The continued growth of the internet of things and connected devices (Gartner predicts a total of 20.4 billion connected things in use worldwide by 2020) has resulted in an exponential growth in data — with a promise to make appliances smarter, processes more efficient and life, in general, easier. While this massive generation and collection of data certainly has its benefits, easy access to data also comes with increased vulnerabilities — unsecured IoT devices pose serious risks to personal and corporate information.
Securing IoT devices is challenging for several reasons. A rapidly increasing number of gadgets are becoming smart devices, and as manufacturers roll out new products more quickly, security can be given low priority as the focus is on time-to-market and return-on-investment metrics. A lack of awareness among consumers and businesses is also a major obstacle to security, with the convenience and cost-saving benefits of IoT tech appearing to outweigh the potential risks of data breaches or device hacking.
For years, consumers and businesses alike have been obsessed with securing computers and smartphones. But in reality, those devices are less at risk than more simplistic connected items. PCs and smartphones, while penetrable, benefit from over a decade’s worth of security developments and regular updates to guard against new threats. The requirement to protect sensitive data that was stored on and/or transmitted through PCs and smartphones was recognized early. However, certain connected devices, like a children’s toy that can be linked to an interactive smartphone or PC app, may not be equipped to deal with the same standard of threats because they are not necessarily associated with handling the same type of information.
An unsecure connected toy, though, poses an entirely different sort of danger than hacking into a computer. Malicious hackers could use these toys to gain access to the home’s internet or communicate with and even physically harm children. While it’s an unlikely scenario, it is nonetheless important for parents to be keenly aware of the security and data collection methods of their children’s favorite toys.
A blessing and a curse
The internet of things promises more freedom and functionality for businesses than ever before, with the technology being used in sectors like supply chain, transportation, logistics and healthcare. Eventually we could see almost every home device connected to the internet — with either explicit broadband connectivity or “behind the scenes” data collection used by enterprises as part of their managed services models, which can be incredibly valuable for businesses. Much like the children’s toy example, most IoT devices can serve as entry points into a home or corporate network, exposing families and companies to significant data breach risk. For industrial IoT, those entry points can provide hackers with access to private servers, which is problematic given 80% of the world’s data sits on private servers, mostly operated by businesses. And it’s not just corporate sensitive information at risk — many of these business servers contain sensitive personal data of consumers, which could be jeopardized in attacks and leave unwitting customers open to theft.
Data that lives natively on an IoT device is similarly vulnerable. For instance, the use of commercial drones has become prevalent in sectors like agriculture, military and construction, due to their versatile applications and access to real-time data. If the operators of these drones leave them unsecured, hackers can access them and install malware to strip out sensitive business data, including pictures and video.
While businesses cannot stop IoT attacks from happening, they can be proactive in mitigating threats to network security and protecting valuable data and IT systems. Emerging platforms like blockchain can help secure IoT devices by getting rid of a central authority in IoT networks. This would enable devices in a common group to issue alerts if asked to perform unusual tasks, thereby decreasing the capabilities of a hacker through a single entry point.
For their part, consumers must hold businesses to higher standards and approach any IoT-related purchase with a critical eye. They should conduct thorough research and verify that everything involved with their smart device purchases is legitimate — from the website reviews that inform their decisions to the retailers and manufacturers from which they buy. Luckily, organizations appear to be aware of the increasing threats to IoT security. A recent Gartner report indicates that worldwide IoT security spending will reach $1.5 billion in 2018 and will more than double to $3.1 billion by 2021.
While securing the internet of things is a monumental challenge, doing so will become increasingly important in preventing business and personal catastrophes. It will also allow companies to put the focus back on the primary intents of IoT — to collect and analyze more data to optimize processes, reduce costs, improve quality of service and enhance the customer experience.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
In the age of digital transformation, we’ve become accustomed to living our lives immersed in technology. We maintain relationships that follow us seamlessly from the physical world to online platforms and social media, whether we are communicating with old friends or new retail brands. Consider how many times a retailer “follows” you across multiple websites with merchandise recommendations based on a recent purchase or online search.
Of course, omnichannel scenarios are largely limited to a specific experience or company today. When it comes to coordinating actions or decisions across various vertical markets and use cases, humans are still very much involved. But given how far technology has come in a relatively short time, one might wonder if — or, perhaps, when — computing will become truly ambient and span these virtual siloes.
Consider, for example, the task of arranging a vacation, including hotel and car rental, flight reservations, pet boarding and scheduling time off work. Could a software system be enabled to drive various workflows to plan the entire vacation for me based on my specified interests and personal profile? Yes, this can happen … with the right help.
