The internet of things is expanding its reach! Early last year, Gartner calculated that around 8.4 billion IoT devices were in use in 2017, up from 31% in 2016. It also noted that this number is set to reach 20.4 billion by 2020. In terms of spending, IDC predicted that total expenditures will hit $1 trillion in 2020 and $1.1 trillion in 2021. It’s clear that now’s the time to start monetizing your business for IoT, that is, if you haven’t already begun. But what steps should you take to get there?
1. Have a firm grasp of your business model — and nail the fundamentals
Ultimately, everyone wants to drive revenue and create profitable IoT offerings. That will come from new digital business models and operational efficiencies. BUT, the best business model won’t help when you don’t get the basics right:
- Ship a secure product that’s free of vulnerabilities. Then, monitor and manage vulnerabilities during the device lifecycle. Literally every IoT offering uses open source components, but only a few suppliers manage them diligently.
- Implement a licensing and monetization technology that enables you to actualize new business models, deliver software and updates to devices, capture device and usage insights, and manage compliance.
2. Make it customizable
Use the power of software to differentiate devices and activate premium features for customers at the push of a button. Flexible activation of features is the key that differentiates a smart device from a dumb one. Your customers will appreciate the flexibility and the accelerated time to value.
3. Use the value of data and insight
A successful digital business model is based on insight. When thinking of IoT and data, many just think of the process data that comes back from sensors. But there’s more: Which device is using what software? And which customer is using what and how much? By aggregating device, software, customer and usage data, you build the groundwork for strategic decisions and future business success. You can proactively react on status changes on devices and serve your customers better. And, most importantly, you can also make better decisions for the future because you know exactly how your products are being used.
4. Monetize the full IoT stack while keeping your customers top of mind
Start monetizing the value of software and be smart about it. Build packages that can be consumed as a service, rather than monetizing components of your IoT offering differently or, in some cases, not at all. One thing’s for sure — recurring revenue models like subscription will outpace the more traditional models. With this trend, a close customer relationship is more important than ever. Know what your customers are using, measure the value they’re getting from it and act at the right time when you identify growth potential or attrition risk.
All you need to embark on this journey is a software monetization platform. So, what are you waiting for?
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 today’s IoT world, two things are abundantly clear. First, with the number of IoT devices expected to grow dramatically in the coming years — up to 31 billion in 2018 alone — the potential business opportunity is extraordinary. Second, only the fittest of businesses will survive.
Want proof? Consider the sobering tale of one trucking company telemetry firm that made the decision to employ IoT modules in its day-to-day fleet activities. The company exhaustively tested its system prior to implementation, but did so under the assumption that the cloud server would always be present. Once in operation, the cloud server failed. Within 24 hours, the IoT modules had consumed so much cellular airtime trying to find the server that the company couldn’t afford to pay its network bill at the end of the month and was forced to close.
At every step in the IoT product lifecycle, missteps like these can occur that hamper a business’s ability to compete effectively in the marketplace or derail its efforts altogether. One misstep product makers commonly make is underestimating the true cost of their IoT device. It’s a mistake with profound consequences on a business’s brand, image and profitability.
Failures drive true device cost
Many think the cost of an IoT device is the price a user pays to own it. It’s not. Its true cost also includes the price of any maintenance and to find and fix errors and failures. If the IoT device is involved with processes of great value, as is the case with mission-critical IoT applications, then the cost of those errors and failures can be greater than the value of the device itself. A device selling for $10 could easily end up costing the product maker $1,000. That’s not a sustainable business model under any circumstance.
Think of it this way: If a smartphone fails, the impact may affect one or two users. If mission-critical IoT devices fail, the impact may be much greater since those devices are often embedded in large, complex systems or in hard-to-reach locations.
Just imagine a medical alarm in an elderly patient that fails to operate on the very day it’s needed to save the patient’s life. And what if there is a recall of an implanted medical device that fails? It might only require a doctor’s visit for a firmware update, but the faulty hardware could also have to be surgically removed and replaced. What about a failure in an IoT sensor that monitors temperature? It might cause a boiler to overheat, which is costly enough, but what if that sensor is used in an industrial cooler and its failure allows a dangerously high temperature that causes food contamination? The resulting costs could be substantial.
