This is the second piece in a three-part series. Read the second piece here.
How can companies deploy AI efficiently? It’s an important question to find the answer to, since industry sources estimate that as few as 29% of U.S. companies regularly use AI. In this article, I’ll explain why efficient AI is essential in propelling your company’s realization of the benefits delivered by ethical AI and explainable AI.
Efficient development resources
Computing power and software are the bread and butter of AI development. It makes sense to optimize both of these resources to maximize the efficiency of the way your organization builds AI solutions.
- Compute resources: How easily can compute resources be provisioned? If it’s a challenge to get large amounts of computational horsepower and storage on-demand from the IT organization, cloud computing is a better strategy. In the cloud, development resources and testing can cohabitate seamlessly, with compute power and storage dialed up or down as needed.
- Software resources: How many shared assets can analytic scientists leverage? Rather than writing code — including training algorithms — from scratch, open source AI tools give you the pre-packaged ability to build models quickly. An open source-heavy development environment in the cloud makes for maximum efficiency.
- Buying decisions: Even with the availability of on-demand compute resources and open source software, there can be a variety of purpose-built machine learning application enhancements you can use to super-charge AI adoption. These are often advantageous in analytic areas with years or even decades of development efforts and purpose-built technology, such as fraud detection, which would be very difficult to reproduce with commodity AI tools. These technologies often come in the forms of machine learning studios where APIs exist to access purpose-built machine learning algorithms, and often with example models to get data scientists familiar and produce rapidly.
Implementing best practices
In any aspect of life, not learning from mistakes makes for an inefficient future. AI development is no different. Data scientists who have managed analytics, AI and machine learning development teams have the experience to know the mistakes every new scientist makes, many of which can have significant negative impact.
However, true efficient AI development is gained through the experience of not just individual managers, but the entire organization. The most efficient organizations provide access to lessons learned and AI assets beyond open source, as well as taken the time and resources to implement methodologies and resources for training, collaboration, code testing, unit testing and ongoing knowledge sharing.
Specifically, organizations that take best practices seriously have shared code assets, automated testing and entire development processes that tie directly into AI governance. The development processes help ensure that costly mistakes are not made during the haste to be efficient. Best-practice processes come with valuable code, tools and testing that allow models to be built quickly and utilized with confidence.
Ultimately, efficient AI is AI that solves a business problem quickly; it’s not necessarily who builds the model the fastest. Efficient AI organizations focus on deployment and understand that AI runs within a larger software cradle, which is metaphorically rocking 24/7. Thinking about the end game of where the model will be deployed should be the starting point of any AI development. Without it, the model build should not proceed. Once the constraints, such as data, latency, storage and software, are understood, then AI can be built to ensure the model can live and operate in an environment where its value can be achieved.
In other words, you can develop an effective model quickly, but it has to be designed from inception to run within an operational environment. The model must process a certain number of transactions per second — within latency limits — and with clear expectations of all lifecycle stages, such as production, support and maintenance. From my meetings with data science organizations around the globe, this is the biggest challenge I see. The truth is, they can’t deploy a model because it’s built in such a way that it can’t be operationalized. Operationalization is hard, and as such it takes deep architecture discussions with the software developers, IT and data scientists to achieve success.
Steps toward efficiency
Building efficient AI is an attainable goal, but it doesn’t happen overnight. Here are two steps to focus on to get your organization moving in the right direction:
- First, understand that data scientist and software developer roles are merging. Many of the people on my team are very effective at software; they understand Kubernetes, Docker, Java and APIs. Our professional service teams are nearly at the same level of expertise as senior enterprise software developers. Today’s AI and machine learning scientists need to have an extremely granular understanding of the software implications of all their work products and the most successful will identify with — or as — software engineers.
- Second, from a business perspective, companies must take advantage of institutional knowledge from across their organization. Organizations that don’t have a available AI experience could develop a strong peer review focus and agile development processes for AI projects that include important checkpoints such as unit tests, functional tests and what-if model tests. Those lacking these abilities should work to bring that expertise in through consultation or, even better, a board of advisers that will review AI initiatives bringing critical feedback into the process.
At the end of the day, efficient AI development comes down to people, process and technology. You’ve got to inventory the building blocks you have right now and develop plans to acquire the rest.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
As we continue to add streaming capabilities to data infrastructures, the amount of data created by IoT and connected devices is expected to reach 847 zettabytes per year by 2021, leaving organizations with a new challenge to overcome: storing and analyzing this massive amount of data for the best business outcomes.
IoT and connected devices contain real-time data flows or streaming data sources that must be managed and assessed in real-time, because some of the data can be time-sensitive to an organization. Using the proper type of data management system with AI and machine learning-powered analytics allows you to not only react in real-time, but also perform multiple rounds of cross-sensor and historical analysis to get the most from your data.
