Tag: IoT

The Next Big Leap: Autonomous Supply Chains

MV EverGiven ship blocking the Suez Canal

In the world of supply chains, a transformation is underway. I recently had an intriguing conversation on the Digital Supply Chain podcast with Sanjay Sharma, CEO of Roambee, a company at the forefront of this transformation. Sanjay and his team are harnessing the power of real-time data, AI, and machine learning to reimagine and reshape supply chains, paving the way to a future where supply chains are not just automated, but fully autonomous.

An autonomous supply chain sounds like something out of a sci-fi movie, doesn’t it? But the reality is closer than you might think. Autonomous supply chains represent an era where our supply chains can analyze, learn, and make decisions independently. This has massive implications for efficiency, resilience, and agility in our global logistics systems.

During our conversation, Sanjay shared an enlightening example of how an autonomous supply chain could potentially manage disruptions. Remember the Suez Canal incident? That one seemingly small event had an enormous ripple effect on global supply chains. But what if we could model the impact of such micro events and extrapolate them into macro models, allowing us to predict, and more importantly, prepare for their effects? “Can I take that event and start looking at macro models such as would there be an impact on pricing?” Sanjay pondered.

This is exactly where Roambee comes into the picture. They’re working with advanced technologies like graphical neural networks combined with AI, ML, and RPA to build a new generation of network propagation detection systems.

Starting your journey towards digitizing your supply chain might seem daunting, but Sanjay’s advice is surprisingly simple: “Start with the basics of simply lighting up your supply chain and identifying the glitches… That itself will get you 50% of your, towards your ambition of digitizing the supply chain.”

In the end, it all comes down to this: the path to revolutionizing your supply chain starts with understanding and enhancing your current operations. The first step towards an autonomous supply chain is bringing visibility to your existing one.

We’re on the cusp of a new era in supply chain management, with the concept of autonomous supply chains fast transitioning from fiction to reality. Leaders like Sanjay Sharma and companies like Roambee are spearheading this change, taking us closer to a future where our supply chains are smarter, more responsive, and amazingly autonomous.

Want to delve deeper into the future of autonomous supply chains? I invite you to listen to the full episode of the Digital Supply Chain podcast for more insights and in-depth discussion. Join us as we explore this exciting journey together.

Call to Action: Don’t get left behind! Tune into the full episode of the Digital Supply Chain podcast with Sanjay Sharma here and stay ahead of the curve in the supply chain transformation journey.

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How the Internet of Things Can Make Your Manufacturing Business More Sustainable

The Internet of Things, often abbreviated as IoT, refers to the network of physical devices, vehicles, home appliances, and other items that are embedded with electronics, software, sensors, actuators, and connectivity which enable these objects to connect and exchange data.

The Industrial Internet of Things, or IIoT, is a specific application of the Internet of Things that pertains to the manufacturing sector. In recent years, sustainability has become an important issue for manufacturers as consumers increasingly seek out products that have been made sustainably and with minimal impact on the environment.

Fortunately, the IIoT can help manufacturers reduce their environmental impact and become more sustainable. Here’s how:

  1. Collecting Data to Increase Visibility and Transparency Across the Value Chain
    The first step to becoming more sustainable is to have visibility and transparency across the entire value chain. This means understanding where your raw materials come from, how they are sourced, how they are used in your manufacturing process, what happens to your finished products after they are sold, etc. In order to gain this visibility and transparency, manufacturers must collect data at every stage of the value chain. This data can be collected manually or automatically through sensors and other digital technologies. Once this data is collected, it can be analyzed to identify areas where your company can become more efficient and reduce waste.
  1. Connecting Machines to Improve Efficiency
    One way that manufacturers can use the IIoT to become more sustainable is by connecting their machines together in order to improve efficiency. For example, if one machine is idling while another machine is overloaded, this presents an opportunity to optimize production by redistributing work among the machines. By connecting machines together and using data analytics to optimize production in this way, manufacturers can avoid wasting energy and resources.
  2. Using Renewable Energy Sources
    Another way that manufacturers can use the IIoT to become more sustainable is by using renewable energy sources such as solar or wind power instead of traditional sources such as coal or natural gas. While renewable energy sources may have been more expensive in the past, advances in technology have led to a decrease in cost while simultaneously increasing efficiency. As a result, many manufacturers are making the switch to renewable energy sources in order to reduce their environmental impact.
  3. Implementing Predictive Maintenance Schedules
    Predictive maintenance is a type of maintenance that is performed before problems occur. This is in contrast to traditional preventive maintenance which is performed on a regular schedule whether or not problems exist. By using predictive maintenance schedules based on data collected by sensors, manufacturers can avoid unexpected downtime due to equipment failures. In addition, predictive maintenance can help extend the lifespan of equipment which leads to fewer replacement cycles and less waste over time.

The IIoT offers many opportunities for manufacturers to become more sustainable businesses. By collecting data across the value chain, connecting machines together for improved efficiency, using renewable energy sources wherever possible, and implementing predictive maintenance schedules; manufacturers can reduce their environmental impact while simultaneously improving their bottom line. As consumers increasingly seek out sustainable products, there has never been a better time for manufacturers to take advantage of these opportunities presented by the IIoT .

How IoT Helps Fight Climate Change


The internet of things, or “IoT,” is a system of connected devices that share data and work together to achieve a common goal. By 2025, it’s estimated that there will be 75 billion IoT devices in use worldwide. That represents a major opportunity to reduce carbon emissions and make our economy more sustainable. Here’s how IoT is already reducing carbon emissions, and how it can do even more in the future.

Monitoring and reducing energy usage: One of the most direct ways IoT is reducing carbon emissions is by monitoring and reducing energy usage. Connected devices can track everything from how much electricity a building is using to how much water a factory is consuming. This data can be used to make real-time adjustments that result in significant reductions in energy usage. In some cases, these reductions can be as much as 30%.

Improving transportation: Another way IoT is reducing carbon emissions is by improving transportation. Connected devices can be used to optimize shipping routes and traffic patterns. This results in fewer vehicles on the road and less congestion. Additionally, IoT can be used to develop new alternative fuel sources like electric vehicles.

Increasing green energy use: In addition to reducing energy consumption, IoT can also be used to increase the use of renewable energy sources. For example, wind turbines and solar panels can be outfitted with sensors that allow them to adjust their output based on real-time conditions. This ensures that they’re always operating at maximum efficiency, which reduces the need for traditional (and emitting) forms of energy generation.

IoT presents a major opportunity to reduce carbon emissions and make our economy more sustainable. By monitoring energy usage, improving transportation, and increasing green energy use, IoT is already having a positive impact on the environment. As the number of connected devices continues to grow, so too will the potential for even greater reductions in carbon emissions.

If you’d like to know more about successful climate emissions reduction strategies, don’t forget to check out my weekly Climate 21 podcast. With roughly 100 episodes published, you’ll be sure to find lots of learnings there.

Digital Supply Chain, Industry 4.0, and the Covid-19 Coronavirus – a chat with Martin Barkman

We are in a very strange times! On this third Digital Supply Chain podcast on the theme of Industry 4.0, I had chat with Martin Barkman. Martin is an SVP and the Global Head of Solution Management for Digital Supply Chain at SAP, so I was keen to have a conversation with him about that, but the conversation went a bit off track!

