IoT Agenda


October 18, 2019  5:07 PM

Why connected devices aren’t always as smart as you think

Michael Greene Profile: Michael Greene
connected devices, Cyberattacks, Data privacy, Data protection, Internet of Things, iot, IoT cybersecurity, IoT devices, iot security, Security threats

As the holiday shopping season looms on the horizon, sales of connected devices are expected to flourish. From a plethora of intelligent assistants such as smart fitness mirrors and connected doorbells, there is a connected device for you. However, these devices are often a hacker’s prime target due to lax security.

While a lot of time and money is invested in the features and functionality of these devices, security is often woefully neglected in the rush to get products to the market. This has been a key driver in manufacturers deploying default passwords as standard and failing to ensure that software is frequently updated.

The looming regulation in California — coming into effect in 2020 — should help to reduce the use of default passwords, but it will not eradicate them. It is the first regulation in the U.S. that will help ensure manufacturers of IoT devices equip their products with security features out of the box.

However, many manufacturers appear to be ignoring the pending regulation as evidenced by the 600,000 GPS trackers that were recently manufactured in China, and have been shipped across the globe. These devices have a range of vulnerabilities including a default password of 123456. Making the situation worse, these devices were to help parents track their children. This is just the tip of the iceberg in terms of the magnitude of the default password problem.

It’s clear that the rapid growth of IoT is resulting in many vulnerable devices entering our homes and businesses, expanding the potential attack vector for hackers. By 2020, a staggering 25% of cyberattacks within enterprises will involve IoT devices, according to Gartner.

If manufacturers’ recent track record is any indication, we can expect many organizations to continue to circumvent IoT security regulations. At the same time, the U.S. government shows no urgency in punishing these organizations or enforcing broader policies. As such, the responsibility falls to consumers and employers to take action and mitigate the security risks associated with smart devices.

To do this, consumers and employers must explain the steps people need to take to protect their personal information when using connected devices. For home use and enterprises, it’s about replacing default passwords before devices connect to the network. However, it’s also important that the new password is both strong, unique and uncompromised before using or connecting the device.

You wouldn’t drive your car without a seatbelt on, and you shouldn’t use a smart device with a default password. It is also recommended that IoT devices are not connected to networks with personal or corporate data. Many security experts recommend connecting them to a hidden guest network with separate security settings.

As the physical and digital worlds continue to blend, security must play an increasingly prominent role, and everyone must educate themselves on how to protect their valuable data. This holiday season, make sure that in the rush to embrace all things digital, choose safe passwords and keep your IoT devices off sensitive networks.

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.

October 17, 2019  4:58 PM

How do you know your AI is making the right choices?

Sudhi Sinha Profile: Sudhi Sinha
AI and IoT, ethical AI, ethics, Internet of Things, iot, IoT analytics, IoT and AI, IoT data, iot security

There is a lot of conversation around data right now. Its value continues to increase, whether as something that can be monetized for profit or savings, or in terms of improving understanding and operations for a business that uses it effectively. That’s why the advent of artificial intelligence (AI) and machine learning — which allow us to quickly gain insights from vast quantities of data that was previously siloed — has been such an incredible revolution. Most are gaining actionable insights from smart systems, but how do we stay accountable in the age of the machine? How do we know we can trust the data and resulting insights when human beings are a lesser part of the equation?

There are three things to consider when determining how to create a structure of transparency, ethics and accountability with data. The first is access to the raw data, whether it’s from a sensor or a system. It is critical to maintain a transparent pathway back to that raw data that can be accessed easily.  In a building context, for example, analytics can help quickly search through video footage during a time-sensitive security event to identify and pursue a perpetrator. They can do this based on clothing color, gender or other details rather than having to manually search through hours of footage. It remains important to have access to the original footage however, so that there cannot be claims that the footage was edited to challenge the findings.

The second consideration is context. Raw data by itself may not make any sense. It needs to have some level of context around it. Without that, there is no picture of what’s going on. This is true for humans and it is true for machines. Decision making is a result of information, but also of relevant context that informs what action is taken. For another building systems example, take an instance of an uncomfortably warm inside temperature. This could lead to the belief that the HVAC system is not functioning. However, if there is also a meeting taking place that resulted in higher than average usage of the space, that can be an important factor. Without the ability to make determinations based on both data AND its context, systems wouldn’t be considered “smart.”

The third item to prioritize is data security. People need to feel their information is safe and secure from bad actors and misuse. Strategies to increase security have included two-factor authentication of logins or financial transactions in some settings, but they must continue to be a priority moving forward.

