Did you ever think you’d be talking to your phone like it was a friend, asking it where to find good tapas? Or that your refrigerator would be able to talk to you and let you know you’re low on milk? We used to use watches to tell time. Now, we rely on them track our heart condition, get directions, send emails and texts and talk to our friends. The way IoT has transformed how we interact with our personal devices and how we live would have seemed like science-fiction just a few years ago. In 2020, IoT is going to revolutionize the way we work. Here are four things you can expect to see:
Work will be less of a chore
They wouldn’t call it work if it was fun. Or would they? Technology has made work more complicated and frustrating than it needs to be. Every year, companies spend billions on applications to streamline functions and processes and make work simpler. But they’ve put too many in place that are too hard to use, which has only made things worse. The devices we rely on at home to manage our lives know our preferences and modes of operating. They make it super easy for us to stuff done. “Alexa, call me an Uber.” At work, company-issued technology seems to just slow us down. On average, it takes four or more applications just to execute a single business process!
In 2020, the same technologies that have made our personal lives so easy will become pervasive in the office and turn the employee experience on its head. Tactical busy work will take a back seat to the strategic, value-creating stuff we want and are paid to do because devices will automatically deliver the insights we need when and where we need them and in many cases, just do the work for us.
Virtual assistants will ease the pain
Statistics show the average employee spends about 65% of their time on busy work and in meetings and 20% searching for information. That leaves just 15% — or roughly 1.2 hours a day — for meaningful work. Virtual assistants who know who we are, what we do and how we like to do it will give us this much-needed time back. We won’t need to go through the painful process of digging through enterprise apps to execute simple workflows, like requesting time off or booking travel. We’ll just ask our virtual assistant to do it. Beyond that, sometimes we won’t even need to ask. Sales opportunities will automatically be moved out of pipeline and into the system of record as soon as you close them. Recordings of virtual meetings will automatically be sent to participants as soon as they are over.
Technology will shadow us
The days of lugging laptops, tablets and mobile devices everywhere may finally be over as technology will follow us. Digital workspaces will deliver the apps and information we need anywhere, anytime, to any device. So, when we walk into a conference room for a meeting, we won’t have to dial in attendees on the Polycom or fire up a WebEx or Zoom session. The IoT-enabled workspace will already know who we are, the meeting we are there to attend and presentation we need and just get things started using the equipment that’s already there.
Augmented reality will redefine collaboration
Augmented reality used to be all about fun and games, but software developers have gotten serious, and augmented reality is set to transform the way we collaborate at work. We’ll see and interact with colleagues and customers around the world in new ways through smart glasses and AirPods; break the isolation of working remote and experience corporate meetings as if we were there in person; test new products as if we were in the field; learn new skills in digitally enhanced classrooms; and we’ll receive information in context and process it more quickly than ever before to make better, more informed decisions.
There are still people out there who think IoT is just for toys. And some of them thought the internet was just a consumer fad, too. IoT means business. And in 2020, we’ll see proof.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
The universe of connected devices continues to snowball and has now surpassed the number of smartphones globally and is projected to reach 18 billion devices by 2022. Smart devices and hyperconnected systems are becoming ubiquitous, ranging from connected doorbells to smart cities to hospital systems. Organizations need to rethink how they test and monitor the devices and services they are delivering. Determining what works is very different now than in the days of static failure notices.
Simply evaluating code compliance doesn’t provide any insight into whether you are delivering the experience that a user expects. Take the smart home with a range of connected smart devices, including a security system, thermostat, sockets, oven, coffee machine and voice-enabled devices. A user expects that the devices will all be interconnected and able to react and respond to the data provided within the ecosystem. For example, as a homeowner approaches, they expect the heating system to adjust the temperature of the home to their individual preference and only open the front door once they are within five feet, and their biometrics have unlocked the door.
From a manufacturer’s perspective, merely testing what you have built no longer works. Take the smart font door example, testing if it works in isolation doesn’t suffice because you need to understand how it interacts with the entire smart home. You don’t want a scenario where when the indoor temperature increases to 80 degrees Fahrenheit, the front door opens and cools the house down.
IoT is a combination of multiple protocols, devices, operating systems, firmware, hardware and networking layers. Testing in this hyper-connected world needs to focus on the value proposition and test everything that is part of the user experience. Organizations must shift and embrace a strategy that examines the user perspective and delivers insights to optimize the experience. This requires test automation that moves beyond static failure notices to show teams where the problems lie and significantly reduce the time it takes to resolve issues. In a nutshell, testing needs to detect and fix problems in interactions of applications with people, other devices and locations, and then learn and improve the experience delivered.