With all that is going on in the world right now it is difficult to avoid talking about the current Covid-19 coronavirus pandemic which has turned all of our lives upside down. So, despite not intending to, our conversation quickly veered into a discussion of the implications of the coronavirus contagion, and its effects on supply chains, manufacturing, and ourselves.

This is an extremely topical podcast, which ends on a positive note. I hope you find it useful.

Listen to the podcast using the player above, and/or see the full transcript below:

Martin Barkman [00:00:00]   The first thing that I think in in times like this organizations have to understand this is what is my what is my supply? Where do I have products? Can I get the product? Am I relying upon regions that are even more hard hit by the particular crisis and whether it’s this viral situation or just in general I think companies are rethinking making sure that they have alternative sources.
Tom Raftery [00:00:29] Good morning. Good afternoon or good evening. Wherever you are in the world, this is the Digital Supply Chain podcast and I am your host Tom Raftery.

 

Tom Raftery [00:00:39] Welcome to the Digital Supply Chain podcast. We are in the series themed around Industry 4.0 and my special guest on the show today is Martin. Martin, would you like to introduce yourself?

 

Martin Barkman [00:00:52] Absolutely, Tom. And thank you for having me. I am Martin Barkman and I head up solution management for SAPs digital supply chain area based in the United States and super excited to be here talking to you today.

 

Tom Raftery [00:01:08] Thank you. Thank you, Martin. so, digital supply chain and industry 4.0. How are they connected?

 

Martin Barkman [00:01:16] It’s a great it’s a great question. I mean, there’s a lot going on with supply chain today. Obviously, the topic at the moment is everything the world is doing to mitigate the effect of this virus. But even before the virus, supply chains were becoming more prominent and more central to the conversations in company boardrooms and frankly, even amongst consumers. Geopolitically, we saw things like trade tariffs, and regulations coupled with uncertainties around the exit of Britain from the United, from the European zone. All of these put pressure on companies supply chains. And then at the same time, you also have consumers that are pickier and have more desires than ever before.

 

Martin Barkman [00:02:15] Whether it’s the personalization of products or even the speed…

 

Tom Raftery [00:02:21] They’ve been spoiled, consumers have been spoiled by the likes of Amazon who are now giving them deliveries same day and even, you know, sub-hour times and things like that. so, that’s gotta put huge pressure on supply chains as well.

 

Martin Barkman [00:02:32] Yeah, it’s interesting. So, you have governments, you have individual consumer. And then there’s this underlying thread around topics of sustainability. You know, consumers are starting to figure out that having the delivery truck come to their house many, many times every day maybe isn’t the most sustainable option. So, we’re seeing a convergence of a lot of these global trends, consumer trends, and it’s converging around the supply chain. And so, how do you set up a supply chain that can really accomplish all of this in a fundamentally different way? You asked about Industry 4.0, and it’s an interesting term. It actually originated in in Europe many, many years ago. And it was primarily focused around the automation of the factory or the plants. Now we’re seeing the concepts actually extend to the entire supply chain, to the assets that are deployed throughout the supply chain, all the way to the way distribution and logistics is handled. And it’s all about using technology and data to fundamentally change and take a step change in productivity. Other times it’s called industrial Internet of Things, so, I just wanted to throw that out there, that that’s also a term that’s often used.

 

Tom Raftery [00:03:52] Sure, sure. And I mean, we’re not going to harp on the whole Coronavirus thing because, you know, there’s lots of other people talking about that. And, you know, people better, better informed than us. But things like that are going to be putting huge pressure now, you gonna think on supply chains. I mean, particularly there’s going to be a huge increase in the requirement for logistics as more people, you know, stay at home and have a requirement to have things delivered to their home. so, that that’s going to that’s going to change the logistics industry. It’s going to grow the logistics industry, and it’s going to completely you got to think change how a lot of supply chains are organised.

 

Martin Barkman [00:04:31] Yeah. No, no, no doubt. And it is it is absolutely the topic of the day and what companies are focusing on. I mean, you know, the first thing that I think in in times like this organizations have to understand is what is my what is my supply? Where do I have product? Can I get the product? Am I relying upon regions that are even more hard hit by the particular crisis and whether it’s this virus situation or just in general, I think companies are rethinking, making sure that they have alternative sources identified. They understand the implications of those sources.  They have the ability to switch and shift order volumes from one, one to the other. You know, so. That that I think is kind of step one in a time like this, of course, with that comes also an understanding of where you have inventory in the supply chain and how can you use that inventory to ultimately create new finished goods and move those finished goods to the point where they are most, most desperately needed. I think at the same time, demand is is really, really changing. We’re seeing spikes in demand for products that are absolute critical.

 

Tom Raftery [00:06:01] Toilet Rolls?

 

Martin Barkman [00:06:01] Whether it’s. But it’s not just I mean, it’s paper products in general. Right. Diapers and such. Certainly, in personal hygiene products. I mean, right now, Amazon is prioritising the delivery of those to consumers at the expense of maybe some products that are not deemed to be quite as urgent. I think for companies, what’s critical is understanding, you know, just by how much and where and to what degree demand has changed, because ultimately that picture has to be you have to form the unified picture of demand and supply and ultimately how you how you solve for that. so, you want to get your arms around. So, I yeah. This is a you get your arms around that. That demand certainly part of the supply picture is also the capacity. And you mentioned people are now working from home, certainly in some professions that’s a possibility. In professions like running a manufacturing operation, that’s not always the case. The customers we have that I’ve talked to are trying to keep these critical plants up and running plants that are involved in producing products that are more needed now than ever before. But the method in which you do that right, the way you run your shifts, the way you inform and encourage people to work when they are on the shop floor is different. Right. We can’t stand shoulder to shoulder anymore. We have to maintain the social distancing even in the workplace. so, I think its capacity, its inventory, its supplier and supply and its demand and forming that picture and understanding also what is it saying I need to do today? But what are the what ifs and the scenarios? We live in an extremely dynamic environment. so, this week is fundamentally different than last week. so, whatever I thought was my plan last week, it’s very likely that that plan now needs to change. so, I need an environment and an ability to rerun those scenarios very, very effectively. Once I choose a scenario and I say, OK, this is the one I’m going to operate, that, how do I put it into action all the way down to planning the transportation and understanding how to get it ultimately to the end consumer?

 

Tom Raftery [00:08:29] And demands have got to be swinging wildly as well at the moment. I mean, we talk about people working from home. That’s going to mean a huge drop in demand for, you know, petrol, diesel those kinds of fuels to get people to and from work. And on the other hand, there’s going to be a huge uptick you got to think and demand for things like webcams so, people can more effectively work from home.

 

Martin Barkman [00:09:00] Yeah. so, it’s interesting right now, I think we’re all trying to come to grips with what is the the new…the drop in, you know, what is the the drastic change in demand, and as I mentioned earlier, how do companies get their arms around that? But soon we will have to start to plan for the recovery. Is the recovery going to be like the letter V, where it’s a sharp drop and then a sharp rise, is it going to be like the letter U where it’s a drop and then it’s a period of really, really low band in general, but then an uptick. Or frankly, it’s almost gonna be like the letter L you know, the classic where we’re gonna be at a low point of demand for quite some time and then maybe we see a gradual, slow recovery. And the answer is, of course, we don’t know, and it may actually differ for different products. I also think we have to think about the possibility that when we emerge from this, yes, things will be fine, but they will be different. Right. so, if you think back to the 9/11 crisis, we started to fly again, but airport security was fundamentally changed. Will our way of working be fundamentally different when we emerge from this crisis? so, we have to understand how we will emerge and what the scenarios are so, that we can plan accordingly. But then let’s not assume that everything returns to the way it was. It may not be for certain parts of the economy or for certain industries or for certain types of products.