Machines as decision-makers: An ethical question

For nearly all of history, decision-making has been a human prerogative, where judgements about right or wrong can be applied (the subjective nature of right and wrong notwithstanding). When the machine becomes the decision-maker, it becomes an ethical question. How do we maintain data trustworthiness as the need for human involvement decreases? In other words, how do we hold machines accountable?

It comes down to transparency: access to raw data as mentioned above, but also referential integrity for all data and the context used to analyze it. The employment of knowledge graphs, a visual way to represent the “thought process” of intelligent technologies, becomes very useful. They provide a way to visualize how AI, in whatever form it may take, got to its decision. Just as there are traditional practices to keep humans accountable for their decisions and resulting actions, machines must have standards put in place now.

In addition to knowledge graphs, having insight into the learning process of your technology through a “digital twin” is a crucial part of machine accountability. By being able to see a representation of physical systems and play out scenarios to answer “what if” questions, it can give insight into the decision-making process. This provides peace of mind and confidence in the machine’s ability to properly analyze the information it is collecting, whether it be from an HVAC, security or lighting system, or something else entirely.

In the future, when machines are driving more decisions, we want technologies to maintain ethical and authentic practices and access to private information that we see now. It is important to establish best practices now and to understand the decisions that are being made and the learning processes that machines are utilizing. With any decision, made from human or machine, it is important to maintain transparency and a logic chain for accountability and peace of mind. By establishing a logic chain to truly understand the decisions that are being made by machines, it becomes possible to understand why they make the recommendations they do and provides accountability and the opportunity to adjust accordingly for a smarter building.

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.


October 16, 2019  2:29 PM

How IoT is transforming energy efficiency tactics

Mike Jeffs Profile: Mike Jeffs
Automation, commercial IoT, Internet of Things, iot, IoT analytics, IoT benefits, IoT power, IoT sensors, Machine learning, retail IoT

The level of electricity generated in the UK last year was at its lowest level since 1994, with only 335TWh of electricity produced, according to Carbon Brief.

Although the figure was only a small reduction since 2017, it was substantially lower than 2007, which was the peak of electricity production in the UK.

As the country becomes more conscious of its energy consumption, there is a growing demand to reduce our carbon footprint. Businesses are aiming to become more efficient with their energy usage and using renewable sources where possible. Output from renewable sources in 2018 rose to a record high, contributing to 33% of the UK’s total energy consumption. There has been a 95TWh increase in renewable output since 2005.

With major shifts towards energy efficiency, IoT will become integral to help many businesses provide critical information on energy monitoring.

Source: Hark

Driving energy efficiency

The retail sector is just one of the many industries that’s seen a rise in overhead costs because of energy bills. IoT applications will enable retailers to improve energy efficiency with real-time tracking and monitoring insight.

A combination of sensors from existing systems and additional IoT sensors can be used to create a unified feed of data. The additional IoT sensors can be integrated into key assets in the stores, such as HVAC systems and refrigerators. Data is collected from each of these sensors to create an interconnected network of devices that feed data into the cloud. This unified feed is used to influence decision making and add intelligence in real-time.

Due to the real-time nature of IoT technology and the data it provides, business are able to optimize their operations, and prevent asset failure and subsequent loss of energy.

Source: Hark

Predictive maintenance with machine learning

Machine learning algorithms use collected information to highlight potential failures and inefficiencies within a company’s operations. Slight changes in energy patterns at a micro and macroscopic level can indicate possible control problems or failures in components such as compressors and heating elements. The algorithms can automatically analyse patterns and monitoring assets, creating real-time alerts to potential areas of concern to prioritize callouts.

This can prevent downtime, reduce callout charges and mitigate loss of product. For example, sensors integrated with refrigeration systems can provide insight into how it’s operating through power draw analysis, and ensure that any issues are fixed before failure occurs, preventing produce spoilage.

Automation helps save on costs

IoT is allowing for automation within retail and other industries through the speed and accuracy of real-time information. A great example of this is lighting. Lighting is a high cost for all retailers; but if lighting grids could automatically react to external, ambient light levels, there’s a huge potential for conserving power.

This concept is especially useful during triad periods when energy costs are at their highest. All stores should aim to reduce energy usage during peak times and if they are equipped to do so, move to backup generators to avoid the high charges altogether.

The Power Factor for energy efficiency

A key performance indicator for energy efficiency is power factor. In technical terms, the power factor of an AC electrical power system is the ratio of actual power to apparent power. A lower power factor results in more electricity being drawn to supply the actual power.

