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David Oro's Posts (186)

We often don’t compare technology to fable stories, but when it comes to the internet of things (IoT), the story of Pandora’s Box comes to mind. It’s a technology that has great potential, but where the weakness and possibilities lie are in it’s lack of basic security measures. We might even go as far as to say, what security? These are the concerns we’re thinking about at IT Security Central.

As a completely remote company, we’re taking measures to understand how the internet of things can impact our company data security. Hackers look to exploit technology vulnerabilities to access valuable information. Hacking an IoT connected fish tank, smart fridge - these aren’t far-fetched stories. These are stories that are happening now. 

The lack of secured IoT devices starts in the development phase. These devices are developed on a basic linux operating system with default codes that buyers rarely change. When these devices are developed, security isn’t on the agenda; rather, developers are looking at human behaviors and outside threats. When they should be looking inwards.

An unsecured IoT device is the weak link in the connection. As one of the fundamental purposes of the technology is to provide connection and accessibility, this one weak link can bring down the entire network. And if your remote worker’s BYOD devices are in someway connected to that network, your company just became vulnerable.

Remote workers or ‘the gig economy’ is expected to increase in frequency. According to the Global Mobile Workforce Forecast Update, employees working remotely is suppose to increase to 42.5% of the working population by 2022. At that time, the world is projected to see half of its population working outside the office either full-time, or part-time. 

Security vulnerabilities, remote workers and IoT - where is the connection? The scary thing, remote workers are likely to already have IoT devices in their work environment, and most likely, they are not protected. These devices can mostly be smart home devices that workers have acquired to make their daily lives easier. Common devices include Amazon Echo, Neo and GeniCan.

The first step in active prevention is to make your employees aware of the importance of data security and then aid them with the tools for success.

Best Practices for Protecting Your Network (from Remote Workers)

With the wealth of internet-based security technologies, the idea of protecting your network with in-house servers and the traditional firewall is (well) old school. With cloud-based companies, you can now access and protect data in easy step-by-step processes, and the best news, most of these companies do the data management for you.

One of the most progressive approaches to remote worker security would be to adopt a monitoring service to collect data and actively look for anomalies in the network. Through data collection and analysis, a monitoring software creates a user profile of normal, everyday behavior. The administrator can set ‘alerts’ for when certain data repositories and files are accessed, or when sensitive data is moved. The longer a data breach goes undetected, the larger financial implication for the company. Requiring remote workers to download and use a remote monitoring software is one of the highest levels of protect against data loss.

But if monitoring isn’t on your agenda, these are a few basic tactics that employers can encourage remote workers to undertake.

Permissions Management

Though the workers are remote, administration can set limits to data access. This process starts by undergoing a through analysis and understanding of each position. It’s important to understand who needs access to what information, and who doesn’t need access to information. Once this is understood, administrators can restrict information, and they can also set ‘alerts’ when information is accessed without prior approval.

Home Network Policy

Once employees leave the brick & mortar walls, the manager has little access where and on what internet network they’re accessing information. But don’t fret, this freedom and flexibility is part of what make remote work appealing. Where privacy might be a factor, we don’t suggest to go as far as asking remote workers to eliminate IoT devices on their network. Rather, we encourage to create a policy that specifically states the security requirements that the IoT must have in order for the work network to be accessed. By educating your employees, you can save them and data loss heartbreak.

Encryption

Encryption, encryption, encryption. You’ve heard the importance of encryption. For remote workers, the company can never be too safe, so they should go the extra mile and set remote workers up on an encrypted network. A VPN ensures all connections and communications are encrypted when the network is accessed. Don’t worry about IoT connectivity in their home, or when remote employees connect to an unsecured public wi-fi connection. A VPN provides the next level of security through encryption, and a hacker won’t be able to access communication or data without alerting administrators to a potential breach. 

IoT devices are already integrating into our at-home lives, and when remote workers access their at-home networks, suddenly the topics collide. As more workers go remote, it’s important to look inwards towards security to see how everyday IoT devices impact company data. Take the time to ensure that remote workers are protecting the network effectively.

Guest post by Isaac Kohen. Isaac Kohen is the founder and CEO of Teramind (https://www.teramind.co/), an employee monitoring and insider threat prevention platform that detects, records, and prevents, malicious user behavior in addition to helping teams to drive productivity and efficiency. Isaac can be reached at [email protected]. Connect with Isaac on social media: LinkedIn, IT Security Central and Twitter @TeramindCo.

 

 

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Guest post by Romain Wurtz, Chief Technology Officer, NarrativeWave

As companies engage in the implementation of analytics and data science applications, many challenges lie ahead. According to the Harvard Business Review, many data science applications fail due to poor goal definition, a lack of understanding of the key data, or a lack of focus on business value.

We believe the best route to data analytics and particularly analytics for the Industrial Internet of Things, must have several key elements:

Key Elements of Effective Analytics:

Builds upon your Subject Matter Experts’ existing knowledge. Allows engineers to use the platform and be part of the analytics process.

Enables automation of key processes.  Builds a solid foundation for more complex analytics (e.g. predictive).

This article takes a look at each of these elements in further detail and explores why they are important to driving value for your organization.

Having a platform built on your subject matter experts’ knowledge is the best starting point.

Your Subject Matter Experts (SMEs) and engineers have been building and maintaining your equipment for decades. Their expertise and knowledge is the best available expertise on how your equipment should be operated, maintained, and evaluated. Incorporating their knowledge to best evaluate data from the equipment and what that data means, is the ideal starting point for the application of analytics.

Analytics platforms using purely Machine Learning or Artificial Intelligence may lack insight on what the data means and the meaning of events within the data. Without human interaction or interpretation, more advanced analytics, such as predictions, have a difficult time achieving the desired outcome. Without a determined outcome, the process can take months to evaluate, and even then, the analytic effectiveness and accuracy can remain unknown and unproven.

We believe the best starting point for analytics is one that starts by using your own proven analytic methods as a foundation and then allows for a natural, building blocks approach.

Using a platform that allows engineers to be part of the process helps with the adoption of analytics.

