A while ago, I would have only known what the letters stand for and not what it actually is, and I don’t think I’m alone on this. However, the IoT is all around us and will continue to grow. I have been on a steep learning curve and thinking about this made me wonder about what we think we know and what are the common misconceptions about IoT? I have created my top five list of what I believe are the main misconceptions about IoT and here I will try and debunk them (in a non-techie way!) for you.
Wearables such as wristbands, smart fridges or thermostats are of course examples of IoT applications which are well known, ask most of the public for examples and this would be it. However, there are so many more examples of IoT in the business environment away from the more obvious ones. For example, within urban environments IoT can monitor air quality, provide adaptive traffic control and environmental monitoring. On construction sites, IoT can monitor PPE usage and provide predictive maintenance. IoT can be found in all industries, for more information drop me a line and I will provide you with further examples.
The reason many solutions are only implemented by bigger business is because they pay large consultancies to demonstrate the economics; find the right supplier and this should come as part of the package, therefore making it much more viable for a SME to evaluate and implement.
There are many solutions that are simple to install and have business impact that any businesses can deploy to start their IoT journey, for example:
Security has to be one of the key points and I would strongly advise anyone interested in IoT to talk with their security advisor about. It is most definitely not a straightforward one line answer, the reality is that almost any system has vulnerabilities, so it is about designing the solution so that these potential vulnerabilities become impotent.
For instance, it may be possible to intercept the data from a parking sensor, however by ensuring there is no pathway from this device back into the cloud, network security is maintained, and any potential data interception is entirely meaningless.
Security should be like an onion with many layers, each layer providing a different type and level of protection because hacking a system should not be as easy as knowing a password or IP address.
It is certainly possible to blow the budget on high end systems, however unless the system is being deployed for ecological benefit (which is priceless) the general purpose of using IoT in a busines environment is to generate savings, gains or increase output. All of which result in a return on investment and therefore are not an additional cost burden to a business. With Capex and Opex options commonly available, cashflow doesn’t need to be negatively impacted either.
The technology adoption curve dictates that as IoT becomes mainstream prices will decrease and therefore utilisation increases. A real-world example of technology adoption in industry is the car industry, where Formula 1 drives innovation that filters down into the cars that you and I drive at an affordable price.
People have always feared technical change, the most obvious example are the luddites, a secret oath-based organisation of textile workers in the 19th century, they were well known for destroying textile machinery in protest, which stemmed from the fear of losing their jobs to machinery. Jobs were lost but others grew and what was gained was a better quality of life, better health, and the creation of less harmful and dangerous jobs. There will be some job losses, Gartner predicts that 1.8M jobs will be eliminated but more positively 2.3M jobs will be created with AI. There will be new economies and new businesses developing. Our lives will be changed but we can’t replace humanity, for example would you be happy with a robot cutting your hair?
This is just the tip of the iceberg regarding misconceptions and questions around the IoT. It’s interesting to look beneath the fears and drill down on the possibilities of IoT.
We enjoy questions and would be more than happy to answer any concerns or dispel any myths that you may have heard around the IoT in a user-friendly non-techie way. Please contact us if you have queries, which are not in my top 5 and we will be happy to help you.
Artificial intelligence is the beginning of a revolution, but in one way it is just like every other revolution: It can be abused. Whether or not you already use any AI, you need to understand two things; that AI is cranking up the severity of security threats, but it can also offer improved security.
AI systems are fast and dynamic, meaning they learn from experience instead of relying on pre-programmed assumptions. AI-powered malware doesn’t require the hacker to know anything about you in advance. However, an AI-powered defence system needn’t depend on fixed definitions of who to trust and who not, or how they gain access. It can learn to recognise suspicious activity.
AI will power more advanced intrusion attempts into systems that are themselves more powerful. End users need to understand that the sophistication of AI-powered tools does not mean they are secure. For example, facial recognition systems powered by AI can potentially be spoofed by another AI, providing building access to criminals, or framing innocent people with forged video footage.
A report from Forrester “Using AI for Evil” says “mainstream AI-powered hacking is just a matter of time” and Ciaran Martin, of the National Cyber Security Centre, said it’s a matter of “when not if” [there will be a major attack on the UK].
