Article 1

IoT and Blockchain Convergence: Benefits and Challenges

Ahmed Banafa

The Internet of Things (IoT) as a concept is fascinating and exciting, but one of the major challenging aspects of IoT is having a secure ecosystem encompassing all building blocks of IoT-architecture. Understanding the different building blocks of IoT, identifying the areas of vulnerability in each block and exploring technologies needed to counter each of the weaknesses are essential in dealing with the security issue of IoT.

 


Article 2

IoT: a Mobile Network Operator Perspective

Giovanni Perrone and Massimo Vecchio

The world that is shaping in front of us brings visions of hyper-connectivity or, to put it another way, of an incredibly large number of connections between the different elements of the world that we see. The skeleton supporting IoT is, at the end of the day, exactly that: a dense network of connections between a multitude of points that makes possible a level of vision, perception, awareness and, last but not least, control on the world that surrounds us that was simply not possible even to think about before.

 


Article 3

IoT for Electric Power: Smart Grid was the Beginning

Jeffrey S. Katz

For many electric power utilities, the Smart Grid was their first Internet of Things project. Just as some early smart grid projects were started before the term became popular, and were originally known as the intelligent utility network, or advanced distribution automation, so too was smart grid an early version of internet of things for utilities.

 


Article 4

Internet of Things for Buildings that Make Life Safe and Secure

Takumi Ito, Mikio Hasegawa and Takashi Nakajima

Recently, there have been numerous discussions about the Internet of Things (IoT) delivering benefits in a variety of areas such as the provision of more comfortable human lifestyles and improvements in business efficiency. Most of the discussed topics and interests are focused on the development of specific underlying technologies.

 

 

This Month's Contributors

Ahmed Banafa has extensive experience in research, operations and management, with a focus on the IoT area.
Read More >>

Giovanni Perrone has been working in the mobile and Telco domain for more than 12 years, coming from another 10 years spent in the design of digital solutions for renewable energy and industrial automation applications.
Read More >>

Massimo Vecchio received the Laurea degree in Computer Engineering (Magna cum Laude) from the University of Pisa and the Ph.D. degree in Computer Science and Engineering (with Doctor Europaeus mention) from IMT Lucca Institute for Advanced Studies in 2005 and 2009, respectively.
Read More >>

Jeffrey S. Katz is the Chief Technology Officer of the Energy and Utilities industry at IBM.
Read More >>

Takumi Ito is an associate professor at Tokyo University of Science, Japan.
Read More >>

Mikio Hasegawa received his B.Eng., M.Eng., and Dr.Eng. degrees from Tokyo University of Science, Tokyo, Japan, in 1995, 1997, and 2000, respectively.
Read More >>

Takashi Nakajima received his B.Sci., M. Sci., and Ph.D. degrees from Tokyo University of Science, Tokyo, Japan, in 2003, 2005, and 2008, respectively.
Read More >>

 

Contributions Welcomed
Click Here for Author's Guidelines >>

 

Would you like more information? Have any questions? Please contact:

Raffaele Giaffreda, Editor-in-Chief
raffaele.giaffreda@create-net.org

Massimo Vecchio, Managing Editor
massimo.vecchio@uniecampus.it

 

About the IoT eNewsletter

The IEEE Internet of Things (IoT) eNewsletter is a bi-monthly online publication that features practical and timely technical information and forward-looking commentary on IoT developments and deployments around the world. Designed to bring clarity to global IoT-related activities and developments and foster greater understanding and collaboration between diverse stakeholders, the IEEE IoT eNewsletter provides a broad view by bringing together diverse experts, thought leaders, and decision-makers to exchange information and discuss IoT-related issues.

IoT for Electric Power: Smart Grid was the Beginning

Jeffrey S. Katz
January 10, 2017

 

For many electric power utilities, the Smart Grid was their first Internet of Things project. Just as some early smart grid projects were started before the term became popular, and were originally known as the intelligent utility network, or advanced distribution automation, so too was smart grid an early version of internet of things for utilities.

This is not surprising, considering utilities have more "things" distributed over a wider area, as a vast, complex, interconnected machine, than almost any other industry. Smart Grid embodies a subset of IoT principles, and some of the more advanced projects made use of today's IoT concepts, before groups such as the Industrial Internet Consortium popularized them. Applying IoT to the changing world of distributed and renewable energy generation is but one of the IoT business cases. Utilities often start with an IoT strategy in the context of their already familiar smart grid projects. As they begin to encompass more of the aspects of IoT, such as analytics platforms, IoT cloud, sensor fusion, and data governance, they may use these principles in continuation of smart grid, either in different jurisdictions, or for advanced functions such as distributed intelligence.

The most plentiful "thing" in electric power IoT is the smart meter. There were 400 million such devices estimated to have been installed worldwide by 2014, with an expected growth to 925 million by 2020 [1]. Similarly, equipment revenue for smart grid sensors is expected to expand by an order of magnitude in a similar period. However, smart lighting, estimated to be 46 million units in 2015, is projected to grow to 2.54 billion units by 2020, thus outpacing the smart meter. Just think of the number of municipal street lighting systems that are becoming not only smarter, but becoming Wi-Fi hot spots and other citizen service points. The total number of connected devices managed by utilities may be 1.53 billion in 2020, which is more than triple that in 2013.

Lessons learned

So what to do? A few lessons learned already from such projects can be summarized as:

  • Everything goes well until the project starts to look for and use the data. Generations of data acquisition systems, SCADA historians, "standard" data repositories, engineering data warehouses, data lakes, and more often mean there is no consistent format for the years of data that form an experience base.
  • Systems co-exist, but automation requires integration. An IoT approach is part of a business strategy for interoperability. Classic Enterprise Service Buses have been a good approach, but may not provide the desired data ubiquity.
  • Governance of data can stall the project. Even if the problem suggested in the first bullet is not a speed bump in a utility, continuing to properly curate new IoT data often does not get the attention it deserves, leading to unexpected project costs down the road.