Adopting new analytics and data driven business models is fundamentally about changing the way business has been done for many years. In an effort to make this transition, gaining adoption and trust of key players within your organization will significantly impact the success of a new program. Having a platform where SMEs can interact and engage, without having to be a data scientist or a developer, results in higher adoption and more impactful business outcomes for the organization.

Implementing a platform that automates current processes creates short-term and significant value.

In order to gain value from large data sets and sensor data, only a platform that starts to automate part of the process can create scalable value. Meaning, the platform must be able to interpret data, generate insights, and provide recommended outcomes for end users. Otherwise, it becomes just another way to visualize and explore data. This can add value on its own, but doesn’t reach the impact that automation provides. As noted earlier, building a system on your proven analytic methods, and then adding a layer of more advanced analytics, such as machine learning based predictions, is the best route to a highly accurate, automated platform.

Building a platform with a solid foundation of your experts’ knowledge is the best way to approach implementing an entire suite of analytics.

Building a platform configured by your own SMEs creates the optimal foundation for an entire range of analytics. Your experts can provide knowledge about significant areas such as:

The meaning of key data. How sensors are related to each other.

What constitutes an actionable event?  What constitutes a false alarm?

Exceptions to the rule.

Once this knowledge is part of an automated platform, adding a full range of analytics becomes more impactful. For example, knowledge of what constitutes a false alarm can lead to an insight describing what turned a false alarm into a valid alarm and what indicators are worth automatically tracking. By contrast, an approach that solely tries to use machine learning or AI techniques without these key understandings, can struggle with the “right” business outcome, accuracy, dealing with exceptions, and delivering significant value to the business.

Business Cases & Outcomes

These business case examples show how we at NarrativeWave impact customer’s operations, profitability, unplanned downtime, and workforce efficiency.

Improved Accuracy of Event & Alarm Analysis.

Challenge: The traditional workflow of diagnosing events or alarms on large industrial assets is a manual process for engineers. A manufacturer was looking for a solution that would increase accuracy and reduce the risk of costly human errors. 

Solution: NarrativeWave’s platform allowed the customer’s engineers to create detection models and equations through the SaaS platform. Currently, this manufacturer receives accurate and automated root-cause analysis of events in near real-time.

Impact: The software provided a 25% increase in accuracy of diagnosing events, which means a more consistent, predictable solution for this manufacturer’s engineers and clients.

Reduced Time Spent Diagnosing Alerts & Alarms

Challenge: Sensors on large industrial assets generate millions of data points per second. When an alert was triggered, engineers spent hours conducting redundant, manual research to diagnose the problem and produce an actionable report for clients. The diagnostic process can take up to 16 hours and technicians were struggling to keep up with the expanding service requirements. 

Solution: The NarrativeWave platform automated their manual processes, delivering an analysis, actionable insights, recommendations, and a report to their engineers in less than 3 minutes. This allowed their engineers to make near real-time decisions on what happened, why it happened, and what to do next.

Impact: The outcome resulted in a 95% time savings in diagnosing alerts and alarms, which reduced unplanned equipment downtime, improved workforce efficiency, and enhanced service contract profitability. This proved the opportunity for a multi-million dollar savings per year for this OEM, and better supported real-time service contracts.

Optimized Productivity of Skilled Engineering Labor

Challenge: More than 50% of all industry alarms are false positives, which still have to be diagnosed and solved. A customer was looking for a solution that would allow their engineers to optimize their workflow and spend less time servicing invalid alarms. 

Solution: The NarrativeWave platform automated the root cause analysis of events to produce actionable insights based on the manufacturer’s data. The outcome was an explanation of the event that occurred and guidance on what to do next, which was provided to the engineers within a few minutes.

Impact: The platform accurately and quickly invalidated false alarms, allowing engineers to focus more time on resolving valid alarms and serving their clients. For the first time, engineers were being leveraged in the best way to impact this manufacturer’s operations.

Increased Efficiency in Creating Detection Models

Challenge: A large enterprise client had a robust analysis setup with 3 detection models and 150 threshold variants. The client’s process for iterating detection models originally took 3–4 months and required engineers to rely on development from either a software engineer, data scientist, or an outside software vendor. 

Solution: NarrativeWave’s platform provided an intuitive pipeline, enabling their business users to quickly create, manage, and iterate their own detection models. The platform is user-directed, managed and utilized by the customer’s internal engineers, without the ongoing need of developers or data scientists.

Impact: The iteration timeframe has been dramatically reduced since using NarrativeWave. More importantly, this customer’s engineers can setup iterations on their own, allowing for immediate impact on the business operations and for their clients.

Enhanced Next Generation Knowledge Base

Challenge: Engineers have been detecting alarms individually for 30 or more years. While working with a major engine manufacturer, NarrativeWave found the detection process was not recorded, standardized, or made available to other engineers and management within the organization. 

Solution: The platform is setup to record the engineers’ knowledge and feedback, resulting in a platform that gets smarter over time. Engineers can customize the business analysis and recommendations to make them as accurate as possible, therefore creating an evolving knowledge base for SMEs. 

Impact: The outcome resulted in the manufacturer, for the first time, being able to capture their engineers’ knowledge. This increased collaboration between engineers, improved standardization, and allowed valuable knowledge to be visible across the organization.

Improved Fleet Health & Management

Challenge: Manufacturers and equipment operators currently lack visibility into assets across their entire fleet, making it difficult to identify poorly performing assets and best performing assets. 

Solution: With NarrativeWave, asset performance can be evaluated near real-time, enabling organizations to better manage critical assets and plan for future actions, all by the click of a mouse.

Impact: The platform-wide view provides significant time-savings of tracking and managing fleet health for equipment manufacturers and operators. Additionally, the platform reduces unplanned downtime and helps organizations prevent critical equipment failures.

Improved Predictive Analytics & Maintenance

Challenge: Manufacturers and equipment operators are interested in deploying predictive models for better asset maintenance and warranty support. Pure machine learning approaches lack a solid foundational basis and can be difficult to implement successfully.

Solution: With the NarrativeWave Knowledge Base, key information such as the meaning of events, the relationship of sensors, and what constitutes a valid alarm are already known. By applying machine learning techniques to a solid NarrativeWave foundation, predictive analytics is more effectively implemented. 