Use streaming analytics to understand complex IoT data
Being able to understand the data collected at the edge begins with using the right data management tools to adequately perform an analysis, which provides the most beneficial data-driven decisions. However, the use of traditional analytics tools simply cannot meet the requirements today to perform real-time analysis on this scale of complex, fast-moving data. Next-generation technologies are required to meet the data challenges of today and tomorrow.
The two critical factors that limit the value of data in most businesses is the depth of analysis and the speed of analysis.
For example, consider the retail industry. Using a traditional analytics tool that only stores historical data would allow the retailer to analyze an increase or decrease in demand for a specific product as a whole over a certain time frame. Historical data can tell the retailer that a certain product performed better in terms of sales compared to another product, therefore the first product is better. However, what if this is not the case?
By leveraging the power of streaming analytics and location intelligence combined with the historical data collected over time, retailers have the ability to drive accurate replenishments of a well performing product to locations with a higher demand for that product.
Traditional analytics tools are simply not cut out to perform analysis on the incredible volume of data streamed and stored at the edge. Businesses looking to perform an accurate analysis of their data must look towards an active approach to data analytics by combining the power of historical analytics, streaming analytics, graph analytics, location intelligence and machine learning-powered analytics to make data-driven decisions in real-time.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
IoT is maturing fast and 2020 will be a tipping point where companies will begin to take advantage of connected technologies. From what we see, a stronger return on initial IoT investment is creating momentum with companies moving quickly out of planning and accelerating through early deployment and into extensive networks of insight and experience, unlocking IoT solutions.
One of the sectors advancing quickly is facilities management. Companies are looking to transform workplaces to inspire their people with flexible spaces that bring a new spirit of creativity and productivity. This is creating new opportunities for building owners and operators to generate higher revenues and lower costs.
The shared workspace booms
Workplace studies have shown that optimizing people’s workplace experiences through the use of connected technology has tangible productivity benefits. As a result, shared workspaces are popping up around the world at an extraordinary rate. We’re seeing a spike in remote workers seeking out WiFi-enabled places to work and mingle with other “digital nomads”, triggering a global trend estimated to reach more than five million people in 2022, according to Emergent Research.
This social trend is being supported by an increasingly pervasive deployment of IoT technology to optimize internal and external experiences and services, which reinforces the combination of IoT devices data with digital data to positively change the economics of businesses.
IoT and analytics are key to smart spaces
IoT technology for an office space often consists of a network of sensors that monitor occupant activity or environmental conditions, such as temperature and humidity. Not only can they monitor these conditions, but they can also control devices such as smart locks and smart plugs, which gives both the facility managers and tenants more granular control and personalized experiences. These sensors are typically deployed throughout a building, allowing property managers to capture valuable information on how employees or customers use a building’s available space.
For example, occupancy-detection sensors can determine that a large conference room is rarely more than 50% occupied, while the facility manager’s access control or booking systems highlight that smaller meeting rooms are over-subscribed. With that information, a shared workspace provider can split the conference room into two smaller rooms, allowing the company to serve more occupants, improve availability and generate more revenue. Conversely, if sensors reveal that the rooms are occupied more frequently than the room reservation system indicates, the provider can act to make sure occupants are paying for the rooms, thereby recapturing lost revenue.
Other types of IoT sensors that can help optimize a shared workspace include beacons, cameras, tags or Wi-Fi access points and access control readers, all of which can capture data on how different spaces and resources are utilized. But all these disparate data feeds from a diverse range of sensors require managing, updating and securing, so it makes sense to deploy an IoT platform that can streamline all these tasks, allowing property managers to focus on how space is used instead of figuring out how to better deploy IoT.
Information from a diverse range of inputs can then be consolidated into one dashboard, then modeled over time to plan and allocate space for maximum efficiency. By providing improved visibility into how space is used, an IoT platform can allow property managers to operate their space more efficiently and help increase their revenue per square foot.
Thriving in Dublin
One example of how this is being deployed in the real world comes from Dogpatch Labs, a shared workspace provider in Dublin that is the epicenter of Ireland’s start-up ecosystem. With more than 40,000 square feet on three floors, the Dogpatch Labs co-working environment has a mix of dedicated offices, an urban garden and event space, and a hot desk area where techies can plugin by the hour or for the day.
As a mixed-use space that hosts a blend of temporary and long-term occupants, Dogpatch Labs must allocate space dynamically. To do that, the company uses a mix of cameras and IoT sensors, analytics and visualization software to understand how the space is utilized.
By merging data from physical IoT systems with data from digital systems, such as an enterprise room-booking application, these systems can yield powerful insights. Building operators can create better floor plans that could provide more occupants access to natural light, which can enhance their experience and increase renewal rates. It allows them to improve the scheduling and utilization of high-demand, shared assets such as conference rooms.
