-to-sensor communication, sensor-to-gateway communication, and system updates and maintenance. Regardless of where data is stored, it will need to be treated in a secure and private manner.
Shifting gears: Getting smarter
The distinction between flashy buzzwords and discussions around making a real change in the market is in truly understanding the details. Talking Industry 4.0 is important, but what does it really mean to move your mechanical data to the cloud? Industrial IoT is nice to talk about, but what are the actual security implications? We did a lot of talking in the previous months, but now we are primed to implement these changes to make good on the promise of the connected industry.
At the end of the day, nobody knows a facility better than the people who spend hours every day working to ensure the health of their own machines. The main challenge will be to navigate this fast-moving technology landscape to choose the vendors that are right for your equipment. This year will be one of uncovering new ground, a necessary milestone in ushering factories and facilities into the smart future.
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.
Data is in a funny place these days.
On the one hand, it’s at the core of many of the hottest trends.
IoT? That’s often about connecting information technology to physical operational technology through data flows.
Artificial intelligence? As practiced today, it’s mostly focused on machine learning, which depends on huge training sets to work its (apparent) magic.
On the other hand, the storing of personal data is under increasing scrutiny. Current attention is mostly focused on the European Union’s GDPR regulation. But it’s reasonable to assume the retention and use of personally identifiable information will become subject to more and more rules over time.
This presents something of a conundrum.
At the MIT Sloan CIO Symposium in May, Elisabeth Reynolds, the executive director of the Work of the Future Task Force, observed that “the regulatory framework is often opposed to sharing data for the greater good.”
The anonymization challenge
For example, data about vehicle traffic, electricity usage or personal health metrics could potentially be aggregated and studied to reduce congestion, optimize power generation or better understand the effectiveness of medical treatments.
However, the more fine-grained and comprehensive the data set, the harder it is to truly anonymize. The difficulty of effective anonymization is well-known. Either your search history or your car’s GPS tracks would probably leave little doubt about who you were or where you live.
The problem is only compounded as you start mixing together data from different sources. Gaining insights from multiple data streams, including public data sets, is one of the promises of both IoT and AI. Yet, the same unexpected discoveries made possible by swirling enough data together also make it hard to truly mask identities.
Is the data useful?
Conversely, swirling together lots and lots of data doesn’t always lead to insights that let you improve some outcome popping out the other end.
This also isn’t a novel result.
The last time the IT industry went through an infatuation with data was the 1990s, when data warehousing was the fad du jour. One common problem was that even reams of data often didn’t lead to novel or otherwise non-obvious observations. We sell more snow shovels during snowstorms? You don’t say.
Furthermore, even unexpected correlations often don’t lead to useful actions. A popular fable of the data warehousing era involved a drug store chain which discovered that men swinging by to pick up diapers on the way home on Friday would often pick up a six pack of beer at the same time. The story apparently has a basis in reality; it stemmed from a study NCR did for Osco. But it never led to shelves being rearranged to further encourage the observed behavior.
Reynolds wondered if we’re seeing a similar pattern of inaction with smart cities, the concept that cities which are instrumented in various ways can be optimized based on that information. “Smart city 1.0 was ‘we have all this data and it’s great.’ But to what end?” Reynolds asked. She raised the specific example of Toronto, where Google has wired up a couple of blocks with sensors that can tell us what’s happening in the area. “But does the city have resources to do good with that?”
Rhyming with the past
There’s a certain familiarity to both the opportunities and the challenges associated with using data today. The details are different than in the past. And the scale of what’s possible arguably acts as a magnifier for both the good and the bad.
But, at some level, we’re still wrestling with many of the same basic issues. There’s a tradeoff between the utility and the anonymity of data at scale. And knowing things isn’t the same as doing something about them.
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.
IoT is the hottest topic in the marketplace right now. It’s coming into virtually every person’s life in terms of equipment and devices being used. In effect, IoT is automation coming to your doorstep, your home, car and coming into every workplace.
Printed circuit board (PCB) design software, more commonly known as “tools,” is the basis for creating today’s advanced IoT devices. Considerable credit goes to PCB design tool suppliers who’ve led the industry with state-of-the-art software to properly design and layout IoT PCBs. The field has a number of suppliers, but only a few leaders. One example is personal automated design solutions, or PADS, from Mentor Graphics which, over time, has become the most popular for regular PCBs and now, IoT PCB designs.
The IoT PCB designer faces a number of design challenges and relies on PADS features and characteristics to accurately deal with those challenges and overcome them. For starters, the IoT PCB designer largely depends on the GUI on the workstation screen to visually and intuitively lead him through each stage of a design, especially those that are most challenging.