Impact: This approach provides a strategic method of utilizing predictive analytics and improves the outcome of implementing analytics. The result is a highly accurate, auditable platform rather than a pure “black box” approach.

 

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Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .

“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?

 I have often used this diagram to crisply define IoT.

Even 10 years ago, the first two blocks in the diagram were major challenges; in 2017, sensors, connectivity, cloud and Big Data are entirely manageable. But extracting insights and more importantly, applying the insights in, say an industrial environment, is still a challenge. While there are examples of business value generated by IoT, the larger value proposition beyond these islands of successes is still speculative. How do you make it real in the fastest possible manner?

In a slogan form, the value proposition of IoT is ”Do more at higher quality with better user experience”. Let us consider a generic application scenario in industrial IoT.

IoT Data Science prescribes actions (“prescriptive analytics”) which are implemented, outcomes of which are monitored and improved over time. Today, humans are involved in this chain, either as observers or as actors (picking a tool from the shelf and attaching it to the machine).

BTW, when I mentioned “Better UX” in the slogan, I was referring to this human interaction elements improved by “Artificial Intelligence” via natural language or visual processing.

Today and for the foreseeable future, IoT Data Science is achieved through Machine Learning which I think of as “competence without comprehension” (Dennett, 2017). We cannot even agree on what human intelligence or comprehension is and I want to distance myself from such speculative (but entertaining) parlor games!

Given such a description of the state of IoT art in 2017, it appears to me that what is preventing us from hockey-stick growth is the state of IoT Data Science. The output of IoT Data Science has to serve two purposes: (1) insights for the humans in the loop and (2) lead us to closed-loop automation, BOTH with the business objective of “Do More at Higher Quality” (or increased throughput and continuous improvement).

Machine Learning has to evolve and evolve quickly to meet these two purposes. One, IoT Data Science has to be more “democratized” so that it is easy to deploy for the humans in the loop – this work is underway by many startups and some larger incumbents. Two, Machine Learning has to become *continuous* learning for continuous improvement which is also at hand (NEXT Machine Learning Paradigm: “DYNAMICAL" ML).

With IoT defined as above, when it comes to “rhyming with history”, I make the point (in Neural Plasticity & Machine Learning blog) that the current Machine Learning revolution is NOT like the Industrial Revolution (of steam engine and electrical machines) which caused productivity to soar between 1920 and 1970; it is more like the Printing Press revolution of the 1400s!

Printing press and movable type played a key role in the development of Renaissance, Reformation and the Age of Enlightenment. Printing press created a disruptive change in “information spread” via augmentation of “memory”. Oral tradition depended on how much one can hold in one’s memory; on the printed page, memories last forever (well, almost) and travel anywhere.

Similarly, IoT Data Science is in the early stages of creating disruptive change in “competence spread” via Machine Learning (which is *competence without comprehension*) based on Big Data analysis. Humans can process only a very limited portion of Big Data in their heads; Data Science can make sense of Big Data and provide competence for skilled actions.

 

To make the correspondence explicit, "information spread" in the present case is "competence spread"; "memory" analog is "learning" and "printed page" is "machine learning".

 

Just like Information Spread was enhanced by “augmented memory” (via printed page), Competence Spread will be enhanced by Machine Learning. Information Spread and the Printing Press “revolution” resulted in Michelangelo paintings, fractured religions and a new Scientific method. What will Competence Spread and IoT Data Science “revolution” lead to?!

From an abstract point of view, Memory involves more organization in the brain and hence a reduction in entropy. Printed page can hold a lot more “memories” and hence the Printing Press revolution gave us an external way to reduce entropy of “the human system”. Competence is also an exercise in entropy reduction; data get analyzed and organized; insights are drawn. IoT Data Science is very adept at handling tons of Big Data and extracting insights to increase competence; thus, IoT Data Science gives us an external way to reduce entropy.

What does such reduction in entropy mean in practical terms? Recognizing that entropy reduction happens for Human+IoT as a *system*, the immediate opportunity will be in empowering the human element with competence augmentation. What I see emerging quickly is, instead of a “personal” assistant, a Work Assistant which is an individualized “machine learner” enhancing our *work* competence which no doubt, will lead each of us to “do more at higher quality”. Beyond that, there is no telling what amazing things “competence-empowered human comprehension” will create . . .

I am no Industrial IoT futurist; in the Year 1440, Gutenberg could not have foreseen Michelangelo paintings, fractured religions or a new Scientific method! Similarly, standing here in 2017, it is not apparent what new disruptions IoT revolution will spawn that drop entropy precipitously. I for one am excited about the possibilities and surprises in store in the next few decades.

PG Madhavan, Ph.D. - “LEADER . . . of a life in pursuit of excellence . . . in IoT Data Science” 

http://www.linkedin.com/in/pgmad

This post original appeared here.

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Quantifying IoT Insecurity Costs

Ever wonder what is the real cost of IOT insecurity?

Well reseachers at the University of California, Berkeley, School of Information recently published a report that attempts to lay out the costs to consumers in the context of DDoS attacks. The report focuses on exploiting vulnerable devices for their computing power and ability to use their network’s bandwidth for cyberattacks—specifically DDoS attacks on Internet domains and servers.

Researchers infected several consumer IoT devices with the Mirai malware and measured how the devices used electricity and bandwidth resources in non-infected and infected state. Their hypothesis: compromised IoT devices participating in a DDoS attack will use more resources (energy and bandwidth) and degrade the performance of a user’s network more than uninfected devices in normal daily operation.

Based on energy and bandwidth consumption they developed calculator to estimate the costs incurred by consumers when their devices are used in DDoS attacks. Two recent and well publicized attacks, and one hypothetical, were calculated:

  • Krebs On Security Attack: According to their cost calculator, the total electricity and bandwidth consumption costs borne by consumers in this attack was $323,973.75.

  • Dyn, Inc. Attack: They calculate the total cost borne by consumers as $115,307.91.

