As any technological system grows, it can either be advanced or surpassed by other technologies. Sometimes, this lesson is learned the hard way. For instance, many legacy photography companies either pivoted or shuttered with the advent of cloud photo sharing, mobile phone cameras and the improvement of home printers.
Even the most buzzed about technologies of the past decade are seeing disruption rear its ugly head — including IoT, cloud computing, social media platforms, virtual reality and the like.
With the internet of things, we are at an inflection point. Data being collected from devices, buildings and sensors is vast, so massive that, a lot of the time, it never is used because the data isn’t understood. Part of the problem with IoT data — and more specifically, industrial IoT data — is that it is collected on central servers and not the IoT devices themselves. Most of the time, these servers are either on the cloud or part of an in-house data system.
For a manufacturer in need of real-time IIoT data analysis of a device or sensor, this creates added complexity and an unnecessary blocker to getting information directly from the system. If you need to retrieve data from a source other than the IoT device built into production, you may not know where the data is specifically coming from, or worse, you may not be able to connect to the device and its related information to make integral business decisions.
The solution is bringing the analytics to the edge, which allows data to be analyzed at the point where the equipment is actually transmitting the information and there is no networked cloud or server data to sift through.
Edge analytics is perfect for manufacturers who need to be able to analyze and take the corresponding action in response to the massive amounts of data transmitted by IIoT sensors or the data transmitted from the production line. Beyond cutting down reaction time and the sifting of vital data, edge analytics also increases data security, especially in production facilities that create a continuous stream of data ripe for data attacks.
Here are a few more benefits for manufacturers who implement edge analytics processes into their IIoT programs:
Varied connectivity and data mobility
Implementing edge technologies removes the potential downtime risks and connectivity issues often inherent in production lines and manufacturing centers. Edge analytics systems can operate in places that might limit or require intermittent connectivity to the cloud.
Instead of relying on access to networks or the cloud for computing, storage, backup and analytics in manufacturing facilities where the infrastructure is often weak, businesses can have more faith in their sensors or devices processing and collecting operational data than if tied to servers or the cloud.
Need for real-time decision-making
In manufacturing, decisions need to be made as quickly as possible. Additionally, any problems or complications to production lines or automated process need to be identified and managed as quickly as possible.
Edge analytics allows data to be processed instantly, at least in sub-second speeds. For technologies like advanced robotics or automatic manufacturing line machinery, for example, the quicker issues can be identified and data can be analyzed is integral to the business. IIoT devices and sensors need to be able to do analytics locally without first sending data to the cloud, so decisions can be made rapidly.
Localized compute power
Many IIoT sensors and devices have space constraints due to the nature of manufacturing. Edge analytics hardware is lightweight and rugged, which is ideal for production lines, warehouses and other manufacturing needs.
More than anything, this creates an environment in which fast, secure and confident decisions can be made at the device level without the support of bigger computing power. This ensures reliability and uptime performance.
New storage and security needs
If you peruse any cybersecurity industry journal or dedicated blog, you will see how recent technological advancements — IoT and the cloud, to name a couple — are prized by hackers with malicious. The reason being that all these nascent technologies have easily exploitable loopholes that have not yet been solved by the market and the industry security systems.
As the numbers of sensors and IIoT manufacturing devices generating data on remote and sometimes mobile devices grow, so does the need for not just efficient storage, but data that can be secured in a variety of environments. Limiting the transfer of data to one step versus moving to servers or the cloud eliminates an easily exploitable threat.
Edge analytics is not a fad to be ignored
By not exploring edge analytics, manufacturers are limiting the potential benefits they can reap from their IIoT platforms. When the transmission of data, the ability to quickly analyze data and information security are not localized to a device or product in the manufacturing industry becoming more reliant on IIoT, then the potential for disastrous lags in response time or the loss of key data analytics occur without any even noticing.
Limiting where IIoT data analysis can be completed affects not only what manufacturers can offer to their customers, but also the amount of value that can be derived by advancements such as an IIoT-enabled production operation.
How edge analytics improves the system
To understand how important edge analytics could be to manufacturing, imagine if you will, a remote monitoring operation of the paint spraying process on an automotive line. The amount of paint applied in this specific process is critical to quality. The under- or over-application of paint is unacceptable and requires significant reworking and sunken costs.
When the performance data of this process is analyzed by IIoT devices and is then relayed across the cloud, the ability to respond with the necessary amount of speed to detect these fluctuations and the take action is lost. Facilities undertaking this car production process also often lack proper connectivity, which makes data transmission beyond the location of the device unreliable. As such, fluctuations in the painting process can be missed or detected too late to elicit a response.
To overcome these issues, edge analytics can be employed at the local level, where the IIoT devices are operating, allowing for the measurement of specific, combined operating parameters and issue alerts when these complex parameters are breached.
Building edge analytics into manufacturing is similar to starting an IoT system; you need to start with a simple threshold alerting systems that are easily and quickly understood by production engineers, product managers or field service technicians. This allows for a shift from a proactive approach to IIoT to a truly predictive data collection and analysis model.
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.
Organizations across all industries are currently undergoing a digital transformation as advancements in technology offer the opportunity to optimize business operations and improve customer experience. The advent of 5G networking technology and the burgeoning internet of things are set to impact the aerospace and automotive sectors in particular, significantly disrupting various aspects of their manufacturing, operations and design capabilities, among others.