PADS helps the designer effectively work with such troublesome areas as high-speed designs, trace length matching, board stack up and impedance control. Later on in the design cycle, the software plays a major role by incorporating all the manufacturing information from doing the drilled hole charts to fabrication notes to assembly drawings. Entering fabrication and assembly notes is an easy process when it comes to doing the PCB layout design using PADS.
Aside from design software, the savvy designer must have knowledge of the hardware design and PCB layout and work together with the software since the design tool isn’t equipped to handle certain issues that only an experienced designer can resolve. In many cases, an IoT device is based on a combination of small rigid-flex circuit boards. For example, when making the transfer from rigid to flex, the designer needs to know the kind of bond adhesion between the rigid and flex boards when current flows from one to the other material.
He must also recognize how changing the medium – i.e., from flex to rigid — can trigger changes in the coefficient of thermal expansion between the rigid and flex boards. Plus, the designer has to be extra careful when doing the layout to minimize the flex circuit’s bending effect. Bends in the flex circuit must be carefully routed. If there are 45-degree or 90-degree bends, it’s highly probable that acid entrapment can result from PCB cleaning solvents during the fabrication process. This is difficult to eliminate and the IoT PCB product being designed won’t operate efficiently.
The design software itself is also of paramount importance when it comes to IoT PCB rework, which is common practice in the industry. The software makes it easy for the designer to make necessary changes to an IoT PCB design originally designed using PADS. It preserves signal routing earlier performed in PADS for an IoT PCB product and then changes can be made. Those changes might include adding or deleting some components. This is an important feature because component placement during PCB layout incurs considerable time. This software avoids duplicating all that extra design work. Other changes include altering design speeds, heat dissipation factors, signal transmission and reception, signal-to-noise ratios and signal routing, among others.
The design software also comes in handy post-processing. When the IoT PCB design is complete, power planes sandwiched in the rigid and flex circuit boards need to be split into different power planes. These power planes may have three of four different voltages. That’s done easily when the designer uses a tool like PADS for IoT PCB design.
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.
Early in the internet era, consumers made a bargain with tech companies that neither fully understood. “Give the tech firms your data,” the agreement went, “and we will provide valuable services, free to you, by monetizing that data.” This agreement worked fine and has largely continued without a noticeable hitch; however, recent breaches and misuse of data in high=profile cases (Cambridge Analytica, anybody?) has called into question this value exchange and whether consumers are getting their money’s — or is it data’s? — worth. As data-capturing increases, so has consumer expectations.
The next major tech disruption — the internet of things — is slated to drive data capturing and usage to new heights. IoT has been called “the next Industrial Revolution” because of its potential to impact not just technology, but also work, transportation, the environment and even the broader economy at large. For the first time in more than a century, a new industry is emerging that will shape a new level of intimacy with customers, while restructuring business models and even national economies on scales that we haven’t seen in generations.
Before we can understand the impacts of data in this environment, it’s important to define what, exactly, IoT really is. In short, IoT combines the online space with the physical world. Consider a smart irrigation system that you can turn on and off remotely from your smartphone. Smart thermostats learn your family’s preferred temperature settings and adjust them at specific times of the day. Samsung’s new smart refrigerator can connect to other smart devices in your home, allowing you to adjust the thermostat or lights — all from its touchscreen.
Not to mention, the dashboard computer on your car is already transmitting tons of data about you to its manufacturer. IoT devices are highly efficient data-gathering machines and they are increasingly ubiquitous in our daily lives. Statista estimates that more than 30 billion IoT devices will be installed worldwide by 2020, a 10 billion increase from 2017. That’s a lot of internet devices online — and a lot of data being transferred over the internet.
Of course, if the internet age has taught us anything, it’s that this data will be used to monetize different products and services and may be used to advertise to us. While data-driven marketing is nothing new, the continued spurt of IoT devices will overhaul how we collect, make sense of and apply large data sets. To reach audiences in more meaningful ways and execute high-impact campaigns, successful brands in this space will be those that create personalized experiences across these IoT channels, while being careful not to offend a consumer’s privacy sensibilities. It’s through these disparate channels that marketers will learn to better understand their consumers’ preferences — likes, dislikes, lifestyles and habits — while creating moments of “serendipitous marketing” that appear seamless to the overall experience. Here’s how marketing departments can adjust their data and digital marketing approaches and make the best use of all this new information.