  • "Worst-Case" Attack: This hypothetical “Worst-Case” scenario approximates the costs that could result if the Mirai botnet operated at its peak power using a UDP DDoS attack. The projected cost to consumers of this attack is $68,146,558.13.

Commenting on the study, Bob Noel, Director of Strategic Relationships and Marketing for Plixer said, “Organizations with enslaved IoT devices on their network do not experience a high enough direct cost ($13.50 per device) to force them to worry about this problem. Where awareness and concern may gain traction is through class action lawsuits filed by DDoS victims. DDoS victims can suffer financial losses running into the millions of dollars, and legal action taken against corporations that took part in the distributed attack could be mechanism to recuperate losses. Companies can reduce their risk of participating in DDoS attacks in a number of ways. They must stop deploying IoT as trusted devices, with unfettered access. IoT devices are purposed-built with a very narrow set of communication patterns. Organizations should take advantage of this and operate under a least privilege approach. Network traffic analytics should be used to baseline normal IoT device behavior and alarm on a single packet of data that deviates. In this manner it is easy to identify when an IoT device is participating as a botnet zombie, and organizations can remediate the problem and eliminate their risk of being sued.”

Or as we've argued before, regulation is key. And now that we have an economic cost on IoT insecurity, we have better information for regulators to pursue strategies and legislation for enforcing workable security standards to reduce the negative impacts of IoT devices on society.

 

 

 

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IoT Fight

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Surprise! Operations and IT aren't getting along when it comes to IoT.

451 Research announced new survey results that show operational technology (OT) and IT stakeholders are not aligned on IoT projects. Sure will be harder to drive business results if this doesn't get fixed. Here are some key findings:

Research shows that IT and OT personnel are not well aligned on IoT initiatives, and they need to cross that divide for those enterprise IoT projects to prove viable.

  • Only one-third of OT respondents (34%) said they ‘cooperate closely with IT’ on IoT projects from conception to operations.
  • A relatively small group of respondents said they were in ‘active conflict’ with IT over IoT, OT professionals are four times more likely to characterize their relationship with IT that way.  
  • More than half (55%) of the OT survey respondents currently deploy IoT within their organization, and 44% have successfully moved those projects from proof of concept to full-scale deployment.
  • New operational efficiencies and data-analytics capabilities are driving successful projects; however, many IoT projects face roadblocks in the trial stage due to the IT and OT divide and budget, staff, and ROI concerns. 

Additional details in the graphic below. Want the full findings? 451 Research will happily sell it to you.

 

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Counterfeit Menace

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IoT Survival Guide

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As demand for location services in all areas of the Internet of Things (IoT) grows, so too has the requirement for precision location. For many applications, especially those that need to scale to cover large areas, providing ”proximity zone” types of location is simply not accurate enough. That means the old way of determining location—primarily using Bluetooth beacons—is no longer sufficient.

Bluetooth beacons have been the go-to solution for determining location for years, but they have three limiting factors:

  • Beacons only work with smartphones, not tags, which limits how they can be used
  • They are able to locate objects in best case within 3-4 meters, which is fine for determining a general location, but is not refined enough to meet the requirements for many of today’s applications
  • Beacons are battery-operated, which impacts their ability to deliver real-time location; frequent transmissions drain the device’s battery, meaning frequent replacements are necessary

The shortcoming of beacons and other location technologies that rely on smartphones has spawned an industry shift to a more network-centric approach, with the intelligence moving to the receiver antenna and a centralized software application, rather than the intelligence residing in a smartphone app. That, in turn, has launched the development of a wide range of active, low-cost Bluetooth Low Energy (BLE) tags with long battery life and possible on-board sensors.

Another shift occurring is a change in how signals from these tags are measured to determine location. The traditional method—using signal strength to estimate location—does not take into consideration how the signal will be impacted by its environment.  While a weak signal could indicate an object is far away from a beacon, it’s also possible a physical object, such as a concrete pillar or wall, is impacting the signal. 

Two new approaches are emerging for BLE angle estimation. The first is based on the signal’s Angle of Arrival (AoA)—the precise direction the device is from the receiver antenna arrays. With AoA, multiple antennas are used within the same devices to measure the signal. This allows the antenna to locate a tag or smartphone with accuracy of 10 to 20 centimeters, not meters.

The second approach considers the signal’s Angle of Departure (AoD). In this approach, the location intelligence is moved back to the mobile devices. The AoD approach works like "indoor GPS," where the fixed infrastructure devices (aka Locators) are only broadcasting and are not aware of the receiving devices, similarly to how a GPS Satellite works. This means the capability to locate an unlimited amount of devices, and no privacy issues. 

As the use cases for indoor location services continue to grow, with every industry from manufacturing and logistics to healthcare and retail, to law enforcement and beyond clamoring for more precision, new approaches beyond Bluetooth beacons need to be considered. The AoA and AoD methodologies are quickly gaining momentum as the next generation of location technology.

Guest post by Antti Kainulainen is CTO & cofounder of Quuppa. Before Quuppa, he was with Nokia Research Center (NRC) during 2005-2012, where he was the lead engineer in several projects related to indoor positioning. He also took part in the standardization work of the Bluetooth Wireless technology. Antti received his M.Sc. degree in technology from Helsinki University of Technology in 2007. He has 16 granted patents and 22 pending patent applications. More at www.quuppa.com

 

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Farm to Fork IoT

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Trapped in the Groundhog Loop

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New Developments in IoT Connectivity

 

Guest post by Peter A. Liss.

Connectivity is wrongly thought of as a commodity, including in the IoT context. This article will give an overview of current developments in IoT Connectivity, and look at their effect on Network Operators, Platform vendors, IoT Solution Providers, and Enterprise & Consumer customers. 

I also cover the likely impact of 5G, Narrowband IoT and programmable SIM cards, and SDN (Software Defined Networks). These new connectivity technologies will bring differentiation, innovation and new revenue from IoT.