Retailers should aim to improve their energy efficiency by increasing their power factor and reap the benefits of reduced energy costs. Power factor ranges between negative one and one, with one being totally efficient with no energy wastage. However, it is technically impossible to reach one as there will always be some form of heat loss, so a power factor between 0.95 to 0.98 is an acceptable range. It is important for a retailer to monitor this number and aim to be as close to one as physically possible.

HVAC systems and lighting systems are main contributors to a bad power factor. A smart solution ensures that sensor data is analysed in real-time to evaluate performance, allowing businesses to identify the exact piece of equipment that is lowering the power factor.

Key metrics analysed can range from power factor fluctuations, kilowatts draw, individual phase frequency, amperage and volts.

By having control over their energy systems and monitoring their power quality indicators, a retailer can benefit from range a of advantages such as significant and immediate savings on energy costs, longer device lifetime, and reduction in low-power factor penalties and carbon footprint.

With such significant benefits that can be gained from implementing IoT solutions, it’s no wonder there has been huge growth in the sector.

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.


October 16, 2019  2:05 PM

The secret to powering IoT devices

EJ Shin Profile: EJ Shin
Batteries, connected devices, Internet of Things, iot, IoT data, IoT data management, IoT devices, IoT power

Nowadays, it’s hard to not find connected devices everywhere you look. Every second, another 127 “things” are connected to the Internet according to Stringify CTO Dave Evans, and Gartner predicts that there will be 25 billion IoT devices by 2021.

Connected devices are only as valuable as the data they gather, the knowledge they impart and the actions they inform from data analysis. This is true not only for bigger, high-profile applications such as smart homes and cities, but also for the ever-increasing number of smaller-scale IoT applications. These smaller applications — like smart labels, smart packaging, smart pills, smart tags, smart cards, smart medical devices and diverse wearables — impact lives and business activities every single day.

As more things are transformed into connected devices, the type of power source they use plays

a surprisingly large role in how efficiently they sense and transmit data, and how usable — and therefore, how frequently used — they are. Device makers who rely on conventional, off-the-shelf batteries that are thick and rigid often have limited success due to design restrictions that affect usability.

Energy storage advancements can make devices truly useable

Energy storage solutions have advanced more than many manufacturers realize. New battery innovations free manufacturers to create truly user-friendly IoT devices that enable efficient data sensing and transmission. Next-generation, high-performance battery solutions that are lightweight, thin, bendable and flexible can be seamlessly integrated into connected devices. This enables device hardware to be designed much more aesthetically, providing a better user experience with greater comfortability and ultimately leading to stronger market adoption.

For instance, if a patch for monitoring biometrics or for therapeutic purposes were to have a thick and rigid battery cell embedded, it would be uncomfortable for users to wear. This discomfort would limit their usage time, resulting in low data collection and thereby unhelpful analysis. But if the patch had a thin and flexible battery seamlessly integrated instead, it wouldn’t impede their daily movements. In fact, users wouldn’t be so conscious about wearing it at all. This would naturally increase usage. With each consumer using the patch more often, more data is gathered and more valuable, informative feedback can be provided.

Key battery advancements

So just how flexible is a flexible battery? Very. We did bending tests on a battery that has a 20mm radius. After being bent 10,000 times, the battery still had about the same charge and discharge performance as a non-bent battery. This degree of flexibility is a must for devices that need to be curved or bendable and ultimately helps consumers feel comfortable using them.

Other significant flexible battery advancements have to do with weight, safety, customization and thinness. Batteries can be configured in thicknesses as little as 0.5mm. This thinness is very useful for sensors, smart cards, wristbands and other applications where weight and thickness are crucial success factors. These features are also key to enabling batteries to fit into small spaces in device hardware.

Next-generation batteries must also be safer. Even though manufacturers put tremendous effort into making sure batteries are durable and international safety tests are required, this doesn’t guarantee that batteries won’t overheat, explode or leak. Flexible rechargeable batteries made with gel polymer electrolyte technology deliver greater safety than batteries with liquid electrolyte; the gel electrolyte has higher resistance to heat and won’t leak if punctured.

Instead of off-the-shelf, rigid batteries, manufacturers now have the option of customizing flexible batteries to better utilize the space and hardware design of their devices. Rather than having to revisit their design at the end of the creation process because those off-the-shelf batteries do not fit the optimized product design, engineers and designers can now take advantage of battery manufacturers’ customization services to create a flexible battery solution that best meets their size, capacity, thinness and shape requirements, and delivers better user experience.