To achieve this, test automation incorporating breakthrough technologies like AI, machine learning, deep learning and analytics is now essential. The pass-fail model is no longer relevant in a digital world driven by experiences. As the IoT continues to evolve, organizations need to quickly pivot and evaluate experiences, not just code compliance.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
It’s hard to think of public restrooms — those at airports, hospitals, sports venues and casinos — as hubs of IoT innovation. But that’s exactly what they are. Significant innovation in public restrooms started several years ago with the introduction of battery-powered devices, like battery-powered automatic faucets, flush valves and soap dispensers.
Before devices that could be charged by batteries came along, the only other options were device models that would draw a low-voltage current from an AC transformer. In other words, a power cord would need to be plugged into an electrical wall socket to send power to an automatic faucet, for example. Running power cords in a restroom environment posed many challenges and risks. Restrooms are inherently water-rich environments, and public restrooms often undergo power washing, which poses an obvious risk to electric power cords and wall sockets. The other challenge that came along with devices that could only draw power from being plugged into an outlet, were on the installation side. Routing power cables through walls often require ripping up tiles and drywall and can take a significant amount of installation time and cost.
The introduction of battery-operated devices
When automatic restroom device manufacturers innovated and started introducing battery-powered device models, the risks and challenges went away. Bathroom equipment manufacturers worked hard to optimize these devices for long battery life. In a large airport where there can be more than 40 public restrooms, longer battery life meant less maintenance and battery replacement costs.
IoT changed everything
Over time, it made sense to turn simple battery-operated devices into more intelligent IoT devices that could provide information such as when a soap dispenser started getting low on soap. If such reporting capabilities are not available, the dispenser might run out of soap, leading to a poor visitor experience, or soap might be replaced too early, leading to undue time and cost of maintenance. For another example, facility managers can use IoT to closely monitor water use to detect major leaks and easily identify when products or fixtures need maintenance. If a faucet or a toilet reports that it is not being used, it might indicate a problem. A clogged toilet would cause visitors to use a different toilet, which would result in reduced usage of the clogged one, alerting the problem to janitors.
The problem with turning faucets and other bathroom products into IoT devices, however, is power consumption. IoT capabilities ––where the device is pulling and pushing usage information — requires much more power than traditional or even longer-lasting lithium ion batteries can produce. If the IoT device can’t properly rely on battery power, we then run into problems of inconsistent reporting or devices dying without notice, ultimately resulting in a poor user experience and an even greater headache and cost for maintenance crews.
Enter long-range wireless power
Long-range wireless power can solve all of these challenges and provide the steady power stream of a hardwired solution and the ease of battery installs without any of the associated drawbacks.
Here’s how it works. A wireless power transmitter sends safe infrared beams to a receiver that is typically embedded in the bathroom devices to be powered, and a small photovoltaic cell in the receiver converts the light to electricity. This concept is similar to solar panels converting sunlight into electricity. Infrared beams can travel with little degradation over a distance to efficiently, safely and reliably providing wireless power across a room to the device, eliminating the need for power cords or batteries.
Long-range wireless power can truly up the innovation game of IoT devices, such as those within public restrooms in the following three ways:
- Reduce maintenance and installation costs. By eliminating the need to install wires or replace batteries, significant time and expense is saved. The user experience improves because the devices that need to be on are indeed always on.
- Enable smarter devices. Adding smart capabilities to automated fixtures — such as those in public restrooms like data on how low a soap dispenser is getting or if a hardware fixture is malfunctioning — requires more than batteries can reasonably provide. Moving away from batteries toward long-range wireless power will be key for manufacturers to develop smart automated fixtures.
- Support sustainability. Despite advances in battery technologies, batteries require constant replacement in order to support the innovation of IoT-enabled fixtures and the increased power consumption that comes with them. Each year, we discard approximately 180,000 tons of batteries — more than three billion batteries — of which 86,000 tons are single-use alkaline batteries which cannot be recycled. Placed end to end, the dead alkaline batteries alone would circle the world at least six times. Much of this waste ends up in landfills, not only taking up precious land, but also allowing harmful chemicals to leach into the surrounding soil and waterways. Long-range wireless power significantly reduces the need for batteries, and thus is a promising solution to e-waste.
The Public Restroom of the Future has Wireless Power
Overall, long-range wireless power will support the public bathroom and other public services of the future by enabling vendors and facility managers to truly innovate, cut costs and reduce battery waste. Additionally, consumers will benefit as well. They’ll be able to experience clean, sanitary and well-stocked restrooms at all times because of the reliability that long-range wireless power provides.
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.
AI is transforming the world as we know it. Contextual awareness paired with AI is opening the door to many positive solutions for healthcare, environmental protection, conservation, smart cities and public safety. Enterprise AI applications also proliferate in marketing and sales, HR and recruiting, security, autonomous operations and financial services. On the other hand, the rapid advancement of AI also raises questions and concerns around data ethics, which are only beginning to be addressed.