Reliability is priority one
Fixing these types of faults requires intervention from a technician. If the technician has to climb a ladder, go down an access hole or venture into a remote location or harsh environment, that fix can easily equate to 100s of dollars or more. For the product maker, these unforeseen expenses drive up the true cost of an IoT device, making it imperative that those devices be as reliable as possible.
How does a product maker ensure their IoT devices are reliable? In a smartphone, users play a role by serving as unpaid technicians (see the Figure). They dutifully reboot their devices when they fail to connect to Wi-Fi. They download software patches to fix problematic updates. And they replace their phones without fuss when failures become too much of a nuisance. When it comes to mission-critical IoT devices, which must be 10 to 100x more stable and reliable than the standard $1,000 smartphone, this level of quality and reliability is, quite simply, not good enough.
Eliminate hidden device cost with test
Avoiding these hidden costs and positioning a business to thrive in IoT requires one key thing of product makers and device manufacturers: test, and lots of it. IoT devices in mission-critical applications must be properly tested to ensure reliable performance, even if that testing is more expensive than the device itself.
The challenge is that IoT devices operate in very different environments. They may be mounted in the air, down a hole or against concrete or metal. To ensure they will work as expected, they must be tested after final assembly and under conditions that simulate real-world deployment. By measuring a device’s important performance indicators under normal operation and with production-release software, product markers can catch any potential flaws before they have the chance to drive up the IoT device’s true cost.
Various approaches can be employed to perform this testing, such as using a golden radio, paired devices or parametric testers. If a less complex, more cost-effective system is desired, an IoT device functional tester can do the trick. Which approach is utilized will depend on the product maker’s specific situation and requirements; however, selecting one that features test automation software can be a dramatic time and cost saver.
The internet of things is ripe with opportunities for those businesses fit enough to overcome its challenges and sidestep its pitfalls. Understanding the true cost of an IoT device is one pitfall product makers can avoid by employing adequate manufacturing and development test to improve product reliability. It’s a smart investment for any business looking to make its mark in the rapidly growing IoT industry.
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.
Ignore the scary “human vs. robots” headlines. The complex reality is actually one of mutual growth and gradual change.
Just over the horizon awaits an army of robots, standing motionless in endless columns, their metal heads gleaming in the moonlight. When the signal comes, they will march forward into our offices and factories, shove us out of our desks and workstations, and take our jobs from us.
That’s what it feels when you read the news. You’d be forgiven to think that the rapid advances in robotics and AI are converging squarely on everything it means to be a productive member of society. When McKinsey estimates that “between 400 million and 800 million individuals could be displaced by automation and need to find new jobs by 2030 around the world,” it’s hard not to be scared.
Some perspective is in order.
Why robots seem so inevitable
Before you begin panicking about robots and AI, it’s important to understand why a business would choose to deploy a robot over a person.
Let’s take manufacturing, which is where my background lies, and which is often considered ground zero for automation.
You’ve probably read about the resurgence of American manufacturing. And you’ve also probably read about the labor shortage faced by American manufacturers. It may come as a surprise to people who are worried about automation, but humans remain absolutely essential to manufacturing. In fact, Boston Consulting Group estimates that up to 90% of manufacturing tasks are still performed by humans. The exact number varies within manufacturing industry verticals, but it’s safe to say that humans are the greatest contributor of value in the factory.
Human are, unfortunately, also the factory’s greatest contributor to process variability.
So, today’s manufacturers don’t see the problem as one of having too many humans. The real challenges are high turnover, labor recruiting shortages, long training times and worker safety risks — and the unpredictability that these factors create within the value chain. Manufacturing operates on extremely tight timelines (remember kanban?) and low margins; unpredictability is unwelcome because unprofitability often follows.
But if it were just so easy as to summon a horde of robots to kick all the people out, that would have been done by now. The truth is that, even with robotics and AI advancing at extreme rates, there are some very physical limitations on robot proliferation. I’ve outlined three of them below.