With so many things going “smart,” competition among connected device manufacturers is heating up as never before. The kind of battery a device maker uses to power smart devices or their components, or to transmit data, plays a huge role in how innovative and useful their devices can be, and how compelling users find them.

Next-generation flexible and thin batteries are key to delivering the kind of highly usable, aesthetically pleasing and reliably connected devices that give forward-thinking IoT device manufacturers a competitive edge.

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.


October 15, 2019  12:09 PM

The future of work and enterprise IoT

Steve Wilson Profile: Steve Wilson
connected devices, Consumer IoT, Enterprise IoT, Industrial IoT, Intelligent device, Internet of Things, iot

IoT is exploding. According to Gartner, there will be 20.4 billion IoT devices by 2020. No longer just a pipe dream, IoT is shaping up to be the backbone of our technological future. Not only will it drive some really cool improvements in the way we live and work, but it will also generate between $4 and $11 trillion in economic value by 2025, according to McKinsey.

Connected devices have simplified our personal lives in so many ways. Thanks to Siri and Alexa, we’ve been freed from mundane tasks that take time away from the things we really want to do. With Nest, we can rest easy if we forget to turn close the garage door in our haste to get to work. We want this same simple, intelligent experience at work — and it’s coming.

I recently spoke with Nivedita Ojha, Senior Director of Product Management for Enterprise IoT at Citrix to see where things stand.

Steve Wilson: For a long time, IoT was kind of like the Jetsons: fun to watch and a cool concept, but no one was convinced it could ever happen. Where are we today?

Nivedita Ojha: IoT has really moved from concept to reality. It is creating new business models that are transforming entire industries and driving unprecedented operating efficiencies. Think smart shelves in retail stores and sensor-fueled tractors on farms.

Wilson: When most people think of IoT, they think of consumer applications like Siri and Alexa or industrial uses like sensors that track inventory and shipments. But the lines seem to be blurring. What are your thoughts?

Ojha: For a long time, IoT was black and white. It was either consumer or industrial. But there is a new category taking shape: Enterprise IoT. Because the industry has made things on the personal front so simple, we are now starting to see consumer devices make their way into the enterprise workspace where they can do the same thing. Bring your own device has really become “bring your own thing.” Alexa is now in the office giving commands to open a file or start a meeting. Work is becoming handsfree, intelligent and autonomous.

Wilson: And are employees happier as a result?

Ojha: Definitely. They have the freedom to use the devices they prefer to remove a lot of the complexity that bogs them down and keeps them from doing what they want and are paid to do. They are more engaged and productive as a result. At the end of the day, it’s the little everyday experiences matter the most.

Wilson: What does all of this mean for IT? It seems to open up a whole new set of challenges in terms of securing these devices.

Ojha: Managing IoT devices definitely requires a different approach to security. Traditional models don’t adequately protect against the new vulnerabilities that connected devices open. To effectively secure them, IT needs to take a more intelligent and contextual approach and put in place a model that supports roaming, wirelessly connected, mobile users without getting in the way of their experience.

Wilson: And how do they pull this off?

Ojha: It requires an integrated set of tools that combines management, security, workspace and mobility into a centralized infrastructure that allows IT to monitor and secure all types of endpoints, applications and software from a single pane of glass, and they do exist.

Wilson: Any final thoughts?

Ojha: Enterprise IoT is one of the most interesting developments on the digital transformation front that we have seen in a long time. While it is still in its nascent stage, it is fast driving the convergence of digital and physical workspaces and transforming the way work gets done in very positive ways.

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.


October 14, 2019  4:53 PM

IoT monetization framework: The IoT stack and how to monetize it

Cris Wendt Profile: Cris Wendt
IIoT, Internet of Things, iot, IoT monetization, IoT software, IoT strategy

This article is the second in a six-part series about monetizing IoT.

The previous article addressed the key goals of efficient IoT monetization. The next step in the monetization process is understanding how to monetize your IoT offering in a structured framework. The two-part framework presented here will help you move forward. Developed with software and hardware manufacturers, it delivers monetization approaches based upon the value the customer receives from an IoT product.

What is being monetized?

The IoT Solution Stack recognizes that an IoT solution isn’t necessarily a single element, but multiple elements connected conceptually as a stack to provide value individually or collectively. The embedded software in these different elements is what provides new levels of performance, capacity and functionality, forming the foundation of new value streams. This approach recognizes that a supplier may provide and monetize products that comprise only part of the stack, or that the supplier may provide a solution that encompasses the entire stack. How much of a solution you provide will very much drive your monetization strategy.