 

Tom Raftery [00:10:57] And how do companies plan for that?

 

Martin Barkman [00:11:02] Yeah, I think…

 

Tom Raftery [00:11:07] The 64-million-dollar question?

 

Martin Barkman [00:11:08] Yeah, look, I mean, you hear it said every day. Right. These are unprecedented times. Companies that have a good handling of their data, of their information and they’re able to bring it into one environment where they can run these scenarios. Not to pretending that they know exactly what’s going to happen, but they can say, you know what, if this happens, what if we have a quick recovery? What if we have a prolonged recovery? What if they make some more of our products coming out of the recovery maybe is a little bit different? What if a part of the world relapses later this year and the epidemic comes back in a limited form? so, I think companies that have that kind of digital environment are going to be able to plan these different scenarios. They may not know, but they can certainly weigh the different options. But I also think it’s interesting. Right? so, Industry 4.0 if we over time, are able to automate and run more critical parts of the supply chain in an autonomous or perhaps in a remotely controlled way. And this is already happening. I mean, I’ve been to see many production operations. You know, the people there are operating them behind a glass wall or in the case of milling and mining, significant parts of the operation might be controlled in a control centre that’s located hundreds of miles away and then using cameras and digital infrastructure they’re able to control the equipment. The interesting thing about that is when the next pandemic, and I hate to even say it comes, supply chains might be able to operate more autonomously, because people are not necessarily working and standing right next to each other. It’s not that we have eliminated the need for people completely, but we’ve eliminated the need for people to stand closely together performing the tasks and potentially risking their safety as a result.

 

Tom Raftery [00:13:38] so, Martin, I think one of the most important things at this kind of time is transparency in supply chains. Can you talk a little bit about that for us?

 

Martin Barkman [00:13:48] Absolutely. And it’s really interesting because supply chains almost by nature, right? You think everything happens in sequence from one step to the other it’s very linear oriented, and in many cases, it is, right? You start with a but raw material and you convert it into something that you ultimately distribute and sell. However, that’s a very simplified view. And what has been happening already is supply chains are becoming more networks. Right? so, you source raw materials more through a network, in many cases. Your manufacturing setup is a network. You have your own manufacturing sites and you have the ability to go out and work with contractors in a network type of capacity. Transportation. Same thing. You source transportation through a network and you work with a network of providers. And as a result, the supply chains are actually becoming less linear and sequential and more networked. Now, more than ever, visibility of what’s happening in your supply chain is very important. And because it’s more networked, you need the visibility through your network. so, you need to understand. Not just what’s happening within the four walls of your supply chain, but within your supply chain network. so, this is a topic that was already becoming important. I think now more than ever, it’s of upmost importance. Companies are setting up, you know, war rooms and crisis management centres to understand how to maximize their ability to serve their customers. And of course, information and visibility are very, very key to that. Now, beyond this pandemic, there are other cases where having visibility is very important. What if there’s a product recall? How do I ensure that I can trace the source of the recall or the cause of the recall through my supply chain and remove the product that is subject to the recall without overdoing it, without removing a product that does not have to be subject to the recall. so, there there’s just a lot of ways in which this connecting everything and then having that be rendered simultaneously more closer, if not real time. It’s becoming very, very important.

 

Tom Raftery [00:16:23] And for organizations who are in the throes of this right now, I mean, what would you advise them to do if they haven’t got the kind of transparency that they need or if they are starting on that project or if they’re even if they’re in that in that project and they’re looking to increase their  visibility into their supply chain where we’re should. What should they do? What kind of steps should they take?

 

Martin Barkman [00:16:51] Yeah, it’s hard to think of a one size fits all, but. There’s a good chance that there are some pockets of places in their supply chain where the information resides digitally. Sometimes that could be very large pockets, large repositories. I would say an initial key step is assess what is the digital environment you have? What are the existing tools you have in place and look for ways to activate elements of those tools that maybe you haven’t otherwise activated. So, for example, we have customers that are running the SAP integrated business planning application to do the scenario analysis that I talked about earlier. It has inherent capabilities for things like visibility. We call it the control tower. Ensure that you’re leveraging those capabilities to the fullest, which in some cases, if you aren’t, isn’t a big undertaking to go do.

 

Tom Raftery [00:17:53] Okay.

 

Martin Barkman [00:17:55] And certainly that’s something that that companies can consider.

 

Tom Raftery [00:18:00] All these things are kind of on a curve so, they can move kind of further to the right on the curve to increase their visibility, you’re saying?

 

Martin Barkman [00:18:07] Yeah. I mean, it’s a matter of time too, right? And, you know, are there quick wins that can be attained right now? At some point, companies may look to say, you know, how do we how do we take a step change in our in our digital environment, in our infrastructure, so, that we can do this on an ongoing basis, not just when a pandemic comes across, but frankly, sometimes you see a spike in demand that you hadn’t forecasted. You would like nothing more than to meet that demand. But you don’t know if you can or what it would take to meet that demand. so, you need to be able to run these plans and rerun the plans more often. You know, that’s the kind of capability that I think companies at some point are going to start to say, you know what, it makes sense to pursue that.

 

Tom Raftery [00:18:53] Excellent. Martin, we’re coming towards the end of the podcast now. We’re at about 18 minutes, 19 minutes into the into the podcast. Before we end up before we finish up, is there is there any question that I have not asked you that you think I should have?

 

Martin Barkman [00:19:14] I perhaps one thing we should conclude with is, you know what what is, pandemics aside, if we allow ourselves the luxury and the pleasure of removing that that new lens just for a second, maybe what is on the other side? And what do we think is is of utmost importance to companies? And I’d just like to talk about that, because I think we have to allow ourselves the ability to think in those terms, right? For the future and to us and what we see from our customers is supply chain is moving increasingly, from a pure back office function to something that’s at the at the boardroom level, very much part of the discussion. And the reason is we are moving into an era where it’s all about the experience economy, meaning what is it that customers want to experience when they do business with you? What is it that your employees want to experience when they go to work? What is it that your shareholders are looking for you to accomplish right in your community? Same thing with the environment. And we think that’s very exciting for those of us that are passionate about supply chain, because how can you accomplish something on all those axes and on all those vectors without a really, really comprehensive approach to supply chain management, right? What is the point of selling a product that’s marketed well, if in the end the product doesn’t meet customer needs from a quality and functionality standpoint? What is the point of having the most perfectly manufactured product with all the bells and whistles if in the end it’s delivered late to customers? so, the supply chain is what brings that ultimate experience very much together. And we see companies making investments in supply chains in ways that traditionally wouldn’t have been wouldn’t have been thought of. And it’s so, that the supply chain can help the company be successful in the experience economy. And we think that’s exciting and we think that’s very much on top of minds of companies right now, maybe a little bit further back of their mind, given the urgency, but nevertheless, something that absolutely has to be continued to be addressed.

 

Tom Raftery [00:21:57] Excellent, excellent, excellent. Martin, if people want to know more about Martin or about supply chains or about business planning or any of the above, where would you have me direct them? I’ll put some links in the show, notes in the description, this podcast so, you just tell me what to put in there.