OVERVIEW – CONNECTIVITY AND DIFFERENTIATION IN IOT

These new IoT developments include:

1.   Newer networks such Sigfox, LoRA, Narrowband IoT, and soon 5G.

2.   IoT platforms that can manage all types of connectivity.

3.   The growth of eUICC (e-SIMs) or programmable SIMs.

4.   IoT connectivity platforms using SDN (Software Defined Networks).

There are two opposing views about connectivity. On the one extreme, some Vendors pitch that “IoT Connectivity is the foundation of differentiation” (recent Ericsson Webinar). At the other extreme, some Enterprise customers buying these services assume “all IoT connectivity is the same”. 

In my view, the truth is in the middle. On the one hand, IoT hardware such as sensors and IoT applications could drive even bigger differentiation and innovation than the type of IoT connectivity. On the other hand, IoT connectivity should never be viewed as just a commodity that is plug and play.

HOW TO DIFFERENTIATE WITH IOT CONNECTIVITY:

Let’s take a closer look:

1)   There are many different types of Connectivity to choose from (cellular, WiFi, Zigbee, Satellite, and different types of LPWAN (Low Power Wide Area Networks). The criteria for selection include data cost, device cost, data rate/speed, battery life, outdoor and in-building coverage, and latency. Some of the much talked about networks like 5G are not yet available, and Narrowband IoT is in its infancy.

2)   The variety of connectivity offerings are increasing. Even taking a single technology like 4G, the offerings in terms of coverage, cost, roaming, integration effort, and customer service do differ widely.

3)   Costs are declining– the cost per MB has decreased, however, this is not the same as connectivity being a commodity (i.e. indistinct service). On the contrary, with more offerings and price competition, there is a greater need to choose the connectivity provider carefully. Pricing models may differentiate not only on cost per MB, but also with additional charges for VAS, the period charged for (monthly, per annum etc.) or number of connections included, or amount of data included in a packaged price. In the case of LPWA, charging can be per message, and not just per MB.

4)   The IoT Connectivity platform is where some of the disruption is happening. This platform manages the cost of connection, quality of service, SIM and device status. Along with the type of connectivity chosen, hardware (gateways & sensors), and IoT Applications built, the connectivity platform will be a key differentiator to your business case or service launch. 

My scheme below shows the place of the IoT Connectivity Management platform as the foundation of the IoT technology stack. Some differentiation could be achieved at any level in the Stack, but the effort required to offer a total solution will depend greatly on the Connectivity chosen at the bottom of the stack.

WHAT USER CASES WILL NARROWBAND IOT SUPPORT?

Narrowband IoT (NB-IoT) greatly improves network efficiency and spectrum efficiency and can thus support a massive number of new connections. The same is true of the sister technology Cat-M1 in US, which may also play a role in Europe in future. The majority of these new IoT connections will be industrial IoT (IIoT) solutions that require long battery life, and ubiquitous coverage (including remote areas or indoors). These user cases also require competitive pricing models for low bandwidth solutions, since many industrial IoT cases are not data hungry. 

Some examples of Industrial use cases are monitoring of oil and gas pipelines for flow rates and leaks, noting that often there is no external power in inaccessible areas. Warehouses are another industrial user case for tracking goods with pallets equipped with an NB-IoT module. NB-IoT modules have a long service life, require no maintenance and have a link budget gain of 20 decibel compared with a conventional LTE deployment, giving approximately 10x more coverage than a normal base station, thus penetrating deep underground, and into enclosed spaces indoors. 

Consumer examples of NB-IoT are luggage tracking (click for link to Sierra Wireless Case study), air quality monitoring, and children’s communication devices, and parking solutions.

NB-IoT, is a software upgrade to existing cellular Base Stations (or if the Base Station is old, a new circuit board must be inserted). The Core network also needs some upgrading. NB-IoT is reliant on a SIM card in the IoT device/gateway and partly because of the SIM it offers the same security & privacy features expected of cellular networks. LPWA technologies, such as NB-IoT and category M1 (LTE-M), also offer increased network coverage over a wide area, at a low cost, and with very limited energy consumption. In the case of Narrowband IoT, a battery life of over 10 years or more, is promised by Vendors (it remains to be seen - in the field, it might need a larger battery at an extra cost of approximately 20 Euro).

NB-IoT networks are already becoming available, for example, Deutsche Telekom has rolled out its NB-IoT network to approximately 600 towns and cities across Germany since launch in June 2017. According to Telekom, more than 200 companies now trialling the technology already via commercially available test packages. Nationwide rollout in the Netherlands was completed in May 2017 and Deutsche Telekom brought the technology to six further European markets by the end of 2017. Other major operators have similar roll outs for NB-IoT.

As expected, many IoT platforms are now being designed or upgraded to offer Narrowband IoT connectivity management. Cisco already announced in 2018 the availability of NB-IoT on its Jasper Control Center platform.

WHAT WILL 5G BRING TO IOT?

5G is not yet available commercially, and we can expect the first roll-outs in selected countries in 2019, and even then, just city coverage, or home-based 5G. High speed, high reliability and low latency are the main benefits of 5G.  Whilst NB-IoT is targeted specifically at the IoT Market, 5G is targeted at business & consumer users too. Also, worth noting is that the NB-IoT roll-out is ahead of 5G.

Regarding the high bandwidth of 5G, example uses include security cameras and monitoring, computer vision used in Industrial production, connected car user cases (infotainment, autonomous vehicles, and safety), and traffic control in Smart Cities. The increase in speed between 4G and 5G can be as much as 100 times. This makes a big difference to user cases that require uploading and downloading of video-based content faster and in larger volume.  It remains to be seen whether IoT applications will need to use such high data speeds. Perhaps it will be the Augmented or Virtual Reality cases (AR and VR) that utilise this bandwidth.

With 5G there is very high reliability, which is important to support mission critical services in IoT (e.g. medicine, industry, traffic control). However, the real benefit for IoT is likely to be with the low latency of 5G. Low latency allows more of the computer processing or data analysis required by a device (IoT Gateway or Smartphone) to happen in the cloud. With latency of under a millisecond, there is almost no difference that the data is processed in the cloud rather than the device. This has perhaps more implications for the IOT Solution architect, rather than the user.

