2017 and 2018 are characterized by an explosion of urbanization with as IoT enables smart cities to optimize services to their residents. According to the recent World Cities report of the United Nations over 3.7 billion people are now living in urban areas, while this number is expected to double by 2050. Urbanization trends are accompanied by a rise of the aging population and the emergence of entirely new lifestyle work patterns (e.g., telecommuting).
All these changes are putting extreme pressures on modern cities, which have to cope with the depletion of natural resources (e.g., water, energy) and the support of new lifestyles in a way that ensures sustainable development. In this context, the concept that IoT enables smart cities is a reality, such as vendors such as SIGFOX covers more than 10 million objects registered on its network which currently spans 26 countries.
IoT networks are able to leverage both advanced technologies and a city’s human capital in order to optimize urban operations, improve environment performance, create new sustainable business opportunities and improve the citizens’ quality of life. Smart cities are based on advanced ICT infrastructures and technologies such as high-speed broadband connectivity, multi-purpose low power sensors and actuators, as well as cloud computing infrastructures that facilitate scalable collection and processing of large volumes of data about the urban context. Most of these technologies are underpinning the Internet-of-Things (IoT) paradigm, which explains the close affiliation between smart cities and IoT.
Overall, as IoT enables smart cities becomes saturated in terms of sensors and mobile devices (e.g., smartphones used by citizens), they provide umbrella environments for the development of many different smart city applications. The latter can be classified according to two major (yet orthogonal) criteria:
Their application domain, which leads to a classification in categories such as smart energy, smart transport, smart healthcare, smart industry, smart water management and more. A larger number of different devices and applications are developed and deployed in each one of the above application domains.
Their geographical scale, which leads to a classification in applications about smart homes, smart neighborhoods, smart cities or even smart regions comprising multiple cities.
Developing a Strategy IoT Enables Smart Cities
Given the multitude of IoT technologies and applications in smart cities, policy makers need to prioritize the development of their IoT projects and infrastructures in-line with their urban development strategy. The latter strategy defines the city’s goals and substantiates them based on tangible KPIs (Key Performance Indicators), such as improvements in CO2 emissions and environment performance, reductions in urban traffic and the average time of urban trips in the city, increase in GDP (Goss Domestic Product) of the city, quality of life indexes and more.
With this strategy at hand, technology advisors and city CIOs (Chief Information Officers) can work towards preparing a comprehensive strategy for the tasks that IoT enables smart cities requires in terms of the infrastructures to be developed and the IoT projects to be implemented. The selection of projects should consider the application domains that need to be targeted in order to meet the specified performance indicators. The development of a city’s IoT strategy is usually a complex task, as it should consider multiple factors and trade-offs, including financial, business and technology factors at the same time. For instance, as most cities operate on quite constrained budgets it’s always important to define projects with realistic budgets, which could be financed either by the city’s budget or as part of public-private partnerships. The latter is a very popular paradigm for financing the usually costly IoT infrastructure development projects.
As a prominent example, the LinkNYC project, which provides New Yorkers with super-fast WiFi for free, is a result of a public private partnership between the city and the CityBridge consortium where Intersection, Qualcomm, CIVIQ Smartscapes and other companies participate.
In terms of technological factors, IoT enables smart cities a strategy that should specify key technological choices, including:
The networking technologies to be deployed (e.g., WiFi and LTE (Long Term Evolution) connectivity).
The types of sensors (e.g., smart meters, traffic cameras) needed. The software and middleware infrastructures to be used (e.g., databases, cloud and virtualization middleware).
Open datasets to be exploited, and the timeline for the development and deployment of these infrastructures, including relevant procurement issues.
Many benefits for IoT enabling smart cities using AiDespite the variety of technology choices, one must consider IoT enabling smart cities options for their financing and gradual deployment. Cities tend to follow a staged approach based on the following four phases:
An Infrastructure development phase, which aims at establishing the various digital infrastructures that will empower the smart city applications, including broadband networks, sensors, actuators, clouds and open data infrastructures.
What lies ahead for IoT enables Smart Cities Urban Development?