On the road to tomorrow
Many industries are already seeing how pervasive connectivity can be used to benefit business processes through the industrial IoT, which is growing at an annual rate of nearly 25%. The ability to predict equipment failure based on intelligent sensors and algorithms enables significant improvements in inventory management, cost control and resource availability, not to mention the ability to increase safety by preventing failures. The integration of data, analysis, intelligence, process integration and reporting is key to implementing IoT systems. Yet, human intervention and decisions are still required today. Could these diverse systems intelligently communicate without human intervention?
If we envision the next step in IIoT evolution, we can imagine a scenario such as the intersection of automotive IoT and smart city functionality, with a tremendous amount of data coming from smart streets and parking lots, drivers, as well as the vehicles themselves. Car manufacturers could learn from operational data and driving patterns, while municipalities could benefit from information related to traffic patterns, effects of emissions, pedestrian and driver safety, and emergency response situations.
At Aricent, we are actively engaged in a number of vertical markets to enable IoT systems for specific use cases. We see many use cases that are driving IoT development and 5G adoption, such as autonomous driving, smart grids, intelligent retail or healthcare. However, we have yet to see the industry working together to merge systems in an intelligent fashion in order to provide real value across vertical segments.
The key to achieving this vision will be readily available access to relevant data, and a method of translating this information to be understood across various systems. The ability to provide layered data architectures that are rapidly accessible across intelligent systems is paramount; and to that end, we are focused on developing artificial intelligence and machine learning technologies with associated services for vertically specific learning.
Are we there yet?
Essentially, we have the technology to do this today. Emerging 5G networks and other networking technology will enable these systems to scale across many millions of devices that will exist in an operational scenario. Business analysts can translate the current process environment into the next-generation automated workflow. However, enterprises first need to understand the value of integrating vertical systems in order to drive implementation of these scenarios and realize the vision of ambient computing.
Ambient computing allows enterprises to simultaneously use many sources of data, both internally and externally sourced, to improve customer experience, competitiveness, market relevance and product excellence. For example, a hotel chain may be interested in usage variables in order to maximize its appeal to particular consumer groups or business travelers. That data might be derived from rental information, events, sports activities and other consumer data associated with a specific geography or demographic. Collecting and analyzing broadly sourced information allows for more agile and responsive business processes, leading to greater returns.
Digital design plays an important role in all of this. Creating an experience, workflow, usage and integration patterns and, most importantly, a conceptual journey of where the enterprise needs to go in the next five years is central to design-focused engineering. Creating top-down plans that include opportunity discovery and conceptual design can drive the required technology, data and workflows needed for ambient computing systems.
Full speed ahead
As we move toward these more complex and data-rich services, AI and machine learning technologies will enable greater autonomy to identify usage patterns and variables, either as the result of direct information or inferred decisions. Machine learning intelligence can then directly update algorithms and data, thereby improving customer experiences and product offerings. In this way, we create a continuous improvement process to search for relevant information and trends across the entire ecosystem, while minimizing human interaction.
With a better understanding of how to integrate ambient computing into business processes and the back office, enterprises can enable access to real-time and relevant data across industries and vertical markets. And with a little help from digital design engineering, a world of business opportunities will be realized in the very near 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.
As IoT devices continue to be adopted by organizations in record numbers, two things have become clear. First, far too many of these devices do not include adequate security, meaning they can be easily compromised to serve as slaves in IoT-based botnets, act as a conduit for the spread of malware, or even become an attack vector to infiltrate networks. Attacks such as Stuxnet, Mirai and BrickerBot all had a strong IoT component and were able to cause widespread harm. But they are just the most visible players in an IoT-based cybercrime trend that has literally thousands of variants.
Second, most organizations have no efficient way to identify, inventory or track these devices. And one of the first rules of security is that you can’t protect — or protect yourself against — what you can’t see. The volume of IoT devices, applications and traffic being added to the network, the speed at which they are being implemented and the ease with which end users can connect these is unprecedented. Which means that most IT teams cannot tell you how many IoT devices are currently connected to their network, let alone where they are located or what resources they have access to. Even organizations with aggressive BYOD policies in place have found that the explosion of IoT in their networks has quickly overwhelmed their ability to identify and track these devices.
Because of this two-pronged threat — risk plus opportunity — securing IoT resources from compromise while simultaneously defending their network from attack using exploited IoT devices has become a critical security priority for many organizations. The challenge is that IoT devices play an increasingly crucial role in helping organizations compete in today’s digital marketplace. Providing adequate protections without interrupting essential business operations is beyond the scope of many traditional security devices, and instead requires an integrated security approach that combines high performance with broad and consistent visibility and centralized control.