Below is illustration of this IoT Solution Stack:

Source: Flexera

Let’s look at the elements of this stack, starting from the bottom:

Device. These are the edge devices or the “T” in “IoT.” They are the high-volume software-enabled devices that are connected via the internet. Depending upon the solution, this includes myriad phones, sensors, meters, cameras, valves, switches, systems, vehicles, scanners, medical instruments and more that are networked to form an IoT solution.

These edge devices are becoming more intelligent and flexible with the increasing role of their embedded software. One example is a medical instrument that offers various software-enabled functions along with connectivity to electronic medical databases with patient and medication information.

Gateway. In the middle of the stack are intermediate control and aggregation points found mostly in Industrial Internet of Things (IIoT) deployments. A good example is the programmable logic controller (PLC) found in manufacturing environments. PLCs usually perform device management to control a subset of the edge devices in a factory floor such as switches, valves and robots. Their monetization is often derived from the rich set of different functions they provide and the number of edge devices or data they manage.

Cloud Analytics & Control.  At the top of the stack are the data aggregation, analytics, control and decision-making functions. These solutions tend to be cloud-based software that rely on combinations of big data, AI, blockchain and scalable cloud-based infrastructure technologies to make sense of tremendous amounts of data.

This level of the stack provides solutions that tend to be the “brain” of IoT networks and is used for functions such as controlling factory floors, optimizing supply chain performance, detecting defects and errors in utility networks or controlling lighting throughout a city. Value is often driven by the type of functions that are provided, scaling by the number of edge devices and data controlled and managed by this level of the stack.

As a rule of thumb, the value of IoT follows the direction of the stack; the higher up you go in the stack, the higher value the offering provides. The highest level is most aligned with producing the desired outcomes of connecting a variety of devices. Of course, given the large number of end devices in a deployment, the total dollars in a solution might be driven by the total number of edge devices.

And the highest value is achieved when the entire stack is provided by a single supplier, such as when a utility meter provider sells the entire electric, gas or water stack as a service to a municipality.

How to monetize the stack

The three dimensions of monetization form the basis for determining the structure of your monetization models. The following metrics are the underlying monetization structural elements, not buying programs or discount models to tune the actual pricing.

Source: Flexera

Revenue model. Every monetization model relies on an underlying structure for producing revenue that is designed to support a revenue-generating business model that matches the way customers want to consume the product or service. Common options include:

  1. A one-time, up-front model based upon physical goods and perpetual license model where there are ongoing transactions to sell new or expanded products
  2. A recurring revenue model based upon time or a measure of consumption (e.g. number of hours expired, number of analyses performed), where revenue is generated based upon measurements of value and usage
  3. An outcome model based upon achieving a specific outcome or measurable value, such as improvement in crop yield per year

Monetization metrics. Metrics define the units of usage or value that are used for individual product pricing. This allows product managers to effectively price those units of value that are important to customers based upon how they derive value from the product. Metrics are the units of value that enable a company to generate more revenue through increased use or adoption, for example, more customers using management software; more endpoints being managed by an IoT cloud analytics solution; or the amount of data processed for an analysis.

Product packaging. Product packaging discusses approaches to meaningfully partitioning your product functionality into different products or commercial units to grow revenue. This dimension of monetization considers different approaches for your products to meet varied market opportunities or to monetize the customer journey as customers become increasingly expert and want to increase the value they realize from a solution.

The third article in this series will cover monetization models — perpetual, subscription, usage, and outcome — and how to select the one that’s most suited to different offerings.

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.


October 14, 2019  4:30 PM

Who says cellular IoT can’t be used in farming and agriculture?

Svein-Egil Nielsen Profile: Svein-Egil Nielsen
cellular IoT, Internet of Things, iot, IoT application, IoT connectivity, IOT Network, smart farming

I’ve been reading and hearing a lot recently about cellular IoT not being suitable for smart farming and agricultural applications. The main reasons given are that it uses too much power, and does not have the coverage or range needed.

But that doesn’t reflect the world that I am seeing. For example, Finnish startup, Anicare, is already using narrowband IoT (NB-IoT), one of the two categories of cellular IoT, the other being LTE-M. Both track the health and location of farmed reindeer — and other herding animals — that spend most of the year in the wild.