 

Martin Barkman [00:22:17] Sure. Let’s assume they want to know about supply chain more so, than they know about me. Certainly, I’m on LinkedIn. But for for supply chain and what we’re doing at SAP, I would invite everyone actually to go to SAP.com, and in there we have sections for supply chain management. We have a lot of interesting content of what we’re seeing are the big trends and what companies are doing. And we have a lot of testimonials from companies with whom we work. And I think that’s an exciting place for people to start to learn more.

 

Tom Raftery [00:22:55] Super, super. Martin, thanks again for joining us on the show today.

Martin Barkman [00:23:01] Thank you so, much. It’s a pleasure.

 

Tom Raftery [00:23:04] OK. We’ve come to the end of the show. Thanks, everyone, for listening. If you’d like to know more about digital supply chains, head on over to SAP.com/digitalsupplychain or simply drop me an email to Tom.Raftery at sap.com. If you like to show, please don’t forget to subscribe to it in your podcast application to get new episodes right away as soon as they’re published. And also, please don’t forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.

Digital Supply Chain, Industry 4.0, and IoT/Edge Computing – a chat with Elvira Wallis (aka @ElviraWallis)

On this second Digital Supply Chain podcast on the theme of Industry 4.0, I had a great chat with Elvira Wallis (@ElviraWallis on Twitter and Elvira Wallis on LinkedIn). Elvira is the Global Head of IoT at SAP, so obviously I was keen to find out her take on how Digital Supply Chain, IoT and Industry 4.0 intersect.

We had a great conversation covering Supply Chain, Internet of Things, Edge Computing, Cloud – their use cases, challenges and opportunities.

Read the full transcript of our conversation below, or listen to it using the player above.

Elvira Wallis [00:00:00] The Internet of Things is a key enabler for industry 4.0, and it is required to make industrial IoT, to make industry 4.0 possible because you need to connect to sensors, you need to connect to autonomous systems. You need to connect to CoBots. You need to connect to big data lakes and so forth.

 

Tom Raftery [00:00:21] Good morning, good afternoon or good evening. Wherever you are in the world, this is the digital supply chain podcast. And I’m your host, Tom Raftery. Hi, everyone, welcome to the supply chain podcast. This is another of the industry four-point all themed podcasts of the digital supply chain podcast. And my very special guest on the show today is Elvira Wallis. Elvira would you like to introduce yourself.

 

Elvira Wallis [00:00:48] Sure Tom. Thanks for having me on the podcast. So hello, everyone. My name is Elvira Wallace and I am running Internet of Things here at SAP.

 

Tom Raftery [00:00:58] Super. Well, that’s a great role. Can you tell me Elvira, we’re on the obviously Industry 4.0 themed podcast today, so how are we connecting Industry 4.0 and Internet of Things? Cause, you know, for a lot of people who think about Industry 4.0, they might think about maybe, you know, improvements in manufacturing and things like that. But it is just that? Is it more than that? How do you how do you see Industry 4.0 and the connection to IoT?

 

Elvira Wallis [00:01:27] Yeah. So, let me maybe start with some, you know, regional flavour here. In Europe we often like to call things industry 4.0. If you look into North America the same phenomenon, namely the phenomena of an industrial transformation using new digital technologies such as Internet of Things or Edge and cloud computing, big data lakes and so forth, is termed industrial IoT, so dependent on the region of the world, the terms industry 4.0 and industrial IoT are used interchangeably and referring to an industrial transformation using new digital technologies. And if you didn’t go to Asia, it’s called ABC Country 2025 or D E F Country 2030. In other words, we’re all talking about a phenomenon of industrial transformation which we often call Industry 4.0 in Europe. And it requires new digital technology such as the Internet of Things, edge and cloud computing, big data lakes. So, in other words, the Internet of Things is a key enabler for Industry 4.0. And it is required to make industrial IoT to make industry 4.0 possible, because you need to connect to sensors, you need to connect to autonomous systems, you need to connect to Cobots, you need to connect to big data lakes and so forth. So, you need an enabler. And the key here is, all of that data in and by itself is relatively uninteresting. Where SAP comes in… And that has to do with our rich history and also our hopefully very rich future is bringing this type of data with our technologies in the context of business processes.

 

Tom Raftery [00:03:21] OK, OK. Now, for people who may be unfamiliar… We’re obviously not a hardware company. We’re a software company. And IoT is very much a mix of hardware and software. So, where do we fall into that kind of ecosystem?

 

Elvira Wallis [00:03:37] It’s a very, very good notion that you bring up. Clearly, Industry 4.0 as well as Internet of Things is not a one person’s island. Whoever sets out with the idea of it’s me, myself, and I shall fail miserably. It is an ecosystem play that requires the OT players, it requires the hardware players. It requires some clearly various software companies and even into software realm, it’s not SAP alone, it’s us and our esteemed ecosystem. Where SAP is playing is clearly solely in the realm of software, right? Not hardware. Of course, we have a lot of hardware partners that we work very closely with so we can recommend to our customers in specific situations, specific types of hardware.

 

Elvira Wallis [00:04:23] So we’re not ignorant, we’re just not owning that space. Yet to your question, where we’re playing, we’re playing in two places if we cut it very broadly. One is the cloud where we have, of course, the applications that run in the cloud as well as the underlying technology for Internet of Things that works in conjunction with the applications and the second realm where we’re playing is edge computing. The world is moving more and more towards distributed computing. And when SAP says edge computing, we’re of course again referring to software and our software runs on various types of hardware, very close to the source of data. And as to the hardware we run on we’re agnostic, we play with many of the key industry leaders here.

 

Tom Raftery [00:05:17] OK. OK. So, for anyone who is unfamiliar with the concept of edge computing, could you just give us a 101 on that?

 

Elvira Wallis [00:05:25] Oh, definitely. And it’s one of my favourite topics. So, let’s not start with, you know, with SAP. Let’s start with the trends in the market. Right. Great. And. If we put it very, very generically, then edge computing is a new form of distributed computing, meaning not all data will be processed in the cloud. Some data will be processed at the edge. So, what is the edge? It’s basically edge computing means running data applications and business processes near the source of that generated data. So, the source of the generated data could be a factory, a plant, a mine. And it refers to the concept of running the data running the application, the business process near to the source of the data, and if people now say, oh, isn’t it very far away and do we need to deal with that today?

 

Elvira Wallis [00:06:19] Maybe some data points, Tom. If we’re if we’re looking at edge computing, it has been growing steadily in the past and if you if you listen to the analysts, Gartner, for example, predicts that by 2025, 50% of enterprise generated data would be created and processed outside a traditional centralized cloud data centre. Now, 50%, is that a lot or not? Well, that would be up from 10% in 2019. So that’s quite a big growth in the ability to, you know, extend and run business processes at the edge, meaning in the plant, in the factory close to the source of data that enables customers to automate and run their operations independently, and that’s what a lot of people want in the world of industry 4.0, in the world of industrial I.T. in order to endorse the digital transformation. They say, hey, my plant, my factory needs to run independently of the cloud. So, in order to endorse the cloud, we see a new form of distributed computing, namely the edge. And the edge addresses customer concerns with running and low latency. Right. Very often we hear that I need to run low latency, low bandwidth. And then let’s not forget in many places of the world there, specific security and regulatory requirements which says, hey, the data must be processed locally instead of in a centralized cloud. So, it can also be regulatory reasons why edge computing starts to prevail. And if you listen to some more data points and then IDC, for example, predicts that by 2023, 70 percent of IoT deployment will include edge-based decision making, right. So, the decisions will be made decentral supporting the organization’s agenda. So, meaning we can do industrial IoT. We can do industry 4.0 without it, meaning some central cloud-based system taking over. Local autonomy can happen if edge computing is involved. And if we look at the IDC saying they’re saying, OK, 70 percent of all enterprises will run varying levels of data processing at the edge. And that also means organizations will have to spend a lot on IoT edge infrastructure in that timeframe.