The critical role of access control
The first place to start in establishing an effective IoT security strategy is by ensuring that you are able to see and track every device on the network. Issues from patching to monitoring to quarantining all start with establishing visibility from the moment a device touches the network. Access control technologies need to be able to automatically recognize IoT devices, determine if they have been compromised and then provide controlled access based on factors such as the type of device, whether or not it is user-based and, if so, the role of the user. And they need to be able to do this at digital speeds.
Another access control factor to consider is location. Access control devices need to be able to determine whether an IoT device is connecting remotely and, if not, where in the network it is logging in from. Different access may be required depending on whether a device is connecting remotely, or even from the lobby, a conference room, a secured lab or a warehouse facility. Location-based access policies are especially relevant for organizations with branch offices or an SD-WAN system in place. Remote access control technologies need to be able to seamlessly synchronize with network and security controls to ensure seamless policy enforcement across the distributed network.
Access control and network segmentation
Once a device has been identified and authenticated, the access control system needs to assign it to a specific network segment automatically. Ideally, the network segments that IoT devices are attached to have already been isolated from the production network. Keeping IoT devices and traffic isolated helps prevent exposing critical internal resources to potential threats and attack vectors. Internal segmentation firewalls, for example, can then monitor and inspect IoT applications and traffic to identify and prevent potentially compromised devices and the lateral spread of malware, while edge firewalls can block compromised devices from communicating with an external command-and-control server.
Access control systems also need to be able to seamlessly hand off device information to other security, networking and management devices. IoT device intelligence, including the applications they are running and the data they are providing and collecting, all need to be collected and correlated with other network resources. These tools need to do things like establish and monitor IoT traffic baselines so that rogue devices can be easily tracked and monitored using techniques such as behavioral analysis.
Access control and quarantining
Once a rogue device has been identified, deep integration between security and network technologies play a critical role in promptly addressing that threat. The detection of unusual or malicious traffic coming from an IoT device, regardless of the security tool that finds it, needs to automatically trigger a coordinated response, including redirecting traffic, closing down paths of communication and using the access control technology to isolate it. One way to do this is to simply reassign the device to a quarantined network segment where it can be staged for evaluation, remediation or removal.
IoT devices are part of today’s new normal as they play a critical role in the radical digital transformation of business, and our society in general. They are not only essential components of today’s digital markets, however, but for cybercriminal activities as well. Protecting organizations from the risk of compromised IoT devices without compromising business objectives is increasingly challenging not only due to the volume of devices and related traffic being connected to today’s networks and their relative insecurity, but also because defensible network perimeters have eroded and skilled security professionals are increasingly difficult to find.
Unfortunately, given the speed of digital business today, a compromised IoT device that takes down even a small piece of your infrastructure can have significant financial and reputational consequences. What organizations need is an automated and integrated security framework that secures network access, monitors traffic and behaviors, and can implement a coordinated response when a threat is detected anywhere across the distributed network. Access control systems play a critical role in such an approach, ensuring that visibility is established, access controls are universally applied, device intelligence is shared and rogue devices can be quickly removed with minimal impact to critical business transactions and workflows.
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.
Technical terms are used extensively — and sometimes misused — when it comes to IoT devices and the technologies they are rapidly absorbing. One such term is microelectronics, spoken and written about since the day the transistor was invented.
Today, microelectronics takes on another name — namely wire bonding, which again isn’t a new technology since semiconductor manufacturing has been using it since day one. What is new is that wire bonding has landed right squarely on IoT printed circuit boards and all other small PCBs.
Why, you ask, is wire bonding necessary for IoT PCBs? Here’s why: IoT circuitry is remarkably tiny in size. Plus, IoT devices are increasing in functionality, meaning even more circuitry is demanded on those small areas. The IoT PCB is extremely small, so small that conventional device packaging taking up valuable space has to be eliminated to make room for more and more circuitry to be placed on that PCB.
The bottom line is a bare, packageless chip is now placed on the board and connected by very thin wires going from the chip itself and bonded directly on the substrate or PCB. We’re talking about infinitesimally thin wiring, hundreds of times thinner than the conventional soldering wire that hobbyists use.
Wiring going into your IoT PCB may be gold, aluminum, copper or some other material. Wire thickness can be one, two, three, four, five or six mils. A mil equals one-thousandth of an inch or 0.001 inch. Typically, however, thickness of the wire used is one to three mils.
Wire bonding has two categories that go under that term: wedge and ball bonding, each distinctively different. Each requires separate and different sets of systems and temperatures for wire bonding operations. For wedge bonding, either aluminum or gold are typically used. For ball bonding, gold wiring is typically used. Wedge and ball bonding also differ in the way the wire bond is made on the chip side. The bond is made resembling a gold ball, while the end of the wire is in a wedge-shape for wedge bonding.