The Anicare Healtag tracker is attached to an animal’s earflap, and autonomously measures vital functions for up to five years. Data is sent via cellular network to the cloud for immediate access via a smartphone application. This means injured or sick animals can be automatically identified for rescue and treatment. This device is very small, and is testament to the low power capability of cellular IoT technology.

But how can this application be helpful when used regions of Lapland and Scandinavia, where regular cell phone coverage can sometimes be a challenge?

NB-IoT is built for range

The good news is that NB-IoT is designed to offer enhanced coverage in hard-to reach areas. This includes indoors and uninhabited rural areas. It offers 20+dB (x7) better coverage compared to LTE-M. Maximum coverage is achieved by using a low 200kHz bandwidth, and simpler signaling structures and retransmissions up to 2,048 times.

Furthermore, NB-IoT has three deployment scenarios: standalone, guard band and in band. Paired with its narrow 200kHz bandwidth, NB-IoT can deploy even to occupied lower cellular bands. These lower frequency bands have excellent propagation characteristics and provide excellent performance in terms of coverage. As such, an NB-IoT signal has a real-world range of over 30km. Indeed, the longest-range a NB-IoT connection achieved in a commercial network is 100km.

Another application example already on the market is an NB-IoT emergency alarm currently available in Holland from Dutch startup, Montr. The Montr Emergency Button is designed to protect people in vulnerable situations, such as lone professionals at risk of physical attack or isolated accident, as well as seniors living at home. During internal tests, Montr found the NB-IoT signals could penetrate into locations such as deep basements commonly found under swimming pools, which have zero traditional cellphone signal.

Cellular is everywhere

Even though cellular IoT is ready for smart farming and agriculture applications today, the future looks even rosier. There are numerous initiatives around the world now underway where cities are being blanketed in high-speed cellular coverage, and rural areas having none is increasingly being deemed unacceptable.

This is a push-and-pull scenario where there is market pull from consumers living in rural areas, and regulatory push from governments and telecom regulators to ensure it happens. For example, carrier U.S. Cellular recently announced plans to bring fairness to cellular network availability by actively targeting rural areas.

I predict, within a few years, hardly anywhere on this planet will not have access to cellular connectivity. I also predict that in certain smart agriculture and smart farming applications with particularly low-duty cycles, you will have cellular IoT-based solutions that consume such small amounts of power that they could have infinite battery lifetimes. This will be achieved through the use of energy harvesting solutions such as solar or inertial energy.

So the next time you read — or are told — that you can’t use cellular IoT for smart farming or agricultural applications, I’d question the source of that information.

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.


October 11, 2019  2:28 PM

Innovating field service IoT devices in the business 4.0 era

Gopinathan Krishnaswami Profile: Gopinathan Krishnaswami
AI and IoT, field service, Internet of Things, iot, IoT analytics, IoT data management, IoT devices, Machine learning

Developing cutting edge commercial IoT technology means being at the forefront of the high-tech industry. As part of this movement, we are hearing much talk about what it means to build next-generation high-tech field service IoT technology, and what the seemingly limitless potential could bring to enterprises of all industries. Innovation is being driven by strategic implementation of AI, machine learning and deep learning, helping bring field service capabilities and end-user convenience to new heights.

Optimizing data collection

Field service technology is unique in that it serves as a connection between end-user devices and the entire enterprise supply chain; operating at both the near and far edges. When servicing end-customers in the field, these IoT devices not only use data aggregated throughout end-device analytics, but they also generate ample amounts of data in their own right. Field service devices provide all enterprises with a gold mine of data that can be repurposed to help further optimize future and existing customer interactions, streamline supply chain operations, and further develop field service IoT device capabilities to best fit customer and enterprise needs.

For example, consider cable providers: Field service technicians are naturally required for the installation and maintenance of cable boxes, routers and other home connectivity devices. These interactions between field technicians can be optimized through AI and machine learning technologies, which crunch the data that is gathered through each customer interaction.

This data can help companies develop AI-driven field service devices that are able to understand and evaluate individual situations in real-time. By understanding both the profile of the end-user and the device history, field technology IoT devices will be reimagined through the ability to predict what tasks will be required from the technician, prior to arrival on-site. This will drastically reduce the amount of time needed for diagnostics during maintenance and repair, and will make for a better experience for the end-user as well as the technician.

Reducing energy waste through IoT innovation

Building management also has the potential to be impacted by high-tech innovation in the field service sector. If you take one specific industry field application, such as a data monitoring center, you’ll see that IoT is responsible for controlling some of the physical attributes of the center itself. Specifically, IoT controls the temperature, humidity and other things that make the day-to-day aspect of the center more comfortable for employees.