Once the data is under control, there are often business cases based on optimization, such as root cause determination and fault location, or maximizing use of renewable energy. Experience tells us that optimization is in the eye of the beholder (read purchaser). The electric grid is interconnected and has many coupled effects. An IoT project should not be a surprise to the rest of the company, nor should individual optimization projects be undertaken without thinking of some overall supervisory system that keeps a watchful eye on the local optimizations, so the whole system benefits. Often this is the place where cognitive computing merges with IoT.

Another potential IoT danger is that while the traditional utility is working on an IoT strategy, new competitors are forming innovative business models using IoT from the beginning. Think of Uber, or Nest.

IoT connectivity needs security for a critical infrastructure industry such as electric power. Therefore, security is a starting point, not a non-functional requirement tossed back to IT. Security in IoT also includes privacy and trust, not just concern about hackers.

One should also think of Internet of Things by parsing the phrase. "Internet" is not necessarily the public Internet. There is the more select Internet2 for example. There are regional systems proposed for utilities such as the Eastern Interconnect Data Sharing Network. "Things" include people; causing some to use the phrase "Internet of Everything." Technicians, trucks, poles, consumers, wind turbines are 'things' in the broader view of IoT. Measurements as well as simulation results are all useful data.

Thinking points

Some points for IoT thinking that can be derived from these implications:

  • If you are still talking about IT/OT convergence in your company, then you may not be ready for IoT. Alternatively, to look at it another way, IoT is already converged.
  • Develop end-to-end trusted networks.
  • Insist on encrypted storage at the cloud. Test your vendor.
  • Look for cloud center interconnections that are not over the public Internet.
  • Take notice of what is new in IT:
    • Agile development
    • Concerns about the customer and their smartphone being smarter than enterprise IT
    • Vendor equipment having more intelligence than can be used in a utility
  • Think of proofs of concept as in-house engineering staff education. See for example the IoT recipes at IBM's Developer Works [2] (and the IoT Foundation Quick Start [3]).

Brief mention has been made of cognitive computing [4] and IoT in a supervisory role among optimization software. Software at the edge is not new, however, significant intelligence at the edge is. Classic programming embodies the programmer's view at the time of the coding, rigidly defined. However, the 'edge' is not monitored as well as data center IT. Often it is helpful to think of the centralized software component as the adult, and the edge computing as the child. The total system can learn what is normal, from both the system operation and security point of view. It informs the child computers of global conditions. It helps detect emergent behavior between distributed intelligent systems.

A short Energy and Utilities IoT 'to do' list:

  • Focus on security [5]
  • Implement Cloud Computing and Big Data and Analytics pilot projects
  • Re-invent the end-user experience (customer or technician)
  • Embrace innovation
  • Plan holistically
  • Pilot, learn, adapt

A closing remark about IoT analytics. Thinking that every analytic based on IoT data has already been done can lead to lack of innovation. Listen one weekend to the most popular show on National Public Radio, "Car Talk." This is a great demonstration of how symptoms, diagnoses, and correlations are not all obvious, even though the automobile has been around longer than the computer, and is a similar vintage to widespread electrification. Data discovery tools can provide unexpected ROI, as well as new insights and shorter paths to fault resolution and optimal operation.

 

References

[1]          http://destinhaus.com/energy-trends-2020-the-energy-internet-of-things/

[2]          https://developer.ibm.com/recipes/tutorials/category/internet-of-things-iot/

[3]          https://quickstart.internetofthings.ibmcloud.com/#

[4]          http://www.ibm.com/cognitive/

[5]          http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=WH&infotype=SA&htmlfid=RAW14382USEN&attachment=RAW14382USEN.PDF

 


 

Jeffrey S. KatzJeffrey S. Katz is the Chief Technology Officer of the Energy and Utilities industry at IBM. He is a Senior Member of the Institute of Electrical and Electronics Engineers. He is a member of the IBM Academy of Technology. He is a co-chair of the Industrial Internet Consortium's Energy group, and is a member of the Internet2 working group on the Internet of Things.

He was a co-chair of the IEEE 2030 Standard on Smart Grid Interoperability Guidelines IT Task Force. He is on the Advisory Board of the Advanced Energy Research and Technology Center. He was appointed to the IEEE Standards Association Standards Board for 2014. He is an Open Group Distinguished IT Specialist.

He can be reached at jskatz@us.ibm.com

 

IoT and Blockchain Convergence: Benefits and Challenges

Ahmed Banafa
January 10, 2017

 

The Internet of Things (IoT) as a concept is fascinating and exciting, but one of the major challenging aspects of IoT is having a secure ecosystem encompassing all building blocks of IoT-architecture. Understanding the different building blocks of IoT, identifying the areas of vulnerability in each block and exploring technologies needed to counter each of the weaknesses are essential in dealing with the security issue of IoT.

Figure 1

 IoT architecture can be represented by four building blocks:

  1. Things: These are defined as uniquely identifiable nodes, primarily sensors that communicate without human interaction using different connectivity methods.
  2. Gateways: These act as intermediaries between things and the cloud to provide the needed connectivity, security, and manageability.
  3. Network infrastructure: This is comprised of routers, aggregators, gateways, repeaters and other devices that control and secure data flow.
  4. Cloud infrastructure: Cloud infrastructure contains large pools of virtualized servers and storage that are networked together with computing and analytical capabilities.

Challenges to secure IoT deployments

Existing security technologies will play a role in mitigating IoT risks but they are not enough. The goal is to get data securely to the right place, at the right time, in the right format. It's easier said than done for many reasons, and here is a list of some of the challenges:

  • Many IoT Systems are poorly designed and implemented, using diverse protocols and technologies that create complex and sometimes conflicting configurations.
  • Limited guidance for life cycle maintenance and management of IoT devices
  • IoT privacy concerns are complex and not always readily evident.
  • There is a lack of standards for authentication and authorization of IoT edge devices.
  • Security standards, for platform configurations, involving virtualized IoT platforms supporting multi-tenancy is immature.
  • The uses for Internet of Things technology are expanding and changing—often in uncharted waters.