Inspection and verification are two critical aspects of precise IoT PCB wire bonding. The electronics manufacturing services (EMS) provider must use the correct inspection equipment. This wire bonding process requires that wire strength be accurately measured. Also, the wire’s loop radius between chip and board connections must be measured and verified. A high-end inspection system captures those minute connections via high-resolution video images, and then real-time measurement is performed.
While IoT wire bonding may not be rocket science, this major IoT PCB assembly process is critical and demands top expertise. So here, the EMS provider performing your IoT PCB assembly must have a keen knowledge, experience and advanced systems on the assembly floor to produce a successful product. He must be savvy enough to be able to assemble surface-mount packaged components along with wire-bonded devices on the same PCB.
Therefore, the IoT device OEM must closely partner with its EMS provider to assure the correct wiring is not only designated at the design and layout stages, but also accurately used in assembly and manufacturing. Further, a word of caution: The OEM must also keep in mind that many EMS providers may be latecomers as far as adopting wire bonding, and/or they may try to convince you they have the knowhow and capability and then farm it out to unproven contractors.
One has to be wary simply because they focus solely on earlier and conventional PCB technologies and not wire bonding. To assure you’re successful with your IoT product success, it’s important to first carefully vet potential EMS providers and then discuss your IoT assembly requirements, including their knowledge of IoT wire bonding.
It has been argued that the industrial internet of things is one of the most groundbreaking developments in the history of manufacturing operations. In fact, according to a recent report, the global IIoT market is expected to reach approximately $232.15 billion by 2023, up from $145.81 billion in 2017.
Adding sensors to equipment and systems is not new to the industry, but recent advances in analytics capabilities and decreasing sensor costs have empowered many manufacturers to use the advantages of IIoT, making improvements in productivity and quality without breaking the bank.
While predictive analytics in particular has been used to help avoid machine failure and downtime, manufacturers must also be able to stream data from IIoT-connected devices and equipment in real time to not only help improve productivity, operational efficiencies and reduce costs, but also gain important insights that help shape current and future business decisions and assess risks.
Overcoming analytics barriers for IIoT
IIoT is characterized by high sensor density at a site or at the edge (a typical IIoT architecture has thousands of sensors), and with IIoT on the rise, the volume of data coming from IIoT-connected devices and equipment is exploding. With thousands of sensors at sites generating rapid measurements at sub-second intervals, data volumes can quickly reach terabytes of data per day.
The large volume of sensor data can be overwhelming for manufacturers, and most sensor data has a limited time period before it loses value, necessitating real-time analysis to capture business value that can be immediately acted on. This requires an end-to-end IIoT architecture that can support real-time streaming analytics and scale to handle large volumes of data.
Benefits of real-time analytics in IIoT
Today’s organizations across industries need actionable insights faster than ever in order to compete, meet customer expectations, reduce risks and capitalize on time-sensitive opportunities. And IIoT is no exception. By immediately connecting insights with action using real-time analytics, manufacturers can improve productivity, operational efficiencies and reduce costs. They can also avoid losing important insights that help shape immediate and future business and financial decisions, and assess risks in real time.
Some of the industry’s biggest players rely on real-time analytics every day. CGI has a smart metering IIoT system with over 50 million meters (electric, water and gas) in the UK that use an in-memory database management system to process large volumes of continuous messages sent by a network of electricity and gas suppliers. The system retrieves information from the smart meters, as well as provides real-time analytics for downstream decision making. Similarly, Mitsubishi Electric utilizes real-time analytics through speed data ingestion for swift analysis and rapid decision-making for 6 million smart meters deployed in Hokkaido and Shikoku provinces in Japan.
As the amount of data generated by IIoT devices continues to climb, and technological advancements directly affecting the industry, such as 5G and artificial intelligence, continue to roll out, having a nimble, end-to-end IIoT architecture that can both support real-time streaming analytics and scale to handle large volumes of data will only become more critical. At the end of the day, not only do real-time analytics help manufactures prevent unplanned production downtime, optimize material flow and improve product design, but also execute at the speed and capacity needed to stay ahead in the today’s digital economy.
The internet of things has evolved drastically over the past five years and there is no sign of it slowing down. While excitement over connected devices is more measured than it was around 2013, the technology is maturing and firms are getting significant results from IoT investments. Gartner predicts there will be more than 20 billion connected devices by 2020 and more than 65% of enterprises will adopt IoT products. Others say it can be as many as 1 trillion devices by 2035 and $5 trillion in market value.
To start thinking about using IoT in your company, from a product perspective, it’s important to consider the types of new data that could provide the most value, as well as how to securely store, manage and analyze that data to gain a competitive edge.
The unique value of IoT data is that it reveals important consumer insights in the context of real-time situations. It largely takes the consumer out of the equation, using artificial intelligence and automation to either fix problems people don’t know they have or avoid problems in the first place. And that’s an amazing customer experience. But that also doesn’t mean every product should be IoT.