Using “bot manipulation”, malware can use AI to adapt its appearance so that antivirus software doesn’t recognise it. It can also use AI to sample normal network activity and use it as camouflage, known as “generative networks”. When the target is itself an AI system, a malicious actor can feed “poisoned” data to the engine in order to bypass filters or simply cause damage. AI can also learn to impersonate a legitimate person or company in order to launch a social engineering attack.
The ability of AI to react quickly and adjust its responses as situations evolve also makes it ideal for defenders. An AI security system gives defenders the edge by providing early warnings and rapid incident response, so attack vectors can be closed down before any real harm can be done. Darktrace is one such tool.
Behaviour analytics is another important defence tool. Detecting unusual activity allows the AI to close access to key resources while a deeper examination is undertaken, for example, using Varonis. Mastercard’s director of cyber and intelligence solutions in South Africa, says AI is saving $20 billion per annum by detecting fraud in this way. Embedded malware code can be detected using a similar method.
AI-powered solutions also help by improving activity logging; centralising it in a single place and providing tools to zoom in on significant trails. The logs collected by Azure and other Cloud platforms provide a good basis for an effective SIEM system. These tools also enable you to create and evaluate your alert response workflows.
Once in the Cloud you have access to specialist security products and expertise that few enterprises can deliver in-house. Specialist companies constantly monitor the global situation to stay aware of threats emerging in particular sectors or locations. An ideal SIEM integrates this digital intelligence with your standard procedures such as logs, asset inventory, AI pattern detection and automated incident responses, and makes it easy to demonstrate your statutory compliance.
Unfortunately, we can’t wait for someone else to solve our cybercrime problems. The very people we should be able to trust to protect us, the NSA and GCHQ, created the EternalBlue tool used in recent ransomware attacks such as WannaCry, NotPetya and BadRabbit. They also left exploitable flaws in Windows and implanted backdoors into server and router firmware. Although this is similar to the warnings against Huawei, the NSA have placed similar backdoor access into products from Cisco, Juniper and Fortinet.
The problem with creating these weapons is that everyone else soon uses them; innocent companies are the victims. According to Wikileaks on 7th March, the CIA regularly listens in on Samsung televisions and iPhones and can take control of numerous IoT devices and car computers. When they do it, others will soon follow.
For businesses the goal is clear, keep spyware and vulnerabilities out of your software and hardware. That means taking a keen interest in where your IT products come from and investing in good security. There are limits to what is practical, but an integrated security system powered by AI is the best possible solution
5G has suffered bad press from both detractors and supporters. Spoof stories about it spreading coronavirus were soon dismissed, but banal predictions of refrigerators ordering milk and shoppers wearing headsets to receive advertising were even more likely to blunt our interest. 5G undoubtedly creates the groundwork for an enormous technical revolution but adjusting the central heating with our smartphone or watching B-movies in higher resolution is not the point. Manufacturing and logistics industries will lead the real 5G revolution.
Although the public 5G network will take some time to get up to speed, local area networks can implement true 5G more quickly. This will enable factories, ports, universities, farms and airports to have their own industrial IoT systems (IIOT) today. Numerous factories are already claiming the ‘first’ 5G production lines, including a Nokia factory in Oulu Finland, Worcester Bosch in the UK, Mercedes Benz in Sindelfingen Germany and General Motors in Michigan.
Speed is often mentioned as a key advantage of 5G, but it helps if we break down the meaning of ‘speed’. 5G radio waves don’t move more quickly than 4G ones, rather the entire system has been optimised for faster data transfer. 5G can reduce latency to as little as a millisecond, enabling machinery to respond to sensors almost instantly.
Consider how quickly a driverless car must respond in order to operate safely and you will understand the value of low latency. In a similar way, 5G will enable a whole new generation of robots and automated machinery to radically improve dexterity, quality control and safety. Ericsson’s vice-president Åsa Tamsons explains:
"With one millisecond latency, you can sense whether there is a deviation in the process before the tool even hits the blade and you can stop the machine before the error happens".
‘Edge’ responses in today’s driverless cars are achieved by mounting the control device directly on the vehicle. 5G cars will achieve similar response times but with all the benefits of environmental network connectivity too.