Capturing and learning from consumer habits
With high-octane, real-time data collection, IoT devices can provide marketers with a live feed of how, where and when consumers interact with their products or services. It’s kind of like the holy grail of marketing intelligence: a round-the-clock focus group, matched with actual buying behaviors, which gives marketers in-depth visibility into how their brand is perceived, where it’s positioned in the competitive landscape and what consumers are buying — all through one unified, consumer-centric data feed.
Take a wearable device like Fitbit, for example. It’s a simple wristband, sure, but the type of information it gathers is staggering. Fitbit monitors real-time activity, dietary and sleeping habits; tracks places frequently traveled to; and provides invaluable insight into the user’s overall health. Plus, it connects to other IoT devices for data sharing — including Peloton’s Cycle Exercise Bike and Amazon’s Echo.
But Fitbit goes beyond that, integrating other applications, like MyFitnessPal, which tracks diet habits, or the Withings digital scale, which tracks body weight and composition. That means Fitbit has data on where you go, what your exertion level is, your biometrics, your location, what you’re eating and the impact that it all has on our weight and body fat count.
Tied together, these technologies offer a more accurate and more dynamic story about the user than we’ve ever seen before. You get an understanding of users’ interests, temperament, what they value in a brand, what they’re looking for, how they prefer to go about buying it. Plus a host of other factors, like where they actually are, their commute path or what causes variations in their routine.
This has significant impacts for brick-and-mortar businesses. A retailer, for instance, might map customer foot traffic by placing sensors on shopping carts and baskets. That way, they can gather data about customer habits, such as areas of the store often or seldom visited.
From there, store owners can reconfigure shelves and aisles, as well as strategically showcase products typically outside customer browsing patterns. Or, an advertising firm might place digital billboards and banners in a retailer which changes messaging strategies based on time of day, foot traffic and the specific buying and using behaviors of the pedestrians walking by.
Applying what were once unobtainable learnings helps marketers develop highly texturized user profiles so they can listen to and address the needs of their customers with the right message, at the right time, on the right platform, with the right product.
Omnichannel: Engaging customers holistically
Omnichannel is one of those exclusive-sounding marketing terms many haven’t heard of. But what it encompasses is of utmost importance and can shape a better experience for your customers.
Omnichannel marketing means creating a seamless experience across different mediums or channels. That means smartphones, tablets, laptops, desktops, smart TVs and printers (i.e., mediums), as well as retail, national retail, online and delivery (channels). IoT devices have the potential to revolutionize this practice — by embracing all those customer touchpoints effectively, marketers can furnish a holistic experience for their customers.
It’s important to note, too, that customers shouldn’t experience the medium or channel — they should experience the brand. Consumers, at their core, don’t distinguish between the brand, what it sells and the experience the brand creates for them. To the average consumer, it’s all one integrated experience with the brands they shop from.
Think of it this way: The user might not remember on which device he experienced your brand, only that he remembers experiencing it. To curate this seamless experience successfully, the mission, tone and message need to be understood across departments.
So, does your sales team communicate with your marketing team? Does your e-commerce team collaborate with your social media experts? The experience you create for users should be genuinely consistent across those channels. If you have a siloed marketing department — or even company — your customers will notice.
IoT technology gives marketers far greater visibility into factors hindering or helping a sale, such as weather conditions, customer feedback and product or equipment defects. In addition to the improved visibility, IoT offers the potential for hardware or product data to be seamlessly integrated with the marketing stack, helping to better understand what drives consumers to purchase and use their products. Marketers can then tweak their strategy for each customer interaction and adjust service on the spot. More importantly, it means service providers can deliver technologies that identify each customer as an individual.
But not only does an omni-device strategy enable marketers to create targeted offers and cross-sell, it also allows users to gain insight into a product or service and easily find answers to their questions. IoT empowers consumers to pick what they like and what they want at the drop of a hat, and marketers will be expected to deliver.
Using IoT to provide creative offerings
Listening to your customers and providing quality service go without saying, but are nonetheless important to come back to. Thinking outside the box with IoT can help create a better end-to-end customer experience.
Back to the retail store example: How many times have you had to endure grueling lines at checkout? Wouldn’t it be great if the store sent notifications to alert shoppers of new lanes that’ve just opened up? Or if the store used push notifications to alert staff that lines are getting too long before consumers become aggravated? Or better yet, what if every item you put in your bag was just automatically charged? No checkout, no clerk, no hassle.
Or what if, say, you find a brand-new armoire at a furniture store but don’t want to commit to purchasing it just yet? Pinterest and Tok&Stok, a furniture store based in Brazil, launched a campaign that lets you save products to your Pinterest board right from the store so you can decide whether to buy them later.