Robots aren’t rabbits; they multiply very slowly
A robotic system is a very complex manufactured good. Ask Elon Musk about how easy it is to scale up production of a complex manufactured good, even when incentivized by staggering demand. It’s not.
The International Federation of Robotics expects the global industrial robot population to increase from 1.8 million in 2016 to 3 million by 2020. Sound like a large number? Well, according to Goldman Sachs Research, there are more than 340 million people working in manufacturing worldwide. So, the robot population is actually growing at a fairly slow rate relative to the perceived demand.
If economists Daron Acemoglu and Pascual Restrepo are correct, each robot replaces 5.6 workers. Their estimation seems large at first glance, but it’s actually less than 2% of the global manufacturing workforce.
The market demands skills that robots don’t have
Henry Ford would have killed to have a few good robots in his factories. His was the ideal use case for robots: a high-volume, low-mix product that rarely changes and has very few variations.
Unfortunately (for robots), today’s manufacturing environments are driving toward the exact opposite trend: from mass production to “mass customization.” Lot sizes of one. Here, the manufacturer strives to deliver flexible and even personalized products without incurring the high unit costs associated with artisanship. The best example comes from Ford: 100 years ago, Henry Ford said, “Any customer can have a car painted any color that he wants so long as it is black.” Today, the Ford F-150 has a staggering 4,147,200 build combinations — or two billion, depending on what you count as a variation.
This kind of environment is precisely where robots struggle. “Machines excel in highly repeatable, high-volume operations,” said Peter Marcotullio, vice president of commercial R&D at SRI International. “Unfortunately for machines, the trend in manufacturing is for mass customization — small production runs, more process variations, constantly changing components — which is very hard to automate because of the intrinsic upfront costs of getting a flexible robotic system tooled and programmed. But it’s very easy for a person to adjust on the fly. People are more flexible and can learn faster than machines.”
Behind every robot is a cadre of … humans
Factories operate on a very delicate cadence, marching to the beat of the takt time. The process engineers know exactly how fast a person is supposed to work, and have designed complex systems to ensure that raw materials and components reach every workstation in exactly the right rhythm to ensure the operator never has to stop and look for parts.
If a robot is to work faster than the person it replaces, then the materials flow around that workstation needs to be rebuilt as well. A factory is a complex system, and any change at one node cascades throughout all the adjacent nodes.
That’s why every robot requires an ecosystem of programmers, process engineers and skilled technicians just to get started, and far more significant redesigns to reorient the process around the robot’s natural advantages. The second-order effects cascade through the supply chain, which requires people to address — who, as I’ve already mentioned, are actually the scarcest resource in any factory.
The real way this movie plays out
Everyone loves a good invasion story. Robots, aliens, body snatchers — that’s what fills movie theaters and sells newspapers (or, in this day and age, attracts clicks).
In reality, I expect the relationship between people, robots, AI and future unknowable technologies to continue the same pattern we’ve seen in 200 years of technological change: Some jobs are made redundant, some jobs are enhanced and many new jobs are created.
There’s no doubt our society will reorient and be reoriented by new technology. But the invading robot armies will remain the subject of fiction for a long time to come. The real story — which will be exciting to historians but less so to moviegoers — is one of humans and machines, not humans versus machines.
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.
Our hyper-connected world has created a complex and ever-changing landscape that many IT teams are struggling to navigate. With continuous everything becoming the new norm, every aspect of application development needs a rethink. This includes testing, which needs a complete overhaul in order to avoid delays in deployment, updates and user acceptance.
IoT has helped accelerate the complexity of systems with many now consisting of an array of data systems, devices and apps. It is clear that testing in its current state is not ready for this “smart new world.”
Below are five steps that DevOps teams need to take to deliver smart IoT testing today:
Manual testing can’t be the foundation of test strategies with IoT due to the complexity and variation of products and services. Automation of test execution doesn’t suffice as the entire testing process from creation through to analysis needs to be automated. This requires intelligent models to auto-generate tests, with AI, machine learning and analytics allowing DevOps teams to analyze data from testing and to identify the patterns with bugs.