As a case in point, the New York Police Department (NYPD) has been challenged by AI bias concerns for its new crime analysis AI tool. The tool is intended to help identify crime patterns for faster response and crime prevention. To avoid bias, the NYPD removed race, gender and location attributes from the historical data that was used to train the tool. However, as one analyst noted, if racial or gender bias played any role in past police actions, even if it’s not explicitly captured in the data, the tool’s predictions will still be impacted by race and gender. As the AI market continues to explode, clarifying an ethical approach to scenarios like these will be paramount.
How fast is the AI market exploding?
IDC predicts that global spending on AI systems will reach $79.2 billion by 2022 at a compound annual growth rate of 38% between 2018 and 2022. For a good visual reference of just how fast the AI topography is evolving, just compare the AI business landscape from five years ago to the current2019 AI landscape. AI topography and the number of AI inventions follows similar paths of acceleration, as this visualization of AI patents illustrates.
What’s to fear? The rise in AI ethics
If AI can really help us make the world better, then what’s the problem? Consider this example: A city has a network of smart traffic lights to reduce congestion. AI algorithms time the lights to minimize traffic buildup and capture license plate images of any vehicles that fail to stop for a red light. The system automatically matches license plate numbers to vehicle owners, enabling the city to process traffic violations faster and more effectively.
In this scenario, you may not be surprised to receive a traffic ticket in the mail. But what if your insurance company notifies you that your rates are going up as a result? While that raises questions around citizen privacy, addressing AI bias may be an even bigger challenge. For instance, what if AI model that determined your initial insurance rate was trained on historical data that contained bias with respect to your race, gender, or education level? In fact, IBM researchers working to mitigate AI bias have identified and classified more than 180 human biases that could affect AI models.
Most AI ethics concerns can be generally categorized into these general areas:
- Human and machine interaction. Machines impersonating or fooling humans; autonomy gone wrong in weapons, accidents or rogue robots, and human abuse of machines.
- Data collection. Collecting more data than is needed; collecting data without permission; surveillance, selling or connecting different data sets without permission and perpetuating bias and human error contained in data used to train AI.
- Data use. Deep fake videos, fake news, social manipulation, invasion of privacy, social grading based on insurance, credit or jobs and discrimination.
Fortunately, many governments and companies with a stake in AI are aware of the potential for bias and working to implement ethical approaches. For example, The European Union published a set of guidelines for ethical AI for companies and governments. The U.S. Department of Defense is hiring an AI ethicist. Industry consortiums such as The Partnership on AI and the IEEE have developed guidelines on AI ethics. The Partnership on AI, which includes 100 corporate and nonprofit members, also recently announced a research fellowship to advance diversity and inclusion in AI. Many tech giants, including Google, Microsoft, IBM have developed their own AI ethics guidelines, and Amazon has committed $10 million to AI fairness research.
Growing ethical AI is bigger than just one stakeholder or policy, but typically include principles of fairness, inclusion, transparency, privacy, security, accountability and societal benefit. Data is at the heart of many of these areas as it really boils down to how data is collected and used to train AI models.
How trusted data exchanges could help
AI models are as good as the data used to train them. Larger sample sizes with diverse characteristics that have been cleaned of bias and errors will result in fairer, more accurate AI models. Additional data sources added over time can also help improve AI models. For example, Siemens built an AI model that analyzes sensor data from trains paired with historical data to predict faulty components. In the future, the company could add data from other sources — such as route-based weather forecasts — to further improve the model.
Data exchanges are emerging as one way that organizations can better use the data they have, including monetization, as well as tap into data from other sources. Combining data from different sources across IoT data exchanges can improve AI models, yield deeper insights and open the door to new services. Trust is an essential building block.
Data exchanges built with the principles of a data trust are better equipped to address data privacy concerns. By directly and securely interconnecting IoT ecosystem participants, data, and algorithms, a trusted data exchange can generate maximum shared value while keeping data private and safe in transit on low-latency, high bandwidth infrastructure.
As Jeni Tennison, CEO of The Open Data Institute put it, “We only unlock the full value of data when it gets used, so we really need to find good ways to share data more widely without putting people at risk.”
The agriculture industry is facing challenges as the global population continues to grow and the amount of arable land decreases. As a result, farmers are using technology to streamline operational processes, influence the way food is being produced and to leave a longstanding positive impact on the environment.
Just about everyone understands the importance of watering plants to ensure they grow, but what if irrigation could not only ensure optimal yield, but save costs on labor and inputs? Precision agricultural irrigation companies, such as WaterBit, think of this when they set out to use IoT technology to make smart irrigation systems.
Farmers are seeking solutions for data that enables them to make pin-pointed irrigation and fertilization decisions, which help them optimize their crop yields. Water and soil are the main factors that drive crop yields, and when farmer has more control over these factors they have more control over their outcomes.