Another creative IoT application is geofencing, which uses GPS to create digital “fences” around physical locations. When someone enters that space with their smartphone, an actionable message is sent to their device. Geofences have myriad applications, including product selling, customer poaching, creating safer job sites and reminding employees to clock in or out.
The ultimate goal should always be to understand your customers from all angles — from their tastes and preferences to their shopping style. Are they introverted or extroverted? Do they prefer in-store customer service, doing research online or both? Are they type A planners or last-minute improvisers?
By keeping these ideas in mind, marketers can provide users with an effortless experience, create meaningful relationships with each user and make a lasting impression. This is the promise of IoT –seamless product and acquisition experiences, centered on the user.
The internet of things is changing society and industry in a profound manner, but with the introduction of AI, consumers, enterprises and governments will be able to embark on projects never before thought possible.
For many years, we will find a mix of unconnected machines, connected machines and AI-enabled machines. Our challenge is to make them all collaborate under ethical principles and to avoid using AI for creating psychopath and sociopath machines.
Let´s start connecting every machine
Every machine that can be connected will be connected. Machine-to-machine communication has been building a promising basis for innovative and disruptive business models that will open up new opportunities. Take a look at “How do machines talk to each other?” for a simple explanation about connected machines.
The goal of IoT is to connect every machine to everyone, everything, everywhere … in real time.
Next step: Get value from data collected from machines
But connecting the machines themselves is only an intermediate stage. The continual flow of information that connected machines make available permits management of the machine’s entire lifecycle, from the installation stage to that of maintenance and up to replacement.
For machines owners, this translates to guaranteed system operation, with a development in the business model for the machines, which moves on from the purchase of a physical item to the purchase of the expected benefits. The provisioning of a suitable machine, its appropriate installation and its corresponding maintenance are entirely the responsibility of the supplier.
A key aspect in achieving this goal is data processing. The volumes gathered are such that the provision of valuable services is impossible without adequate information management. As IoT devices generate a large amount of data and we want to do the analysis of the data, we need machine learning to find out the insight of the data.
For machine manufacturers, capturing and processing machine data in real time will allow them to design more freely and manage their machine’s health remotely for better after-sales service. Their customers will also enjoy a better user experience and be able to easily monitor and control their information in real time from anywhere.
Connected machines talking to each other and with humans will dramatically change the way we will live and work.
The time of machines with artificial intelligence is arriving
Artificial intelligence and the internet of things become even more powerful together. AI and IoT are symbiotic; AI makes the machine learn from its experiences and manage new data. I am not exaggerating when I say that AI is the best friend of IoT.
As IoT scales to millions and millions of increasingly intelligent and interactive devices all around us, collecting, distributing, and processing data in a in a combination of fog and cloud computing, many observers believe that AI offers the best chance of quickly and accurately making sense of all that data and putting it to work solving real-world problems. Data lifecycles, flow, classifications, reporting and countless aspects of IoT will be dictated by the intelligence of AI.
A study reported in Science Magazine shows that self-taught AI is better than doctors at predicting heart attacks because of the complexity of risk factors involved.
Both AI and IoT are still in the early stages of their development cycles, saddled with immature technology, limited tooling and still-emerging use cases, often struggling to demonstrate enough real business value to justify their investments and live up to their advance billing.
In the short term, however, AI can help design more efficient IoT networks, ensuring there’s enough capacity without overbuilding and enhancing security. There are many decisions made by AI engines that need to be fed back quickly and accurately to IoT devices; the potential advantages and benefits of IoT and AI are unlimited — the confluence of IoT and artificial intelligence is set to redefine the world.
Must we fear that in a not distant future, an AI system will be able to design other AI systems? We will walk with AI machines that have consciousness, AI machines that can form representations about themselves. We must not fear walking with AI machines, nor that all AI systems must have consciousness.
The challenge of living in a new brave world of AI machines and enhanced humans
“Humans are going to be artificially intelligent.” That’s the prediction of Ray Kurzweil, director of engineering at Google. Kurzweil predicts that humans will become hybrids in the 2030s — a prediction that is line with my article, “Bring your own cyber human part one: Augmented humans.” As we humans formed societies that allowed us to have social interactions, AI systems will form societies that allow them to have cyber-social interactions.
If AI systems are indeed ever to walk among us, they’ll have to be able to understand that each of us has thoughts, feelings and expectations for how we’ll be treated. And they’ll have to adjust their behavior accordingly.
We are in the dawn of a new cyber-society, a society where organizations will design plans to utilize the unique skillsets of both AI systems and humans. A society where humans and AI systems will work and live together and without fear. A society where humans will use newfound time and freedom to advance strategic skills and individual talents.