Indeed, the user cases that depend on 5G’s low latency are still to be proven in practice. For non-IoT user cases (i.e. human interaction), the latency (such as changing of a pixel on a TV, or response time for instant messaging and online Presence) might not be noticed. However, for an M2M or IoT application in theory there is a great need for low latency and a machine might notice the difference in latency when a human does not. For this reason, the low latency is being pushed by the 5G industry as compelling for IoT (but yet to be proved). IoT user cases that are expected to benefit are remote industrial control, and autonomous vehicles, where milliseconds could be critical.

As explained in the discussion of latency, one change with 5G could be more processing in the Cloud, especially with Edge computing being a focal point in the architecture, and this might help reduce 5G IoT device prices. Other Emerging developments that might affect IOT include virtualised RAN (Radio Access Network) and network slicing. Virtualised RAN is intended to offer bandwidth with lower network costs, since by “slicing” the RAN, it is not necessary to utilise the whole core network, but rather allocate a part of it and the associated costs, thus allowing for profitable use cases with 5G.

WHAT ADVANTAGES DOES A PROGRAMMABLE SIM OFFER IN IOT?

Programmable SIM cards (also called eSIMS or eUICC ) are not new. What has changed is the number of service providers that offer them for IoT. Some prominent examples are Stream, EMnify, Cubic Telecom, KORE, Nokia WING and Teleena. Furthermore, the new generation of Smart SIM and associated management platforms are challenging the MNOs in terms of quality of service and signal coverage. They might also challenge MNOs in terms of cost - see the section below on SDN.  

The “e” in eSIM can mean both electronic (it can switch network and be programmed over the air) and embedded (i.e. deep inside machinery, a car or a remote location). In other words, you do not need physical access to the embedded SIM to update it or to change network, service or security settings.

The advantages of an eSIM are that it can be programmed over the air to find the strongest signal, or according to customer network & service preferences. When a data-service failure is detected, the eSIM can switch dynamically to the best network service. Consider a user case such as Smart Metering. The meter is always connected by being programmed not only to select the strongest signal, but also to select the signal that is best for your Meter technology and customer requirements.

In sum, the IoT Service Provider does not own a network, but can still offer the following to its customers:

•Issue own SIM cards, that can be embedded and switch operator over the air.

•Attach to the best or cheapest radio signal (RAN) – automatically

•Billing capabilities, often in real time, for the pricing of new IoT services.

WHAT IS THE IMPACT OF SDN ON IOT?

As explained above, the e-SIM is the first disruptive step to being able to offer an IoT service, without being tied to one specific radio network (RAN). The second step is to bypass the Operator’s core network. This is now possible with some Service Providers using Software Defined Networks (SDN) and NFV (Network Feature Virtualisation). They have built their own virtualised core network that is cloud hosted. EMnify is one example that can offer the following advantages:

•Low cost, because designed for IoT, and using proprietary technology (therefore no licencing costs)

•Auto-configuration and scaling. Because it is Cloud Based the service is truly elastic (i.e. can be quickly and simply expanded to meet customer demand for increased data volume, or larger number of SIM cards)

•Pay-as-you-grow pricing

•Flexible and Real time billing that is accessible online

•Have own numbering resources (IMSI, IPv6, MSISDN)

•Manage your own virtual mobile IoT network including Elastic Packet Core, Subscriber Management, OSS/BSS, Management Portals and open APIs. 

•A private and secure device cloud and implement own security policies (such as own VPN – virtual private network - in the core network in the cloud).

The “Gorilla” MNO (e.g. Telekom, Verizon, Vodafone etc) is reduced to providing only the radio network, and with the eSIM you can actually switch networks. To be clear, you are not reliant on the operator for the core network at all, and you have a choice of radio network. In sum, the advantage is that such a virtual network in the Cloud allows IoT user cases that have lower revenues, because the IoT platform is designed for lower connectivity costs.

 

CONCLUSION – DISRUPTION IN THE IOT CONNECTIVITY MARKET

I have built the case that “boring” connectivity is going to be disruptive for IoT, and it will generate growth. In sum, this is because many IoT business models require lower costs for the lower “micro” or “mini” ARPU/revenue that they generate. Secondly, these new network technologies bring improved speed, latency, battery life, and coverage. Thirdly, new technologies like eSIM and SDN, give the customer choice and independence from the MNO.

Enterprise customers will need to get more knowledgeable about the types of connectivity on offer, and the pros and cons, and costs of each technology. Disruption in the market is starting, due to many new offerings from MNO, and MVNOs that are IOT focussed. 

Price declines for NB-IoT and 5G enabled devices will also be business drivers. Many connectivity platforms will struggle to distinguish themselves, but can do so, for example by focussing on particular Verticals, or a specific geographical focus, or own Cloud-based packet core. Enterprise customers need to get the balance between a price that enables the business case, but also choosing connectivity that provides the best service level. 

LPWA technologies such as Narrow-Band promise to open-up new business models due to lower device and connectivity costs better coverage and longer battery life. NB-IoT is still in its infancy and these benefits like lower device costs are still to be proven.  Importantly, the connectivity costs of NB-IoT (as well as module/device costs) will need to be low enough to support the proposed new business cases like parking meters, water meters, luggage tracking, pipe monitoring, and tracking goods in warehouses. 

5G for IoT will enable data hungry business models, insure against capacity constraints, and provide wider coverage and almost no latency. Since 5G roll-out is still in the future, it remains to be seen if (or when) the required network density (using such small cells) is enough to provide the wider coverage and higher data rates promised. Almost zero latency is likely to be the most interesting feature of 5G for the IoT World, especially for critical applications like autonomous driving and industrial control.

Big data, Analytics and Application Enablement Platforms/AEP might sound more exciting and promising for innovation and differentiation in IoT. They sound more compelling than a connectivity management platform and new types of connectivity. However, Connectivity is still the foundation of the IoT business case. It is not a commodity. In particular, Narrow-Band IoT, eSIM and SDN will drive new growth in IoT, together with the imminent roll-out of 5G.

Copyright: Peter A. Liss, an independent and commercially focussed IoT expert, based in Germany, who is also available for freelance consulting work.

This post originally appeared here.