 

Elvira Wallis [00:08:53] So I think edge is here to increase in prominence and in relevance for our customers, and it’s a good idea to get prepared. I mean, we at SAP we’re very well positioned to run data driven business processes at the edge. We can run manufacturing processes at the edge orchestrated from the cloud, and we provide our customers the option to run applications in a hybrid approach meaning, at the edge and clouds and this hybrid cloud edge offering helps customers accelerate the transition to the cloud by addressing their need around data privacy, around security, around latency and regulatory requirements.

 

Elvira Wallis [00:09:37] Now, going back to no person is alone. It’s, of course, clear that we also in the realm of edge computing, we’re in need to be committed to a strong ecosystem. No one can do it alone. You need the hardware providers, and we have announced strategic partnerships with the hyper scalars and also in some cases regional industry specific players in IoT and edge where we leverage the strength of all the players in the ecosystem to help our customers be successful. It’s a joint digital transformation where SAP participates together with our customers and our partners.

 

Tom Raftery [00:10:14] OK, super, super for any of our customers, potential customers or just anyone who’s listening, who is interested on embarking on some kind of industry 4.0 project. How do you start something like that? Where do you kick off?

 

Elvira Wallis [00:10:35] And so it’s a very good point to raise. My first perspective would be. There is no one size fits all right? Customers are. By and large, all increasingly challenged to adapt to ever changing conditions. Now, mind you which of these conditions is the most prevalent and in which line of business is it the trade wars? Is it managing the global supply chain? Is it skills shortages? Successful customers need to embrace the digital transformation right to discover new ways to solve their business problems and to keep their customers engaged. Because this is also to do with customer experience and customer loyalty. Now, customers might start in different areas. They all centre on their customers. But whether they start with reinventing production to centre on their customers or whether it is connecting various departments in their company to overcome their own segregation of duties in a way that is hindering success. That is something that customers really will vary. In other words, SAP can help make industry 4.0 an everyday reality. Now where customers start, whether it’s with the intelligent asset and managing the overall equipment effectiveness or whether it’s the intelligent product where customers want to understand the business impact of design and engineering changes in products, or whether it’s the intelligent factory where IoT helps enterprises to be agile and deal with varying production volumes and new manufacturing technologies, or whether it is with empowering people so that people can fulfil complex tasks with a fast work-around that is really dependent on the customer need. We need to understand that it’s important to centre on the customers and connect the entire company, but it doesn’t mean you need to start everywhere at the same time with the same urgency. Our clear perspective is customers have a choice where they start and we recommend to start somewhere, where of course there is an immediate need and it can be time boxed because nothing is more convincing than initial positive results and then you can widen the exercise.

 

Tom Raftery [00:13:02] Okay, very good. What kind of challenges are companies likely to face on a journey like this? I mean, you mentioned, you know, having skilled staff there. Is it is the staffing or is it technology or is it a combination or is it something else entirely and you know, having then identified a couple of the challenges, what would be ways of overcoming them?

 

Elvira Wallis [00:13:28] It’s a very good question. And there are some interesting studies out there in the market that I enjoyed. One is by McKinsey and that study showed clearly that the success rate of these digital transformation projects are not necessarily tied to the area within which they are started. So, you couldn’t say, oh, let’s start it in production or let’s start around the asset and as it is more successful than production or, vice versa right? What they showed is it is other factors that correlate with success. In other words, the more initiatives a customer ran. So, in other words, if they addressed digital transformation in more lines of business, they were likely to be more successful than if they were just doing what I would call island exercise in one area. So, spreading wide helps clearly with the RoI. The other thing that some of the studies showed is time boxing is key, having a line of business sponsor is key. So, in other words, it doesn’t work if you have just some little IT exercise or if it’s just some innovation centre not connected to the line of business. So, sponsorship, time boxing, clear KPIs as to what do we want to achieve, and which problem do we want to solve. In other words, all that is more successful than what I would call analysis paralysis and looking for the perfect case. Or the what I would call research approach where let’s take some sensors and collect them and produce a dashboard. So, you need to have a clear proof business problem to solve, a business sponsor, time boxing, clear KPIs and ideally more than one initiative. Spreading it and seeing what are the successful front runners and building on those. Those are clearly some of the what I would call non-technology challenges in a way they are common sense that we learned from various studies, but also from working with our customers.

 

Tom Raftery [00:15:30] OK. OK. Very good. We’re coming up towards the end of the show, now Elvira. Is there any question that I haven’t asked you that you think I should have?

 

Elvira Wallis [00:15:44] It’s a very good question. I would say when we look at the type of use cases, what kind of typical use cases do we see is one question that I very often get asked and I mentioned before, yes, we have the area of intelligent asset, intelligent product, intelligent factory and empower people. Now, another dimension to look at it would be what type of goals are people pursuing? Is it about new business models? Is it about efficiency? Is it about customer experience? In other words, what type of goal do people look at? And one thing I’d point out is we see increasingly people looking at some product as a service offerings. Now, that doesn’t work for all types of offerings, but that is something that we see a shift to product as a service in the construction, transportation, hospitality, realm and insurance industries. Where we see a shift and I believe we look at new customer experience, in other words, does my digital transformation help me create a better, better customer experience is clearly something that we see where people look at their customers, but also their customers customers. And I would encourage people to take that line of sight to look in addition to the productivity gains and the overall production. Really the focus on the customers and to put that at the forefront and the centre of a digital transformation.

 

Tom Raftery [00:17:17] Superb. Elvira if people want to know more about Elvira, or IoT, or Industry 4.0, or any and all of the above where would you have me direct them and feel free to give multiple links? I’ll put them into the description of the show notes when I publish this.

 

Elvira Wallis [00:17:35] Oh definitely join me on Twitter. Join me on LinkedIn. And of course, we have our flabbergastingly great web site SAP.com/IoT. And not to forget, we’re going to run an openSAP IoT course in the near future. And I would really appreciate you joining us in that openSAP course.

 

Tom Raftery [00:17:56] Fantastic. I’ll have links to all of those in the show notes. OK, that’s been great. Elvira. Thanks a million for joining us on the show today.

Elvira Wallis [00:18:01] Thank you, Tom. It’s always great to be one of your interviewees.

And if you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

8 predictions for the Internet of Things (#IoT) in 2018

As 2017 comes to a close, it is customary to look forward to the year ahead and think about what will come. Some of us in SAP put our heads together to come up with a list of likely trends in the Internet of Things space for the next 12 months.