Bringing smart spaces technology to new industries
As you might suspect, these capabilities are valuable to other businesses and industries beyond shared workspaces. For example, hotels, restaurants, retail outlets, art galleries and shopping malls can adopt the same approach to improve conference space scheduling or simply make better use of underutilized spaces at specific times.
New entrants and early pioneers alike are benefitting from insights based on physical IoT and digital information that can positively affect the bottom line through lower heating and lighting costs, while optimizing operations. They’re combining this with IoT-driven insights that can enhance the user experience, which ultimately drives revenue through increased loyalty to gain a competitive edge in an increasingly competitive market.
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.
Once viewed as science fiction, devices such as smart doorbells not only exist, but are relatively commonplace. Unfortunately, the software and chipsets that make these devices “smart” has also made them a target for cyberattacks and, as you might have seen in the news recently, Ring doorbells and cameras are the latest in a long list of IoT devices compromised by attackers. More than 3,000 Ring accounts have had their credentials compromised, resulting in a number of highly publicized incidents. In one case, a hacker accessed a Ring camera in a young girl’s bedroom and told her to direct racial slurs toward her mother and generally misbehave.
Although terrifying, this is not the only major incident reported. Ring users have reported other incidents, such as hackers taunting them through their cameras, which has led to a class-action lawsuit being filed in California. Ring issued a statement insisting that their systems were not breached, and that the problem was due to outside systems being compromised. The statement indicated that the credentials used to “hack” the devices were in fact duplicate credentials that had been obtained from a separate, non-Ring service and used to access the accounts in question.
What happened and why
Attacks similar to those targeting Ring devices are known as “credential stuffing” attacks. When a user’s account information is compromised in a data breach, those stolen credentials might find their way into the hands of malicious actors who will attempt to “stuff” them into other systems. Due to the frequency with which individuals reuse passwords and other login information, a hacker with a large set of stolen credentials to work with will invariably find a number of accounts that they can breach.
Ring’s advice is sound: frequently changing passwords and using two-factor authentication are smart steps to take. That being said, the statement implies that the hacks are solely the result of user error, which obscures Ring’s own responsibility for device security. Manufacturers such as Ring can and should build additional security into their devices, particularly as this is not the first time the company has popped up in the news for an incident such as this. Ring has made headlines for issues ranging from leaking Wi-Fi credentials to users remaining logged into a device even after the password changed.
This most recent breach also demonstrates a failure to learn from the mistakes that led to the Mirai Botnet, the most famous example of malware that took advantage of weak IoT credentials. The botnet, which used default passwords to access a variety of IoT devices, clearly demonstrated the danger posed by static credentials. Use of static credentials places undue burden on device users and are increasingly inadequate when today’s advanced authentication technologies would inherently prevent such hacks.
Repairing the damage
Ring might be the company in the news right now, but it is hardly alone in its need for stronger security measures. The early days of IoT are over, and the technology is now being adopted en masse. As it becomes increasingly widespread, IoT demands more tailored security solutions. The weak or nonexistent security that accompanied IoT devices in the past is no longer acceptable in the marketplace, and the vulnerabilities that these very public hacks have revealed have damaged consumer confidence. It is incumbent upon the makers of these devices to restore that confidence.
External regulations are beginning to come into play in that regard. The European Union and the state of California have each taken a strong stand on the issue of IoT security, enacting legislation that requires additional protections for connected devices, and other governmental bodies are following in their footsteps. Government bodies such as the FDA have also begun to step in, implementing regulations and guidelines of their own. Security is already a must-have for market acceptance, but it will soon become a necessity for basic compliance across many jurisdictions.
The future of device security
There are a number of steps that manufacturers can take to prevent breaches similar to the one that affected Ring. Requiring multi-factor authentication and using certificate-based authentication for devices are two major steps in the right direction. Simple measures such as these can go a long way toward preventing breaches — even those typically caused by human error — and demonstrate that the manufacturer is taking security seriously.
In addition to protecting the device from attacks, security means protecting the integrity of the device and enabling device identity, so that encrypted communication over the internet can commence safely. There are many ways to accomplish these goals, including:
- Device Identity Certificates: Digital certificates added during the manufacturing process ensure that the devices are authenticated when they are installed on a network before communicating with other devices on that network.
- Secure Boot: Ensures that a device has not been tampered with between the initial “power on” and application execution. Developers can also use it to securely code sign boot loaders, operating systems, application code, microkernels and data.
- Embedded Firewalls: Embedded firewalls prevent communication with unauthorized devices in addition to blocking potentially malicious messages.
- Hardware Roots of Trust: For devices that handle particularly sensitive information, such as medical devices, manufacturers should consider using a trusted platform module or an embedded secure element for secure key storage and to establish a hardware Roots of Trust.