Cover photo by Federico Beccari on Unsplash

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IIoT Use Cases, Puzzles and AI

 

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Drones, Cloud and an Urban Future

 

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Is it Time to Adopt eUICC?

 

Are we ready for an IoT paradigm shift? Are security needs, flexibility to address regional and regulatory challenges, and international globalization enough to encourage the IoT industry to accept embedded SIMs (eUICC), along with subscription management, to achieve reduced logistical and manufacturing costs with a single stock-keeping unit with a unique identification number (SKU)?

Shifting to a new technology always is a slow process if for no other reason but caution. The technology standardization and go-to-market approaches are yet evolving in parallel for interoperability. This requires preparing for the bigger picture by taking small steps with calculated risks, sincere effort, and commitment from multiple players.

Moving forward with subscription management

We now are in the third version of GSMA Removable SIMs standards. In the consumer market of smartphones/tablets, it even can be said that the industry now is moving toward the early adopter phase of the product life cycle. The IoT market still is in the innovator phase and needs more commitment from different actors across the industry. GSMA specifications clearly have defined the processes, systems, and interfaces for remotely managing eUICCs in a secure and standardized way — for downloading, enabling, disabling, and deleting subscriptions using Subscription Management–Secure Routing (SM-SR).

Subscription management has evolved significantly across different arenas, such as standard organizations, SIM suppliers, module vendors, operators, and connectivity platform providers. Now that the vision is understood, and the usefulness of the new platform is clear, it becomes easier for any one player to come out of their comfort zone and succeed in implementing the vision against any challenges that exist. The telematics industry seems to be taking a lead, with other verticals following up close behind.  

With this ongoing adaptation and interoperability, mature applications can be designed to provide flexibility in operator selection on the basis of defined criteria and to hand control of the connectivity to users. The manufacturers can take advantage of new programmable SIMs and build generic devices, while providing the flexibility of MNO selection to customers.

Examples of IoT eUICC use cases:

  • Insurance for Life: IoT devices for regulatory monitoring and the security vertical usually have long lifespans, so making use of an eUICC is perfect for these use cases. The use of an embedded SIM gives freedom to OEMs in relation to their mobile network operators (MNO) contracts, in addition to regional regulation or connectivity spectrum changes such as 2G/3G. OEMs who use an eUICC have independence from long-term ties to MNO contracts and changing market conditions. They can opt for new MNO/MVNOs with better coverage simply by replacing the subscription on the SIM remotely, without touching the device. This saves assembly time, field validation, and addresses challenges of reaching remote places, as well as eliminating the related costs of field visits. Thus, the devices that operate in remote and harsh environments have insurance if they adopt eUICC. This provides the device operator flexibility, with increased life expectancy and security, and enables the OEM to remove and update aging standards and technology.
  • Global Product Launch: Using an eUICC provides an option to an OEM to enter global markets with a phased launch of a device. OEMs initially can use any bootstrap MNO profile, with a minimally viable product, to evaluate market interest. Later, on the basis of market validation and product demand, the OEM can switch the profile remotely to a local MNO and then scale up for ROI post-market validation. This approach allows individuals to secure the best service by area, while using local MNO/rates, meeting local regulatory requirements, and avoiding roaming costs as volume increases. This model fits particularly well with expensive heavy machinery, which moves from place to place, such as military equipment, construction vehicles, leased farming machinery, etc. The key advantage of an eUICC is giving the dealer/terminal provider the capability to switch from one MNO to another, without any constraints.
  • Frequent Subscription Changes: In this approach, the user holds greater control and can actively switch from provider to provider and take advantage of region-specific pricing. Applications with high data usage, such as hotspots on a moving vehicle, can take advantage of eUICC flexibility to avoid roaming charges while increasing the availability of cellular networks. By managing subscriptions in near real time, OEMs will be able to lower connectivity costs while maximizing connectivity reliability for users. This use case may take a bit longer to commercialize in comparison to the first two.

Is it that simple?

The key to success in any of these above-mentioned use cases is understanding all the relevant parameters and dependencies, including MNO certification related to device modules, the technical know-how of the subscription management platform, and policy control for security via secure routing. My recommendation for successful migration to the eUICC platform is to assemble technical teams that understand MNO network coverage, the design of an eUICC deployment, and device module capabilities. There is a risk in adopting eUICC, which can be mitigated by overlapping deployment and effective application management with proper monitoring by technical experts, especially in the initial phase. This flexibility comes with increased complexity and, in order to address this, connectivity management providers need to lock arms with application providers, as well as with experts in the device capability field.

Guest post by Pratibha Sharma. This post originally appeared here

Photo credit: Igor Ovsyannykov

 

 

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Keys to Success with Urban 4.0

 

In a recent guest post by Andrew Hamilton, he looked at the future of urbanization and what a holistic approach means in actual urban development. As a follow-up to the story, he offers these key to success.

1) Focus on the city’s main goal or identity

While cities and large developments share many concerns and challenges, each one has a unique mix of issues. Is it concerned about accommodating existing growth or attracting more growth? Is it looking mainly to improve livability, or to make it easier for businesses to operate? Would it like to double down on its existing strengths as a city, or shift the economy in new areas? Some cities and developers find it helpful to focus on a simple theme or vision. London, for example, is investing heavily in making it easier for residents to access, analyze, and exchange data. While any smart urbanization project should lay the foundations for future capabilities in many areas, it’s essential to focus actual investments in a few areas with the greatest consensus and payoff. Pursuing multiple areas will make timely delivery on these already complex projects nearly impossible.

2) Rethink your RFP relationships with vendors

Governments and developers have relied on the RFP-based vendor management process for good reasons, but this structure gets in the way of integrated developments. It’s especially important to start working early with a knowledgeable guide that can work with you for the long term. It’s time to create new negotiating processes that enable Urban 4.0 while still featuring accountability and protecting the public.

3) Focus on transformational improvements

Smart urbanization involves an array of sophisticated technologies that offer big benefits over the status quo. With political and budgetary pressures, it will be tempting to aim at a flashy, short-term gain rather than to invest in capabilities that will pay off much more in the long term. Avoid that fate by setting out a blueprint for the vision that will drive public plans and accountability, without constraining your ability to adjust with evolving technology and city or client needs. Quick wins can help build momentum and support, but should not divert you from achieving even more valuable results.