Along with improvements, of course, this disruption will bring challenges that will need to be addressed. Lessons can be learned from other similarly disrupted industries, however, and provisions made that will allow automotive and aerospace business to fully capitalize on the opportunities that this high-speed, low-latency, connected future offers.
The benefits of 5G and IoT
Given its promise of high-speed data transfers, ultra-low latency and increased connectivity, the potential benefits of 5G are manifold. A significant increase in the amount of computing power made available to vehicles and aircraft will enable greater accessibility and performance of entertainment and communications applications, for example. This will substantially improve the customer experience, especially with the degree of personalization and targeting afforded by real-time location intelligence. Advances in intelligent applications and the use of AI and machine learning technologies will provide entertainment and personalized services in automotive and aerospace scenarios that vie with services that are provided in traditional home, business and mobile experiences.
This same capacity for real-time intelligence will also enhance the safety of road vehicles considerably, providing satellite navigation devices with more accurate predictive traffic patterns and supplying the next generation of advanced driver-assistance systems with vehicle-to-vehicle or vehicle-to-infrastructure data in order to avoid collisions. Improved networking and availability of diverse and significant data from IoT systems in air and on ground will enable advanced sharing of information across other aircraft and ground operations. This will improve safety as well as on-time performance across the industry. Using open cloud-based services such as SWIM (System Wide Information Management) in concert with improved networking and relevant data accelerates these new capabilities.
Likewise, aircraft pilots and navigation systems will similarly benefit from accurate, up-to-date airspace and traffic information.
Enabled by 5G, the myriad connected devices that make up IoT will transform the automotive and aerospace manufacturing process. With integrated sensors providing continuous feedback on the performance of any given component or part, and on its usage once deployed, R&D teams can make ongoing iterative improvements to any design based on accurate, real-life data. Indeed, analysis of a component’s performance and, where necessary, its failure, will allow for far better inventory and vendor management. Identifying a point of failure as and when it occurs, for example, will help manufacturers to streamline their supply chain and, ultimately, improve the efficiency of their overall operations.
Design and preparation
The examples outlined above are just some of the many opportunities for improvement that a digital transformation offers the automotive and aerospace industries. Consideration must be given, however, to ensuring that implementing such disruptive technologies will add value to a business and its wider ecosystem. Indeed, adopting the latest technology “just because everyone else is” could be counter-productive and lead to unnecessary, inefficient “bloating.”
Design-driven engineering is key. While its many benefits may be attractive, all functionality introduced by implementing an IoT system should be foundationally connected to real, considered business requirements which themselves are tied to an overarching business case for delivering quantifiable improvements. The systems architecture work that underpins the implementation of such a system should detail how it will achieve the desired improvements without introducing unnecessary costs or reducing system availability.
Preparation is important too. After all, a digital transformation program is not something to be undertaken lightly and its effects are likely to be felt throughout the entire organization. The business should invest in enterprise architecture design, for example, to ensure that digital integration is actioned efficiently across the whole organization and includes back office applications, which can provide automated workflows to enable intelligent supply chain, for example.
What’s more, an organizational plan should be put in place that clearly defines the revised roles and goals of a company’s workforce under the new, transformed business model, in which back office functions will be increasingly digitally integrated and automated. And with IoT fundamentally reliant on the real-time back and forth exchange of data from various connected sensors, devices and machines, it’s imperative that businesses have a secure and accessible data architecture in place. A data architecture that can be easily “exported” to business partners enables integrated digital transformation.
Many businesses are already a long way into their digital transformation and have learned important lessons along the way. Having tried to create next-generation mobile applications with the aim of improving customer experience and influence purchase decisions, for example, some retailers have found that, if these apps are not designed with user experience, accessibility and clear performance goals in mind, they are unlikely to succeed. Enabling and embracing agile methodologies in deploying transformative systems is critical to the success of ensuring high-value business requirements are met.
While they are yet to reach their full potential, disruptive technologies such as 5G and IoT are set to transform the face of the automotive and aerospace industries. Real-time data generated by external sensors will improve the safety of aircraft and road vehicles; widespread connectivity and fast data speeds will improve system performance and availability; and predictive failure patterns and continuous performance analysis will reduce manufacturing costs and optimize the supply chain.
But, all of this depends on preparation and design of system architecture, enterprise architecture and data architecture. For many businesses, however, this new digital environment is unchartered territory, the navigation of which can be greatly assisted by the employment of third-party strategy, design and consulting services.
By ensuring the necessary architecture is in place, and that any implementation is aligned with its business objectives — whether around safety, efficiency or customer experience — automotive and aerospace organizations, in common with those in many other industries, will be placed to reap the rewards that a digital transformation can offer.
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.
Life is in constant motion. People move from place to place, from one moment to another, from one stage in their life to the next, changing personalities and needs along the way. When you can understand not just where people are going, but why and how — having high motion intelligence, if you will — you can unlock amazing new possibilities.