Test the product, not the code
Teams need to re-orientate from focusing on the code to the product and the actual user experience. With IoT, products and services are composed of multiple technologies from an array of vendors, and user experiences are therefore based on products from an array of vendors. Testing is no longer a compliance function; thus, you have to move from testing the code as smart IoT only magnifies the gap between testing code and testing the product.
Test channel consistency
Products and services are now accessed through a range of interfaces including mobile, web and voice interface, or an on-device screen. The system also could be interacting with other products via APIs. For example, if different information about where an item is located is provided depending on the interface, this will create confusion and result in errors. DevOps teams testing IoT systems need to ensure users receive a consistent view of the service independent of the interface used. So, it’s essential with smart IoT systems to test for channel consistency.
Converge testing and monitoring
By converging testing and monitoring, DevOps teams bring the user into the automated testing process, so testing is not just product-focused, it’s really user-focused.
Teams observe what users actually care about, what impacts their productivity, what impacts their effectiveness and what impacts their sentiment. They can then use this to determine whether the test was a pass or failure for a smart IoT product. IoT is often about bringing technology deeper into our lives, and user acceptance is critical; therefore bringing the user into testing is even more critical in IoT than elsewhere.
Get ready for load testing
As IoT continues to gather steam, DevOps teams need to start thinking about load testing. Many companies add IoT technologies to their existing IT infrastructure, but very few are ensuring their infrastructure can handle the resulting surge in data. Load testing is an essential preventative measure that DevOps teams must undertake to ensure their network can cope with the explosion in data volumes without impacting the product or user experience.
By adopting these five steps, DevOps teams will be able to deliver smart IoT testing, ensuring that the digital experience delights.
Last week, when I took a sip of my first cup of coffee in the morning, I discovered the milk was sour. I wanted to know everyone and anyone who could be held responsible — the store manager, the delivery truck driver, the quality control supervisor of the dairy farm. You don’t want to mess with my morning coffee.
Until recently, it may have seemed too much to ask, but it’s now possible, with today’s technology, to track every step of the supply chain for the contents in your refrigerator. Today manufacturers are using IoT to track products through their lifecycle to achieve higher levels of efficiency. The combination of smart sensors, cloud technology and analytics are making supply chains smarter and more efficient, with the ability to track each product through every stage of its lifecycle.
Here are some examples of how IoT can be used to better manage the supply chain:
- Inventory control — IoT can be used to provide a real-time window into inventory levels by measuring product quantities and, when necessary, automatically sending an order to a supplier for depleted stock. Product availability can be displayed on a screen to respond to customer inquiries. Eskimo Cold Storage uses RFID tags to track the location of its 32,000 pallets in its 10.9 million cubic foot cold storage, eliminating $208,000 in costs associated with locating lost inventory and $25,000 in annual chargebacks due to lost merchandise.
- Shipping — When shipping products, companies are using IoT to monitor the product condition during the entire trip from beginning to end, instead of relying on testing at the end of the journey. Maersk uses IoT to monitor 300,000 refrigerated containers containing fresh produce that needs to be shipped in a tight range of temperature and humidity. In addition to protecting perishable merchandise, Maersk only needs to visually inspect 60% of its containers since data from sensors provides certainty that the goods in these containers have been kept in good condition during the shipping process.
- Warehouse management — Using IoT, every single part can be tracked from when it’s first manufactured to when it’s assembled and shipped to an end customer. Walmart cut taking physical inventory from one month to just 24 hours by using sophisticated drones that fly through the warehouse, scan products and check for misplaced items. BMW uses sensors to follow a part from the point it was manufactured to when the vehicle is sold from all of its 31 assembly facilities located in over 15 countries, ensuring everything gets to the right place while utilizing the minimum amount of resources.
- Delivery — The last mile is essential. Estimated time of arrival synchronization can help trucking companies place the right trucks in the right areas at the right times to avoid backups in the loading areas and ensure that other resources, like fuel and hourly employee time, are not wasted. Grocery retailer Ocado equips delivery vans with a range of IoT sensors to log valuable information, such as the vehicle’s location, wheel speed, engine revs, braking, fuel consumption and cornering speed, to select the best route for the most efficient delivery.