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Facebook recently admitted that almost all of its more than 2 billion user accounts have been scraped and used for any number of advertising or manipulative purposes. Users, congress and the press have reacted with outrage, canceling their accounts or issuing stern warnings.
The reality is that the sharing of personal/private data is something we all agreed to many years ago when we signed up for Facebook. As Sharon Sandberg so coldly delivered, Facebook could have simply charged users instead of selling their data.
A privacy nightmare in our home
Leaking your brand preferences, political affiliation and cultural bias so that you can be manipulated is bad, but it’s not the worst part. The scariest thing happening right now is that we, consumers, are blindly trusting and sharing even more data about ourselves every day, and the same reporters and politicians demanding change are also ignorantly pushing people into the arms of a much worse privacy nightmare.
The smart home devices from Google, Amazon and Apple are nothing more than live snooping agents collecting more of our personal data. The purchase of these devices doesn’t cover the cost of the servers and computation that’s going on in the background. Alexa is not making our lives better out of charity; Amazon is injecting itself into our lives to be able to understand and monetize our data for years to come by being in our home, with the ability to listen to every conversation, comprehend our every request, hear our best and worst parenting moments …
If we continue on the monolithic cloud path that Amazon, Google, Apple, Facebook and Microsoft are pushing us toward, things don’t get better — more of our data gets compiled, aggregated and used by big companies. Things get worse. These companies won’t make things better, and it’s up to an ecosystem of innovative disruptors to find a better way.
Edge computing to protect privacy
Good news; we see the beginnings of a new technology pattern called edge computing that can solve this. Edge applications offer a sea change of technical alternatives for companies and users piling data into big clouds. Edge processing turns the cloud model on its head, using it only as a deployment tool rather than an omnipotent controller. The information no longer goes to a cloud server, gets saved, parsed, interpreted, shared and manipulated. Every transaction is no longer a possible monetization activity for some company to take advantage of user preferences.
Edge computing is different; it allows developers to still create amazing technologies that give people the possibility to interact with their local and wider world capabilities. For example, edge developers build applications that fully run and execute only on local devices where the users are physically present and monitoring. These edge applications are not dumbly spewing relay information like Alexa, but instead are complete and competent on their own. Three core elements are different with edge processing over monolithic clouds:
Data stays local
When an edge application runs, it stores its own data. The idea that you need Facebook to store the 2 GB of your profile information is silly. Massive amounts of storage are readily available in the tiniest of forms, and 100s of GB to terabytes can be packed and redundantly backed up with in local devices. These local devices become our storage instead of the corporate hard drives of the clouds.
Applications communicate directly and efficiently
Applications now also have the ability to communicate securely and directly with each other. In the Facebook world, this means that when someone views your profile, it’s not a single server bringing that information forward, but it’s your Facebook app that is serving up the information. Not only is your device able to give a more accurate real-time set of information, it’s actually a source of truth that can be unrivaled.
Secured on the device
Data is not secured according to a cloud vendor’s whim, arrogance and business model. Instead, each edge device and each edge owner gets to define the information they share and how it’s used. This model protects people from an all-or-nothing approach that so many apps require today just to get started. Alternately, your contacts, your messages, and your queries are all actually under your control.
Today we have Amazon Echo devices in our homes gathering data about us as we use those capabilities. To protect and prevent another huge abuse of our data, we must transition from these dumb corporate agents and into a model that protects users. The clouds have been unable to protect; we must transition our architectures to serve and protect people using the edge.
We all know full well by now that the internet of things is well established in the technology universe, and it’s continuing to grow, spreading roots across a variety of industries. Take manufacturing, for example. Because of the growing IoT and industrial IoT, factories are now getting smart. The manufacturing industry is currently in the midst of the fourth industrial revolution, which combines cyber-physical systems with automation and IoT to form the aforementioned smart factory. However, incorporating IoT into machines isn’t as simple as putting nuts and bolts together; rather, it requires a fundamental organizational shift to elevate from machine-to-machine and machine-to-human interactions to full-fledged machine-to-business connectivity. Enter “machine as a service.”
In a nutshell, machine as a service encompasses a factory machine’s contributions to business goals through IIoT connectivity. Machines are becoming a comprehensive business asset to manufacturing companies, not only driving sales by generating product, but also increasing business revenue through the growth and scalability that come with automation and IoT. Customers don’t just buy the oil, metal and other elements that make up the machine — they now buy a “subscription” to the IoT connectivity that provides ongoing service and benefits, leading to the concept of machine as a service. Specifically, machine as a service is comprised of two key components: service lifecycle management and customer touchpoints.