In no particular order:

  1. The IoT hype is over – but the trough of disillusionment typically precedes mainstream adoption. Customers have by now generally accepted IoT as a main driver of digital transformation, however, in 2018, they will be looking for business value and outcomes in every project. There is no doubt that all newly released products and installed assets will be connected with an increasing amount of sensors and intelligence embedded
    IoTvsCloudTrendshttps://trends.google.com/trends/explore?date=all&q=%2Fm%2F02vnd10,cloud%20computing&hl=en-US
  1. The IoT cloud platform market will consolidate quickly
    Microsoft Azure and Amazon AWS will probably take the largest shares. IBM Cloud, Google Cloud Platform, SAP Cloud Platform, and Oracle Cloud will be runners up. Most other IoT vendors will move (or have ported) their IoT offering onto a leading cloud platform-as-a-service stack (e.g. GE, Siemens)Here’s Why GE Shelved Plans to Build its Own Amazon-Like Cloud: http://fortune.com/2017/09/06/general-electric-cloud-pivot/
    Mindsphere debuts on Amazon Web Services http://news.usa.siemens.biz/blog/digital-factory/mindsphere-debuts-amazon-web-services
  1. IoT vendors will refocus and lead with IoT solutions delivering value to their installed base. GE Predix is now focussing on selected verticals and asset-intensive industries; while Microsoft is looking to manufacturing (with new focus on OPC-UA)GE https://www.ge.com/investor-relations/sites/default/files/GE%20Investor%20Update_Presentation_11132017.pdf (page 18)
    Microsoft IoT Central broadens reach with simplicity of SaaS for enterprise-grade IoT https://blogs.microsoft.com/iot/2017/12/05/microsoft-iot-central-broadens-reach-simplicity-saas-enterprise-grade-iot/
  1. IoT architecture will evolve from data ingestion and analytics to an intelligent event-driven solution for end users
    Data science, machine learning, and physics-based models will extract meaningful events from IoT data for users to take prescriptive actionGartner https://www.gartner.com/newsroom/id/3758164
    Blog referencing Gartner https://realtimeapi.io/2020-50-percent-managed-apis-projected-event-driven/
  1. The edge will move from connectivity to distributed intelligence
    Edge solutions are becoming increasingly intelligent and autonomous, adding analytics and machine learning, while distributed edge-cloud programming paradigms emergeGartner https://www.gartner.com/smarterwithgartner/what-edge-computing-means-for-infrastructure-and-operations-leaders/
    Amazon Greengrass https://www.forbes.com/sites/janakirammsv/2017/06/07/amazon-makes-foray-into-edge-computing-with-aws-greengrass/#47b0bc0b3298
    Microsoft IoT Edge https://azure.microsoft.com/en-us/blog/azure-iot-edge-open-for-developers-to-build-for-the-intelligent-edge/
  1. Digital twins will evolve from concepts to blueprint and implementation for data sharing within and across companies
    While many early IoT projects focus on efficiency and cost reduction, the long term business value of IoT is in the network of business partners and digital twins. Marketplaces start to emerge to monetise IoT data while blockchain technologies ensure data provenance and device traceability (and payment)Digital Twins https://www.i-scoop.eu/digital-twin-technology-benefits-usage-predictions/
    IDC Predictions https://www.idc.com/url.do?url=/getfile.dyn?containerId=US43193617&attachmentId=47282916&elementId=54584641&term=&position=4&page=1&perPage=25&id=89172f0a-fdd7-48a1-871b-3bb213638507
    IOTA Data Marketplace https://blog.iota.org/iota-data-marketplace-cb6be463ac7f
    IBM IoT on Blockchain https://www.ibm.com/us-en/marketplace/iot-blockchain/details
    SAP IoT Blockchain initiative https://news.sap.com/sap-announces-first-co-innovation-customers-partners-in-blockchain-initiative-for-internet-of-things/
  1. Integration will remain challenging despite advances in open standards and architecturesIndustry standards will slowly emerge to address semantic integration (e.g. OPC-UA, RAMI), but take long to get fully adoptedhttp://opcconnect.opcfoundation.org/2017/06/there-is-no-industrie-4-0-without-opc-ua/
    IIC and RAMI / Industrie 4.0 align https://www.automationworld.com/industrial-internet-consortium-and-plattform-industrie-40-align-architectures
    Edge  http://www.iiconsortium.org/press-room/08-02-17.htm , https://globenewswire.com/news-release/2017/09/25/1131891/0/en/ETSI-and-OpenFog-Consortium-collaborate-on-fog-and-edge-applications.html
  1. Security and privacy will remain key concerns IoT security
    The standalone IoT security market is dead, but IoT security will be embedded into hardware, network, and systems with IoT security becoming a dedicated threat domain; data privacy legislation and concerns (specifically in Europe and China) will impact IoT architectureIoT security outlook Blogs http://www.ioti.com/security/8-iot-security-trends-look-out-2018 & https://www.i-scoop.eu/internet-of-things-guide/iot-security-forecasts/

Hopefully these predictions will give you some food for thought over the holiday season. In any case, enjoy your time off, and see you in 2018 🙂

 

Photo credit Frank Monnerjahn

Predictive Maintenance for People – the endgame for the Internet of Things (#IoT) and healthcare

Predictive maintenance is one of the oldest and most tested uses cases for the Internet of Things (IoT).  For years now, we’ve been able to analyze incoming data from sensors embedded in machines and make decisions about whether or not maintenance activities should be executed.

Typical scenarios have historically focused on things like wind farms, oil rigs, and fleets of trains. And while there’s plenty of excitement and new developments in these areas, what’s grabbing a lot of attention today is how predictive maintenance can be applied to new scenarios.

For example, in an earlier blog, I talked about predictive maintenance for autonomous vehicles – how sensors can send out data on the status of parts and components, allowing manufacturers to analyse this data to predict part failure and, thus, avoid breakdowns.

Yet, even this scenario keeps us in the realm of machines – because, sophisticated as it may be, an autonomous vehicle is still a machine. But what if we could now take the same general idea of predictive maintenance for machines and apply it to our bodies? Call it preventative maintenance for people – or just predictive healthcare. The reality is that in many ways, we’re already there.

Understanding in context

One of the advantages to predictive maintenance for machines is that incoming data about what’s going on in the moment can be analyzed in the context of historical data about the same machine. Let’s say an HVAC machine on the top of a hotel in Seville – where I live – sends out a high-temperature alert.

In and of itself, yes, this may be cause for concern. But when you realize that the machine sends out the same alert every month at the same time – well, maybe it’s not so concerning. Maybe the HVAC unit runs continuously for 8 hours on the first Monday of every month to help cool a large conference room on the used for the packed monthly meeting of the Seville Dog Walker’s Association.

Or maybe there’s another reason. The point is that in such a scenario, the high temperature alert is understandable and predictable in context – and thus of little concern. It would be nice if we had something similar for healthcare.

More than a snapshot

Here’s the problem: On a typical trip to the doctor you wait in the waiting room for 10-15 minutes, with other people, some of whom are likely sick. When you finally see the doctor, you’re thinking of the next appointment you have across town in 30 minutes so your anxiety levels go up.

My sister Mary was recently diagnosed with high blood pressure because when she was in the doctor’s clinic her blood pressure measured 150/89. The doctor advised her to get a connected blood pressure cuff, and to take regular measurements. When she did, it turned out her blood pressure was 108/75 – completely normal. She was suffering from what doctors call White Coat Syndrome.