In addition to the above list, new security technologies will be required to protect IoT devices and platforms from both information attacks and physical tampering, to encrypt their communications, and to address new challenges such as impersonating "things" or denial-of-sleep attacks that drain batteries, to denial-of-service attacks (DoS). But IoT security will be complicated by the fact that many "things" use simple processors and operating systems that may not support sophisticated security approaches.

A prime example of the urgent need for such new security technologies is the recent massive distributed denial of service attack (DDoS) that crippled the servers of popular services like Twitter, Netflix, NYTimes, and PayPal across the U.S. on October 21st, 2016. It was the result of an immense assault that involved millions of internet addresses and malicious software. One source of the traffic for the attacks was devices infected by the Mirai malware. The attack comes amid heightened cybersecurity fears and a rising number of internet security breaches. All indications suggest that countless IoT devices that power everyday technology like closed-circuit cameras and smart-home devices were hijacked by the malware, and used against the servers.

The problem with the current centralized model

Current IoT ecosystems rely on centralized, brokered communication models, otherwise known as the server/client paradigm. All devices are identified, authenticated and connected through cloud servers that sport huge processing and storage capacities. Connections between devices have to exclusively go through the internet, even if they happen to be a few feet apart.

While this model has connected generic computing devices for decades and will continue to support small-scale IoT networks as we see them today, it will not be able to respond to the growing needs of the huge IoT ecosystems of tomorrow.

Existing IoT solutions are expensive because of the high infrastructure and maintenance cost associated with centralized clouds, large server farms, and networking equipment. The sheer amount of communications that will have to be handled when there are tens of billions of IoT devices will increase those costs substantially.

Even if the unprecedented economic and engineering challenges are overcome, cloud servers will remain a bottleneck and point of failure that can disrupt the entire network.

Decentralizing IoT networks

A decentralized approach to IoT networking would solve many of the issues above. Adopting a standardized peer-to-peer communication model to process the hundreds of billions of transactions between devices will significantly reduce the costs associated with installing and maintaining large centralized data centers and will distribute computation and storage needs across the billions of devices that form IoT networks. This will prevent failure in any single node in a network from bringing the entire network to a halting collapse.

However, establishing peer-to-peer communications will present its own set of challenges, chief among them the issue of security. And as we all know, IoT security is much more than just about protecting sensitive data. The proposed solution will have to maintain privacy and security in huge IoT networks and offer some form of validation and consensus for transactions to prevent spoofing and theft.

To perform the functions of traditional IoT solutions without a centralized control, any decentralized approach must support three foundational functions:

  • Peer-to-peer messaging;
  • Distributed file sharing;
  • Autonomous device coordination.

The blockchain approach

Blockchain, the "distributed ledger" technology, has emerged as an object of intense interest in the tech industry and beyond. Blockchain technology offers a way of recording transactions or any digital interaction in a way that is designed to be secure, transparent, highly resistant to outages, auditable, and efficient; as such, it carries the possibility of disrupting industries and enabling new business models. The technology is young and changing very rapidly; widespread commercialization is still a few years off. Nonetheless, to avoid disruptive surprises or missed opportunities, strategists, planners, and decision makers across industries and business functions should pay heed now and begin to investigate applications of the technology.

What is blockchain?

Blockchain is a database that maintains a continuously growing set of data records. It is distributed in nature, meaning that there is no master computer holding the entire chain. Rather, the participating nodes have a copy of the chain. It’s also ever-growing — data records are only added to the chain.

A blockchain consists of two types of elements:

  • Transactions are the actions created by the participants in the system.
  • Blocks record these transactions and make sure they are in the correct sequence and have not been tampered with.

What are some advantages of blockchain?

The big advantage of blockchain is that it's public. Everyone participating can see the blocks and the transactions stored in them. This doesn't mean everyone can see the actual content of your transaction, however; that's protected by your private key.

A blockchain is decentralized, so there is no single authority that can approve the transactions or set specific rules to have transactions accepted. That means there's a huge amount of trust involved since all the participants in the network have to reach a consensus to accept transactions.

Most importantly, it's secure. The database can only be extended and previous records cannot be changed (at least, there's a very high cost if someone wants to alter previous records).

How does it work?

When someone wants to add a transaction to the chain, all the participants in the network will validate it. They do this by applying an algorithm to the transaction to verify its validity. What exactly is understood by "valid" is defined by the blockchain system and can differ between systems. Then it is up to a majority of the participants to agree that the transaction is valid.

A set of approved transactions is then bundled in a block, which gets sent to all the nodes in the network. They, in turn, validate the new block. Each successive block contains a hash, which is a unique fingerprint, of the previous block.

The blockchain and IoT

Figure 2

Blockchain technology is the missing link to settle privacy and reliability concerns in the Internet of Things. Blockchain technology could perhaps be the silver bullet needed by the IoT industry. It can be used in tracking billions of connected devices, enabling the processing of transactions and coordination between devices; this allows for significant savings for IoT industry manufacturers. This decentralized approach would eliminate single points of failure, creating a more resilient ecosystem for devices to run on. The cryptographic algorithms used by blockchains would make consumer data more private.

The ledger is tamper-proof and cannot be manipulated by malicious actors because it doesn't exist in any single location, and man-in-the-middle attacks cannot be staged because there is no single thread of communication that can be intercepted. Blockchain makes trustless, peer-to-peer messaging possible and has already proven its worth in the world of financial services through cryptocurrencies such as bitcoin, providing guaranteed peer-to-peer payment services without the need for third-party brokers.

The decentralized, autonomous, and trustless capabilities of the blockchain make it an ideal component to become a foundational element of IoT solutions. It is no surprise that enterprise IoT technologies have quickly become one of the early adopters of blockchain technology.

In an IoT network, the blockchain can keep an immutable record of the history of smart devices. This feature enables the autonomous functioning of smart devices without the need for centralized authority. As a result, the blockchain opens the door to a series of IoT scenarios that were remarkably difficult, or even impossible to implement without it.