Service lifecycle management
Service lifecycle management — which traditionally involved installation, maintenance and repair — is the foundation upon which machine as a service is built. In ages past, installation would mean the assembly of various physical parts and materials. You’d perform maintenance as often as industry standards would recommend (e.g., oil changes every 5,000 miles). When your machine breaks down, you’d repair it.
As the world of technology accelerates on IoT’s coattails, the same goes for the three processes of installation, maintenance and repair. Installation now involves the implementation of an operating system within your machine that will, in turn, connect it to IoT. With this greater connectivity comes an accelerated pace and frequency of machine-to-human interactions. Your machines will now proactively remind you when they need maintenance. Additionally, if something is about to break — or is already broken — your machine will be the first to let you know. This then allows your business to run at a faster pace, increasing production and bolstering your revenue numbers.
The lifeblood of this greater connectivity lies within the operating system and related software updates. However, the software and service behind your machine not only allows it to do what it’s supposed to do, but also enables it to do more than it was designed to do. Which leads to the second point …
Similar to service lifecycles, customer touchpoints also revolve around two traditional stages: the sale of the product and the maintenance/repair of the product. IoT connectivity is catalyzing these two interactions with customers, as it brings on a heightened pace and standard of customer expectations. The machine as a service is fine-tuned to help your business keep up with these heightened demands. However, it also offers an opportunity to dive deeper into a third emerging stage of customer touchpoints: upsell and expansion opportunities.
While the operating systems and software updates support IoT connectivity in your machines, they also offer a chance to expand the portfolio and capabilities of the machine, extending its usage before the true end of life of the product. Your machines are no longer stagnant entities; within the confines of the functionalities listed in the user manual, they’re now dynamic business assets. IoT opens a plethora of opportunities for expanded uses, extending the shelf life of a product that would have been otherwise phased out. This allows your machines to keep pace with the scalability of your IoT-connected business, enabling you to drive business growth and continue to meet and exceed your customers’ expectations.
The IoT-driven future
Machine as a service is just one example of the greater productivity and functionality that an IoT-connected device brings. Across many verticals, we’re seeing widespread IoT adoption to keep pace with today’s technological advancements. As consumers embrace the accelerated world of IoT, the onus is on the business to think outside the box to ensure its products and services stay ahead of the curve and continue to satisfy business goals.
When it comes to mobile applications, design has a significant role. Thus, mobile designers and mobile app development services should be focused on precision and usability.
A mobile app design company typically delivers the right kind of app services that meet various customer requirements. Moreover, service providers cater to clientele across all industry verticals and from small, medium and large companies alike. With the rise of mobile gaming, a lot of mobile app developers at present cater to clients engaged in providing gaming applications. There are also many freelance developers that provide various technologies.
A mobile app development company understands application design and development, particularly when making gaming applications. The design of the app is where the app begins to be transmuted to reality from a mere idea. Many designers can make an application, but only those with varied and substantial experience can provide the right output when it comes to aesthetics and appropriateness.
Opportunities with the internet of things
Today, the reality is that IoT has endless opportunities in the gaming industry. As more and more devices join the internet of everything, the possible effects on people’s daily lives remain a hot topic of conversation due to everything from security implications to logistical implementation.
Video gaming has undergone massive change and overhaul in the last 10 years or so. While desktop devices and consoles still remain hugely popular, it’s the mobile gaming industry that has experienced the biggest surge, due in big part to the continuous stream of free games released to the market.
There has also been a drive from developers toward creating general applications that are more social; many mobile games have become more and more focused on communities. Gaming hardware and devices also are getting more and more IoT friendly.
IoT is giving a facelift to mobile gaming
From snake to virtual reality casinos, it only took two decades for mobile devices to open up new revenue streams. Mobile gaming existed long before the iPhone, but was deemed a more modernistic way of having fun on the go and less as an operable field. Thus, the sizes of the screens of mobile phones were small, and handsets were hugely ineffectual and incapable.
At present, there is a big shift in how consumers game, toppling the balance of power in the international video game scenario. The mobile video game field keeps the ball rolling, driving a mushrooming wave of free-to-play games, as well as casual successes such as the Angry Birds of Rovio Entertainment. As a matter of fact, consumers allocate a lot of money and time playing games on their smart devices.
Casino games are without doubt the fastest growing genre in the mobile gaming field. Prospective players flock to online poker websites and try their hand at different casino games as a way to learn the rule of the game before visiting a physical casino.
The impact of IoT in mobile gaming
The internet of things has the makings to refashion gaming on the web in two ways: by traversing the physical gap between a player and the platform, or through harmonizing online platforms with concrete casinos.