Here are five things to consider before turning your product into an IoT device:
- Have you put proper device management protocols in place? Adding intelligence to your product by turning it into an IoT device brings with it the complexity of both the creation and the ongoing operation maintenance of the device. How will you send bug fixes, security patches and software updates to the device? Are you managing that IoT device or sending the necessary patch/update?
- Connectivity. Have you thought about how you are going to connect and communicate with the device? Wi-Fi is the most common connectivity option. However, there are several other options, like Bluetooth and long-range connectivity technologies. All options have advantages and disadvantages, so it is important to factor in the best way to connect to the internet at the planning stage of your IoT device. In particular, make sure to consider how your device will keep retaining data and being useful when it temporarily loses connectivity to the internet.
- Increase of data complexity and scale. Integrating IoT scale can make things complex from an IT perspective. As an example, let’s consider a washing machine. If you are collecting data from multiple sensors every minute while each washing machine is on, you will quickly amass an extraordinary amount of data — especially considering the variety of models you sell multiplied by the different sizes and variety of data that your systems will collect. Make sure that you’ve considered exactly the type, size and frequency of data collection you need. Also, make sure that you have a single integrated data collection and storage system that will allow you to take advantage of all this data in one place — for example, with a data lake.
- Is the information you are collecting being used and integrated to your business processes? IoT device data provides an immense opportunity to improve your customer’s overall experience. Let’s go back to the washing machine example — those signals can be analyzed and communicated to the proper department to automatically schedule a water pump replacement before it becomes a problem. This enhancement in customer support can go a long way to improving the lifetime value of your products to your customers. Additionally, data can be used to improve your sales and marketing efforts and possibly open opportunities for new lines of business. Today, more than ever, marketing integrates with product, customer success and acquisition retention efforts. If marketing communication is not part of your IoT strategy, it will not be successful.
- Does the IoT element add value to the end user? This may be the most important but often overlooked consideration. You want to make sure the device’s connectivity isn’t just for your benefit, but provides significant new value to the end user. Otherwise, customers aren’t going to be responsive to it and you’ll have a failed product on your hands. A great example of a successful IoT initiative is when Brita launched its self-reordering water filter program that automatically orders a new filter for the customer just before the last one stops working.
P.S. A great tool to successfully manage your IoT products is with Daniel Elizalde’s IoT Product Landscape — a framework to make sure you consider all the different possible areas for IoT product development and management.
Every company is obsessed with data. Whether it’s a security team monitoring logs or a retail grocer checking temperatures of a trailer filled with fresh produce to ensure its freshness and safety, companies rely on data to make better decisions that improve their business. Effective data capture helps leaders gain a clear view into their operations. However, data collection is only as valuable as the usable insights that it provides. Incomplete or inaccurate data capture — or collecting the wrong data — leads to bad analysis and poor decision-making. This is made worse when data collection is a manual or ad-hoc process that is error-prone and increases costs. Adoption of IoT technology can make a huge difference as IoT sensors, compared to low-tech approaches, do a far better job of autonomously providing the level of data and insight needed to inform proactive decision-making and course correct inefficiencies.
Let’s consider the fresh food industry for example. Food waste is a significant issue in the United States. The NRDC’s recent “Wasted” report states that up to 40% of the food produced in the U.S. goes to waste, and this costs us an estimated $218 billion per year. Much of this is due to challenges within the supply chain where food industry leaders don’t have adequate data and insights for effective decision-making. As a result, about a third of fresh food spoils prematurely, driving up costs for growers, shippers and retailers.
Getting to the root of the issue
To see the fresh food supply chain in action, we can take a deeper look into the significant temperature variations that fresh produce or proteins can experience during processing or in trailers transporting the food to the retailers. Significant temperature variations at the pallet level can result in premature spoilage and food waste. For example, fresh berries should be kept at 34 degrees Fahrenheit throughout shipment from the supplier to the retailer. Twenty-six pallets may be loaded into a trailer that is at an optimal temperature of 34 degrees Fahrenheit. Though parts of the trailer may be at the optimal temperature, it’s the pallets of berries that need to be monitored because studies have shown that pallets in a single trailer load may experience substantial temperature variation that leads to premature spoilage. Pallets near the refrigeration system may be at 34 degrees Fahrenheit, however pallets at the back of the trailer may be at 40 degrees Fahrenheit. In one study, five of 26 pallets (that’s nearly 20%!) experienced temperature variations that had significant impact on shelf-life. Additionally, one pallet was at 46 degrees and lost almost 10 days of shelf-life, meaning it was essentially spoiling as it was delivered to the retailer, leading to waste and lost profits.