- Secure Remote Updates: Secure remote updates ensure that components are not modified and are authenticated modules from the manufacturer. Validating that device firmware has not been modified before installing it is a critical security element.
Safeguarding devices and data from cyberattacks is an ongoing challenge, and no solution will ever be perfect. It’s a constant tug-of-war between attackers and defenders as they each strive to stay one step ahead of the other. Hackers are always devising new methods of attack, even as cybersecurity teams develop new ways to stop them. Staying abreast of new attack vectors, ensuring compliance with new regulations and accepted best practices, and building security into new devices from the start, will provide the strongest possible defense against future cyberattacks.
The energy transition is at an inflection point. The changing climate demands an urgent shift from historical reliance on fossil fuels to widespread integration of renewables. Data, made possible by pervasive IoT, is the currency fueling new business models for utilities and end-users to speed up the energy transition.
In the coming year, IoT and data will play an integral role in advancing the energy transition. Here’s how:
1. Transforming current business models to support prosumer-driven renewables integration
In the past, power reliability was relatively simple. Power plants produced energy and then distributed that energy to end users. Today’s landscape is much more complicated. When energy is produced, there is a global urgency to reduce the environmental impact of production.
Decentralization of power distribution has taken hold. Distributed energy resources (DERs) are rapidly coming into the energy mix and are on pace to surpass fossil fuels in many countries around 2025. With the development of DERs, energy consumers are becoming producers, also known as prosumers. This prosumer transformation is opening a welcomed door for creating new business models to better serve commercial and industrial end-users with a sharp eye on sustainability goals.
In 2020, the acceleration of data will transform the common business model for utilities in both regulated and de-regulated markets. Yet, the burning question remains: How can utilities manage the profound impact renewables will have on their traditional business model? If you fast forward to a grid player 10 years from now, there could be a time where the need for energy from utilities is zero, as well as other times when everyone requires grid energy at the same time because of environmental factors, such as weather fluctuations. This scenario isn’t about choosing the right technology. Rather, it’s about leveraging innovation to create wholly new ways of doing business.
We can look to the early days of the internet as a strong parallel to what is now happening with utilities’ rapid adaptation to the energy transition. If you remember the early days of the internet, we were all paying by data volume. That is the current model: customers pay by kilowatt consumed per hour. In the internet space, we pay to be connected with a guaranteed level of bandwidth. You don’t pay by traffic anymore.
A similar disruption is brewing for the long-standing utility business model — one that will have to account for the rise of prosumers in the commercial and industrial space.
2. Moving from connecting things to managing data for 24/7 reliability with renewables
The story of IoT has evolved by leaps and bounds in recent years. No longer are we talking about connecting things and objects. Connectivity on a massive scale has arrived, and the groundwork for connecting grid infrastructure with proven, robust technologies has been solidified. But data quality and sharing are presenting new challenges. Twenty one percent of companies aren’t sharing their data enterprise-wide, and only 18% are using IoT to obtain energy and sustainability data, according to Schneider Electric. The focus this year will be on improving the quality of data from these connected assets and leveraging data insights to support reliable renewable integration.
IoT and data analytics are enabling the kind of energy flexibility needed to add more environmentally friendly sources of energy without giving up power reliability and availability. With flexibility on their side, end-users and utilities can manage the variability of renewals and power adjustments based on external conditions from grid operators. In fact, more than 200 big companies are committed to RE100, setting a public goal to source 100% of their global electricity consumption from renewable sources by a specified year. As of September 2019, those companies will demand more than 220 terawatt hours a year. This is equivalent to eliminating 40 coal-fired power plants in one year.
3. Strengthening collaborative ecosystems to bring AI, IoT and cybersecurity to new levels
When you look at IoT end to end, it’s clear that no company on the planet has a technology stack that can cover everything. There is a need for a collaborative ecosystem to design, install and operate IoT-based solutions, such as weather forecasting AI models that empower end-users to better forecast, control and lower energy use. This type of competitive collaboration is not new, yet it is a burning issue in the context of IoT because the complexity of an end-to-end approach really deserves to have multiple partners to get it right.
New generation developers want to work in open, collaborative ecosystems instead of betting their individual knowledge and expertise on narrow, proprietary use cases linked to only one company. The payoff here for the energy transition is a collaborative ecosystem teeming with specialists and experts coming together to respond urgently to the climate crisis.
Within this framework, we can expect an acceleration of data as a service (DaaS) opportunities. DaaS is the continuation of a movement we have seen in multiple industries in the past around open data. Either by regulation or decision, more organizations are publishing data sets for the sake of sustainability efforts. This approach could shift to a model associated with revenues. For example, if you are a large facility developer, you could create new revenue streams to make data sets available to improve building energy consumption within the parameters of data privacy and confidentiality.