For example, when developing their smart irrigation system, WaterBit’s goal was to create a reliable networking product in agriculture. WaterBit’s irrigation solution has streamlined farming operations and increased overall productivity where deployed. With LoRa devices and the LoRaWAN protocol, this solution provides two-way communications in response to the primary needs of irrigation and fertilization.
By implementing LoRa, batteries in production units can be eliminated and duplex communication is enabled. Automatic identification systems enable growers to maximize yield across soil types, all while optimizing the use of labor and other input resources. This solution can be used across crops such as tree nuts, corn, cotton and berries.
As the demand for increased crop yields continues to grow, commercial farmers are closely monitoring overhead costs, and turning to technology to minimize expenditures, grow their businesses and feed a growing population.
We’re seeing more LoRa use cases pop up in agriculture given its long range and low power capabilities, which are suited well for the rural environments in which devices are deployed. It’s enabling growers to act based upon events as they happen on the field. Many farmers are also turning to companies such as Semtech to deploy scalable automatic identification systems that are reliable and provide real-time data and information.
The agriculture industry faces many challenges that they cannot control easily, such as the weather. However, technology is enabling farmers to take more of the control back into their own hands through better automation and the ability to streamline their agricultural operations.
IoT is coming of age.
In recent years, the technologies behind IoT connectivity have powered new products, new market categories and new ideas while impacting business decisions, consumer behaviors and economic trends. And now, from health trackers to real-time video surveillance, IoT products and services are not just changing lives, they’re also gaining traction.
Now, as IoT technologies continue to break new ground, the opportunity to apply IoT-based solutions to some of society’s greatest challenges becomes more realistic. Consider how efficient transportation networks or smart factories might affect energy consumption, lower pollution levels and boost regional economies.
To better understand how IoT will revolutionize industries and markets and regions, it’s important to look at how the technologies not only power the IoT ecosystem but how they also work together to open doors to new possibilities.
Consider the value that three important connectivity technologies — cellular, short-range radio and positioning — provide on their own.
When it comes to device tracking or remote monitoring — perhaps a medical monitoring device or a smart streetlight — cellular technology is what allows data to be shared with a central location. But with a range of demands and use cases, the levels of cellular connectivity needed can vary based on a number of factors.
Short-range radio technologies such as Wi-Fi and Bluetooth may be widely recognized for their consumer applications, but the ability for these technologies to enhance digital experiences within defined physical locations — think corporate campuses, airport terminals or manufacturing facilities — can change the way IoT applications are adopted in the workplace or public venues.
Positioning technologies, which are most recognized for their impact on the advancement of autonomous vehicles initiatives, are a critical piece of the IoT equation. In large part, its importance is centered around the accuracy that it needs to deliver while taking into consideration that latency issues that must be tackled to deliver precise results.
Emphasis on reliability
As we’ve learned with other technology product categories, not all products are created equal. For any number of reasons, some products will be inferior to others and experiences could be sub-par. But it shouldn’t be because of the technology.
When it comes to the technology, reliability — the ability to access the device and get the data when it’s needed most — is key, no matter the product, the manufacturer or the vendor. A smart streetlight, for example, might only need to report data about its energy usage or illumination levels on monthly basis, but that doesn’t mean it shouldn’t be able to transmit a maintenance issue outside of the pre-scheduled update window. Compare that to a heart-monitoring device that needs constant connectivity, not only to monitor the patient and transmit medical data but also to monitor the device’s power consumption.
Increasingly, issues like power management and security — elements that traditionally had been part of the device itself — are relegated to the technology, too. When the security technologies are implemented at the chip level, the device has the highest level of security and will generate the secure keys that are needed for the application.
The demand for IoT solutions continues to grow, and along the way, it’s unveiling some unique problems that need to be solved, not necessarily by a single approach but more by a multi-pronged approach that includes custom solutions developed through a mixture of technologies. Perhaps the solution involves the need for more data, advanced sensor capabilities or enhanced machine learning. Perhaps it needs a combination of them.
That’s what’s important to remember about the next wave of IoT and the technologies that are powering it. As we’re able to introduce a greater range of IoT-powered solutions, solutions can be designed to address specific problems by implementing the right mixture of connectivity technologies.
When it comes to IoT, the limitations are shrinking while the opportunities continue to grow.
There has been a tremendous amount of excitement around the arrival of 5G over the last several years. The hype is now finally giving way to progress as proof of concepts, field trials, buildouts and early deployments emerge. But despite the many recognized advantages of 5G, some mobile network operators are still looking for concrete evidence of ROI.
The reason for this is many mobile network operators are not yet prepared to offer 5G at scale. When operators launch a new service, the first phase typically involves building out and scaling up within their own networks. Only after the internal build up is done do they start exploring interoperability and interworking between networks.