Building management device innovation can be beneficial to all companies. Many businesses have integrated IoT into the building management support, significantly reducing power consumption. This integration allows companies to proactively shut down systems that they didn’t even realize weren’t being used to reduce their own energy waste. Thus, IoT and high-tech in field technology keeps the process and operations as optimal as possible.

Challenges with incorporating IoT and high-tech

While the benefits these technologies bring to companies can be exponential, there are also challenges and minor inhibitors that might make the technology seem less glamorous to some. Optimizing and maximizing field service IoT device capabilities is still a work in progress. Part of this is due to a reliance on legacy infrastructure and minimal high-tech investment.

As these organizations continue to undergo their digital transformational journeys, they will ultimately understand the importance of building new digital infrastructures. By building a high-tech infrastructure, businesses will be able to truly reinvent their products, services and internal operations, including field technology IoT integration.

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.


October 10, 2019  2:10 PM

How to protect data privacy in connected cars

Julian Weinberger Profile: Julian Weinberger
commercial IoT, Connected car, connected car data, Consumer data, Internet of Things, iot, IoT attacks, iot privacy, iot security

From monitoring our driving habits to tracking our location, connected cars know our every move. With a black box or event data recorder collecting information inside 96% of automobiles, modern cars are as much a computer as they are a means of transportation.

However, many drivers and passengers aren’t aware of the privacy risks that come along with connected cars. Personal data stored in cars is not always encrypted, or subject to legal restrictions.

While details such as seat-belt use, speed, and braking are proving be to useful for insurance companies and law enforcement, personal information including phone contacts and text messages could also be collected without a person’s consent.

Connected cars on trial

In most countries, police only require probable cause to search vehicles and are not obliged to obtain a warrant before downloading data. The legality of this has already been tested in the courts.

Such cases call on individual courts to decide whether laws dating from before the digital age should be extended to let police gather more information than was originally intended, according to the American Civil Liberties Union. In the absence of universal legal protections, the problem will continue. Every new technology and connected device will bring up the same challenges.

Manufacturers promise security

Under regulations like EU GDPR, customers have a right to expect information will remain private unless they expressly give their consent. This puts the responsibility on the vehicle manufacturers to build appropriate security measures that will protect an individual’s personal data.

Advanced driver assistance systems (ADAS) such as collision avoiding automatic brake systems provide higher margins for manufacturers. The market for ADAS is expected to grow by more than 10% every year and reach $67 billion by 2025. Manufacturers have every incentive to ensure that these systems comply with data protection regulations and keep sensitive customer data secure.

So far, about 20 carmakers have signed up to build systems featuring built-in security. The plan is to give car owners the ability to manage the data collected in their vehicles, and obtain customer consent to use location and biometric data for marketing.

Encryption drives data protection

To better protect customer data, auto manufacturers will need to introduce encryption technology into their vehicles. VPN software can effectively encrypt data within the vehicle and as it passes over the Internet. By creating an encrypted tunnel for data communications with the auto manufacturer or smart city system, a VPN renders personal data indecipherable and protected from cybercriminals.

Overall, as advances in connected car technology and next generation bandwidth inevitably increase, the number of cases in which personal data in vehicles is analysed without the owner’s consent will continue to occur. To prevent this, manufacturers must take the proper measures to meet data protection laws. Implementing VPN software can ensure that personal information stored in event data recorders and central computer systems is secure, and safeguarded from unauthorized parties.

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.


October 9, 2019  2:35 PM

Securing your supply chain is as important as securing your devices

Wayne Dorris Profile: Wayne Dorris
cybersecurity, Internet of Things, iot, IoT cybersecurity, iot security

The Ponemon Institute published its annual report on third-party IoT risks in May, 2019. The report focused on identifying what companies do not know — or understand — about the risks inherent to IoT devices and applications, particularly when used by third parties. The report drives home the fact that, although integrators and end users understand that it is important to protect connected devices, many do not understand the full landscape of threats that these devices face.

Concerningly, the Ponemon report indicates that the percentage of organizations that have suffered a data breach, specifically because of unsecured IoT devices or applications, has risen from 15% to 26% in the past three years alone; a number that Ponemon points out is likely low due to the unfortunate reality that it is often difficult to recognize when a breach has occurred.