IoT has greatly spurred because of the increased use of smartphones. Smartphones and tablets have a plethora of hardware and software, including accelerometers, sensors, touch and pressure sensors, cameras and heart rate monitors. All of these can be tapped into by mobile applications to report and collect data on user experience. Through analyzing and tracking the correct data, gaming platforms will learn how customers coordinate with online games.
Just as casinos analyze players’ reactions via their facial expressions, nonverbal speech and cues, mobile devices could scrutinize and measure the satisfaction of a player during the game. Thus, all mobile gaming platforms could balance collection of data, as well as preserve the privacy of a player. Another way IoT could impact online gaming is via amalgamation with the experience of physical gaming. This is not applicable only to casinos, but to any gaming platform, as well those shared a player tracking system. With the type of games played in casinos today, only the operator gathers revenue provided the player is physically present. With smart devices, casinos and game operators have more tools to inspire players.
These days, an app development company can cater to the software development requirements of the gaming industry. As online and mobile games get more and more mainstream, developing mobile applications has become a very lucrative venture for developers, wherever they may be located in the world.
While IoT has been all the rage in the past half a decade, the last couple of years have seen frenetic activity in the development of IoT platforms by almost all recognizable players. While the debate continues about which of these platforms will emerge as the first among equals, there is a very real need to tap into the massive amounts of data floating about in an ocean of connected devices.
Just to provide some context, Gartner predicted that there will be 11.19 billion connected devices in 2018, with this number expected to rise to 20.4 billion by 2020. At the same time, IHS forecasted that the IoT market will grow from an installed base of 15.4 billion devices in 2015 to 30.7 billion devices in 2020 and 75.4 billion in 2025.
Not surprisingly, the talk of building an IoT platform has been reaching a fever pitch, and it would be very useful to understand what an IoT platform is, who needs it and how does one go about building it.
What is an IoT platform?
An IoT platform is essentially a suite of libraries, services or components with which an IoT system can be built and deployed to monitor and manage connected devices and systems.
IoT platforms enable the building of highly scalable and performant IoT applications for monitoring and managing devices or systems remotely by collecting and processing data.
Why do you need an IoT platform?
There is clearly a need to integrate multiple systems to achieve efficiencies by continuous data collection from multiple sensors. This data can later be consumed by applications to make intelligent business decisions and carry out real-time analytics.
As there are heterogeneous subsystems used by different business units of the same organization, an IoT platform facilitates interaction among connected devices and business applications. The absence of a consolidated view of the entire system may create difficulties in reporting and monitoring, which drives up the cost of maintenance.
Tell-tale signs you need an IoT platform
An IoT platform is crucial to a business if it relates to at least one of the following scenarios:
Varied technologies that address similar needs: If you have similar connected system requirements from different business units within the organization but are currently using different technologies, an IoT platform would facilitate interaction between the connected devices and different business applications.
Legacy connected systems: Connected systems built over decades with disparate technologies can create challenges in bringing about standardized connectivity and control. An IoT platform resolves these issues by providing the right connectivity and control.
Configure and get connected: Why invest time in constructing a platform when you can just configure it to your use? This results in less development and engineering effort and more of configuration for connected systems.
Ease of monitoring and operations: With businesses increasingly moving towards automation, it is imperative to easily monitor and operate a connected system. This allows for predictive analysis and determining where a machine is likely to fail or turning it off after it has delivered the required output.
All of this contributes significantly toward an easy integration of systems while ensuring an accelerated time to market.
Three approaches to building an IoT platform
There are multiple approaches to building an IoT platform, and it is important to understand the one that best complements your situation. For ease of understanding, let’s look at the three most widely accepted ways of building an IoT platform along with their associated benefits and challenges.
Integrate and transform
For businesses that have made significant investments in technology over long periods of time, it is quite common to have multiple connected legacy systems. In such scenarios, it would be optimal to ensure the coexistence of legacy and modern systems. New features and capabilities can be developed on the new IoT platform and integrated with the legacy system over time.
- Minimal disruption to existing customer installations and on-going business
- Easy migration to the new platform brought about by having tested its stability and reliability
- Integration challenges and platform constraints due to the lack of compatibility between old and new technologies; often technologies have different API’s with different protocols
- High maintenance and operational costs due to running both the legacy and new platforms
Coexist and transform
This approach takes the middle ground by continuing with the connected legacy system as is while building a next-gen IoT platform using the latest technologies. Businesses could look to migrate customers from legacy connected systems to new platforms and eventually retire the legacy technologies. This would be followed by moving to entirely new technologies that are aligned with improving productivity and ensuring a seamless customer experience.