For example, by leveraging the blockchain, IoT solutions can enable secure, trustless messaging between devices in an IoT network. In this model, the blockchain will treat message exchanges between devices similar to financial transactions in a bitcoin network. To enable message exchanges, devices will leverage smart contracts which then model the agreement between the two parties.

One of the most exciting capabilities of the blockchain is the ability to maintain a duly decentralized, trusted ledger of all transactions occurring in a network. This capability is essential to enable the many compliances and regulatory requirements of industrial IoT (IIoT) applications without the need to rely on a centralized model.

What are the challenges?

Figure 3

In spite of all its benefits, the blockchain model is not without its flaws and shortcomings:

  • Scalability issues pertaining to the blockchain that might lead to centralization, which is casting a shadow over the future of the cryptocurrency.
  • Processing power and time required to perform encryption for all the objects involved in a blockchain-based ecosystem. IoT ecosystems are very diverse. In contrast to generic computing networks, IoT networks are comprised of devices that have very different computing capabilities, and not all of them will be capable of running the same encryption algorithms at the desired speed.
  • Storage too will be a hurdle. Blockchain eliminates the need for a central server to store transactions and device IDs, but the ledger has to be stored on the nodes themselves. And the ledger will increase in size as time passes. That is beyond the capabilities of a wide range of smart devices such as sensors, which have very low storage capacity.
  • Lack of skills: few people understand how blockchain technology really works and when you add IoT to the mix that number will shrink drastically.
  • Legal and compliance issues: It's a new territory in all aspects without any legal or compliance code to follow, which is a serious problem for manufacturers and service providers. This challenge alone will scare off many businesses from using blockchain technology.

The optimum platform

Developing solutions for the Internet of Things requires unprecedented collaboration, coordination, and connectivity for each piece in the ecosystem, and throughout the ecosystem as a whole. All devices must work together and be integrated with all other devices, and all devices must communicate and interact seamlessly with connected systems and infrastructures. It's possible, but it can be expensive, time-consuming, and difficult.

 The optimum platform for IoT can:

  • Acquire and manage data to create a standards-based, scalable, and secure platform.
  • Integrate and secure data to reduce cost and complexity while protecting your investment.
  • Analyze data and act by extracting business value from data, and then acting on it.

Security needs to be built in as a foundation of IoT systems, with rigorous validity checks, authentication, data verification, and all the data needs to be encrypted. At the application level, software development organizations need to be better at writing code that is stable, resilient and trustworthy, with better code development standards, training, threat analysis and testing. As systems interact with each other, it's essential to have an agreed interoperability standard, which is safe and valid. Without a solid bottom-top structure we will create more threats with every device added to the IoT. What we need is a secure and safe IoT with privacy protected. That's a tough trade off but not impossible and blockchain technology is an attractive option if we can overcome its drawbacks. 

 

Further reading

http://tech.economictimes.indiatimes.com/news/internet/5-challenges-to-internet-of-things/52700940

http://www.mindanalytics.es/2016/03/01/gartners-top-10-internet-of-things-technologies-for-2017-2018/?lang=en

http://www.cnbc.com/2016/10/22/ddos-attack-sophisticated-highly-distributed-involved-millions-of-ip-addresses-dyn.html

https://www.spiceworks.com/marketing/reports/iot-trends/

http://www.cio.com/article/3027522/internet-of-things/beyond-bitcoin-can-the-blockchain-power-industrial-iot.html

https://techcrunch.com/2016/06/28/decentralizing-iot-networks-through-blockchain/

http://www.blockchaintechnologies.com/blockchain-internet-of-things-iot

https://postscapes.com/blockchains-and-the-internet-of-things/

https://bdtechtalks.com/2016/06/09/the-benefits-and-challenges-of-using-blockchain-in-iot-development/

https://blogs.thomsonreuters.com/answerson/blockchain-technology/

http://www.i-scoop.eu/internet-of-things/blockchain-internet-things-big-benefits-expectations-challenges/

https://www.linkedin.com/pulse/20140403055037-246665791-bitcoin-accepted-here?trk=mp-author-card

https://www.linkedin.com/pulse/securing-internet-things-iot-ahmed-banafa?trk=mp-author-card

https://www.linkedin.com/pulse/industrial-internet-things-iiot-challenges-benefits-ahmed-banafa?trk=mp-author-card

 


 

Ahmed BanafaAhmed Banafa has extensive experience in research, operations and management, with a focus on the IoT area. He is a reviewer and a technical contributor for the publication of several technical books. He served as a faculty member at several well-known universities and colleges, including the University of California, Berkeley; California State University-East Bay; San Jose State University; and University of Massachusetts. He is the recipient of several awards, including Distinguished Tenured Staff Award of 2013, Instructor of the year for 2013, 2014, and Certificate of Honor for Instructor from the City and County of San Francisco. He was named as number one tech voice to follow by LinkedIn in 2016.

https://www.linkedin.com/in/ahmedbanafa
@BanafaAhmed

 

Comments

2017-01-11 @ 3:03 AM by Kolli, Chakravarthy

Great article! Agree that centralized IOT systems will not work because of scalability, privacy and security reasons. However I am convinced storage is an issue especially with sensors. This is because I do not expect sensors to be part of the consensus process. A proxy device with enough storage and processing power could be the node that runs consensus for a bunch of sensors.

2017-01-18 @ 1:51 PM by Borjan, Gabor

Unfortunately, blockchain can't and won't solve the problem you described.

A well designed IoT system is decentralized and bchan can't do anything and in fact it is absolutely not required. You simply described the IoT and the bchain, which is fine.

But as you wrote: "Blockchain technology is the missing link to settle privacy and reliability concerns in the Internet of Things" is simply misleading and FALSE.

No, IoT won't need this kind of silver bullet. It is not a silver bullet at all, and IoT will survive without it. In case of an IoT system, the transaction processing or transaction recording is secondary, especially, if the node is vulnerable.