IMG_4359

But as with the HVAC machine, the high blood pressure reading was understandable in the context of her being in a doctor’s office. Wouldn’t it be great if the doctor evaluating your blood pressure had more than a snapshot of (often misleading) data to work from? Wouldn’t a whole bunch of relevant historical data be better?

With the smartwatch on my wrist, I can now share 3 years of data with my doctor. Now s/he can see things in context and treat me more effectively. I think it’s only a matter time before their office can take my sensor data in automatically – over the cloud. This will make my yearly check-up more productive. Instead of figuring out what the problem is (if there is one, hopefully not) we’ll be able to focus on what to do about it.

A business network for health  

As with so many things IoT, this is only the beginning. But let’s step back for a moment.

One of our offerings here at SAP is the SAP Asset Intelligence Network (SAP AIN). Think of it as a business network application. With SAP AIN, all of the data (metadata, specifications, bills of materials, whatever) that goes into the creation of a device (a compressor, coffee machine, car, whatever) can be stored in a central location.

When connected to the asset intelligence network, the device can push out real-time data that describes its state at any given moment. When the device owner allows access to this data, the manufacturer can then analyse it in conjunction with other data from other devices – making product improvements that can then be pushed out by way of the same asset intelligence network.

In fact, nothing is stopping device owners from sharing their data with whoever they wish – like maybe a service vendor, or insurance company. If a device goes out of tolerance for some reason, the service vendor could receive a notification and schedule an appointment to service the device automatically. Or in the case of an insurance company – they could then set rates according to actual device usage data.

Returning to the theme of health – what if we took this idea of an asset intelligence network and applied it to our own bodies? What if we had a “people’s intelligence network” – where a device like my smartwatch publishes my health data into a trusted cloud application?  When my device senses high blood sugar, for example, this data gets analyzed not only in the context of the unique moment mixed with my own personal health history – but also in the context of similar data from potentially millions of people.

Based on this much larger dataset, the network could then contact my service vendor – in this case, my doctor – and make an appointment if necessary. Yes, this would be convenient. But more importantly, it would move us away from making medical decisions based on poor data and the intuition of physicians, toward something often heralded but seldom achieved – real evidence based medicine.

Photo credit Chelsea Stirlen

Artificial Intelligence and the Future of Jobs

My role here at SAP is IoT Evangelist. It’s my job to go around and speak about how the Internet of Things is changing the way we live, work, and run our businesses. IoT Evangelist is a job title that didn’t exist 5 or 10 years ago – mainly because the Internet of Things wasn’t a “thing” 5 or 10 years ago. Today it is, so here I am.

The fact is, technological change has a tremendous impact on the way we spend our working lives. Many of today’s jobs didn’t exist in the past. Of course, the reverse is true as well: a lot of jobs – mostly tedious/manual labor of some variety, think miners, lift operators, or similar – have gone away.

Robots and much more

Much of the discussion today about the relationship between technology and jobs is a discussion about the impact of artificial intelligence (AI). Robots in manufacturing is the most obvious example. A lot of AI has to do with big data analysis and identifying patterns. Thus, AI is used in data security, financial trading, fraud detection, and those recommendations you get from Google, Netflix and Amazon.

Screen Shot 2017-11-28 at 14.01.55

But it’s also used in healthcare for everything from identifying better subjects for clinical trials to speeding drug discovery to creating personalized treatment plans. It’s used in autonomous vehicles as well – to adjust, say, to new local conditions on the road. Some say it’s also coming for professional jobs. Think about successfully appealing parking fines (currently home turf for lawyers), automated contract creation, or automated natural language processing (which someday could be used to write this blog itself – gulp!).

The spinning jenny

Will AI continue to take jobs away? Probably. But how many new jobs will it create? Think back to the spinning jenny – the multi-spindle spinning frame that, back in the mid-18th century, started to reduce the amount of work required to make cloth.

By the early 19th century, a movement known as the Luddites emerged where groups of weavers would go around smashing these machines as a form of protest against what we’d now call job displacement. But these machines helped launch the industrial revolution.

As a result of the spinning jenny’s increased efficiency, more people could buy more cloth – of higher quality, at a fraction of the cost. This led to a massive uptick in demand for yarn – which required the creation of distribution networks, and ultimately the need for shipping, an industry that took off in the industrial revolution.

As the spinning jenny came into use, it was continuously improved – eventually enabling a single operator to manage up to 50 spindles of yarn at a time. Other machines appeared on the scene as well. This greater productivity, and the evolution of distribution networks also meant there was a need for increasingly comprehensive supply chains to feed this productivity boom.

Muscle vs caring

Economists at Deloitte looked at this issue of technological job displacement – diving into UK census data for a 140-year period stretching from 1871 to 2011. What they found, not surprisingly perhaps, is that over the years technology has steadily taken over many of the jobs that require human muscle power.

Agriculture has felt the impact most acutely. With the introduction of seed drills, reapers, harvesters and tractors, the number of people employed as agricultural laborers has declined by 95% since 1871.

But agriculture is not alone. The jobs of washer women and laundry workers, for example, have gone away as well. Since 1901, the number of people in England and Wales employed for washing clothes has decreased 83% even though the population has increased by 73%.

Many of today’s jobs, on the other hand, have moved to what are known as the caring professions, as the chart below shows. The light blue bars represent muscle-powered jobs such as cleaners, domestics, miners, and laborers of all sorts; the dark blue, caring professions such as nurses, teachers, and social workers. As you can see, these have flipped.

Screen Shot 2017-11-28 at 13.53.19

The Deloitte study also points out that as wealth has increased over the years, so have jobs in the professional services sector. According to the census records analyzed, in England and Wales accountants have increased from 9,832 in 1871 to 215,678 in 2015. That’s a 2,094% increase.

And because people have more money in general, they eat out more often – leading to a fourfold increase in pub staff. They can also afford to care more about how they look. This has led to an increase in the ratio of hairdressers/barbers to citizens of 1:1,793 in 1871 to 1:287 today. Similar trends can be seen in other industries such as leisure, entertainment, and sports.

Where are we headed now?

Will broader application of AI and other technologies continue the trend of generating new jobs in unexpected ways? Most assuredly. Already we’re seeing an increased need for jobs such as AI ethicists – another role that didn’t exist 5-10 years ago.

The fact of the matter is that technology in general, and AI in particular will contribute enormously to a hugely changing labour landscape. I mentioned at the start of this post that my role in SAP is IoT Evangelist – this is a role I fully expect to no longer exist in 5 years time, because by then everything will be connected, and so the term Internet of Things will be redundant, in the same way terms like “Internet connected phone”, or “interactive website” are redundant today.

The rise of new technologies will create new jobs, not just for people working directly with the new technologies, but also there will be an increasing requirement for training, re-training, and educational content development to bring people up-to-speed.

Will there be enough of those jobs to go around – and will they pay enough to support a middle-class existence for those who hold them? That’s another question – but it’s one that’s stimulating a lot of creative, innovative ideas of its own as people think seriously about where technology is taking us.

 

Photo credit Jessie Hodge

Here come the Jetsons: Flying cars and the Internet of Things (IoT)

Part 3 of 3 on the Future of Transportation and the Internet of Things

If you ever watched the cartoon series The Jetsons – or almost any other show set in the space age – you’ll notice that people often get around in personal spacecraft that they themselves drive. Well, the space age is almost here – at least in the form of flying cars. But we won’t be driving them. Instead, like cars they will be controlled autonomously.