- Use disruptive technological capabilities to build next-generation IoT platforms
- Ensure business as usual during the transformation phase by having existing customers on legacy platforms
- Existing customer adaption of the new platform due to concerns arising from privacy, security and complexity
- Significantly large operational and maintenance costs arising from both platforms being active until all existing customers have been migrated to the new platform
Building new platforms
With barriers to entry being lower than ever before, there are a lot of new businesses mushrooming around the world. For new companies or existing ones that have no pre-existing investments in any technology or connected platforms, it is best to build a new platform from the ground up. This would make it easier to simplify IoT devices, quickly build network-enabled products and accelerate time to market.
- A robust and future-ready platform built using the latest technologies and infrastructural elements with no legacy technologies or platforms
- Seamless customer onboarding to the new platform without any migration or upgrade-related issues
- A new and untested platform must go through a natural evolution of its features and capabilities
- Higher time to market to build and test platform compared to using an existing platform
As is clearly evident, there are multiple approaches to building an IoT platform, and each has its own unique set of benefits and drawbacks. While selecting one approach among these depends entirely on your organization’s strategic priorities, the importance of having your own IoT platform cannot be overstated.
With mounting pressure to capitalize on time-sensitive business opportunities, it is imperative to work with a trusted partner that has an extensive background in building IoT platforms and technologies for both enterprise as well as small and medium-sized businesses.
IoT device manufacturers have by and large flooded the market with web-connected products that have little or no security measures to speak of. There remains such a focus on usability, features and time-to-market (especially with the more ubiquitous lower-end devices) that there’s a real threat to the long-term viability of the industry if it cannot achieve a balance delivering products that are as secure as they are desirable and affordable.
This current absence of effective IoT device security is increasingly empowering hackers, who use malware to remotely take command over unsuspecting connected devices. Hackers can then aggregate the bandwidth of these devices for use in botnet-powered distributed denial-of-service (DDoS) attacks, which have proven plenty capable of taking major websites and network infrastructure instantly offline. Alternatively, devices can be exploited to carry out ransomware and other malicious attacks. And, as has also been shown, IoT devices on the market have even automatically opened home router and firewall ports — essentially rolling out a red carpet for hackers, all in the name of simplicity for consumers.
Part of the problem here is certainly the relative difficulty of updating IoT devices with more secure and current firmware. While some device vendors are beginning to provide automatic firmware updates when new vulnerabilities and exploits are recognized, many, many more IoT devices can only be updated manually or no longer have official support whatsoever. In order for updates to arrive, vendors must invest in the infrastructure necessary to develop and deliver new firmware. (This means, of course, they must also see the business value of such an investment.) More often than not, though, vendors support devices for a limited time and vendors that go out of business cannot provide further support at all. Firmware update URLs once belonging to defunct vendors could even be exploited by malicious actors to control device traffic — yet another glaring weakness to the security of these devices.
It’s critical that consumers become savvier when it comes to the IoT devices they select for purchase, thus putting pressure that might be needed to fast-track a change in these practices. But really, the onus is on the manufacturers. Device makers must collectively acknowledge the long-term value of collaborating to adopt and enforce standardization and best practices, in pursuit of a more secure IoT that stops making headlines for massive vulnerabilities and breaches. Ultimately, customer safety and an internet safe from future IoT botnet attacks depend on wise and decisive action by the industry stakeholders of today.
Currently, IoT vendors utilize a variety of disparate and incompatible technologies, from custom closed-source approaches to open source technologies applied in vastly different ways. However, by supporting common standards, such as IoT devices from different vendors using the same technologies and practices, it would become possible to secure and support all devices using widely available open source firmware. Thus, even those devices from extinct vendors could be fully secured.
The industry is seeing the dawn of what could be adopted as these needed standards. One candidate, the Arm Platform Security Architecture, provides a standard framework for IoT device security. A draft document by the Internet Engineering Task Force (IETF) offers the Manufacturer Usage Description (MUD) standard, establishing a common foundation for communication and access requests between IoT and security devices such as routers and firewalls. With MUD in place, even IoT devices with poor security could only access necessary services, thus imposing more effective security on them. In this way, the MUD specification is being explored as a method for preventing IoT devices from being used in DDoS attacks. Some industry vendors are also developing advanced approaches that utilize the technologies including AI, predictive security and proactive behavior-based threat recognition.
The technology and frameworks needed to standardize and secure the IoT industry are quickly becoming available, but vendors must have the will to match. In many ways, achieving a future in which a thriving IoT industry realizes its full potential depends on it.