The old way and the new way
For decades, across the fresh food supply chain, we have tried to solve these waste and data challenges by using low-tech temperature collection devices, like USB data loggers, to collect trailer-level temperatures. These are often expensive single-use devices and are operationally cumbersome, even prohibitive, to deploy at the pallet-level — but, as mentioned, when it comes to reducing waste, it’s at the pallet level where the valuable data resides. As a result, for years we’ve been collecting the wrong data about the temperature of the trailer, which doesn’t provide accurate insight into the condition or freshness of the pallets of product in the trailer. These antiquated approaches paint an inaccurate picture that is insufficient for making informed decisions that solve the food waste problem as demonstrated by the fact that, for decades, we haven’t reduced waste.
Autonomous IoT sensors that monitor at the pallet level, where the temperature variations occur, do address this insight gap into data capture of food freshness throughout the supply chain. Autonomous IoT sensors don’t require a worker to plug a USB drive into a computer and download and email a spreadsheet for each pallet. Instead they can be read autonomously, and the data can be sent directly to cloud-based applications for analytics and decision-making. IoT implemented at the pallet level provides deeper insights into the product in a trailer that may have experienced a temperature excursion during transit (such as hitting 46 degrees instead of the desired 34 degrees), and therefore may spoil well before its best-by date. Stakeholders can use this data to proactively manage the supply chain and implement techniques, such as intelligent pallet routing, to reduce waste.
Because IoT sensors collect data autonomously and are less expensive than legacy data loggers, they are cost-effective and are a viable way to optimize the fresh food supply chain. They stay with the product as it makes its way through the supply chain, and the sensors collect the right data at the right time throughout the product’s journey. This complete view delivers accurate insight into the product’s condition that old-style supply chain monitoring technologies are unable to provide. IoT sensors combined with cloud-based analytics quickly deliver the granular data sets that enable business leaders and operational staff to take corrective action, based on real-time product condition rather than incomplete or inaccurate data, such as the temperature of a trailer during one moment in time.
Like the NRDC study explained, data collection is important in order to have insight into the operations of a business, especially with an industry as time- and cost-sensitive as fresh food. However, data collection alone isn’t enough. Capturing the right data is critical to giving transparent and accurate insight into the effectiveness and inefficiencies across the supply chain. Implementation of cost-effective IoT sensors into operations helps draw out insights, properly evaluate the health of a business and make appropriate adjustments as needed, before an incomplete or inaccurate decision spoils business results.
The connected plant is a crucial component of the internet of energy, but what exactly does it entail? A connected plant means linking physical assets or machinery under management with operators responsible for their production, efficiency, security and safety — in sum, utilizing modern technologies to improve value and collaboration.
Right now, however, the connected plant is mixed in buzzword stew with little cohesive strategy. There is the cloud, the fog, wearables, drones, IoT, IIoT, 3D imaging, geofencing, wireless, apps, smart tags and other technology trends that may or may not be beneficial to a company’s specific needs. Plants may adopt new technologies based on mandates, but lack a cohesive strategy to accompany the digital transformation and see the true value of the tech.
So where does artificial intelligence fit into this litany of potential technologies? Honestly, in all of it.
Drones, artificial intelligence and wind production
One mature area widely using artificial intelligence is image recognition. Currently utilized for lane detection in cars, facial recognition and tagging on Facebook, and monitoring the health of crops via drone imagery, image recognition is also being used in identifying blade damage on a wind turbine.
Drones are poised to deliver significant impact for wind maintenance and safety. According to Navigant Research, the “cumulative global revenue for wind turbine UAV sales and inspection services is expected to reach nearly $6 billion by 2024.” This is a huge opportunity and the use of artificial intelligence is at the forefront.
Only 39% of executives say their organization understand the risks and opportunities of important digital trends.
— Bain Brief, ‘Digital Strategy for Utilities‘
Let’s explore an example of blade inspection via digital imaging and drones. High speed, high-resolution cameras mounted on drones capture several thousand images of the turbine. The captured images are input into a convolutional neural network, a type of deep learning approach, to train and automatically recognize failures without human intervention. Given enough images, not only is identification possible, but the system starts classifying the types of failures and predicting when required maintenance is necessary.
Drones utilize geofencing to fly to the same location and perform the same inspection routine over and over. An operator never needs to leave his truck or climb a tower, and consistent results void of human inconsistencies are analyzed by algorithms. The software raises alarms based on images from the drones, and skilled operators now apply their expertise to diagnose the nuances of the degradation.
Using drones reduces operation and maintenance costs in a number of ways. Drones boost worker safety because they can fly in potentially dangerous areas, reduce vehicle fuel costs and have a scant environmental impact.