Motion data from smartphones has introduced a world of opportunity for companies to create one-on-one relationships with people that are truly personalized and always-on. Analysis of the physical movement of the mobile phone can help detect mobile events that can be translated into meaningful moments, reflecting real-life and real-time context and routines. And all of this can be done while safeguarding consumer privacy through combining first-party business models and advances in edge computing.
According to GSMA Intelligence, there will be over 25 billion connected devices by 2025. While IoT is rapidly becoming a mainstream technology in consumer markets, use cases for IoT are shifting from just connecting devices to addressing specific problems or needs with real solutions.
Let’s examine how enterprises across health, automotive and mobility are putting people at the center by translating motion data into actionable insights to help them better improve people’s lives.
By contextualizing data, healthcare companies are becoming more patient-centric
Wearables and connected health devices provide a treasure trove of data points for healthcare providers. Data such as number of steps taken, heart rate and calories burned from wearables, and nutrition intake, glucose levels or heart rate variability from connected devices can help healthcare providers derive better insights into patients’ health and lifestyles. If they also understand the context of their patients’ behavior, healthcare providers can develop highly personalized treatments for their patients. They can also learn when it’s best to engage individuals to steer them toward healthier outcomes. For example, Dutch medication adherence app MedApp is contextualizing smartphone sensor data to provide personalized smart alarms for medication intake. The app can detect if a consumer is stuck on the subway or driving home and adjust the medication alarm for when he is back home and able to take his medicine.
Another example of where healthcare providers are innovatively using smartphone sensor data to provide one-on-one, real-time patient care is in gait analysis. For patients who recently had back, knee or hip surgery, for example, through sensor data healthcare providers can monitor a patient’s movement post-surgery to see if he is getting back to a normal gait. Instead of taking patients through expensive and exhaustive outpatient care procedures, healthcare providers can inexpensively monitor a patient’s gait through the mobile phone, without the patient ever making a doctor’s appointment.
Car manufacturers are personalizing the in-car experience for drivers
For decades, car technology has traditionally focused on optimizing the vehicle’s internal functions, but attention is now turning to enhance the car’s ability to bring an in-car experience that is customized to fit the needs of drivers and passengers. By connecting smartphones to the car’s dashboard or infotainment system, and using behavioral data and real-time context awareness, car manufacturers can make the driver’s experience more personal, practical and enjoyable. For example, French car company Peugeot paired AI and smartphone sensor data when it built its Instinct concept vehicle. Peugeot then tailored presets and recommendations based on driver profiles and real-time context. With smartphone sensor data, car companies are creating personalized digital experiences during the car journey, as well as delivering relevant contextual assistance pre- and post-trip.
Enhanced driver coaching for ride-hailing companies
Some of the world’s largest ride-sharing platforms are using algorithms to score the behavior of their drivers based on the sensors in the drivers’ phones. By monitoring the movement of a driver’s mobile device, ride-hailing companies can determine how smoothly, anticipatively and legally their employees drive. Smartphone sensor data can also help them detect when their drivers handle their cellphones while they drive. These insights can better inform ride-hailing companies on how they need to coach their employees to become safer drivers.
Car insurance companies can also contextualize smartphone sensor data to get a more holistic profile of a driver’s behavior and essentially form a “driver DNA” for each of their customers. What are their customers doing while they drive? Are they using their cellphones while driving? Where are drivers coming from and where are they going? Do they spend too much time at work and not get enough sleep? Understanding the entire context of a driver is important for making more accurate predictions about risk profiles, and also allows insurers to coach their customers to become better drivers.
Today’s modern enterprises have no shortage of data to make conclusions about how people go throughout their daily lives, and mobile sensor data is increasingly becoming a more necessary component of this data mix. By contextualizing data from users’ smartphones, companies can get a more holistic view into how people move, which can arm them with the right systems to help make people’s lives easier. Be it through personalized health coaching, customized in-car experiences or driver coaching, sensor data from smartphones is at the heart of bringing more seamless lifestyles to users.
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.
The cat, er, robot, is finally out of the bag: In-store retail is not only not dead, it’s in a position to revolutionize shopping in much the same way e-commerce did two decades ago. While e-commerce is growing rapidly, 91% of U.S. retail sales still occurred in-store in 2017 according to Statista, with 86% predicted by 2021.
The path to the “store of the future” — which we’ve been envisioning for years — is well underway with industry leaders. At the very least, predictions of an all-online shopping world should be put to rest for a long, long time.
And everybody will win: consumers, employees, consumer goods partners and the retailers themselves.
We can thank the burgeoning IoT industry; specifically, sensors, beacons, robotics and video — all powered by streaming data analytics. Exemplar retailers have taken the lead in this and are actively testing once “futuristic” applications to further streamline operations and deliver better customer experiences today.
Walmart recently reported that it is actively recruiting top-level computer scientists to develop its initiatives, which include the recent news that it will deploy hundreds of autonomous robots to clean the floors at some of its stores in January 2019. The world’s largest retailer is also testing automated (robotic) scanning of shelves to improve in-store merchandising execution and out-of-stock response.
Other soon-to-be-unveiled IoT-based advancements include using computer vision and data analytics within shopping areas to improve inventory tracking, implement dynamic pricing and better understand consumer behavior.
Today, the goals of IoT and streaming data analytic initiatives can generally be divided into three categories:
- Driving greater operational excellence;
- Delivering personalized customer engagement; and
- Offering relevant and localized products and services.