While there has been a lot of interest around the rollout of 5G networks by major carriers such as AT&T, Verizon and T-Mobile, the fact remains that operators are very focused on their own networks. They haven’t even started to talk about how to make that available to other partners or asked how to support sharing across partners within the network.
So, what difference will 5G make?
A look at 5G
The adoption of 5G in its early stages is going to be critical to fully realize the vision of a mobile-first, connected workforce that has access to optimal bandwidth speeds at the mobile edge, which will help improve collaboration functionality such as augmented reality and virtual reality.
5G will enable an explosion of more advanced IoT use cases that will consume greater bandwidth and remote surveillance, and will increase interactions across different IoT endpoints leveraging AI and machine learning, especially in the realm of autonomous vehicles. These higher bandwidths use cases require a faster and more responsive network on-demand to realize their full potential.
In some cases, 5G will provide more flexibility in access to technology. Similarly, 5G will also leverage software-defined network capabilities to better manage underlying access for the particular use cases that organizations have.
5G in the automotive industry
Arguably, the most 5G-centric use case is autonomous driving. If you examine a car closely, you’ll find that most of a car’s operations are controlled by technology, not the driver. 5G is critical to ensure the vehicle can effectively make intelligent and secure decisions based on the vast amounts of data shared between the vehicle’s system components, other vehicles and roadway infrastructure elements.
A robust 5G mobile network will enable more decentralization, but for autonomous cars to really thrive, a completely seamless mobile experience is critical to keeping cars constantly connected. The challenge will be to design IT architecture that can be deployed globally while still allowing for localized technology to cater to different regions.
Coverage, reliability and scalability must be optimized, and seamless access to multiple mobile networks will require a unified management policy to ensure consistent standards. It’s important that operators, vehicle makers and other ecosystem players, such as transportation authorities, telematics control unit providers and fleet management companies, work together to ensure 5G capabilities are seamless, efficient and effective.
Patience is key when dealing with 5G
The key thing to remember when it comes to these use cases — and 5G in general — is that patience is a virtue. Ultimately, it’s going to take some time for 5G to reach a similar level of availability as 3G and 4G. It is vital that the mobile ecosystem appreciates the limitations associated with frequency allocation, network investment, regulatory restrictions and the availability of funds for investment.
The investment by mobile operators and providers isn’t a small one. In fact, it will likely amount to billions of dollars in new network equipment, licenses, deployment, time and collaboration.
There is no question that we are at the beginning of a new era of global connectivity, with speeds we’ve never seen before. If various parties, including the mobile operators, government and network equipment companies, work together to identify commercially viable and desirable customer solutions, 5G can fulfill the vast potential ascribed to it these past years.
But it’s important to keep things in perspective. We are at the very beginning, and there’s still a long way to go.
Using traditional analytics to steer IoT systems is like trying to steer your car while only looking through your rearview mirror. A new class of IoT tools is flipping the conventional school of analytics thought on its head.
Old-school business intelligence (BI) and data science tools are designed to look only at historical data, or a recording of IoT sensor data, like a DVR of an old football game that’s already been played. This architecture helps analysts understand what has already happened, not what’s about to happen next, while the outcome is yet to be determined.
Looking only at the past assumes the patterns, problems and anomalies observed in the past will happen in the future; this works well enough for financial reporting, many forecasting tasks and generally when the world is stable, repeatable and under control.
Streaming IoT data provides the raw material needed to think differently: to analyze and act on emerging conditions instead of assuming conditions, trends and relationships will remain the same. Here’s how self-service streaming analytics combined with IoT data can change how you think about the game that is your digital business.
The dawn of a new analytics era
Years ago, self-service BI tools put the power to analyze data into the hands of domain experts. By reducing the dependency on IT, these tools ushered in a new era of insight-driven business. Suddenly, if you could use a computer, you could use analytics tools such as Tableau, Qlikview, or Spotfire on your own without waiting weeks or months for IT.
Self-service visual exploration fueled dramatic growth in the BI market, thanks to the productivity gains from making opaque business processes, transactions and data fully transparent to domain experts and process stakeholders. For the first time, they could finally see what had been previously hidden.
A new, similar era of disruption is now upon us, because recent innovations in self-service streaming analytics empower business users to see IoT data like they have never seen before. These technologies are streaming BI and data science in real time.
Streaming BI is like an algorithmic canary in the IoT data coalmine. It provides business users continuous, live insight into what’s happening now by connecting directly to streaming IoT data.
From a business analyst point of view, streaming BI works like a conventional BI tool, but instead of connecting it to historical data, you connect it directly to information in motion: IoT data flowing through messaging systems like Kafka, MQTT, OSI PI or OPC UA, an increasingly popular IoT protocol on Microsoft’s Azure platform.
The magic happens after you create a BI dashboard. Streaming BI remembers the queries needed for each BI visualization and continuously monitors data streams for changes in the query result. The moment the result changes, visualizations update.