- Supplier management — The data obtained through asset tracking is also important because it allows companies to tweak their own production schedules, as well as recognize subpar vendor relationships that may be costing them money. According to IBM, up to 65% of the value of a company’s products or services is derived from its suppliers, which provides companies with a huge incentive to manage the relationship more efficiently. North West Redwater built a new bitumen refinery across six square kilometers that included over 100 contracting companies. An IoT system was used in order to simplify the contractor onboarding process, decrease operating costs and control the project schedule.
There are certain pieces of the puzzle that need to be put in place to make a working IoT system, including a flexible infrastructure for complying with regulations, scalability to manage the data tsunami from thousands of sensors, as well as comprehensive and seamless data integration. Several different systems in the back office as well as the shop floor need to be integrated including product lifecycle management, enterprise resource planning and customer relationship management systems to achieve end-to-end process optimization.
However, investing in IoT to streamline the supply chain is well worth the effort. With all the potential improvements in customer service and efficiency, it’s only a matter of time before IoT is an expected and necessary part of managing the supply chain.
Blockchain, best known for being the technology behind cryptocurrencies such as Bitcoin and Ethereum, has gained significant popularity over the last couple of years. Today, however, its value in other applications may be greater than the initial application which popularized the technology.
Known for its efficiency and digital security features, blockchain is an encrypted distributed ledger, managed by a specific network of individuals or organizations with a digital key to that ledger. The ledger maintains a record of transactions in linked (hence the “chain” terminology), chronological order, forming blocks of data. Once data has been recorded to a specific block, that data cannot be altered without also changing all subsequent blocks in the chain. This not only enables faster information exchange, but also helps keep such exchanges traceable and, thus, secure — key factors for the business requirements of nearly every organization today.
When no particular individual or organization has access to a master copy of the entire chain, no one can modify the information contained within the chain. This itself acts as a deterrent to cybercrime, making individuals less likely to engage in unethical or illegal behavior, knowing that their every digital step could easily be traced. This allows users of data within the chain to be more certain the information they see is of appropriate quality and has not been tampered with in any way whatsoever. Hashes of original content are stored on the blockchain itself, enabling security at an individual object level. And when these objects are stored across various encrypted blocks, a breach at a singular level won’t compromise the data, hence posing a greater challenge for cybercriminals.
Because of these few but impactful benefits, blockchain is well-positioned to disrupt multiple industries and help improve cyber defense operations for the companies that operate within those industries. The technology has the ability to detect any signs of numerous cyberthreats and, as a result, prevent fraudulent activities based on the technology’s inherent characteristics of transparency, integrity and resilient decentralization. When something can connect us not only quickly, but also securely, future business success will not only demand it, but rely heavily upon it.
Sensors and actuators are appearing in everything from our shoes to our cars to our appliances. The much-hyped internet of things is here — and generating exponentially larger and larger amounts of information. Connecting this deluge known as big data to 3D face authentication could deliver a new level of frictionless interaction for all of us.
The perfect digital storm is arriving. Today’s robust, accurate AI-enabled software and tiny 3D cameras are able to manage and rationalize the growing torrent of data generated by IoT and, as a result, enable a new era of secure, effortless personal identification.
There have certainly been precursors that have enabled us to get to this point. 2D cameras and other biometric technologies, like fingerprint readers, paved the way, of course. But it is only now that we can deliver fast, secure 3D-based face authentication in real time in a wide variety of settings and lighting conditions.
Think for a moment about the various situations where you are required to confirm that you are, in fact, who you say you are. Many of these interactions could be made more effortless by using 3D face recognition to parse data generated by IoT, and as a result, simplify our lives.
Let’s forget about the connected refrigerator for a moment and think about frictionless shopping. Amazon Go comes to mind. This innovative approach lets customers literally stroll into the store, pick up an item or two, then simply walk out. No need for interaction with a sales clerk or a person bagging your groceries. A row of gates requires shoppers to have a smartphone app to enter. But a logical extrapolation of this approach would be to install 3D face authentication technology and remove a step.