5G also has far broader channels so that more devices can be connected simultaneously. It is said that 5G will soon be able to connect a million devices per square kilometre. Imagine what an engineer could do with ten thousand eyes and ten thousand hands. All the extra data feeding into AI enabled machinery would provide a precise real-time grasp of complex distributed systems and emergent situations with many industrial applications.
Not all 5G systems need to be this fast, but a typical industrial 5G LAN will match a good Ethernet one. A huge disadvantage of Ethernet is the wires, they are expensive to install, prone to breakages and need regular maintenance. In contrast, once setup a wireless 5G system is easy to maintain and reliable (99.9999% or ‘six nines’ reliability).
One reason for hard-wiring a system rather than using ‘wi-fi’ is because most types of wireless connection can fail to penetrate walls and metal obstructions. However, 5G is relayed between multiple small nodes and can re-route itself instantly if a passing tanker or crane blocks any particular path between devices. The technology is called ‘coordinated multi-point’ (CoMP).
Finally, 5G provides much improved network control, including the ability to subdivide the network. Known as ‘network slicing’, this means each virtual sub-net can be customised and optimised for multiple different purposes.
Whether public or private, 5G networks have applications everywhere. By planting sensors in the ground, farmers will know precisely how much water or fertiliser their crops need and when, or query weather satellites and predict their ideal harvest time and yield. Driverless machinery will often deliver it. The health of herds can be monitored remotely and assets tracked across the farm and supply chains.
The IoT has already demonstrated multiple applications in health and fitness. We are beginning to use proximity sensors and temperature sensitive cameras to track disease outbreaks. In the future 5G may be able to stop a public health threat in its tracks. Augmented reality may also facilitate remote examinations, benefitting people in isolation and the NHS system.
5G supports three rather different kinds of technology; smartphone broadband, large-scale IoT and critical ‘edge’ operations. Because smartphone makers need to sell handsets to pay for the public network, some of the more frivolous ‘benefits’ have been hyped. Many people will receive a Samsung S20 this Christmas and wonder what to do with it. However, the real revolution will be quieter and more impressive: few enterprises will be able to ignore 5G and still remain competitive.
Everyone has heard of artificial intelligence and smart connected devices; they might be fun one day, along with Robocop and jetpacks. However, most people don’t realise they are already here in a big way, in fact they probably use them every day.
Of course, most of us have already encountered Alexa: kids love it and kids are never wrong, but as yet many owners have used it for little other than turning on the lights or doing a hands-free internet search. It’s still not quite as impressive as HAL from the movie 2001, even though it is almost 2021, but there is a lot more to AI and IoT than one might think. According to networking giant Cisco, the number of ‘things’ connecting to the internet overtook the number of people way back in 2008.
A mobile phone is the one connected device almost everyone carries around with them, but we still tend think of them as “phones” rather than smart connected devices or artificial intelligence. In fact, most of them are both.
Many people will be surprised to know that more cars were added to mobile networks in 2016 than telephone handsets. Smart devices are not a novelty, they are already the norm, we have just not noticed.
Consider a stroll down your High Street. The many street cameras and other detectors you pass are probably feeding traffic information into an AI-powered management system. In some towns, they are managing the parking facilities, street lighting and bin collections. Almost every shop you pass has connected devices such as payment terminals, alarm systems, IP phones and CCTV. Some of these are some linked to a facial recognition AI.
Larger businesses along with clinics, hospitals and banks depend on an AI to protect them from network intrusions. Many takeaways will be connected to smart-ordering networks and delivery tracking systems. Uber cars and haulage vehicles rely on a logistics AI and the day is fast coming when AI will be driving them too.
Let’s return to your smart phone. Your mobile carrier’s network depends on artificial intelligence to route tracking signals, calls, Wi-Fi connections and SMS messages. Your camera relies on AI to focus, detect edges and adjust the contrast. Many of the apps you use connect with AI to provide other services, for example to monitor your fitness or detect the presence of COVID-19 infections.
If you need help with any of these apps, your enquiry will probably be answered by an AI bot. When you connect to the Internet, AI chooses the ads you see, the search results you get, the movies shown on Netflix and the music promoted on Spotify. If you upload a photo to Twitter or Facebook, facial recognition AI will probably analyse it to see who else is in the picture.
Figures from 2017, compiled by Gartner, showed 8.4 billion devices connecting over the IoT. That’s more than all the people in the world. This number is now around 20 billion as they are being deployed so quickly.