What can do a transaction ledger to do with an insecure node? Nothing. You can play by the transactions, chains, but if the bad guys will gain access to the vulnerable node, your preferred ledger won't realize it. No, a cryptographic algorythm won't make consumer data more private.

The ledger is tamperproof? Fine, but if the node is not tamperproof, sorry, you are unlucky. Your node will be compromised without your knowledge.

Trustless messaging? I can't count how many times read this crazyness. In case of an IoT system, you need trust and not trustlessness! Hey!

Without trust, your IoT system will fail quickly. If you cannot trust the data you've received , if you can't trust even your own node, how do you trust in some data, you have placed in your ledger? Bchain and IoT in this case are totally different beasts. A good analogy, to better understand this: you have a small grocery. You buy products to sell and you have an accountant to provide the paperwork. If your supplier will send some poisonous food to your grocery, your accountant will be the last person who will realize this. But your consumers will suffer. The authorities will call you and will investigate the supply chain not the blockchain and the last person again will be your accountant who will be interrogated.


2017-01-22 @ 1:21 PM by D, Ollencio

Excellent article but it confused me a bit.Why would you suggest that "centralisation" could occur in a  block chain distributed topology? We are also suggesting two levels on "networks" are present - one "data" using block chain and the other "physical communications" maybe control,  between devices which can be compromised? Maybe I do not know enough about the ecosystem being built around localised sensors but not to have everything including "logging on/off" between devices icluded in the same block chain secure transaction records may not be wise?  Also delays in "decision making" because of the constant referral to the local host - appears to be raised as a weakness.  Is this true if the systems are localised?

IoT: a Mobile Network Operator Perspective

Giovanni Perrone and Massimo Vecchio
January 10, 2017

 

The world that is shaping in front of us brings visions of hyper-connectivity or, to put it another way, of an incredibly large number of connections between the different elements of the world that we see. The skeleton supporting IoT is, at the end of the day, exactly that: a dense network of connections between a multitude of points that makes possible a level of vision, perception, awareness and, last but not least, control on the world that surrounds us that was simply not possible even to think about before.

We are often tempted to limit our thinking only to the points that we want to connect: sensors, smart devices, collection points, processing centers and so on, and sometimes we risk to take for granted those very "connection lines" that transform IoT from a concept into reality. This is now becoming the typical vision of a smartphone user, who expects data connectivity to be available always, at high speed, without interruptions, no matter where the user is and what are the operating conditions.

The evolution curve

One of the authors of this article started to work on Machine-to-Machine (M2M) applications almost 14 years ago, when he was developing a monitoring platform for illumination systems installed on hi-voltage pylons. At that time, the options for creating a network of "things" spread across a country were limited to GSM modems with SMS used to carry messages between the monitored pylons and the main data centre. There were no mobile contracts available specifically for M2M operations and several limitations were in place for M2M use. For instance, a typical mobile contract stated that your SIM had to move; unfortunately, hi-voltage pylons do not move around that much and overcoming this problem was not an easy task at that time. Another problem was the expiration date of the SIM card: to avoid disconnection from the network periodic recharges had to be made to ensure credit was still available.

The mobile world at that time was clearly not M2M-oriented and such applications were considered by Mobile Network Operators (MNOs) more like an annoying niche market unable to bring substantial value to the business.

In 14 years things have changed dramatically: every MNO has started to consider M2M as a potential revenue-generating opportunity and M2M specific requirements have been introduced in telecom standards. At the same time, MNOs are beginning to include offers in their service portfolios that incorporate connectivity and processing solutions for B2B solutions in a single package, like fleet management or similar medium to large scale solutions.

Notwithstanding that, it is still quite difficult for an end user to find a mobile contract that fits normal M2M requirements. The contrast between this reality and the increasing volume of devices that should make use of cellular-based solutions for connectivity (e.g. home or car protection) is simply striking.

This contradiction can perhaps find an explanation in the often contrasting needs a MNO has to manage when it comes to the definition of its commercial offering: efficiently managing a market that requires on one side support for hi-bandwidth, on-off users, like commuters using YouTube, and on the other side billions of smart devices with low transfer rates and very low power requirements, can be extremely challenging.

Where we are going?

The 2016 Ericsson Mobility Report [1] projects a very interesting vision of the future and also gives some insights into what is happening between mobile networks and the IoT world:

  • In 2015, 0.4 billion IoT devices (out of 4.6  billion in total) were using cellular technology;
  • By 2018, the number of IoT sensors and devices is expected to exceed the number of mobile phones and become therefore the largest category of connected devices;
  • By 2021, a total of 15.7 billion IoT devices is expected to be connected – of this amount, 1.5 billion will be using a cellular technology.

In other words, even if cellular-based IoT devices will account "only" for a little less than 10% of the total number of connected devices by 2021, cellular-connected IoT devices will have grown at the same time by a factor of 2.7 compared with 2015.

There are also two interesting items of information that can be deduced from these figures:

  1. The relatively slow diffusion of cellular-based IoT devices seen until now is caused by the technological requirements and limitations of the early mobile networks. GSM, for instance, required significant transmission power and a significant percentage of the total traffic volume was used for the control plane (i.e. the logical connection links used to setup and manage connection, mobility, etc.). These factors posed severe limitations to M2M and IoT applications;
  2. The explosive growth rate by which cellular-based IoT devices is expected to spread is related to the much higher attention 3GPP (the standards body that generates standards for mobile networks) has now put in IoT, resulting in new network standards that fully support IoT requirements [2]. Such new designs, named EC-GSM-IoT (Extended Coverage GSM for the Internet of Things) and LTE-M (Long-Term Evolution for Machines), are based on existing technologies and already licensed spectrum and include low power and extended range support, making it possible to build low-power networks using existing infrastructure with limited changes. Unfortunately, GSMA does not foresee the first commercial deployments of IoT specific cellular networks before late 2016 - early 2017 [2]. Considering the current situation in terms of readiness of the different actors involved together with lessons learnt from previous technology migration events (e.g. the time it actually took moving from GSM to UMTS versus the aggressive forecasts of the GSMA) it is easy to see this prediction as rather optimistic.