Certainly, as the world of mobility is transformed and individual car ownership is supplanted by fleets of roving autonomous vehicles, an option might be to deploy 3D face authentication connected to IoT. Imagine this scenario: The Waymo taxi would pull over, check your face and then open the door to let you in. Your privacy is always maintained based on your preferences regarding data sharing. The vehicle already knows where you are going, of course. Plus, it got a message from your refrigerator that you are low on milk, so it maps a route to swing by the nearest Piggly Wiggly on the way home.
How about implications for hospitality? This new model could let travelers check into a hotel by looking at the check-in kiosk. Once recognized, a room key is issued and the guest is on her way!
Speaking to your smart device is so 2017. Imagine the next generation of Amazon Alexa or Google Home recognizing your face in the morning and then playing your preassembled programming: local weather, national news, favorite sports team scores, stock price updates, the tunes on your “baroque for breakfast” playlist.
Implications for improving healthcare are also huge. No one likes to have to go to the doctor’s office and be handed a clipboard with seven pages of checkboxes to capture your entire medical history. An IoT/ 3D face authentication system could connect your electronic patient record to your face, allowing you to immediately be recognized, and then share all the current medical data from your Fitbit with the healthcare provider.
There are also broader implications, where 3D and IoT could facilitate identification processes associated with the social safety net and even disaster relief. Connecting various data from in-home IoT sensors could help monitor kids in at-risk settings to make sure they got off to school safely. Or it could be used to help monitor a refugee child’s overall health and nutritional needs — simply by recognizing them as they walk around in the camp.
These are just some of the ways that this new intersection of 3D and IoT could potentially transform identification and, in the process, improve lives. Reducing technology-related friction is always a good thing. I am excited to be helping advance this new paradigm.
It’s no secret that the internet of things is expanding at breakneck speed. On average, today’s households have 12 clients or IoT products communicating with each other. These numbers are expected to increase dramatically, and quickly. Intel believes the number of household clients will increase to 50 in 2020, while Gartner looks at business and consumer markets and predicts 20.4 billion connected things will be used worldwide by 2020.
This rapid growth presents significant challenges for design engineers, particularly Wi-Fi front-end designers. These challenges include thermal management, interference, coexistence and RF front-end (RFFE) linearity. This article takes a look at these challenges and offers bulk acoustic wave (BAW) filters as a problem-solver, particularly for wireless access points and customer premises equipment.
Wi-Fi front-end thermal challenges
As the number of IoT connected devices increases in any given location (smart homes, business headquarters, college campuses, hospitals) and new network models (like mesh networks) are developed to service IoT demands, RF complexity within access points is increasing. In addition to more users and connected devices, RF front-ends must now support wireless radio needs as well as Wi-Fi, additional Wi-Fi bands and the ongoing challenges of how to increase functionality while decreasing the size and weight of the device.
That all adds up to an increase in the number of RF chains in routers and access points, which means thermal management challenges. Filters are one of the key RFFE components implicated by heat challenges.
RF filtering drifts to the left or the right due to changes in temperature, as shown in the following SAW versus BAW figure. These shifts can cause high insertion loss on the band edges, which could cause a low gain or POUT response from the RFFE. If the filter drifts too much (as shown in the SAW figure), then the power amplifier pushes more power output to compensate for the insertion loss. This increases current and decreases system efficiency.
Using filters with high insertion loss can decrease linearity and increase the RF chain POUT. One big advantage of BAW filters (like LowDrift BAW filters) is their stability over temperature shifts. Diplexers, bandpass filters and coexistence filters that use BAW technology with lower temperature drift help mitigate insertion loss and lead to good product thermal characteristics, making them lower cost and/or smaller in size.
As more LTE bands are squeezed into the crowded global RF spectrum, the space between bands is shrinking. In some cases, the transition between the passband and stop-band is as small as 2 MHz. This makes it very tough and expensive to meet government regulation requirements using traditional filter technologies. That’s because the variation in filter response, which is dominated by temperature drift as mentioned above, can exceed the width of the transition band itself. The result is unacceptable interference, high insertion loss, or both.