Ecosystems can make these data sets available to third parties. In addition to fine-tuning more sophisticated energy-related AI models, data sets can push forward cybersecurity efforts. Although connectivity never comes without cyber risk, defenses enabled by AI can flag anomalies to initiate early rapid response to hackers targeting endpoints across grid infrastructure and end-user environments.
For several years now, IoT has dominated conversations and decisions about technology investments. But most conversations start and end with connections, failing to look beyond to the innovative and disruptive potential IoT brings to the table. From independent objects, processes and people operating in isolation, the real power of IoT lies in its ability to foster connectivity that drives collaboration and information sharing within a world powered by technology innovation and data-led intelligence.
But despite IoT’s rapid adoption and the opportunities it offers consumers and business users alike, IoT has not yet reached its full potential. There are lingering fears about security and data privacy, and IoT itself is rife with tactical planning that fails to realize a vision that moves organizations beyond the basics of device connectivity.
To achieve a bolder vision centered on an advanced form of IoT, CIOs have a powerful role to play working with their C-suite peers to transform their enterprise’s core DNA and, in the process, change their own roles from cost-savers to revenue-generators. But they need to embrace and deploy clear, strategic IoT programs that encompass intelligent systems acting autonomously while balancing the considerations that come with a connected future.
Harness the full potential of IoT
To start, CIOs must help educate the leadership team to view IoT as more than just sensors collecting real-time data. In fact, CIOs need to believe in and position IoT as strategic to the business so it can have transformative results. By harnessing the full power of IoT and devices acting with intelligence on their own to achieve more efficient operations, enterprises can deliver superior customer experiences, foster collaboration across their business ecosystems, fuel growth and innovation, and deliver on the promise of sustainability and positive environmental benefits.
These examples prove, when used to its fullest potential, that IoT can and will change the world. But with 14 billion things already connected to the Internet and another 11 billion expected by 2021, it is easy for enterprises to lose their way with IoT initiatives.
IoT, automation and AI
Augmenting IoT with automation and AI is where the real promise lies. This combination will take IoT –and the businesses that leverage it — into a new era of connected ecosystems yielding exponential value. In this context, CIOs and technology leaders with expertise in IT infrastructure, data networking, mobility and security are best equipped to lead the way. But CIOs can’t do this work alone. They need to partner closely with the business to navigate an increasingly complex landscape, with the first port of call being developing a multi-year, structured plan that offers a clear path to value.
From the perspective of IoT, this plan is about helping enterprises gain real-time insights on their products, processes, and people and augmenting the physical context with data-driven cognitive insights to power intelligent decision-making. With this approach, enterprises can build value chains where self-aware devices interact with each other. By combining contextual information with AI-led insights, devices will become increasingly intelligent to a level where decision-making can take place at the point where the information is gathered by the device. This enhanced digital intelligence will be a synthesis of human, artificial and cognitive intelligence. In this state, physical objects and processes will come to life as they pulse with data. When harnessed, it will create exponential value for the enterprise and its customers.
For example, consider the medical device industry. Although IoT has enabled connections across the ecosystem — from heart valves and patient monitors to care providers and pharmacies — the lack of integration among these parties often has resulted in poor patient experiences and sub-optimal health outcomes. However, by augmenting this care ecosystem in real time with human and cognitive expertise and pairing that with vast global research, new medications and drug discoveries, the healthcare industry can truly deliver better outcomes for patients and elevate the role of care providers.
As devices start communicating and collaborating, they will develop capabilities to act intelligently, moving the proverbial connected needle from self-aware to self-healing. For example, think of a smart factory. Increased connectivity and collaboration can help prevent collisions and reduce workplace accidents, improving worker safety.
In addition, this powerful combination can improve monitoring systems, processes for predictive maintenance and even enable enhanced sustainability initiatives. By setting a multi-year plan that drives toward acting intelligently, CIOs will unlock the latent, unexplored and limitless possibilities of IoT.
To maximize these benefits, CIOs and their technology teams need to evolve their thinking to encompass the following three principles:
Boundaryless. Embedding sensors in products can offer insights into product performance, but taking this to the next level requires breaking down enterprise silos to connect data from multiple organizational departments. CIOs should look beyond the boundaries of enterprise systems to include partner, supplier and customer data. Through these connections, enterprises can unleash new business models and revenue streams, harnessing multiple value chains and cross-industry ecosystems aligned with their own business purpose.
Pervasive. For future-ready ecosystems, decision making needs to be democratic. As systems evolve and become automatic, they must be backed by data-driven intelligence. From this perspective, owners of data will need to provide trust-based access across the ecosystem to overcome lingering privacy concerns, fueling new possibilities for growth and innovation.