A vertical applications development phase, where applications in vertical areas (such as energy and urban mobility) are developed. An applications integration and interoperability phases, where different vertical applications are integrated in order to monitor or achieve city wide KPIs such as sustainability KPIs based on a combination of transport, energy, mobility and water management projects. An open innovation and citizens’ engagement phase, where citizens and innovators engage with existing infrastructures and applications in order to provide additional social and innovation capital, as a means of expanding and optimizing the operation of integrated applications.
In this landscape, we are witnessing a proliferation of smart city projects in many cities of the developed world. Nevertheless, there are also on-going efforts to improve existing smart city projects and broaden the scope and capabilities of new projects. These efforts concern both technological and non-technological developments and include:
Stakeholders’ engagement and the human factor: Smart city projects are increasingly seen as initiatives that have to engage all stakeholders in the city, rather than being projects that are enforced from the administration in a top-down manner. Therefore, new approaches for engaging citizens across all the phases of a service’s lifecycle (such as co-creation approaches) are emerging. We will see increasingly see co-creation based services in the near future.
IoT Technology evolution: Smart city needs are driving the evolution of IoT technologies in several areas. As a prominent example, the networking community is actively working towards the fifth generation of mobile communications (5G), which is designed in order to accommodate smart city features and needs, such as high speed services in densely populated (i.e. crowded) and sensor saturated environments. 5G is currently piloted by major telcos worldwide and is expected to become commercially available after 2020 in order to empower the next generation of smart city applications.
Recruiting the Right Executives: Cities need to make sure their CTOs and CIOs are well-versed in not just wireless networks, but the evolving IoT standards as well as mobile and cyber security. One such IoT retained executive search firm you can rely upon is NextGen Global Executive Search, whose expertise in IoT, wireless, and connected devices has successfully placed dozens of “A Players” for internet of Things and smart cities for developing Connected Devices & Data, Industrial IIoT and Ai assisted robotics, plus IoT and Mobile Security Applications.
Interoperability solutions: Despite the benefits of interoperability across different smart city infrastructures and applications (e.g., in terms of a holistic approach to meet sustainability targets) most smart city applications are still fragmented independent application islands (“silos”). Therefore, technology efforts and standards are recently focused on ensure technical, semantic and organizational interoperability across different smart city applications. This will empower more interoperability in the near future.
The expanded use of Big Data in the urban environment: Nowadays, only a small fragment of the data that is produced by internet-connected devices is exploited in the scope of IoT applications. McKinsey & Co. estimates this fragment to be around 1%. The advent of Big Data technologies is expected to enable a new wave of data-driven applications in smart cities, including artificial intelligence (AI) applications, which will emphasize predictive functionalities beyond simple reporting and analytics functionalities that are currently available. The self-driving car falls in the scope of such data intensive applications, since it will leverage large amounts of data from other interconnect connected cars and the smart city infrastructure in order to anticipate the driving context.
Overall, the vision that IoT enables smart cities is gradually realized, but much more is yet to come. In this evolving landscape city authorities, technologies providers and other stakeholders are expected to collaborate to develop and execute effective IoT strategies for urban development.
Industrial Robotics Cyber Security Challenges in IIoT
The line is blurring between information technology (IT) and operational technology (OT). As more industrial robotics equipment is connected to the industrial internet of things (IIoT), the vulnerabilities increase. Among the many devices being added to networks are robotic machines. That’s raising red flags for some experts. And it has many people worried. What are the risks associated with connecting an army of robots? It’s the stuff of science fiction.
Industrial Robotics Cyber Security Concerns on the Rise
The World Robotics Report 2016 gives us some insight into the scope of global automation growth: “The number of industrial robotics deployed worldwide will increase to around 2.6 million units by 2019.” It says that the strongest growth figures are for Central and Eastern Europe. The report cites China as the market for growth, and says that North America is on the path to success. “The USA is currently the fourth largest single market for industrial robots in the world,” according to the report.