Wearables: The new source of predictive data
The human body is by far the most critical asset found in a plant, yet there are still nearly 300,000 people who die from occupational accidents each year.
The use of wearables is merging human safety with artificial intelligence to provide predictive or preventive maintenance on humans. For example, in a recent pilot study by IBM and North Star BlueScope Steel, plant managers can observe heat stress and exertion in users by monitoring sources of data like body temperature, heart rate and activity levels.
Similarly, mining company Rio Tinto is piloting SmartCap, a device that looks similar to a baseball cap and conducts regular EEG tests on the wearer. It measures worker fatigue, for example, when truck drivers working long shifts are reaching sleep exhaustion levels.
In both examples the technologies produce data, only now the information isn’t coming from sensor data on a mechanical machine, but from the ultimate machine: the human body. With data comes the capability to perform analytics from simple threshold analysis to complex machine learning approaches. Algorithms start learning normal, or baseline, behavior as well as identifying anomalistic body operating conditions. These wearable systems can then alert management to critical issues or impending dangers.
“Nearly 300,000 people still die from occupational accidents each year.”
While safety is of utmost importance, wearables also boost employee efficiency. Technologies like smart hard hats and smart glasses provide real-time information capabilities to augment workers’ knowledge with a hands-free interface. SparkCognition, for example, has shown the worker of the future looking something like this:
- An operator scans the connected plant and is directed via visual cues to a failing asset (a pump in our demonstration).
- Once identified, the operator utilizes a pop-up, hands-free interface to visualize real-time operating conditions and historical trends.
- The operator can then display maintenance records and work orders previously performed on the pump and load detailed schematics about the asset, all viewed on the virtual interface.
- Finally, if the operator is still unable to make a clear determination on the issue they can “phone a friend” and get a direct line to the pump manufacturer’s support portal where experts help resolve the issue in real time.
What used to take days to fix and diagnose can now be done in minutes. But this technology comes at a cost. When collecting human biometrics, it’s extremely important to ensure the privacy and security of the information being collected about personnel. Guidance for responsible utilization needs to be transparent at a corporate level. Additionally, wearables generate massive amounts of new data. Corporate IT systems, including wireless infrastructures, at a connected plant will most certainly need to be modernized and scoped appropriately for efficient use.
Business justification and strategy
As enticing as new technology like smart glasses, SmartCaps and intelligent pumps can be, the ROI is what justifies the correct approach. Let’s look at some examples. As highlighted in Figure 2, real savings are achieved by providing workers a hands-free environment where information is consistently available to them in real time.
The intelligent pump example is a use case for mobile service workers. The savings captured by transforming a worker’s job out in the field to an assisted, remote operator are demonstrated in Figure 3. With remotely assisted, real-time predictive maintenance, service personnel can be at least two to three times more productive than their traditional counterparts.
From drones to wearables and every application in between, the connected plant will become the new norm in the near future. Technology will play a major part as operators find novel ways to improve the bottom line with a shrinking workforce. Advances in hardware and sensor technologies will drive unforeseen gains. However, the big step change in the internet of energy will occur with the use of artificial intelligence to reduce costs, maximize efficiency and, most importantly, keep workers safe.
M&A update: 2018 year to date
Deal volume as of June 30, 2018 is up, compared to the same period in 2017. For 2018, we have seen a total of 78 transactions close with another 22 announced. As of June 30, 2017, there had only been 45 transactions completed, representing an increase of 73.3% from 2017 to 2018. This puts 2018 IoT M&A on track to get close to or outpace 2017, which had 123 transactions close in the entire year. It should be noted, in addition, that deal volume so far in 2018 exceeds each of the five full years from 2010 to 2015.
Total disclosed transaction value of $1.1 billion in 2018 through June 30 is about 50% lower than the $2.3 billion during the same time in 2017 — a period which included the acquisition of ServiceMax, a cloud-based asset-tracking and field management company, by GE Digital for $915 million, and the acquisition of Comptel Corp., a data fabric and advanced IoT analytics company, by Nokia for $373 million.
So far in 2018, there have not been any deals closed over the $1 billion mark. However, 2018 could be a record year for IoT M&A in terms of dollar volume, with the closing of the acquisition of NXP Semiconductors by Qualcomm possible this year and expected to top $44 billion. With eight of the required nine global regulatory approvals already achieved, Qualcomm is waiting for approval from China before the acquisition can be finalized. This would represent the largest transaction in terms of IoT M&A; the previous largest transaction was Softbank’s 2016 $31 billion acquisition of Arm Holdings.
That said, there are a few other deals currently pending that are above $1 billion in transaction value, which include the $2 billion acquisition of GlobalLogic Inc. by Canada Pension Plan Investment Board. GlobalLogic provides IoT product development services, as well as adaption of existing products and services for a digital landscape.