Experience rich. Looking beyond using data to simply track and manage products, CIOs need to leverage product usage data to discover and respond to the evolving needs, preferences and possibilities of ecosystem stakeholders. There needs to be a seamless feedback loop for frictionless value creation, delivery and consumption to select the most efficient path to value.
Some enterprises, such as Damen Shipyards Group, encompass these elements to help drive their business purpose. For example, Damen Shipyards Group deployed a robust, integrated IoT platform that connected its vessels, collecting data from the thousands of sensors on board to improve safety, sustainability and efficiency.
It also connected the enterprise’s ecosystem players, such as employees, customers and suppliers, to use a single system to track vessels and manage their performance, as well as to keep suppliers informed about when a part or system was due for replacement. Suppliers could then ship the needed part ahead of a failure for quick service, which kept the vessels working and helped to regulate the ship’s carbon footprint. It also helped to deliver goods to their destinations faster.
With this information, enterprises can more effectively work with clients every step of the way — from vessel launch to decommissioning — and offer services such as predictive maintenance, remote support, fuel consumption savings and improved safety.
However, not all enterprises are this advanced with their IoT strategies. Bringing these strategies to life requires executive sponsorship at the highest level, collaboration both within and outside the organization, digital expertise and a daring vision for unlocking the exponential value of IoT.
By augmenting the physical with human, cognitive and digital intelligence, enterprises can maximize their IoT investments to create powerful ecosystems and build new business models, delivering positive outcomes for their customers, employees, partners and even the ecosystems in which they operate.
CIOs shouldn’t be afraid to be bold and to expect more from IoT. The possibilities for transformation with IoT are truly limitless for enterprises today. The key to success is a strategic plan for bringing life to things.
Fires cause roughly $10 billion in property damage every year in the U.S. and unfortunately injures or kills thousands of people. Ensuring that properties are well equipped with the best fire safety technology and solutions is the only way to mitigate this tremendous problem.
Specifically, fires in commercial buildings can spread in a matter of minutes and cause incredible damage to the property and its occupants. So how do we ensure we limit the impact? The answer is simple; early detection. This is key to maintaining the safety of tenants and reducing the amount of property damage caused by fires.
Benefits of smart smoke sensors
During the past few decades, technology has continued to improve, enabling first responders to more quickly combat fires. In the recent era of IoT, smart smoke detecting sensors have drastically helped firefighters better sense the magnitude of a fire and the best course of action to combat it.
One example of this is smart exit signs that include LoRa-enabled sensors that analyze the impact of the flames and help the buildings’ occupants navigate complex hazardous zones in real-time by indicating the quickest and safest direction out of the premises. Companies such as HEX SAFETY, a smart fire prevention company based in Taiwan, create and implement these dynamic exit signs.
When you look at a typical building today, the conventional exit signs only signal where the closest exit is, which might mistakenly lead people into hazard zones. On the contrary, smart exit signs help communicate with the building’s existing fire alarm system and sends the safest direction to every smart exit sign in the building. By enhancing peoples’ decision making and shortening the exit route, smart exit signs significantly increase chances of survival.
By implementing a fire detection solution comprised of smart sensors, firefighters can detect heat, smoke, gas or flames associated with fires earlier, and implement firefighting tactics and deploy personnel more quickly to either prevent or reduce the impact of the fire. Every building must have exit signs and making them intelligent only furthers the potential for saving lives.
The new year is an ideal time to reflect on what’s changed and what’s on the horizon, especially in an era where each day seems to bring new technological advancements. While this list is by no means a comprehensive collection of everything organizations will have to weather in the next year and beyond, these four trends are some of the ways IoT will impact organizations in 2020:
1. Enterprise applications move to the cloud
Many businesses are already in the process of migrating business data, applications and processes to the cloud. This change will drive every endpoint in a workplace to become a connected IoT device, with all data being stored in the cloud as well.
Some of these endpoints are easily recognized, such as desk phones and equipment in meeting rooms, while others might be unexpected, such as badge readers at the front door. A device like a badge reader has been in offices for decades, but as these types of everyday services move to the cloud, companies will be able to do more with them. For example, your badge swipe in the office could trigger a notice to your teammates where you are working.
Moving these endpoints to the cloud also means IT teams will have to change their support strategy. For example, IT teams might have to get out of the business of running servers for applications and services and into the business of providing highly robust internet connections and modern network security.
2. Enterprises crack down on endpoint security
As everything goes to the cloud and more endpoints become connected, the benefits increase; but so too do the risks. The potential impacts of putting all of your critical business functionality in the cloud is significant: With pure cloud services, internet outages can cripple important functions, privacy concerns become more difficult to address, businesses’ costs for the data center processing will be higher and every IoT device becomes a potential entry point.
IT teams must maintain a laser focus on security in order to balance the benefits of the cloud with the inherent risks of connecting everything and hosting all that data where it is potentially accessible to hackers and outside threats.