TechCrunch contributor Matthew Rendall says “Industrial robotics will replace manufacturing jobs — and that’s a good thing”. He writes that the “productivity growth” behind 85% of job losses is all about machines replacing humans. Luddite and famous poet Lord Byron would not have been pleased. But Rendall is not bothered. He says that “more is getting done” by industrial robotics that are safer and more reliable than human beings. And he believes that this robotics revolution will be beneficial to workers and society in the long run.
All this rush to automation might be the best thing since jelly doughnuts. But one question could make all the difference between abysmal failure and glorious success: Can we keep them secure?
Challenge in Industrial Robotics Cyber Security
We probably don’t need to worry about robots taking over the world any time soon. (Let’s hope, anyway.) What concerns security experts is that our computer-based friends can be hacked. Wired Magazine reports how one group of researchers was able to sabotage an industrial robotics arm without even touching the code. That’s especially worrying when you think that most industrial robotics have a single arm and nothing else. These devices are made to make precise movements. Hackers can change all that.
German designer Clemens Weisshaar addressed the issue in a form at Vienna Design Week in 2014. “Taking robots online is as dangerous as anything you can put on the web,” he said. In a video from the forum, Weisshaar talked about how even his company’s robot demonstration in London had been hacked within 24 hours. They even tried to drive his robots into the ground. “If everything is on the internet,” he said, “then everything is vulnerable to attack.”
Industrial robotics cyber security challenges are only one part of what many are calling Industry 4.0. It’s a trending concept — especially in Germany — and it’s another way of referring to the Fourth Industrial Revolution. To understand what this is about, we should first reach back in the dim recesses of our minds to what we learned in history class in school.
The Industrial Revolution, as it was originally called, took place in the 18th and 19th centuries. It started in Great Britain and involved the harnessing of steam and tremendous advances in production methods – the 1st. Next came the 2nd roughly from 1870 until World War I in the USA. This involved the use of electricity to develop mass production processes. Th 3rd brought us into the digital age. Part four is upon us now.
A video from Deloitte University Press introduces us to the Fourth Industrial Revolution — Industry 4.0. It gives a good summary of the four “revolutions”, and it talks about some of the new technologies that now define our age:
Internet of Things (IoT)
Mobile and Edge Computing
Big Data Processing
“These technologies,” says the narrator, “will enable the construction of new solutions to some of the oldest and toughest challenges manufacturers face in growing and operating their business.” They also make up the environment in which hackers flourish.
Industrial Robots Cyber Security Challenges for IoT Data and Devices
In this space we have already discussed the security vulnerabilities of IoT devices. We told you how white hat hackers proved that they could commandeer a Jeep Cherokee remotely by rewriting the firmware on an embedded chip. Imagine what hackers with more sinister motives might be planning for the millions of robotic devices taking over the manufacturing shop floor — supposing they are all connected.
Some researchers tackled the issue in a study called “Hacking Robots Before Skynet”. (You will remember from your science fiction watching that Skynet is the global network that linked robots and other computerized devices in the Terminator movie franchise.) The authors had a lot to say about the current state of cybersecurity in the industrial robotics industry. We can borrow directly from the paper’s table of contents to list what they call “Cybersecurity Problems in Today’s Robots”:
Weak default configuration
Vulnerable Open Source Industrial Robotics cyber security Frameworks and Libraries
Each of these topics could probably merit a full article on its own. The researchers explained further: “We’re already experiencing some of the consequences of substantial cybersecurity problems with Internet of Things (IoT) devices that are impacting the Internet, companies and commerce, and individual consumers alike, Cybersecurity problems for industrial robotics could have a much greater impact.”
What might that impact be? Well, to start with, robots have moving parts. They tell how a robot security guard knocked over a child at a shopping mall. A robot cannon killed nine soldiers and injured 14 in 2007. And robotic surgery has been linked to 144 deaths. It’s not Skynet yet, but connecting robots has its risks.