The biggest closed deals in 2018 year-to-date are 3i Infrastructure’s acquisition of Wireless Infrastructure Group for $249 million and AVX Corporation’s $150 million acquisition of Ethertronics Inc and AU Optronics Corp.’s acquisition of Qisda Corporation for $115 million.
Private placement update
Private placements are also up in terms of transaction volume compared with the same period in 2017. There have been 150 completed transactions as of June 30, 2018 compared to 78 transactions completed by the same time in 2017, representing an increase of 92% year over year.
Dollar volume has also increased from $430 million by June 30, 2017 to $1.6 billion by June 30, 2018. It is noteworthy that the average deal size in 2017 was about $5.5 million and the average deal size in 2018 has doubled to about $10.7 million.
The closed transactions leading the higher dollar volume consist of the December 28, 2017 close of Huaqin Telecom Technology and the May 7, 2018 close of Mesosphere. Huaqin specializes in one-stop services from market research, product design and R&D to manufacturing of IoT products, like wearable devices, smart home products, AR/VR devices and auto electronics. The lead investors were Intel Capital and Hua Capital, raising $133 million. In 2018, Mesosphere leads the closed transactions having raised $125 million with T. Rowe Price and Koch Disruptive Technology as the lead investors. Mesosphere specializes in hybrid cloud infrastructure to power IoT and data-driven applications.
Sometimes I get nostalgic about overhead projectors.
The teacher would turn off the lights, turn on the projector, take out a transparency and a dry-erase marker and begin a lecture. The overhead projector was simple technology that was an essential part of the classroom through the 1990s. Fun fact: 3M, inventor of Scotch Tape and Post-it Notes, was one of the biggest sellers of overhead projectors.
3M stopped selling overhead projectors in 2015 after more than 50 years. They were lapped by a wave of more sophisticated digital devices that ushered in a new era of creativity and collaboration.
The explosion of internet-connected devices, though, has put a strain on business’ technology infrastructure. Tech managers face challenges in dealing with the avalanche of data, having enough bandwidth, managing a multitude of applications and making sure their networks are secure, reliable and scalable. These internet-connected devices need to be centrally monitored and managed in order to deploy them in a scalable way.
To manage these issues, companies — from startups to multinationals — are increasingly turning to the cloud. As Amazon’s Jeff Bezos likes to say, the cloud is “providing all of us with unbelievable opportunities to reinvent our business, add new customer experiences, redeploy capital to fuel growth, increase security and do all of this so much faster than before.”
As cloud computing keeps growing and growing, every company selling equipment to companies to put in their data centers is feeling pressure to adapt. Moving your management infrastructure to the cloud greatly simplifies application management, network design and deployment, as well as data collection and retention. Even seemingly simple devices like AV, lighting and HVAC components benefit from management in the cloud.
Deploy and manage
A cloud application provides tech managers with a centralized tool that enables them to install and manage thousands of devices in the same amount of time as it would to manage just one. Installation time can be reduced by up to 90% because devices can be simultaneously configured as a group before they are shipped to separate locations to be plugged in.
Cloud-based systems are also more efficient to manage when scaling beyond a handful of devices. Rather than having to manage multiple individual devices, each with its own firmware updates and critical security patches, the entire system is managed and updated remotely through a single portal.
Security fixes are installed in minutes, not days. Devices can be moved or replaced, and all the settings are automatically uploaded. Dispatching a programmer to the site? A thing of the past.
With the virtualized network, system administrators can check all the equipment at a glance, even on the go. Problems are quickly detected and can be resolved remotely by the help desk, leading to fewer disruptions. The central monitoring makes conference rooms and boardrooms more reliable and efficient because the devices are always working. That gives people using the rooms peace of mind.
Measure and analyze
With so many devices transmitting data today, just about everything can be measured. How often is the room being used? How often is the video conferencing being used and for how long? A cloud application puts all the data at your fingertips. How do you know if you made a good spending decision if you don’t know how much your equipment is being used? When you can track that, you can get a better idea of whether you’re making the right decisions. This kind of intelligence also is a good planning tool. It allows companies to design spaces and technology around the people that use them.
As we all know, the increasing sophistication of our workplaces has also created more opportunities for chaos. Your laptop won’t connect to Wi-Fi when it’s not docked. The presentation on your iPad won’t sync with the flat-screen TV in the conference room. The video on your videoconference is fuzzy. And the audio is a few seconds behind.
The internet of things and cloud computing can create order out of the chaos. Over three-quarters (78%) of enterprises say the introduction of IoT into the workplace has improved the effectiveness of their IT team, while 75% find it has increased profitability. The creation of a smart office means integrating individual elements, collecting data from them and repurposing it to make the working space — and the people in it — more productive.