Users can create alerts that use rules or data science algorithms to monitor IoT sensor data. When the incoming data shows changes in defined alert conditions, the dashboard changes and alerts are delivered according to rules the business user creates.
For example, you can ask an algorithm to display all trains on a map, highlight in red trains that are predicted to be more than 1 minute late, send me a text message if that prediction becomes greater than 5 minutes late. This visualization constantly updates without re-asking the question. Even if you’re not sitting at your desk, you’ll be notified when something happens that makes or increases the chances a train will be unusually late.
This form of BI completely changes the interaction model between the analyst and data. Insights are live algorithms pushed to the analyst directly. Analysts can just set it and forget it. The public can be alerted that a train is arriving late while they are still driving to the station. Better yet, the problem can be fixed before it happens, and passengers will never know there might have been a problem in the first place.
Now, imagine instead of a train running late, sales are not materializing or a storm is coming that might affect safety. Anticipating such outcomes before they materialize and in real time while you can still do something about it is critical.
Streaming data science powers streaming BI
The second recent innovation in IoT analytics is streaming data science.
The AI field of adaptive learning is the AI equivalent of how humans learn: instead of training models only on what has already happened, adaptive learning can train models on changing data streams by injecting Python, Tensorflow or Java data science algorithms into streaming data for continuous evaluation.
Streaming data science presents new opportunities for adaptive learning. For example, in high-tech manufacturing, a nearly infinite number of different failure modes can occur. To avoid such failures, machine learning models applied to IoT data can help identify patterns associated with quality problems as they emerge and as quickly as possible. When never before seen root causes — such as machines or manufacturing inputs — begin to affect product quality, staff can respond more quickly.
Adaptive learning with streaming data means continuous learning and calibration of models based on the newest data. Sometimes applying specialized algorithms to streaming data can simultaneously improve the prediction models and make the best predictions at the same time.
When you combine streaming data science and streaming BI, business analysts can gain continuous algorithmic insights. This helps democratize data science models by helping humans manage automated algorithmic insights.
Self-service streaming BI and streaming data science at work
These innovations open an entirely new market for BI: digital operations. Until now, BI was useless for digital operations because there’s no value in understanding how you should have acted yesterday to avoid problems or seize opportunities.
For example, smart city transportation analysts can now understand and act on congestion in real time by evaluating sensor data from vehicles, satellite imagery and weather forecast data with streaming BI. Analysts can receive notifications when data science models predict that problems are about to occur and decide how to reroute vehicles, notify drivers or alert the public to avoid problems before they happen.
Other examples of streaming BI and data science at work include:
- Shipping operations can be alerted when a model predicts that a cargo ship will arrive earlier than expected and doesn’t have a place to dock. In shipping, wasted time is wasted money, and shipping operators can use real-time insights to reoptimize port operations and eliminate delays.
- Insurance adjusters can continuously monitor weather patterns and models that predict areas where claims will be prevalent so that they can proactively alert customers and schedule adjusters to reduce financial loss and improve customer engagement.
- High-tech manufacturing operations can monitor sensor readings from equipment, apply adaptive learning models and predict and fix problems before they impact production or quality.
- Online marketers and web user experience designers can evaluate how specific offers are working, change layout and evaluate goal attainment on a commerce site.
Until recently, continuous insights like these were only possible through laborious custom programming. Now, self-service streaming BI and streaming data science puts real-time power in the hands of analysts.
Stop looking at the past and start looking toward the future
Today, nearly every business is stuck looking only at the past. Thanks to the plummeting cost of IoT sensors and innovations in streaming analytics, continuous insights can now be made available to any business user. It’s as easy as opening a spreadsheet.
The agility gained from self-service continuous insight allows subject matter experts to understand what’s happening now, predict problems before they occur and decide how to act while the game is still on.
A decade ago, self-service BI disrupted the analytics market; now, self-service streaming BI promises to democratize continuous, real-time insight. Old-school BI will always have its place, but with ubiquitous IoT data, business users can stop looking at what could have been, get in the digital game, act and win.
With an expected compound annual growth rate of 14.8%, the market value of connected cars is estimated to reach around $220 billion by 2025, according to MarketsandMarkets research. This growth is quite astonishing, and various automakers are investing their resources to develop a series of connected and automated vehicles.
Development in the technology of IoT has brought in a radical transformation in the automotive industry. Its implementation has brought in several dynamic changes in vehicles in terms of safety, comfort and luxury. A person in a connected car is given the connection, entertainment and network that he experiences at his office, home or in an entertainment center. Embedded IoT sensors on the surface of the vehicles further prevent accidents and enforce safe and easy driving.
Connectivity’s influence on the automotive industry
Connectivity capabilities have played a major role in deciding the future of connected cars. The soon to come 5G era can be easily visualized in the present. Recently, Dongfeng Motor Corporations partnered with China Mobile Companies and Tencent Holdings to initiate the development of connected vehicles for 5G connection. Such developments are sure to empower vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connection that will additionally enhance the aptitude of connected cars.