22% of IoT devices are inside factories; automating production lines, training robots, regulating conveying systems and ensuring quality control. Another 15% are specifically involved with energy efficiency management. Retailers currently account for just 12% of devices, for processes such as inventory tracking, footfall counters and security networks, while city management systems, such as traffic control, public transport and policing also use about 12%.
When device suppliers explain the potential benefits of the IoT they often use examples from our homes; central heating that knows how warm you like it, or ovens that switch on when you are on your way home. It is therefore surprising that building management still only accounts for about 3% of smart devices. There is still an enormous potential for growth in this area as well as for wearable devices, in wristbands, spectacles, headbands and integrated into our clothing. The recent craze for ‘Pokemon Go’ demonstrated the enormous popularity and potential of augmented reality.
The smartphone isn’t just a connected device, it is the device most of us depend on to monitor smart devices elsewhere. 5G networks will soon lead to an explosion in consumer-friendly utilities based on AI and the IoT, so phone manufacturers are now beginning to use chips optimised for AI (“neural engines”). The only limit is our imagination.
Never before has it been possible to collect so much data. However, the data is worthless until you can mine it for information, which in turn is useless unless you can understand it. It’s disappointing that most companies are still reliant on two-dimensional charts, graphs and tables of impenetrable figures. The underlying data is labour intensive to collect and processing it can take so long that actionable reports are often out of date.Finally, if you decide to respond in a particular way, you will have a further wait before you can evaluate the outcomes. Visual analytics combines the tools needed to perform all these steps but on a much faster timescale.
Briefly, your information resources can be collected automatically by sensors and cameras or by querying a wide variety of company data resources. Once you have a single point of access, data mining or similar pre-programmed algorithms can rapidly extract and organise it. You will then be able to extract meaningful correlations and aggregate key statistics. At the monitoring end, the salient information is provided in visual forms that human beings can understand at a glance and then respond swiftly.
Although they are complex, visual analytic systems are extremely flexible. If you can gather digital data on the activities or operations you need to monitor, you can apply visual analytic tools to them. This means it has a role to play in business, security, governance and on industrial production lines.
With many tools now available in the Cloud, it is within the reach of small to medium sized businesses for the first time. Many visual analytic systems are configurable using simple drag-and-drop interfaces, so although you need to understand your own operational requirements to design them, you don’t need skilled specialist IT teams to operate them for you.
If you can collect your data in real-time, such as from remote sensors and cameras linked across the IoT, then you can not only respond in real-time, but view the consequences of that response in real-time too. Many analytic suites also enable you to explore the consequences of a policy or production line change before you commit to it, as well as to identify historical trends.
Data science and statistical analysis isn’t something that everyone has time to understand, but pointing and clicking with a mouse is now commonplace. Visual analytic interfaces are designed for operational managers, to help them focus on their own areas of expertise and their own specific issues. Business managers and operational technicians can collaborate to devise solutions without needing to refer to IT specialists or external consultants.
Development is also simple. Sophisticated analytic systems can be built up without ever having to call in a coding team. Your solutions can be built in the Cloud, inside your intranet, or close to critical points in your operational infrastructure. The absence of a steep learning curve means there is a rapid return on investment for the company.
The flexibility of these systems enables, rather than replaces, human insight and experience. There are many areas where you can use these tools, guided only by your own creativity and imagination. In the course of exploring different data views you are very likely to discover answers to questions that you might never have thought to ask.
Before data analytics, if a report made you aware of a problem but didn’t explain the cause you would have to request more detailed information from front line departments and then wait for a further report. In contrast, visual analytics lets you explore a succession of views until you find the one that answers your question. You can dig deeper, or change the way you examine it with a single click until you find the view that makes the answer clear. As a result, your analyses are more thorough, more penetrating and, critically, up to date.
Analytic resources can be used to create a leaner, more agile enterprise, by making your front-line teams and managers more self-sufficient. Visual systems can reveal exactly where your production line bottlenecks are happening, or to predict where they are going to occur in the future. You can then make prompt adjustments to keep production flowing.
Access to a visual analytics dashboard can empower every member of your organisation by revealing exactly how their process is performing and whether it is keeping pace with other dependent processes. It can also be used to track management objectives, such as KPIs and other project landmarks.