How we communicate with machines and how they communicate with each other are matters that require significant attention. Arlen Nipper of Cirrus Link Solutions talks about MQTT, which is a protocol for machine-to-machine (M2M) messaging. Manufacturing designers and operators send instructions to one-armed industrial robotics, who work in a variety of industries from automotive to aerospace to agriculture to packing and logistics. All this talking back-and-forth with industrial robotics cyber security has to be regulated. NIST’s Guide to Industrial Control Systems (ICS) Security has a few references to robots. But maybe not enough.
IoT Recruiting – does your search firm deliver results?
IoT recruiting where a lot of recruiting firms out there – contingency based, RPOs, and retained search firms claim they can deliver results. You have the need to find the right candidate for a key senior executive or functional leadership role. Or you need a key sales, business development, or engineering professional?
The IoT recruiting team of NextGen Global Executive Search has 30+ years experience working for clients large and small in mobile networks, embedded wireless, IoT data and devices, industrial IoT applications and platforms, blockchains, agriculture, IoT consumer product goods wearables in sports, business, and fitness, as well as artificial intelligence and robotics.
IOT Recruiting that Delivers Results
NextGen has successfully recruited CEOs, CTOs, VPs and Directors in embedded wireless, ecosystem partnership development, firmware development, and network design for IoT operators, semiconductor and device manufacturers, and wireless sensors. Reach out to NextGen for your IoT recruiting needs. NextGen has 30+ years experience recruiting for mobile network operators, cellular infrastructure vendors, and wireless semiconductor device manufacturers. As 4G gets ready to evolve into 5G, both industrial IoT continues to grow and consumers will realize the benefits of Internet of Things connected to everything from smart homes with smart appliances to security to energy savings.
Industrial IoT automation dictates that all predictive maintenance systems hinge on the processing of data from many IoT devices, which renders predictive maintenance one of the most common IIoT applications.
Moreover, as predictive maintenance leads to improved OEE, reduced labor for performing the maintenance and better planning of related supply chain operations, it is increasingly considered one of the killer applications for IIoT.
With IIoT reconfigurations take place at the cyber world based on digital technologies rather than at the physical world where processes are much more tedious and time consuming. IIoT automation systems provide a seamless link between the cyber and physical worlds, which ensures that changes in the IT configurations are properly reflected on the field.
Industrial IoT Predictive Maintenance is a Killer Application
Industrial IoT predictive maintenance is expected to generate the large scope of B2B transactions that require data analysis. Indeed, IIoT is on such a growth pattern many of the billions of connected things in the coming years will be industrial assets, which will be deployed in settings like factories, agricultural, oil refineries and energy plants.
According to McKinsey the Industrial Internet has the potential to deliver up to $11.1 trillion on an annual basis by 2025 and 70% of this is likely to concern industrial and business-to-business solutions i.e. the Industrial IoT is expected to be worth more than twice the value of the consumer internet.
The Industrial IoT is at the heart of the fourth industrial revolution (Industry 4.0), which is driven by the interconnection of all industrial assets and the ability to collect and analyze data from them. In the scope of the Industrial IoT, assets are cyber-physical systems, which enable the control of physical devices through their cyber representations and the processing of digital data about them.
The applications of cyber-physical systems span a very broad range, including production control, process optimization, asset management, integration of new technologies (such as 3D printing & additive manufacturing), as well as various industrial automation tasks. Nevertheless, the most prominent application is the ability to continually monitor, predict and anticipate the status of assets, with emphasis on industrial IoT predictive maintenance using predictions about when a piece of equipment should be maintained or repaired.
Industrial IoT Predictive Maintenance is Key to Industry 4.0
Maintenance and Repair Operations (MROs) are at the heart of industrial operations, as they involve repairing mechanical, electrical, plumbing, or other devices as a means of ensuring the continuity of operations. Nowadays, the majority of MRO operations are carried out on the basis of a preventive maintenance paradigm, which aims at replacing components, parts or other pieces of equipment, prior to their damage that could catastrophic consequences such as low production quality and cease of operations for a considerable amount of time. However, in most cases preventive maintenance fails to lead to the best usage of equipment (i.e. optimal Operating Equipment Efficiency (OEE)), as it maintenance is typically scheduled earlier than actually required.