Driving operational excellence through IoT and streaming analytics
Consider one use case already occurring: robots armed with streaming data analytic capabilities that can scan shelves to identify out-of-stock items, shelf schematic compliance and display execution in real time. In fact, Walmart recently announced it has experienced as much as a 50% improvement in out-of-stock labor costs after deploying them. Kroger has also announced experimentation with this technology for similar purposes.
One of the biggest revenue opportunities for bricks and mortar remains mitigation of lost sales through quick replenishment of out of stocks. Keep in mind that out-of-stock items are often not in a distant warehouse, but somewhere else in the store. Also keep in mind that stores will not only frustrate shoppers, miss out on the immediate sale and perhaps leave a negative impression, but also risk losing longer-term business to competitors because of out of stocks. In fact, a recent IHL survey suggested that over 24% of Amazon’s retail revenue comes from consumers who first tried to buy the product at their local stores.
Computer vision insights (using streaming video) are also beneficial for the purposes of informing corporate merchandising teams of in-store compliance (pricing, promotions and placement) in real time, including conditions that may be impacting seasonal sell-through and markdowns. Incremental benefits include data monetization (and disruption of syndicated data providers) by sharing these insights with their supplier partners.
Additionally, connected data and devices within the four walls of brick-and-mortar stores are creating greater operational and cost efficiencies. Just think about refrigeration and freezer units in thousands of grocery stores. There’s not just one big refrigerator; there are several large units in each store (across thousands of locations) to store products such as produce, dairy, deli and meat that may need to be kept at different temperatures. Temperature fluctuations can significantly impact product shelf life and go completely unnoticed by in-store personnel.
IoT and streaming analytics can alert stores to take action in order to ensure freshness and reduce waste. These new technologies can automatically push notifications to in-store associates to inform them that, for example, they lost a half-day’s life on specific dairy products overnight, based upon predetermined business rules contemplating the temperature fluctuation impact on product lifecycles. This advisory can simply instruct the store associate to reduce the price for the day or take other actions to protect freshness and quality.
Delivering personalized customer engagement and improved shopper experiences
IoT and streaming analytics hold great promise to assist merchandising and store operations teams with new insights. These include better understanding of traffic patterns, paths and hot spots within a store. It can look at dwell times: How long are customers spending in the women’s shoes department? How much time are they looking at a display? What is the associated conversion rate after checkout? How long are they waiting to check out?
These technologies and their uses will supply new metrics, insights and actions that retailers have never been able to measure or respond to at this granularity. This is especially meaningful considering tight labor constraints and a desperate need for “actionable intelligence” versus more dashboards or reports.
Emerging technologies such as computer vision (using existing in-store video cameras) are even providing new capabilities to move from prediction to intervention to help mitigate fraud and shrink — a multibillion dollar issue in retail yet today. Whether at the back door, self-checkout lanes, kiosks or in-aisle, IoT and streaming analytics hold much promise to help curtail this bottom-line challenge for all retailers.
Finally, proximity marketing and personalized engagement using mobile applications, Wi-Fi, beacons and RFID technology in-store continue to hold much promise, but remain experimental for most retailers still looking to find the right balance between privacy concerns and the type of customer insights that can be gleaned from in-store technology deployment. North American retailers such as Macy’s, McDonald’s, Kroger and Walmart have been experimenting with this, as is Carrefour, one of the world’s largest hypermarket chains in Europe.
Providing relevant and localized products and services
While the initial benefits of IoT and streaming analytics may have been focused primarily on customer engagement and customer experiential use cases, it seems the use cases for in-store merchandising are also demonstrating solid early results.
Dynamic pricing is yet another nascent e-commerce analytic capability that can be carried over to brick-and-mortar stores. While electronic shelf labels (ESLs) have been around for a couple of decades, the high cost to implement digital shelf tags has limited widespread adoption. However, the transparency of competitive pricing and the growing use of new analytic capabilities to instantly change prices on hundreds (or thousands) of items on e-commerce platforms also provides an opportunity for retailers to push this capability to individual stores using ESLs.
Kroger, America’s largest grocery chain, has just begun to roll out Kroger Edge (Enhanced Display for Grocery Environment), which connects IoT sensors to the retailer’s cloud-based storage, beams real-time data from every aisle and digitally displays pricing, nutritional information, video ads and coupons. This allows corporate and store managers to instantly change prices and initiate flash sales events on individual items. It also saves labor costs, because employees on the floor don’t have to change prices on hundreds of item tags by hand.
Light — and profit — at the end of the tunnel
If it works as designed, Kroger Edge will also be environmentally friendly and cost-efficient. That’s because Edge uses low-voltage LED lighting and will eventually run on renewable energy sources. The need for extremely bright and costly fluorescent or incandescent lighting is basically for customers to read paper tags, but with next-generation ESLs, stores can decrease the brightness of the bulbs.
Suffice to say (and to borrow from Mark Twain), reports of the death of brick-and-mortar shopping was an exaggeration. More than a few “experts” have predicted that Alibaba and Amazon would end the in-store retail experience for good. And while it’s true that e-commerce has had a deleterious effect on bricks and mortar, the retail industry is nothing if not resilient and competitive. Retail executives will always search for innovative ways to increase revenue — even if it means reimagining the in-store shopping experience. IoT and streaming analytics are driving that new imagination.