3. New regulations add a layer of complexity and confusion
California has become the first state to specifically regulate the security of connective devices with a law that went into effect January 1st, 2020. This is not only unexplored territory, but it’s also not totally clear what a connective device means and how it will be enforced. The language of the law itself is ambiguous.
Before laws such as this, manufacturers would develop devices to individual standards they found acceptable. However, what a company finds reasonable and what is required by law can now become two very different things. And the law’s method isn’t always the more secure way.
What is clear is that people are starting to think more about IoT devices and how they should be regulated, and more legislation such as the California bill is likely to be enacted in the future on both state and federal levels. However, IT teams shouldn’t wait for legislation mandating security measures. Instead, they should proactively ensure any connected device within their organization has the appropriate data protection and security measures in place.
4. More management technologies move to the cloud
New cloud-based management technologies allow organizations to simultaneously configure, deploy, monitor and manage multiple connected devices at once.
Previously with on-premises software, many organizations would install the software and then wait until it became essential to upgrade. This means they would be running outdated versions without the latest security patches or bug fixes for months or even years. Now, cloud-based management software ensures updates will be automatically added as developers release them. As a result, companies will always be running the latest versions with the most accurate security features with no effort needed on their part.
Additionally, the capabilities of the cloud, including much more advanced AI and data analytics, will allow IT support staff to become aware of issues much more quickly and enable them to solve these issues from anywhere with an internet connection.
These four trends are just some ways IT teams need to prepare for new technology in 2020. The best way IT professionals can stay ahead of the curve is to ensure they partner well with the management teams within their organization because it’s not the technology that limits us anymore, especially with how fast cloud services can move. Rather, it’s about how fast employees can manage the change to improve their productivity. Establish best practices and ideal workflows, and you’ll be ready to tackle whatever 2020 — and the future — might hold.
IoT offers a myriad of opportunities for value creation and capture. By 2020, there will be 31 billion connected IoT devices, according to Deloitte. These numbers often get thrown around, and while staggering, they aren’t surprising. They represent a fraction of what will likely exist in the future.
As the smart revolution matures beyond its conceptual stage, the furniture industry is beginning to emerge within the IoT market. The Apple Watch, Alexa and FitBit might be popular examples most people default to when thinking of IoT devices, but everyday items such as furniture are quickly joining them. The global smart furniture market is estimated to grow at a compound annual growth rate of 21.8% and reach $794.8 million by 2026, according to PRNewswire.
Designers are looking at connectivity as another differentiator beyond style, quality or price. The physical components combine with the digital capabilities to create smart furniture. Passive materials that have been used for years in the creation of furniture, such as wood, fabric and metal, merge with electricity to create new forms of utility and comfort. For example, a sofa that rearranges via application-controlled gestures, a wardrobe that keeps your clothes clean and wrinkle-free and a mirror with a built-in electronic display are quickly coming to market.
However, one key roadblock remains; how to power all these new devices.
Many IoT furniture manufacturers face a choice between batteries and power cords, each with their own set of issues. Batteries have a limited lifespan and need to be replaced. Power cords have an unlimited supply of energy, but they’re attached to outlets and restrict the mobility of the furniture and the freedom of the user.
Advantages of long-range wireless power
Long-range wireless power provides the ability to deliver power from a distance without wires, batteries and charging pads, which might be the solution to current manufacturers’ problems. Let’s consider this in more detail.
Powering phones and other mobile devices
Mobile phones have become such important devices in our lives that people use them continually throughout their day. As a result, many people require the ability to power or recharge them from anywhere. Charging from a wall outlet is sometimes possible and impractical. For example, one might be sitting in a hospital waiting room or the lobby of an office building. A receptionist might be working at a rolling cart, or a college student might be studying with a lap desk. If there was a charger that is part of that chair, rolling cart or lap desk, one could charge the phone with ease.
Powering the furniture itself
Height-adjustable desks are becoming popular and there is ample talk about the benefits they provide. Electronic height-adjustable desks that can adjust the height at the push of a button are even more popular because they don’t require any physical effort and can remember preset height settings. When such a desk is mobile or not located near an outlet, an alternative source of power is required.
Additional examples of powered furniture might be a gaming chair with built-in audio and vibrations, or a powered recliner. In all these cases, the user might not want to be mandated to place the furniture near a power outlet in order to run a cable to it.
Powering sensors that attach to the furniture
Sensors that attach to furniture can save energy and efficiency. For example, when a shared office building provides cubicles for temporary workers, the ability to sense whether a chair or a desk is being used can turn off lights, control the local temperature or inform the manager that the cubicle might be available.
How can we get this power?
Furniture can benefit from electrical power, but what if an outlet is not available? Powering all of this technology using alkaline batteries will be untenable because these batteries will need to be replaced or recharged often.