MNO challenges and LPWANs

Mobile network operators are challenged by a market with different requirements that have to be satisfied simultaneously. All of that, in a world that now sees connectivity as a commodity, just like electrical power: it is expected to be available whenever it is needed.

Significant investments not only on the radio bearers, but also on the data backbones will be required to support the projected growths in data traffic, generated not only by IoT, but also by all other possible utilizations of mobile broadband (e.g. video streaming).

At a time when MNOs are beginning to seriously consider IoT as a real business opportunity, leaner solutions are already available on the market that can be used today for implementations with short times to market. LPWANs (Low Power Wide Area Network) represent in fact an ideal solution for low-bandwidth, large coverage projects, and thanks to players like LoRa and Sigfox, they are real solutions that can be used today. Chipsets and modules for both technologies are already available from several vendors and, while Sigfox networks are licensed and managed by Sigfox (and therefore area coverage is managed by Sigfox itself), for LoRa it is possible to start building a private LoRa network today using commercially available modules.

Technologies used in both cases promise wide coverage (Sigfox claims to be able to cover up to 40km in open space with a single repeater [3]) with long battery duration (10 years claimed for LoRa applications [4]) bundled with data rates that can range from a few hundred bits per second to 50-100 kbit/s for LoRa [5]. As for coverage and market readiness, as mentioned before, hardware modules and software components are already available in both cases and Sigfox is capable of providing its services in 29 countries thanks to agreements with different business partners [6].

As mentioned in the previous section, 3GPP reacted in 2016 with the release of new standards targeted specifically for the IoT world using licensed spectrum already available to MNOs. While EC-GSM-IOT and LTE-M extend the cellular domain to M2M applications, a dedicated 3GSPP standard for LPWAN, named Narrowband IoT (NB-IoT), has been released in June 2016. The specifications on paper look promising: better data rates than the other solutions, implementation possible by a simple software update on existing LTE eNb nodes and possibility of exploiting the infrastructure of giants MNOs like Vodafone or Deutsche Telekom make NB-IoT extremely appealing.

There is however a crucial factor that will have to be taken in consideration: time.

With the NB-IoT standard just released, commercial applications are not expected to be live before the end of 2017, even if MNOs are making aggressive claims about being ready in early 2017 for live applications [7]. Chipsets and modules are still not available and remote SIM provisioning (using embedded SIM cards for instance) will have to be tested in the field to verify how well it works with small IoT devices.

To further enrich the picture; during 2016 the WiFi Alliance released the highly anticipated 802.11ah standard, designed specifically for IoT applications. While the new standard (also called 802.11 HaLow) promises to combine low power and long ranges, the utilization of the 900 MHz band (also used for GSM) can raise some concerns about possible interference between the two systems. Also in this case, commercial applications are still to become available and the business models that will be proposed, combined with real world performance, will be relevant to the success of this solution.

Studies predict that LPWAN will generate revenues of 27 billion US dollars by 2020 [8] so it is easy to understand that MNOs will be highly motivated to recover lost ground and make a success of MNO-based LPWAN solutions such as NB-IoT . By the time NB-IoT based solutions will be widely available (late 2017 to early 2018) however, even more ground will have been gained by currently available solutions.

To recover the lost ground MNOs will have to make significant investments both in technology and marketing, devising business models that can truly represent a significant competitive advantage, possibly offering differentiated business solutions to different market segments, ranging from raw connectivity to networks operated as a service perhaps integrated with cloud-based computing platforms [9].

Conclusions

Even if projections of a massive use of cellular technology for IoT in the future are confirmed, it seems clear that MNOs will have to make significant steps in several areas to step up to the challenge:

  • Technology more compatible with IoT applications will need to be widely available. Recently released standards go in that direction but commercial deployments risk to be live too late;
  • MNOs will therefore have to maintain a continuous momentum on the evolution of their networks and adapt strategies to successfully manage the challenges posed by other competitor technologies like LPWANs;
  • MNOs will also have to have their sales and market strategy evolving faster than they have been doing until now: M2M commercial offers will have to be much more common than nowadays;
  • Last but not least, security related and network-protection aspects will have to be taken into account: "mass deployment of inefficient, insecure or defective IoT devices on the MNOs' networks" [10] could represent a significant threat to the availability and safety of mobile networks, especially in critical situations [11].

We will have therefore to see where technology and market evolutions will bring the MNO-IoT relationship in the near future, with a possible end scenario being cellular technologies used only for specific applications with a large proportion of smart devices using other solutions such as LPWAN [12].

 

References

[1] Ericsson Mobility Report – https://www.ericsson.com/mobility-report

[2] GSMA IoT – http://www.gsma.com/connectedliving/mobile-iot-initiative/

[3] http://www.iotglobalnetwork.com/products/single/id/571/sigfox-m2m-network-access  

[4] SemTech wireless - LoRa Technology – http://www.semtech.com/wireless-rf/wireless-rf/LoRa-Wireless-Public-Network.pdf

[5] Semtech LoRa FAQ – http://www.semtech.com/wireless-rf/lora/LoRa-FAQs.pdf

[6] Sigfox website – https://www.sigfox.com/

[7] Vodafone to 'Crush' LoRa, Sigfox With NB-IoT – http://www.lightreading.com/iot/vodafone-to-crush-lora-sigfox-with-nb-iot/d/d-id/722882

[8] LPWA Networks Ecosystem: 2015–2030 – Opportunities, Challenges, Strategies, Industry Verticals & Forecasts, SNS Research

[9] Huawei NB-IoT whitepaper – http://www.huawei.com/minisite/iot/img/nb_iot_whitepaper_en.pdf

[10] GSMA IoT Connection Efficiency Guidelines – http://www.gsma.com/connectedliving/gsma-iot-device-connection-efficiency-guidelines/