Enterprise customers are still bullish on the internet of things, but their enthusiasm has been tempered by the realization that complete systems may take longer to implement and yield a return than they had originally expected. Bain & Company’s research found that, despite these readjusted expectations, the market for IoT hardware, software, systems integration, and data and telecom services could grow to $520 billion in 2021, more than double the $235 billion spent in 2017 (see Figure 1).
Since our last extensive survey on the internet of things and analytics two years ago, customers believe that vendors have made little progress on lowering the most significant barriers to IoT adoption –including security, ease of integration with existing IT and operational technology systems, and uncertain returns on investment. These customers have extended their expectations about when those use cases will reach scale. On average, they are planning less extensive IoT implementations by 2020 than they were just a couple of years ago (see Figure 2).
In spite of these concerns, enterprise and industrial customers still see success within their reach. They are still running more proofs of concept than they were two years ago, and more customers are considering trying out new use cases — 60% in 2018 compared with fewer than 40% in 2016.
Over the past few years, cloud service providers (CSPs) have emerged as more prominent and influential vendors in the space, particularly AWS and Microsoft Azure. CSPs are lowering barriers to IoT adoption, allowing for simpler implementations and making it easier to try out new use cases and scale up quickly. In our survey, customers told us that CSPs and analytics and infrastructure software vendors have the most influence over the IoT systems they are buying. Many customers see CSPs as leaders in providing easy access to IoT tools that collect, aggregate, curate and analyze data.
CSPs are using their deep expertise in analytics to expand across the IoT market and to strengthen their position in analytics and cloud services for enterprise and industrial customers. But their broad horizontal services provide little optimization for industry-specific applications, leaving a significant opportunity for vertical offerings from systems integrators, enterprise app developers, device makers and telecommunications companies.
This pent-up demand represents a huge opportunity for technology providers that can meet customer needs. Meeting those needs will require a solid understanding of customers’ concerns. Our survey found that vendors are aligned with customers on some barriers (security, returns on investment), but less so on others (integration, interoperability and data portability).
Based on the experience of previous technology cycles, the key to addressing these concerns lies in focusing on fewer industries in order to learn what customers really want and need. Gaining deep experience in a few use cases helps vendors anticipate customer needs in those industries and allows them to create a repeatable playbook and end-to-end systems.
The number of consumer IoT devices entering the U.S. market is staggering. Gartner said a typical family home could contain more than 500 smart devices by 2022. These devices represent internet endpoints that will penetrate every household before we know it, and those endpoints will rapidly multiply from there. This trend is fueled by insatiable user demand and substantially enabled by retail distributors that see the windfall economic benefit.
The threat associated with a potential enemy-state’s role in consumer IoT is massive, but the U.S. continues to enable it. Before our very eyes, China is gaining direct access and insight (literally) into our homes through digital access from the connected devices we put in our homes, as researchers from Dark Cubed recently discovered.
An everyday cybersecurity scenario
Let’s imagine a simple scenario. You walk in to a major retailer and see an LED lightbulb for less than $10 that you can control from an app. You think, “Great! I can program this bulb to come on automatically when the sun goes down and turn it off from my phone when I go to bed. $10? It’s a no-brainer.”
You go home, open the box and are instructed to download an app to your phone. You do so, and by selecting “download,” you don’t know it, but you give this app legal permission to access many things on your phone and to do things you’ll never understand.
Once the app opens, you set up an account. You wonder for a second why the lightbulb app is asking for your location and access to your contacts, but you allow it. To be safe, you set your typical password but change one number.
The app tells you to screw the bulb into the lamp and asks for your Wi-Fi password and, like magic, the app is connected to the lightbulb, which is connected to your Wi-Fi router that is likely several years old. You set the schedule for the light and think, “How does it know when the sun goes down at my house? Oh, that’s why it needed my location, makes sense.”
A few days in, you think, “This cheap bulb is awesome.” You get three more. You see a Wi-Fi camera at the store and realize you can add this to your app. You can check from work to see if the kids are doing their homework. Best of all, it’s less than $25. No-brainer!
You receive a notification that you can record video and store it to watch it later. You can get a notification when the front door opens and a 20-second video is captured and sent to your phone. For $5 a month, you can see when your kids get home. So, you enter your credit card number into the app.
The most prominent foreign country that is home to the companies that control the communications from these devices and the apps that control them is China. In the scenario above, this company and its governing nation now have the access and the means to create and maintain an up-to-date profile of this home and its occupants.
Perhaps more frightening is the fact that this company can easily access these devices to find holes in your Wi-Fi network to access computers, hard drives and other devices or data repositories. And remember, you supplied this company with your log-in information; hopefully those credentials are substantially different than your online banking credentials. Password-guessing attacks thrive on clues contained in alternative passwords. This is a reasonably common situation in millions of households right now, and growing rapidly due to the continued distribution of these devices by trusted U.S. retailers.