In my last blog, I talked about autonomous vehicles and how much safer they are than self-driven vehicles. To ensure safety in the air, flying cars depend on the same network-connected IoT technology pioneered first in autonomous vehicles on the road.

Is the space age really here?  

Let’s first take a quick look at some of the leading organisations out there doing serious work with flying cars.

  • Lilium: A German start-up, Lilium tested a full-sized prototype of its flying car in April 2017. The Lilium prototype is entirely electric. It can also take off and land vertically like a helicopter – but then change to forward flight for speeds of up to 300km/h, which is much faster than a helicopter. And it’s quieter than a motorcycle. Lilium has raised $100m in two rounds of funding from Tencent, Ev William’s Obvious Ventures, Niklas Zennstrom’s Atomico amongst others.
  • EHang: A Chinese company with deep experience building drones, EHang is perhaps the furthest along. The company produces the EHang 184 – a one-passenger flying car that has already undergone 100 successful manned test flights. Reportedly, the city of Dubai is this year launching a pilot program for an autonomous aerial taxi (AAT) service using the EHang 184.
  • Airbus: The aircraft giant, Airbus, has developed CityAirbus, an electric vehicle capable of vertical take-off and landing for up to four passengers. Airbus Vahana aims in the same direction but for is for individual travelers. And let’s not forget the hybrid Airbus Pop.Up concept, this modular air and ground system involves a passenger capsule that can be connected to a propeller system on top for flying or to a wheeled conveyance system for driving on the roads.
  • And Uber – who recently signed an agreement teaming up with NASA around NASA’s Uncrewed Traffic Management (UTM) project developing air traffic control systems for uncrewed aerial systems (flying cars/drones).
  • Even Boeing is making investments in this space.

This is starting to look real.

No network, no flying cars

What all of these ventures have in common is connectedness. Using IoT technology, they’re all controlled remotely – with the vehicle in constant connection to home base along the lines of what is now a reality for autonomous road vehicles like those made by Tesla.

Of course, the networked nature of vehicles (flying or not) has relevance beyond safety. No surprise, then, that Uber is moving forward aggressively with plans to test an on-demand flying cars network by 2020 in the cities of LA, Dubai, and Dallas, and 2023 in Sydney. Here the network provides convenience – coordinating a ride-sharing service in the sky that allows passengers to hook up with flying cars on the fly.

Drones for passengers

Essentially, what we’re moving toward is a future of passenger drones. One obstacle to this reality is the need for keeping batteries charged. Because of battery life issues, for example, the EHang 184 can only travel 23 minutes. The Lilium vehicle, it is claimed, can travel up to an hour – enough to make it from London to Paris. This, and advances in battery power storage capacity will iron out most issues around range.

When we solve this problem – and get over some regulatory hurdles – flying cars will become a lived reality for people in cities everywhere. The benefits will be tremendous, too. Count among these benefits such as less pollution (both air and noise pollution) and less traffic congestion (with flying cars taking another route entirely). And when it comes to emergencies, first responders can be deployed faster and more efficiently than ever before – helping to save lives. And let’s face it, flying cars would just be fun.

Next time I get to Dubai I’ll have to try one out.

Photo credit Airbus

Connected Cars, Autonomous Vehicles, and the Internet of Things (IoT)

Part 2 of 3 on the Future of Transportation and the Internet of Things

In my last blog, I talked about the simplicity of the electric engine compared to the internal combustion engine – and how this changes everything. From climate to the structure of the auto industry to the way we store, manage, and distribute energy – electric cars are having tremendous impact.

But what I left out of that discussion was the Internet of Things.

Predictive

The fact is, most electric cars are connected cars – connected through the Internet of Things. This means that sensors in the car constantly communicate with mission control (the manufacturer), sending data on the status of components in real time.

By analysing this data, especially in context of historical data, mission control can predict component failure before it happens. For electric vehicles – with engines that already need far less repair than traditional internal combustion engines – this only increases reliability further.

But what’s more, IoT-connected cars also increase convenience. For example, after realising component failure is imminent, your car could also trigger a work order at the dealership to resolve the issue – while ensuring the needed replacement part is in stock when you roll in. And if the car is autonomous, it could drive itself to be repaired while you are at work, and return ready to drive you home once the repair is completed. Speaking of autonomous…. 

Autonomous and safe

Connectedness is also what makes autonomous vehicles possible. And while some people may distrust driverless cars; the data shows that they’re safer than the self-driven sort – at least according to a report of the U.S. National Highway Traffic Safety Administration (NHTSA).

Back in May 2016, a Tesla Model S sedan in Autopilot collided with a semi-truck in Florida, killing the driver (or passenger in this case?) – 40-year-old Joshua Brown. The car, apparently, crashed into the truck, passed under the trailer, and kept driving for some distance – only coming to a stop after crashing through two fences and into a pole.

As a result of this incident, the NHTSA conducted an investigation resulting in a report that largely exonerated Tesla. In fact, the report says that after the introduction of Autosteer – a component of the Autopilot system – Tesla’s crash rate dropped by 40%.

Self-learning

The accident in question happened when the semi-truck took a left-hand turn into oncoming traffic. The reason the Tesla did not detect such a large object in its path is because it could not distinguish the white color of the trailer from the bright white Florida sky in background.

Reportedly, Tesla has since analyzed the crash data from this accident, identified the problem, and made fixes to the operating system on which its fleet operates. Perhaps it’s premature to declare the problem solved – but the idea at play here is an interesting one indeed when considering the potential for connected cars and the IoT.

What this scenario shows is a learning platform in action. Because all of its cars are connected on a single platform, Tesla has access to a tremendous amount of driver data that it can analyze to continuously improve product safety. I don’t know exactly how the analysis proceeded in this particular case, but one can certainly envision the use of machine learning technology to continuously analyze patterns and introduce safety improvements on the fly – making the self-learning driving platform a reality.

Disruptive

A future in which autonomous vehicles are not only viable but safer than self-driven cars will result in disruptions beyond those I’ve indicated for electric engines.

Take the insurance industry, for example. With fewer accidents comes lower risk – leading to lower insurance premiums. And in a future where most cars on the road are autonomous – connected and controlled via IoT – the insurable entity itself will likely shift from the driver (who is now a passenger) to the operator of the network (presumably the manufacturer). Certainly, if you decide you wish to drive your car yourself, your insurance will be significantly more expensive than the insurance for an autonomous vehicle.

Of course, if autonomous cars can get where they’re going without a driver, why even bother owning a car? Why not just call up the ride when you need it – Uber style?

One result would be optimal asset utilization – where cars that are far less likely to breakdown can be used on an almost 24×7 basis by spreading usage across individuals. This would mean we’d need far less cars on the road – which would alleviate congestion. It would also hit the auto industry with dramatically lower sales volume.

And with fewer cars on the road – cars that are in use almost all the time – we’d have less use for parking. This would have tremendous impact on the global parking industry. An industry which generates approximately $20 billion annually.

Beyond industry disruption, less need for parking would open up tremendous urban space in the form of unused lots and garages. Maybe this would mean more populous cities with room to build for more people to live more comfortably without traffic congestion or pollution. Or how about using some of the space for indoor vertical farming using hydroponics technology and LED lights to grow more food and feed more people? Of course, this is already happening. But that’s a blog for another time.

 

Photo credit Nicole Galpern