High-Q BAW bandpass filters offer many advantages over traditional SAW filters, including:
- Extremely steep skirts that simultaneously exhibit low loss in the Wi-Fi band and high rejection in the band edge and adjacent LTE/TD-LTE bands
- Significant size reductions, which aid designers in creating smaller, more attractive end-user devices for residential and commercial environments
- Resolution of coexistence of Wi-Fi and LTE signals within the same device or near one another
- Unique power-handling capabilities, allowing for implementation into high-performance, high-power access points and small cell base stations
These filters address the stringent thermal challenges of multi-user multiple-input/multiple-output systems, without compromising harmonic compliance and emissions performance. This is critical to achieving reliable coverage across the full allocated spectrum.
In a nutshell, high-Q BAW filters are superior to SAW technology when it comes to band edges, because they:
- Have lower insertion loss, steeper band edges and better temperature stability then SAW technology at Wi-Fi frequencies
- Help engineers provide seamless transitioning between interfering bands
- Extend the range in Wi-Fi band channels 1 and 11 by a factor 2 to 3
Wi-Fi front-end designers should consider bulk acoustic wave filters as an important solution to the challenges inherent in the IoT’s explosive growth of the number of RF devices and resulting demands. BAW filters are inherently less sensitive to temperature change than standard SAW filters, and they generally deliver superior performance with lower insertion loss at higher frequency levels. BAW filters can also overcome interference challenges, due primarily to their extremely steep skirts that exhibit low loss in the Wi-Fi band and high rejection in the band edge and adjacent LTE/TD-LTE bands.
A survey found that 87% of U.S. consumers disliked something about the process of buying a vehicle at a traditional car dealership, and 61% said they felt like they were taken advantage of at some point in the dealership. Another survey found that 75% of respondents said that “if given the opportunity, they would consider making their entire car-buying process online, including financing, price negotiation, back-office paperwork and home delivery.” It’s clear that the traditional car dealership does not have much to offer consumers. Enter the internet of things, which can change the relationship customers have with dealerships and upgrade the entire car purchasing process for buyers.
It’s important to note that the buying process starts online for most consumers. Dealerships need to understand that to get the sale, they need to have better connectivity, engagement and, most importantly, transparency when dealing with these internet-savvy buyers. IoT can change how consumers buy vehicles, and the dealers that get on board this new technology will thrive.
IoT transforms showrooms
In 2016, Bentley launched a car-free showroom, which showed vehicles from every angle and in life-sized perspective. Buyers could review color choices, interiors and accessories via interactive touchscreens. Many showrooms from car brands around the world are implementing virtual reality (VR) and augmented reality (AR) capabilities, revolutionizing how users view vehicles. This technology uses cameras and sensors in empty warehouses to let smartphone users inspect a virtual car.
Dealerships are also including interactive kiosks and tablets to view car features and promotions instead of requiring customers to interact with a dealer right away. Furthermore, dealers that take customer information and use connected devices can offer more personalized buying suggestions based on data, rather than going off of experience. These digital experiences blend the online and offline experience for buyers and reduce the pushy sales experience that users do not want to have.
IoT improves the dealer-buyer relationship
Drivers tend to have a negative connotation when thinking about dealerships, mainly because when drivers go to the dealership, it’s because there is something wrong with their vehicle. This relationship can change through IoT. Using predictive analytics, dealerships can offer automated maintenance capabilities. Instead of waiting for a car part to break, dealers can use connected devices to warn drivers of a potential malfunction, so they can take care of the problem before an accident occurs. Using a connected device in the vehicle, dealers can provide drivers with useful information and tips regarding their maintenance or driving. This technology can change the relationship between dealers and buyers by offering the latter more value.
The internet of things is coming, whether dealerships are ready or not. Since buyers have extremely negative views of the traditional car dealership experience, it’s time businesses use advanced technology to upgrade the car buying experience. Furthermore, dealerships have to compete with thriving online car buying models, so the IoT-based experience, including VR and AR, can help companies stay more competitive in the market. Dealerships can provide a new, unique experience to buyers and offer more transparency using IoT, which can help them remain relevant in a competitive landscape.