Different applications of IoT automotive are emerging that hep fuel the growth of connected vehicles. Fitted with advanced technologies, they will offer a wide range of features and functions that will completely revolutionize the way we travel and interact with them. Here are 9 ground-breaking IoT applications that are driving the future of connected cars:
Autonomous vehicles. Even though the automobile sector is still working towards the development of completely autonomous vehicles, semi-autonomous cars have already been developed and used in some countries.
These vehicles can take partial control over driving to avoid accidents and park itself in vacant spots. Different car manufacturers are attempting to develop a fully autonomous vehicle that can use the capabilities of IoT to take full control over driving. However, their wide implementation will require more time as other technologies, such as vehicle-to-everything (V2X) and telematics, need to be developed properly.
Voice commands. Nowadays, everything can be operated using simple voice commands. Amazon’s Alexa and Google’s Voice Assistant are few examples of devices that have given our voices the power to operate our mobile devices, music systems and even coffee machines.
Various automobile manufacturers and individual vendors have developed in-car speech recognition systems that have enhanced the way in which people communicate with their vehicles. With simple voice commands, a driver can change the radio station, switch on the headlights and look for direction through GPS without even lifting a finger. This lets the driver focus on driving and reduce the chances of accidents.
Advanced maintenance features. A sudden breakdown of even a single component can overheat the whole engine and cause it to fail in unexpected situations. Even with proper inspection, it sometimes gets insanely difficult to detect malfunctions that cause breakdown. IoT-powered predictive maintenance is a logistically prudent and economical method that uses time-series data to identify parts that require maintenance. This time-saving method also reduces the cost associated with part change, and helps drivers avoid frustrating situations on roads.
V2V connectivity. V2V is an advanced application of IoT that has given a push to the automotive industry in creating intelligent and semi-autonomous vehicles. As the name implies, this feature allows vehicles on roads to communicate with each other.
The cars share information related to speed, road conditions and traffic congestion via connected networks. This prevents car accidents and helps drivers to easily glide through big traffic jams. V2V connection along with other frameworks of V2X will allow vehicles to connect with smart traffic signals and signs, along with conducting instant transactions at pumps and tolls.
In-vehicle infotainment. The growing demand for luxurious and smart vehicles has resulted in the development of in-vehicle infotainment (IVI) systems. Modern IVI systems consist of heads-up displays and integrated head units, powered by high-end GPU’s and connectivity modules.
These powerful computation capabilities display the complete real-time information of the vehicle and also allow car owners to connect their smartphones with it. Thus, a car owner using an IVI can make a call from his dashboard and play songs on his phone from the vehicle’s music system.
Brain-to-vehicle technology. Development in IoT technology has brought in several modifications in the medical and healthcare field as well. The amalgamation of medical science and the automobile industry has brought in the creation of brain-controlled vehicles.
With brain-to-vehicle technology, a device is used to measure the activity in the brain that is analyzed by the vehicle’s system to maneuver it. This system empowers a human to control several vehicle functions just by thinking about them. Even though this method of maneuvering cars is still underdeveloped, it opens multiple doors for impaired and specially-abled people to experience the thrill of driving a car. It can also lower the chances of accidents caused due to sudden lane change and related unsafe driving practices.
Telematics. Telematics is a perfect tool for people who are hyper concerned about their cars’ safety. Telematics refers to the long-range transmission of data. Sensor applications gather data about the vehicle and directly transfer it to the smartphone of a car owner. IoT telematics allows a person to confirm the location, safety, and condition of its car at all times. The real-time alarm system warns the owner about the forceful opening of car doors. This remote monitoring of vehicle is helpful for managers who monitor and control a large fleet.
Fleet management. A fleet refers to several trucks or other load-carrying vehicles. Fleet managers often carry the heavy burden of monitoring and controlling the traffic of its fleet. An IoT-powered fleet management system allows a manager to easily track the location of every vehicle in the fleet. With use of different weight and quantity monitoring sensors, a fleet operator can also confirm the safety of the cargo at all times.
Intelligent infrastructure. V2I is another important application of the V2X network. The network connects vehicles with nearby infrastructures, such as traffic signals, signboards, petrol pumps and toll booths. A V2I network smooths the flow of traffic and avoids traffic congestions at various places. It also facilitates quick money transfers at petrol pumps and toll booths automatically.
Implementation of different technologies, such as IoT and artificial intelligence, has transformed cars into a moving computer. The market of connected cars is soon going to soar in terms of market cap and revolutionize the way we interact with our vehicles. The above applications are the evidence of the future that the technology of IoT will bring for the connected cars.