[11] Mobile network operators: Overcome IoT challenges using the power of SIM – R. Dewey, http://internetofthingsagenda.techtarget.com/blog/IoT-Agenda/Mobile-network-operators-Overcome-IoT-challenges-using-the-power-of-SIM

[12] Ericsson Cellular networks for Massive IoT – enabling low power wide area applications – http://www.ericsson.com/res/docs/whitepapers/wp_iot.pdf

 


 

Giovanni PerroneGiovanni Perrone has been working in the mobile and Telco domain for more than 12 years, coming from another 10 years spent in the design of digital solutions for renewable energy and industrial automation applications. In the last 10 years he has been working in the post-sales area, specializing in project and program management, earning a PMP certification in 2007 and a CSM one in 2012 and has more than 10 years of experience in project and program management in Telecom, IT and Hi-Tech domains. In parallel to his working activities, he is currently cooperating with the "SMART Engineering Solutions & Technologies (SMARTEST)" Research Centre of the eCampus University (Italy), where he is completing his Master degree in Informatics and Control Automation. He has a Degree in Electronics Engineering and he is currently engaged in activities ranging from research to business development and leadership and project management seminars and workshops through the PMI CIC chapter.

 

Massimo VecchioMassimo Vecchio received the Laurea degree in Computer Engineering (Magna cum Laude) from the University of Pisa and the Ph.D. degree in Computer Science and Engineering (with Doctor Europaeus mention) from IMT Lucca Institute for Advanced Studies in 2005 and 2009, respectively. His research background is on computational and artificial intelligence techniques, such as metaheuristics for global optimization and fuzzy logic. During his Ph.D. degree, however, his research interests moved towards power-efficient engineering and application designs for pervasive systems and devices. From October 2008 to March 2010, he worked as a research engineer at INRIA-Saclay (France). Then, he joined the Signal Processing in Communications group at the University of Vigo (Spain) as a post-doctoral researcher. Upon his return to Italy (October 2012), he worked as a senior researcher at CREATE-NET (an ICT research center) within the "Smart Internet of Things (RIoT)" research unit, mainly in the field of Internet of Things devices and resources virtualization. Starting from May 2015, he is an associate professor at the eCampus University (Italy), holding also a course on mobile and embedded systems and heading the "Everything Connected (EC)" research unit of the "SMART Engineering Solutions & Technologies (SMARTEST)" Research Centre. He is the author of one book monograph and co-author of two book chapters, as well as several journal and conference papers.

 

 

Internet of Things for Buildings that Make Life Safe and Secure

Takumi Ito, Mikio Hasegawa and Takashi Nakajima
January 10, 2017

 

Recently, there have been numerous discussions about the Internet of Things (IoT) delivering benefits in a variety of areas such as the provision of more comfortable human lifestyles and improvements in business efficiency. Most of the discussed topics and interests are focused on the development of specific underlying technologies.

These technology building blocks include:

1) Power supplies to start and operate IoT systems.
2) Sensors to measure and monitor the state of things and respond to any stimuli.
3) Networks, both narrow and wide area, to disseminate the status and responses of things.
4) Data analyses to identify the state of a system.
5) Data security for safety and security protection.

It is necessary to identify which are the most important areas of focus in any application of IoT. Recently, there have been many discussions in areas such as automobiles, housing, logistics and medicine, concerning applications to implement unmanned operation, automation, monitoring and support. These development trends of fundamental technologies related to IoT are widely recognized to have already started some decades ago.

Aim of our IoT system

We are focusing on the development of an IoT application in the architectural field, which supports everyday life, improves the quality of life, and promotes the safety and security of people. At present, we observe that the possibility of applying IoT in building architectures is mainly confined to the provision of comfortable indoor environments (temperature, humidity, lighting, energy savings, etc.), life support (housework, cooking, etc.), and home appliances with installed IoT systems. In fact, some home appliances with IoT capability have already been developed (air conditioner, freezer, oven, etc.). The main aim of these systems is to realize improvements in the quality of life.

We aim to develop an IoT application for building architectures that provides safety and security, particularly in the prevention of home crimes and in the event of natural disasters. Japan is one of the countries that experience frequent earthquakes, and various types of problem arise during these disasters. We are assuming the responsibility of solving these problems. We name our IoT-architecture approach an "Intellectual house".

Goals and application of our project

Japan is a country with frequent earthquake disasters and a large number of buildings have experienced severe damage from past earthquakes. After terrible seismic disasters, the following problems have been recognized:

  1. Large numbers of victims were injured, lost their houses, lost their families, etc.
  2. Insufficient food, water, and dairy supplies.
  3. Traffic problems such as traffic jams and transport disruption that cause delays in rescue and relief supplies.
  4. Shutting down of lifelines such as water, gas, power supply, etc.
  5. Occurrence of deserted homes and ghost towns because most victims cannot enter the damaged buildings for a while, which reduces home security.
  6. Decline in economic activities because supply chains were disrupted; workforces were short-staffed because workers participated in volunteer activities and caused poor traffic control.

Therefore, the following are required in disaster areas: 1) rapid rescue of victims, 2) rapid restoration of damaged buildings and infrastructures, and 3) rapid reconstruction of cities and countries.

To support these requirements, a rapid-response communication system is vital to identify whether a building is safe or damaged. Victims experience great uneasiness until the next action for restoration has been decided.

In past seismic disasters in Japan, a large amount of time was spent on investigations (few months) and a large number of investigators concentrated on the affected areas (few thousand people and volunteers). To prevent such wastage in time and human resources, our IoT system will estimate the state of buildings (whether safe or damaged) within a few minutes without the need for personal investigators, and the results will automatically and quickly be forwarded to the owners. 

In the field of building structural engineering, experimental methods for measurement and visualization of the behavior and damage of a building have been established with high reliability. In addition, many evaluation methods for damage identification have been proposed. In general, the strain diagram of a column or a beam can be obtained from the measurements of a strain gauge of a building test specimen under loading conditions. The behavior of a building can then be visualized referring to these results and the location of the damage or the points of excitation can be identified. These methods can help the process of what, where, and how to measure the state of a building.