How your home is spying on you
A significant number of these devices, virally spreading to and inside our homes, are in fact controlled by Chinese communications platforms. Consumer demand for connected things in the U.S. has caused device manufacturers to rapidly produce connected devices to meet this demand, but they have to use communications platforms to connect and allow these devices to converse with us over the internet. This has created a challenge for the manufacturers to find platforms that can enable the communications and supply the software that consumers need to control their devices.
A huge new industry has been created in China to solve this challenge, creating a grave problem for the U.S. while enabling a massive opportunity for the Chinese government. What could they do with direct access to and control of hundreds of millions of connected devices in millions of U.S. households? Every single day, data goes from your home to China or to servers in the U.S. owned and accessed by China.
This data becomes more informative every day, and new data is created when new features are added or new devices installed. China leads the world in analytical technologies like machine learning, AI, augmented reality and computer vision. Not only will it have the raw data to know everything about you — your behavior, where you are, where you go, who you know — with its data analysis prowess, it can begin to anticipate your future behavior and locations. Could there be a greater cyberthreat?
Three steps to mitigate the damage
If you didn’t know, China censors everything internet-related domestically — there is no chance that the U.S. or any other state could accumulate this level of insight on China’s citizens. Shrewdly, China clearly understands the impact of the cyberthreat and uses its censorship policies to remove the risks of foreign access. It also realizes that there is no regulation, enforcement or even a level of awareness that might cause friction to its effort to access our population. It sees the demand of these devices, it is eating the cost of hosting and software to make these devices work, and it is catering to the wishes of the U.S. retail community by keeping the pricing of these devices very low. It’s a perfect storm.
The good news is that it is not too late. Massive damage has been done and much cannot be undone, but we can reduce the damage done and prevent further impact. Here’s how:
- Retailers must stop selling connected devices whose software and communications are managed by off-shore communications platforms. These platforms will do everything to obscure their role and function to satisfy non-technical decision-makers, so retailers must align with U.S.-owned and -operated platform providers to protect users.
- Many devices can and should be sourced from China, but the communications function should be American. And manufacturers need to ensure that the devices themselves have an adequate level of cybersecurity protections and are easily patchable.
- Stop the unnatural race to the bottom on device pricing. IoT is made of living objects that require support over time. Like a car that needs gas and maintenance, these devices and their user software must be managed, updated, maintained and hosted for the life of the device. The $10 connected LED lightbulb requires support for the life of the bulb — perhaps 20 years. What happens when it runs out of gas in a couple of years?
Focus on the platform and take a stand for data privacy
Much of the narrative on how to protect ourselves from IoT security risks has focused on the connected device. Sure, without proper engineering in the device itself, it can be vulnerable to a cybersecurity breach. California has taken a bold step in focusing on device protections. The bigger unaddressed problem is the platform governing these data communications. Think of it as similar to your wireless carrier. You have a smartphone likely built somewhere in Asia, but you use a regulated and trusted U.S.-based wireless communications carrier to manage your voice and data activities. The greater problem is that we are allowing unregulated, unknown, foreign entities into our homes with the permission to do and take what they want.
As the number of IoT devices skyrockets, so does the risk to consumer, corporate and nation-state information if a foreign nation is able to use such unprecedented access to individuals’ data. Indeed, industry observers like Om Malik have called for a constitutional amendment addressing digital privacy to help protect against these trends.
Consumers can’t tell the difference between a secure and unsafe IoT device — and they shouldn’t have to. Retailers must take up a bold position along this cybersecurity and privacy frontline to protect their customers from these real risks today.
Networked surveillance cameras fit the definition of IoT devices. They’re an evolution of formerly closed-circuit analog products that have been upgraded with advanced computing and networking capabilities, so they may be connected over a standard LAN/WAN or even via the cloud. So why don’t the security teams that use them or the IT departments that eventually have to support the data they create see them as IoT deployments? And how can we bridge this gap between the security and IT teams?
Lack of coordination leads to unsupported devices
Part of the problem may be something as simple as shifting definitions: The security professionals who use networked surveillance cameras don’t recognize them as IoT devices because they haven’t traditionally been thought of that way. But advancements in technology, new use cases and declining prices have caused an explosion in demand for these devices. This is also what’s causing video security to move into the data center and put new pressures on IT.
In the end, it comes down to competing priorities — security’s focus on risk management and IT’s focus on managing complexity.
Without some level of coordination, you get scenarios like this: Security professionals purchase a large number of networked security cameras, alarm sensors and card readers. This equipment comes with a full rack of servers designed to serve as compute and storage devices, and it’s often bought and installed without consulting IT staff.
There are only so many IT staff members in this organization, and they already spend most of their time maintaining what they consider to be core systems. They don’t have time to maintain these new systems, and they don’t think it’s their responsibility anyway. As a result, these cameras turn into a security hole — a huge number of them sit unprotected on the internet, in plain view of anyone who knows how to use Shodan.
Shodan is a search engine for unprotected IoT devices. Assuming that you know an organization’s IP address, you can plug it into Shodan and see if there are any undefended IoT devices attached to it. If those devices are cameras, you can actually tap into the camera feed and see what it’s seeing. An attacker can even see the version number of the camera’s firmware. If it hasn’t been patched, an attacker can convert it into part of a botnet such as Mirai, which brought down the internet in much of the United States back in 2016.