In industrial IoT predictive maintenance (PdM) alleviates the limitations of preventive approaches. PdM is based on predictions about the future state of assets, with particular emphasis on anticipating the time when an asset will fail in order to appropriately schedule its maintenance.
PdM is empowered by models that estimate when the cost of maintenance becomes (statistically) lower that the cost that is associated with the risk of equipment failure.
Based on an optimal scheduling of maintenance, PdM leads to improved OEE, enhanced employee productivity, increased production quality, reduced equipment downtime, as well as a safer environment where failures are anticipated and repairs proactively planned. McKinsey & Co. estimates that the economic savings of predictive maintenance could total from $240 to $630 billion in 2025.
Nevertheless, there are still many industries that dispose with preventive maintenance, since they have no easy way to integrate and analyze data sets from thousands of heterogeneous sensors that are typically available in their plant floors. As a result only a fraction (i.e. 1% according to McKinsey & Co) of the available data is used, which is a serious setback to unlocking the potential of predictive maintenance applications, such as maintenance as a service, on-line calculation of OEE risk, maintenance driven production schedules and more.
The advent of Industrial IoT predictive maintenance is gradually unlocking the potential of PdM technologies facilitate the collection and integration of data from thousands of different sensors, while at the same time providing the means for unifying the semantics of the diverse data sets. Furthermore, IoT analytics technologies (notably predictive analytics) facilitate the processing of IoT data streams with very high ingestion rates based on machine learning and statistical processing techniques that can predict the future condition of components and equipment.
In several cases, IoT data are processed by Artificial Intelligence based techniques such as deep learning, in order to identify hidden patterns about the degradation of assets. Deep learning techniques are capable of leveraging (multimedia) data from multiple maintenance modalities such as vibration sensing, oil analysis, thermal imaging, acoustic sensors and more. Moreover, advanced deployments of industrial IoT predictive maintenance are not limited to deriving predictions about the future state of assets. Rather, they are able to close the loop down to the plant floor, through for example changing configurations in production schedules, altering the operational rates of machines or even driving automation functions.
Rise of Industrial IoT Predictive Maintenance Products and Services
PdM is looming as one of the killer applications for the Industrial IoT, which is evident not only on its potential savings but also on the rise of relevant IoT-based products and services. Most vendors have been recently releasing IoT-based solutions for PdM. In addition to empowering data collection and analytics, vendors are striving to enhance their products with added-value functionalities that help them stand out in the market. For example:
IBM predictive maintenance solution is able to perform root cause analysis in a holistic way, including predictions about where, when and why asset failures occur.
Software AG’s solution for industrial IoT predictive maintenance integrates with ERP and human resources systems to automatically plan the optimal allocation of tasks to technicians.
SAP integrates predictive maintenance information with business information (e.g., CRM and ERP systems) and enterprise asset management (EAM) systems. To this end, it benefits from its strong presence and installed base in the ERP market.
Microsoft offers PdM solutions over its Azure IoT suite in a way that offers preconfigured solutions (templates) for monitoring assets and analyzing their usage in real-time.
Recently, the DataRPM platform has been also established by a consortium of different vendors and manufacturers. DataPRM claims ability to deliver Cognitive Predictive Maintenance (CPdM) for Industrial IoT, based on the use of Artificial Intelligence for automating predictions of asset failures and closing the loop to ERP, CRM, and other business information systems.
Other major players in industrial engineering and automation, such as SIEMENS and BOSCH are offering their own platforms, while all major IT consulting enterprises have relevant services in their portfolio. Nevertheless, it is indicative of the market momentum of PdM and its positioning as one of the most prominent applications in the growing Industrial IoT predictive maintenance market.
Need an experienced recruiter for a key role in Industrial Internet of Things?
Whether you have a need for a key software engineer, product management leader, ecosystem partnership developer, or sales executive, NextGen executive search has served clients who build IioT for agriculture, industrial automation, LED lighting, and much more. For more information about our IIoT recruitment experience or to schedule a time to speak with us by booking a time on our live calendar, just click on the image below.