E-commerce accounts for just 10% of U.S. retail sales, but it has influenced the way consumers perceive all shopping. We use e-commerce for better pricing, convenience, selection and research capabilities, then feel frustrated when we don’t find the same in stores. Thanks to e-commerce, we expect:
- Detailed product information
- Research options
- One-click checkout
But, there’s something unassailable about physical shopping. Many of us enjoy the social experience of navigating beautiful shopping centers and interesting stores with friends and family. We like to try on products and literally feel what we buy. The immediacy of walking into a store and leaving with goods is pleasing.
More than a few e-commerce companies have opened or acquired physical stores to provide those experiences. Nonetheless, physical stores lack what e-commerce providers value most: data. It’s much harder to:
- Track inventory
- Measure shopper behaviors
- Personalize marketing offers
IoT systems can close the gap between physical and digital experiences. It’s not isolated IoT tools that will accomplish this goal, but rather an approach that integrates many technologies, including RFID communication, mobile apps, cloud platforms, Bluetooth, NFC, sensors, wireless power and others. Combined, these technologies can address all six of the weaknesses listed above.
To illustrate how, let’s map out the retail experience at a hypothetical stored called BullseyeMart for short.
Entering the store
When a shopper enters BullseyeMart, she will open her mobile app and pair it with a shopping cart. Doing so tells BullseyeMart’s cloud platform who has entered the store. BullseyeMart’s artificial intelligence systems generate offers based on that person’s unique shopping profile, which consists of past transactions, offers used or ignored, shopping routes, demographics and other data.
If, for instance, the person used to buy four to five avocados per week but hasn’t bought any since their price increased one month ago, BullseyeMart’s marketing algorithm might generate a special offer for avocados. The app could also present previous shopping lists (of consumables only) and ask if the shopper would like to be guided on the most efficient route to buy those items again.
At BullseyeMart, every item has an RFID chip that connects it to the in-store Wi-Fi. The chips are powered wirelessly from up to 10 meters away, meaning they don’t need an onboard battery or cable. They can submit data to the cloud and be embedded in any item without adding bulk. BullseyeMart regularly pings these chips to update inventory counts and never has to pay an army of staff to scan each item.
The RFID chips are tracked as they move around. If our shopper adds an item to her cart, the cart’s RFID scanner adds the goods to a tab on the BullseyeMart smartphone app. Effectively, it handles the work of a cashier. The system tracks which goods she picks and in what order. It also can tell if she grabs an item but doesn’t place it in the cart, or if she does keep the item but later abandons it.
Research and consumer data
Since every item has an identifying chip, our shopper can use her phone’s NFC scanner to ID and research an item. Let’s say the shopper becomes interested in buying a fitness tracker after seeing BullseyeMart’s neat display. She isn’t sure which one to get. Normally, she would wait until she arrived home, search the web and order online. But at BullseyeMart, she scans three similar wearables with her phone and the BM app brings up a line-by-line comparison of features. The shopper can watch product videos with BullseyeMart experts, read user reviews, pull up media coverage and read about accessories commonly used with the wearable. She can even look up information on how the components were sourced and where they were assembled.
Tap to checkout
When shoppers are near the store exit, the BullseyeMart app’s geolocation service sends a push notification to check out. The shopper reviews the listed goods and taps once to charge a credit card on file. RFID scanners at the exits recognize if someone hasn’t paid for the goods (accidentally or intentionally) and attempts to leave.
Since we’re using our imagination, let’s say that our shopper’s cart is a self-driving variety that returns itself to the cart collection aisle. At BullseyeMart, there are no carts scattered around the parking lot blocking the parking spaces.
Retail without the drawbacks
BullseyeMart’s IoT shopping experience addresses weaknesses that affect both consumers and brands in physical retail. IoT gives shoppers the product information, research options and self-checkout they appreciate online. Likewise, IoT automates inventory, expands data collection and introduces personalization.
The world’s best retailers will soon all have an online and physical presence if they don’t already. And it will be IoT that closes the gap between those two experiences.