When IT admins and security professionals don’t collaborate, in other words, they can end up in a nightmare where strangers have a view onto their premises and can use their own devices for use in criminal acts. Not good. How can we avoid this?
Turning vulnerabilities into an IoT roadmap
Let’s take another approach to this problem. Instead of working separately, security professionals and IT administrators would work collaboratively to support an overall IoT strategy, one that would eventually encompass more than just video surveillance. How would that work?
It starts with security and compliance — if an organization is subject to regulations such as ITAR or FSMA, they are required to keep records of everyone entering or leaving their facility. Deploying digital video surveillance and creating an archive of its data output is a central pillar of these requirements.
The next step is technically supporting the digital video implementation. This won’t be easy — digital video surveillance creates a large amount of unstructured data. Administrators need to work with security to categorize this data, store it — no easy feat, as this could mean terabytes of video per day — and then be able to retrieve it at will.
Once this data is under some kind of structure, however, administrators can use it for things other than security. Digital video is a huge storehouse of data about the organization — for some organizations, it may be the largest data storage application there is. Being able to use this data for purposes other than security — to increase productivity, optimize customer conversion rates and mitigate unplanned downtime — is a huge win. Some potential use-cases include:
- Allowing retailers to monitor their foot traffic and use this data to reorient their shelves and displays in order to maximize engagement;
- Providing targeted advertisements to consumers based on their location within a store, mall or stadium;
- Pinpointing the source of equipment failures within industrial facilities; or
- Enabling smart cities to improve safety in areas like pedestrian crosswalks.
As administrators push a digital surveillance strategy to maturity, they can begin piloting other IoT technologies using the same model. Eventually, IT can use the digital video strategy to build a highly instrumented organization that sees the IoT as a central underpinning, not an afterthought.
As an industry, manufacturing is often seen as risk averse and slow to change. When it comes to IoT, however, manufacturers are anything but. According to IDC, the manufacturing sector spends more than twice as much — $178 billion — on IoT than the next closest industry, transportation. Not only that, but 84% of manufacturers report that they already have digital factory initiatives.
Enthusiasm and optimism for IoT are high, but manufacturers face unprecedented complexity in implementing IoT strategies and systems. They not only have to deploy connected devices, but also create and manage value-added software for those devices.
Increasingly, companies in the manufacturing sector are turning to platforms to overcome these challenges. With a platform, companies can centralize everything they need to be successful: device management, software, developer onboarding, ecosystem commerce and more.
Companies can do all of these things with a platform, but not all will. To be successful, manufacturers must be sure that their IoT platform strategy includes these three essential elements:
Up until recently, manufacturers were used to making one-time sales, usually physical products and perpetual licensing for the software that might go along with it. In the world of IoT, manufacturers must think beyond traditional ways of doing business. A platform strategy allows manufacturing companies to monetize the customer relationship long after the initial sale, but to do this they need powerful commerce functionalities, such as the ability to charge customers for subscriptions, single downloads and more, as well as the flexibility to change pricing as needed.
Ecosystems of software around core products are increasingly seen as vital to success, since they can provide a steady stream of new, innovative digital offerings to meet customer demand. For this reason, platforms that offer a robust developer portal are well-positioned to succeed. A portal should make developer onboarding as easy as possible, with streamlined integration and testing environments, as well as a CMS-like interface for uploading marketing content, such as product descriptions, data sheets, videos and more.
Flexibility to meet changing demands
In the digital economy, the speed of innovation and change is faster than ever before, which means that a platform strategy — and its underlying technology — must be flexible. A system that is API-addressable, modular and able to bridge the gap between new and legacy systems is critical. As Fujitsu explained in a recent report on digital transformation, “Businesses need to fail fast, fail forwards and make it cost efficient to do so. This means creating agile digital strategies and indeed business plans that can be easily and quickly adapted if a project is not progressing as expected.”
IoT is a multibillion-dollar industry that is changing the face of the entire manufacturing industry. To succeed, manufacturers must embrace this new digital reality and provide the connected devices, software, management tools and support that customers demand. A platform strategy is one of the most cost-effective ways to get there, and to get there quickly.
It seems as though 2018 is ending as soon as it began. But, upon reflection on the past 12 months, the year was quite eventful. We have seen the accelerated implementation of new technologies, including machine learning, AI and, of course, the internet of things. From consumers’ mass adoption of voice assistants and connected home devices to increased use of robotics and advanced sensors in the supply chain, it seems as though we are on the verge of a dramatic shift in the way we interact with technology.
As we look forward to 2019, it is once again time to look into the crystal ball and determine what the near future brings for IoT.
Connectivity will continue to march along
IDC estimated that IoT spending will experience a compound annual growth rate of 13.6% over the 2017-2022 time frame, resulting in a $1.2 trillion total spend in 2022. What does this mean? An increased amount of connectivity of digital signals will feed into all aspects of our businesses and supply chains. Look for our homes to continue to become more connected. We already have seen a proliferation of home assistants such as Apple’s HomePod, Google Home and Amazon Echo, to name a few. Not to be outdone, Facebook is pushing its Portal device to try and get some of its dedicated, connected hardware into our homes. Home connectivity is not limited to these devices; some companies are aiming to bring greater connectivity to more traditional home durables, as Samsung is doing with refrigerators. This is also prevalent in the connected car arena. As Apple and Android continue to jockey to make their connected hubs the standard entertainment center in vehicles, one thing is clear: No matter where we are, or what we are doing, we will never be not connected again.