Key points for our IoT system

As previously mentioned, we focus on a warning system for safety and security during disasters. As a visualization of our IoT system, so to speak, the house itself notices pain or discomfort. In the development of this IoT system we consider the following areas: no external power supply; reliable methods for measuring the state of a building; big data analysis; and optimized alert networks.

1) Energy harvesting for power supply

In the event of a severe natural disaster, a large number of buildings and urban areas stop functioning, and power outages occur. To estimate the state of buildings in detail, a large number of measuring points is needed. Therefore, to supply power under these situations and demands, we propose to use energy harvesting, such as vibration under seismic or wind motions, and temperature difference in buildings. In other words, the house itself makes the power supply for the start-up IoT system.

2) Measuring the state of buildings

To identify the status of buildings, organic piezoelectric film is applied to measure the strain induced in the buildings. Piezoelectrics have been promising materials which offer electromechanical conversion for a sensor and an energy harvesting device, because of their easy installation into mechanical sources and relative simplicity compared with magnetic field-based generators. Furthermore, organic piezoelectric film is attractive because of its prospective features of strong robustness and high flexibility. However, there are a large number of measuring points in the buildings, and various conditions of the surface of building materials have to be taken into account. Therefore, the locations of measuring points will be systematically selected on the basis of the reference data obtained through building structural engineering tests.

3) Analysis method of big data of buildings

To diagnose the state of buildings, a large number of measured data points must be analyzed. A house contains various types of building materials (wood, concrete, steel, etc.) which complicates the data analysis. Therefore, we will deploy machine learning and artificial intelligence techniques.

4) Communication method and how to warn people from buildings

To identify the state of buildings after a disaster, the analyzed results will be sent to the relevant people. This information will help the victims to decide whether to go home or not, or whether or not the affected building needs repair. The volume of transmitted data is thereby increased, and the communication area can become wide. Therefore, determining the optimum communication method and devices is important to ensure rapid notification.

In order to collect data within buildings, low power consumption wireless modules should be selected because it is impractical to replace the batteries of wireless devices within buildings. To collect data from sensors in the wider area, longer distance wireless communications working on low frequency bands will be used for IoT. For the longer distance wireless communications, we choose Wi‑SUN, which works on the 920MHz band, with IEEE 802.15.4g for PHY and IEEE802.15.4e for MAC, which is ideal for intermittent low power consumption communications. Wi‑SUN access points placed every several hundred meters will forward the collected data from the sensors to the data center. After analyzing damage to the buildings from the collected sensor data, warnings will be sent to people by various wireless communication systems.

Interdisciplinary cooperation and industry-academia-municipality collaboration

We have just discussed the technology and objectives of fundamental and practical research. The development of an IoT system requires the integration of interdisciplinary methods, devices, and technologies. Therefore, we have launched an association of an interdisciplinary team, which is involved in a cross department project among electrical engineering, theoretical and applied physics, and architecture (Figure 1). Each researcher conducts individual research related to their specialized field, and cooperates with each other.

Figure 1

Figure 1: Relationships within our research team

Furthermore, we have initiated an industry-academia-municipality collaboration. Here, our academic team has requested the provincial city (in Oita prefecture, Japan) to prepare a test field for an actual building with an installed IoT system (Figure 2), which will be used as a testbed.

Figure 2

Figure 2: Conceptual image of the IoT system house

Figure 2 illustrates the notifications envisaged if a building encounters the domestic accident or home crime (Ordinary) as well as those that will occur in the event of a natural disaster (under Disaster conditions).

 


 

Takumi ItoTakumi Ito is an associate professor at Tokyo University of Science, Japan. He received the Dr. Eng. Degree in building structural engineering from the University of Tokyo in 2004. His Ph.D. thesis is "Evaluation method of ultimate seismic performance on steel building structures". From 2004 to 2009, he was in the University of Tokyo as research associate. Since 2009, he stayed in Tokyo University of Science. His research interests are building structures (steel, wooden structures), experimental methodology, and numerical simulation. He has published 42 papers, 57 proceedings, and other papers or reports. He received some paper awards of Architectural Institute of Japan or Japan Society of Steel Construction in 2003, 2004, and 2006. He can be contacted at t-ito@rs.kagu.tus.ac.jp

 

Mikio HasegawaMikio Hasegawa received his B.Eng., M.Eng., and Dr.Eng. degrees from Tokyo University of Science, Tokyo, Japan, in 1995, 1997, and 2000, respectively. From 1997 to 2000, he was a Research Fellow at the Japan Society for the Promotion of Science (JSPS). From 2000 to 2007, he was with the Communications Research Laboratory (CRL), Ministry of Posts and Telecommunications, which was reorganized as the National Institute of Information and Communications Technology (NICT) in 2004. Currently, he is a Professor in the Department of Electrical Engineering, Tokyo University of Science. He is a member of IEEE and has served as a Secretary of the Chapter Operation Committee for the IEEE Japan Council. His research interests include mobile networks, cognitive radio, chaos, neural networks and optimization techniques. He can be contacted at hasegawa@ee.kagu.tus.ac.jp

 

Takashi NakajimaTakashi Nakajima received his B.Sci., M. Sci., and Ph.D. degrees from Tokyo University of Science, Tokyo, Japan, in 2003, 2005, and 2008, respectively. In 2008-2012, he worked at Tokyo University of Science as a research associate. In 2012-2014, he was in the Institute of Materials Research, Tohoku University as a research associate. Currently, he is a junior associate professor in the Department of Applied Physics, Faculty of Science, Tokyo University of Science. He holds the concurrent post of PRESTO researcher of Japan Science and Technology Agency. His research has been focused on the functional properties of ferroelectric materials and ferroelectric devices including the piezoelectric energy harvester. He can be contacted at nakajima@rs.tus.ac.jp