IoT is one of the most recurrent concepts in the planning of IT architectures today. IoT entails the connection of devices and data to each other via the internet. Contrary to what many may think, there are many advantages of IoT for small to medium-sized enterprise (SME). It is not a technology only for large companies.
IoT will facilitate the automation of processes, reduce operating expenses and improve customer satisfaction, which are the three basic pillars to optimize and make any business profitable.
IoT is especially attractive to the industrial sector, but it also has many B2B and B2C applications in other business sectors. The provision of sensors and the machine-to-machine interconnection generates information to start intelligent installations, such as factories, offices and shops, to know how the products are used or to optimize key processes such as the logistics chain.
Examples of IoT use in SMEs
Big data and IoT are deeply interconnected. IoT sensors allow collecting and constantly generating data. Data is optimally analyzed, to automate processes in business management and to make decisions based on real situations and behaviors to increase their profitability. Companies are already using IoT for the optimization of their business.
The sensors in strategic points of a company provide information about the clients in real-time, including the number of people present, the direction of their movement or if they have the company’s app developed by top app development companies. With this data, it is possible to propose individualized offers visualized in the devices.
The management of the warehouses can also be improved thanks to the IoT. The device in a bookshelf can vibrate at the moment when there are no more products in the warehouse.
Logistics companies can have information on each of the phases of a shipment as well as the resources involved in this interconnecting of different devices located in vehicles, warehouses and pallets. The data will give the key not only to improve customer satisfaction, but to save costs by detecting the most optimal routes and the most productive personnel.
The maintenance of facilities and machines is another area where you can see the benefits of the IoT. Imagine an air conditioner in an office that only activates if it detects that people are working. The precise location of sensors can also warn that something is not working well on a computer before breaking down.
What are the benefits of IoT?
It is a truism to point out the speed at which changes are taking place in the digital world. The change accelerates exponentially to the extent that before you learn about a tool, another technology is ready to displace it.
Technology is changing from static websites to mobile and social digital environments. Connecting to the internet and managing life from a smartphone or tablet was unthinkable less than a decade ago. Top app development companies are creating top-notch apps that were never thought about before.
It is in this scenario that the concept of IoT becomes increasingly relevant, a term used to define the integration in our daily lives of technological devices that connect everyday objects to the internet that provide data for its monitoring and control.
Although it is still an incipient technology on the horizon, there are already glimpses of the revolution coming alongside the development of IoT.
Little by little, many of the everyday objects that surround us will have an internet connection, including thermostats, refrigerators and cars. These items will be able to provide a huge amount of data, giving its manufacturers valuable information about its use and customer problems. This will allow companies to know their habits and even anticipate their demands, offering customized and predictive products and services. And this will create a change in the decision-making processes within the companies. Companies can contact top app development companies to get apps that will enable easy sharing of data.
Several sectors will benefit substantially from the development of IoT. For example, IoT will have a great impact on the management of infrastructures, including monitoring and control of traffic lights, bridges or urban and rural roads; detection of changes in structural conditions and immediate response in emergencies.
Thanks to IoT, brands can know what the problems of their consumers are at the same time as them or even before. With apps developed by top app development companies, companies can now get sufficient information from their clients, a circumstance that will not only facilitate the creation of more personalized and predictive products and services, but will also modify the business processes and work structure. Many jobs will disappear, and others will arise due to the need to have experts.
The huge proliferation of mobile devices ensures a broad database of customers, new products and services and knowing what information needs to be linked. There are presently lots of information on the internet, thanks to apps by top app development companies. But, which sectors can benefit from these innovation opportunities?
Infrastructure: Monitoring and control of traffic lights, bridges or roads , detection of changes in structural conditions, immediate response in emergencies and improvement of quality.
Environment: Optimization of resources when it comes to preventing and improving efficiency. For example, establishing quality control of air or water, atmospheric conditions or soil.
Industry and mass production: Programming repair and maintenance activities, control and centralized process management, optimization of the production chain and rapid response to product demands.
Energy: Remote monitoring of energy consumption, intelligent storage, detection and action systems and optimization of energy consumption.
Medicine and health: In this case, apps created by top app development companies can be used to provide operational data in real-time, enable emergency notification systems and remote surveillance or monitor and ensure the general welfare of the elderly or chronically ill.
Logistics and Transportation: Monitoring of transport systems that include the vehicle, driver, and infrastructure, intelligent traffic control, parking choice, implementation of electronic toll collection systems, logistics and fleet management or road assistance and security.
Entertainment: Improvement and creation of sensors in mobile devices, virtual reality technologies or consoles with motion sensors that serve to improve the user experience.
Although it seems easy, IoT requires a tremendously complex structure, in addition to special attention to the security of all stored data. However, its advantages and opportunities make it worthwhile. They add efficiency to our life, and its application is not excessively expensive. It opens up new business opportunities and improves the existing work processes.