IoT will get closer to our heart
IoT will not look to woo our love, but rather get closer to our physical being — literally touching our hearts. Just look at the latest version of Apple products, especially the new watches. These devices integrate technology that can monitor our health. 2019 will see a continued rise of consumer product companies seeking to bring greater connectivity to our physical being. Whether it is through smarter watches, connected fabrics in our clothing or digital pills, companies will seek to use the ability to connect what is happening with our bodies 24/7 into a market for well-being and health, expedited by the FDA’s approval of the first digital pill last year. Companies from Merck and Johnson & Johnson to Apple and Google will all be embarking on greater projects to bring greater connectivity closer to, and inside of, our bodies.
Major data breaches will stoke fears of a more connected world
We all have lived through major data breaches: Yahoo, Sony, Target, Equifax and most recently the Marriott Hotel chain. Some of these hacks, such as Target, can be traced to IoT as the hackers, in this case, accessed the data via the connected HVAC system. However, the public’s outrage did not focus on the “how,” but rather the “what.” As consumers become savvier about their connected world, look for 2019 to mark a pivot where a consumer’s data breach will be traced to all those connected devices and systems that permeate our world. The general media and consumers will realize how much of our world is already connected, likely inciting a knee-jerk reaction of how this connectivity makes us more vulnerable to hacks. This will prompt governments and the public to call for a greater emphasis on how we can harden these hacker targets.
Awareness of greater connectivity will also drive consumer expectations
As consumers, we are all accustomed to tracking our packages from point of origin to delivery. But that is simply the tip of the expectation iceberg. As consumers become more aware of the greater connectivity we have, with IoT they will start asking and demanding increased visibility. Can we see where that product came from? How was it manufactured? What journey did it take to get to me? In addition, an increased sensitivity to such factors as the items’ carbon footprint will incite questions about supply chains, asking for more information and increasing visibility via greater connectivity services. Brands and supply chains can no longer hide and must prioritize having the capability to provide this clarity.
We live in a digital world — that is no news bulletin. However, look for 2019 to be a pivotal year as consumers become savvier to what that connectivity actually means. This will result in increased pressure on the brands and global supply chains to use this digital connectivity to provide greater insights and understanding of products.
By all indicators, the talent shortage in the manufacturing space is at critical levels. Job openings continue to grow at double-digit rates, and it’s expected that nearly 2.6 million baby boomers will retire over the next 10 years, according to the fourth annual skills survey by Deloitte and The Manufacturing Institute.
In this landscape, finding the right talent is the number one competitive driver for manufacturing companies, according to the manufacturing executives surveyed for the report. Executives said for those with digital talent, skilled production and operational manager experience, skills shortages were “very high.” What’s more, the Deloitte report said that this difficulty will triple over the next three years.
But while the stakes and challenges are great, manufacturing is one of the industries leading the charge in adopting cutting-edge technologies to meet them.
It’s in the manufacturing space, in fact, that we are witnessing some of the most exciting and mature applications of IoT technologies, where phrases like edge computing, digital twins and augmented reality (AR) are out of the vaporware stage and into live deployments where they are delivering value. They’re being applied to everything from increasing overall equipment effectiveness to enhancing the roles of the people who work on the shop floor.
And one of the most exciting applications of these technologies is how manufacturing firms are combining them to deal with this skills shortage. They are using these technologies to evolve training strategies to fit both the needs of current workers and the way the next generation of workers will access relevant education and training.
Manufacturing firms are already using IoT and AR hardware to allow experienced manufacturing professionals to essentially document their processes as they conduct them, and new staff to consume that information through augmented reality. In this scenario, an experienced worker clad with an intelligent wearable collects the information about the process as she goes about it, without disruption to her daily routine. That rich knowledge is then visualized in an AR headset for the new worker, as he is led step by step through the process, with the instructions overlaid on the machine itself to guide work or maintenance.
The value of this combination of IoT and AR extends beyond strictly completing the process correctly to include all of the many factors that require years of experience to know how to complete it safely. IoT-enabled equipment can relay information on things like temperature through the AR experience, showing when a part is too hot to touch, or lending the worker crucial insight and indicators on failure points to provide predictive maintenance. AR headsets can even overlay caution tape around equipment, showing the worker areas in which it is safe to step and complete the process, and those that are not.
Thus, training and competency are imparted by experienced workers in a way that doesn’t take time away from their crucial work and, at the same time, is delivered in a relevant manner for the next generation of those who want to both learn and work. This builds competency faster, increases efficiency and further positions the plant to use this IoT and AR base for additional innovation.
This foundation lends itself to interesting integrations with data in the ERP systems. It enables the power of integrating bill of materials information in a way that is easily consumable in the augmented reality experience, or integrating information on inventory to show a worker that a certain part is not available. As a result, manufacturing facilities will drive even more efficiencies into their supply chain processes by optimizing the assets and the processes themselves.
In all, it’s an exciting time to be in the manufacturing space, where the challenges of growth and skills development are driving cutting-edge deployments of these cutting-edge technologies.