Perhaps more importantly, the report also notes that the percentage of companies experiencing data breaches caused by unsecured IoT devices or applications belonging to third parties has risen from 14% to 18% since 2018, and cyberattacks caused by those devices have risen from 18% to 23&. These numbers underscore the fact that even the most secure network can be compromised by failing to properly vet third-party suppliers, and securing your supply chain is often as critical as securing your devices.

Built-in security is key, but it isn’t enough

Understandably, when it comes to keeping IoT devices secure, responsibility often falls on the manufacturer. Smart — and conscientious — manufacturers have a vested interest in ensuring that their devices have strong and effective security capabilities. This is truer than ever now that national and international regulations such as GDPR have taken effect, and even been supplemented by additional regulations incorporating language that mandates information security by design and default.

Both individuals and organizations are increasingly asserting their right to expect a basic level of security when they purchase and use a device. Other groups, like the National Institute for Standards and Technology, have issued their own recommendations for creating a core baseline for securing connected devices.

The concept of by design and default means that manufacturers must make good on many individual’s expectations of built-in security; but it’s important to understand what security really means. Including built-in security measures doesn’t make a device impenetrable, nor does it ensure that users or integrators will understand how to best make use of those measures.

Measures such as creating unique default passwords for each new device can prevent certain malware infections like the Mirai Botnet and its many offshoots from taking control of massive numbers of devices at once. But it can’t prevent an integrator from creating an inadvertent backdoor into the system, nor can it stop an employee from leaving their new credentials lying around where they can be easily viewed or stolen.

Research has shown that 90% of data breaches are can be tied to largely avoidable problems including human error, poor configurations and poor maintenance practices, according to Axis Communications. While end users naturally want to know what manufacturers are doing to build security into a product on the software side, the truth is that built-in security can only do so much.

Ensuring that the knowledge is there to prevent configuration and maintenance errors is equally important. This further underscores why securing the other levels of the supply chain is a critical aspect of IoT security.

Education is key for manufacturers, integrators and end users

When bringing IoT products into a network, the integrator must work closely with the information security team to ensure clear communication of the control set for the network, the framework upon which it is built and more. The communication must happen before the installation even begins, so that the integrator understands how to approach the project in the best possible way. This means end users must understand the products they are purchasing and how they fit into the wider network.

Although manufacturers understand the benefits of built-in security controls, if an integrator or contractor doesn’t line up a network’s controls with its access users, then it doesn’t matter how securely built the products are. Even if the manufacturer has done threat modeling by having a secure software group come in to determine potential attack methods on a given product, information must be effectively conveyed to the integrator so that they can install the product using the most effective security framework. Even a minor communication disconnect between a manufacturer and an integrator can cause major problems in this manner.

Manufacturers can help improve overall security by taking steps to ensure that encrypted connections are established from the start. Many manufacturers are turning to features like Secure Boot, which only allows a device to boot using software that is trusted by the Original Equipment Manufacturer; preventing hackers or other cyber criminals from installing unknown programs onto a device. These measures are not enough on their own, but taken in conjunction with improving integrators’ and end users’ knowledge and understanding of product security, they represent an important piece of the puzzle.

Establishing trust is critical, but that trust must be earned

Vendor and manufacturer vetting are a part of the new trust dimension. Whether or not a manufacturer’s products can provide a solution and meet the technical requirements to solve a given problem are no longer the only concerns for end users.

Today’s businesses want to know the cybersecurity approach taken by the manufacturer before they purchase a given product. Today’s manufacturers have an obligation to educate their integrators to ensure that those products are being deployed in the most effective way. Conveying that to end users is important, and establishing trust in the marketplace is a multi-step process.

Transparency is key. In any industry, organizations that are open and honest will naturally foster greater trust. Similarly, demonstrating good processes and practices when it comes to securing customer data can also go a long way; particularly as data breaches make the headlines with increasing frequency.

Even though most applications on IoT devices don’t contain much Personally Identifiable Information (PII) of the type covered by GDPR, compromised devices can be used as a jumping off point for privilege escalation and cross-breach to the IT network. This is where PII and other data can be easily obtained. End users want to know they can trust a product to secure data effectively, and manufacturers with a reputation for using features like Secure Boot can help provide that confidence.

It is important to strengthen the ties between manufacturers, integrators and end users to create new avenues for communication, and ensuring that a proper level of knowledge of both the products in use and the needs of the customer is established for all parties involved.

Education is critical, and everyone must be willing to take the steps needed to build a more secure and knowledgeable future. For many, this means supply chain mapping to detail every touch point of all material, processes and shipments. As IoT devices continue to become more commonplace across a wide range of industries, securing the supply chain will only become more important.

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


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