This is where long-range wireless power comes in handy. By delivering power from a distance and without wires, long-range wireless power provides a new option for furniture designers and users that allows them to get the power they need, without cumbersome cables or expensive batteries.
Wireless power uses an intermediate physical phenomenon, such as radiofrequency or ultrasound, to send power from a transmitter — that is connected to an outlet — to a receiver that is part of the furniture being powered. A new and promising approach is to use infrared radiation (IR) light, which is the same kind of invisible natural light that is abundant outdoors and similar to the one in your TV remote control. Long-range wireless power systems that use IR light can deliver meaningful power, safely and efficiently at room-sized distances to small receivers that are easy to embed.
As more smarter devices reach homes and offices, furniture must also adapt to the new requirements, and more flexible power solutions must follow to support them. Long-range wireless power is something to consider as a solution to the current power problems. Designers armed with more than batteries and power cords have more room to innovate, simplify and add value.
One of the hottest topics in the economy relates to the cost of healthcare. A substantial part of this involves the use of technology for improving longevity, quality of life and, of course, reining in healthcare costs. Among the technology domains are medical technology devices for diagnostics, medical procedure assists and delivery of medications and services.A high cost area is providing healthcare at the lowest cost point of service. All of these are directly taking advantage of the use of IoT technology to improve outcomes and reduce costs.
Here are a few of the popular areas in healthcare IoT for 2020:
Robotics are not new in healthcare and, in many cases, the current crop of robotics already use integrated, smart, connected IoT technology to monitor system performance, provide human assisted control and to gather and process health sensor data. In 2020, it should be expected that the range of robotic assisted capabilities will expand and become increasingly sophisticated and intelligent.
By assisting with patient monitoring, healthcare facilities are not only managing costs but enabling them to provide a higher level of patient care. Given shortages of qualified healthcare professionals and those in related health services, robotics are one way of filling the gap on routine processes. In such applications, IoT technology is key in enabling the healthcare facility to gather necessary information and apply intelligence on the state of patient health and, as necessary, deploy other resources to assist with urgent medical issues.
In a facility, things such as sample routing or delivery of consumables are relatively simple and routine parts of facility management. Expect to see increased use of robots for such activities. In addition, this activity has to be monitored and integrated with other health and supply management infrastructure.
Health monitoring and sensing
One of the greatest challenges affecting many societies is the aging of the population. It is well known that healthcare, nursing and assisted living facilities represent high cost points of care. Being able to have the aging population safely live at home for as long as possible represents an opportunity for cost containment as well as improvement in quality of life. This is an area where significant development is already underway and is an important domain for IoT technology as an enabler. There are myriad companies currently working on pieces of the solution from wearable devices monitoring vital signs to environmental sensing to tracking movement and activity. All these are domains in which sensing, communicating and creating appropriate response actions are key. In the past, these have been treated as point solutions. Development continues in these areas. However, the biggest area for improvement is in the incorporation of all sensing and monitoring into integrated systems with intelligence to ensure that those living at home are not simply abandoned in place.
Much technology today is targeted at gathering specific data and the development of AI to act on specific sensor responses. In 2020 and beyond, the big win from the IoT front end will be the aggregation of disparate pieces of data and using this to intelligently anticipate the onset of health issues or incidents. IT pros should not expect leapfrog intelligence in 2020, but it is reasonable to expect that such integrated systems will become increasingly intelligent.
Monitoring and destroying pathogens
It is well known that the environment in a healthcare facility can contain extremely toxic pathogens on surfaces and in the air. Hospitals and health care facilities implement rigorous procedures for cleaning and containment in order to prevent the spread and dispersion of pathogens. Despite the best practices and procedures, pathogens continue to exist in these facilities and have a nasty way of migrating from place to place. There is significant activity underway in development of systems to kill pathogens using technology other than chemical agents.
Among the emerging technologies are those using high-powered UV LED technology. Fluorescent UV has been around for many years, but legacy systems are not particularly durable and performance degrades over time. Combined with robotics and other permanent infrastructure, UV destruction of pathogens using LEDs is emerging – especially as the costs and performance of the technology continues to improve. IoT fits into the picture as the deployment and tracking of usage for such systems rolls into facility infrastructure and processes.
Much research is also underway in rapid detection of pathogens that are airborne or present in or on the human body. There is a significant IoT role in this as well. Developing IoT detection devices at low cost could target and isolate pathogens with specific genetic characterizations. While still in early stages and not yet ready for mass commercialization, this technology brings the promise of early detection and isolation of disease before those effected are introduced into the hospital environment. Once sensors or mobile devices can rapidly detect pathogens, this information could be analyzed in a backend infrastructure to isolate affected individuals and intelligently map trends among the population and facility.