4) Reassess the citywide approach

With the rise of supercities, governments and developers will want to break the urbanization challenge into pockets of about five square kilometers. That’s large enough to deliver all the smart services—energy, education, micromobility, food, recreation, entertainment, and job creation—within a contained and sustainable ecosystem. In especially dense areas, a large single mixed-use development could serve as an urban pocket. These highly integrated neighborhoods, combining work and residence, can improve transportation and overall livability while reducing the cost of living. They are also commercially attractive to private developers.

 Photo credit: Roberto Saltori

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Preparing for Urban 4.0

 

Guest post by Andrew Hamilton

It’s time for a better paradigm of urbanization. Conventional models, while still solid, are no longer up to the heightened challenges of the present. Exponentially improving technologies for the Internet of Things (IoT) and artificial intelligence are enabling urban developments with much higher levels of efficiency and flexibility to conserve resources, promote security, and boost the quality of life.

            The key development is not the technologies themselves, but their integration around a holistic view of urbanization that enables a series of smart services. Instead of focusing on single services, or specific buildings or highways, leading organizations around the world are using IoT and analytics to optimize infrastructure generally and evolve with changing needs. While getting there will take a great deal of investment and expertise, the result will be places where residents thrive in unexpected ways in their personalized urban developments. 

The Future of Urbanization

To understand the business opportunity, it’s helpful to break urbanization down into three phases. Over most of history, Urban 1.0, this happened with little general direction or coordination. People gradually moved into towns and cities, and new and old residents adjusted largely on their own. Urban 2.0 started in the early 20th century, as reformers launched ambitious city plans to improve the cityscape and its governance.

            Urban 3.0 came at the beginning of the 21st century, as planners applied computers, automation, and systems thinking to improve efficiency and coordination. This smart urbanization brought many advances. But its focus on solutions for a specific area (a building, street, or factory), or sector (transportation, energy, waste), led to static efforts that failed to realize many potential gains. To take a simple example, buildings got sensors that turned off lights when not in use. But those sensors failed to learn from all the data they were seeing, and they didn’t connect to air-conditioning and other systems.

            It’s time to go to the next level—Urban 4.0. The Internet of Things enables residents and planners to monitor and adjust much of the urban infrastructure. These sensors generate a flood of data, but with machine learning, cloud communication, and advanced analytics, we can optimize planning and operations across multiple components. Buildings can have smart controls that adjust lighting and HVAC according to expected usage, and that predict and indicate when equipment needs to be repaired, replaced, upgraded, or modified altogether. We can also monitor energy usage across a portfolio of buildings, and share efficient practices such as overnight battery storage to reduce demand in peak daytime periods.

            Developers and officials can now “future-proof” their designs by calculating citywide dynamics over time. They can look on a city as a living organism, where all the components have to be healthy for residents to thrive.

            Urban 4.0 goes beyond the direct provision of municipal services. It helps companies take advantage of telecommunications to improve the quality of life. Residents can choose to provide data on their wants and needs, along with their geo-location. Businesses granted access to this information can serve urbanites more efficiently and boost their margins. While these offerings, at least in theory, will eventually be made available everywhere, they’ll initially concentrate in large, mixed-use urban developments to gain scale economies. That’s because many of the large developers are better funded than cities, and eager to distinguish themselves in the marketplace. Thanks to IoT and AI, their developments will make full use of ubiquitous connections.

            While technology is pulling the world to Urban 4.0, serious social and environmental challenges are pushing. Developing countries are in the midst of an urbanization wave the world has never seen, both in scale and rapidity. China alone expects 200 million new city residents in the next 10 years, or 15% of its population, and other Asian countries are similarly shifting. We’re seeing the emergence of supercities, such as the agglomeration around Shanghai, which could exceed 100 million residents by 2050. That’s when 70% of the world’s population is expected to be urban, up from 54% today. Such a massive concentration could overwhelm those societies.[1]

            Even developed countries, many of which have little absolute population growth, are still seeing a continual move to metropolitan areas. City centers are attracting residents, reversing decades of suburban sprawl. Despite early predictions that the internet would encourage people to live and work anywhere, they’re voting with their feet and concentrating in urban clusters. Those same cities, often suffering from decades of underinvestment, are now struggling to handle the newcomers and their high expectations for services.

            Besides the usual difficulties of serving people unaccustomed to urban ways, cities face heightened environmental constraints. Unchecked growth in previous decades has left many areas choking on traffic and smog. Managing water and waste is a challenge in many developing countries and even some developed ones. Climate change has added to the urgency to reduce emissions from vehicles and factories.

            Cities will increasingly compete with one another for high-value investment and trade. The winners will be those that combine efficient services with a good quality of life, enabled by integrated technology. 

Enabling the Transformation

Government officials, developers, and their suppliers around the world are increasingly interested in this integrated transformation. They’re eager for new approaches that take optimization to a new level. The trouble is, most cities are focused on short-term fixing and maintaining legacy infrastructure. They’re reluctant to commit to new systems, especially since those emerging IoT and AI technologies are still in flux. Rather than fancy technological solutions, they want to lay the foundation for new possibilities that can be built gradually and evolve with the changing city.

            Fortunately, the marketplace is similarly evolving to help make that possible. Instead of transactional relationships around one-off projects, some vendors are now willing to work and plan with cities and developers as long-term partners. Instead of the conventional vendor relationship, these providers are taking on some of the risk and responsibility for improvements. This is especially true for large mixed-use developments within cities.

            Rather than implement point solutions, they’re signing on for 10- to 15-year journeys with developers, suppliers, and officials.  They’re learning from one another and residents along the way. And because the vendor expects to be involved over the long haul, its teams can take the wider perspective to encompass multiple systems in a building or multiple components in a city. This long-term perspective is also essential for combating the inherent uncertainty of such complex developments.

            Another innovation is “smart infrastructure as a service,” where the client owns the asset but the vendor builds and operates it, and simply charges the city or private client for usage. Here, the vendor takes on most of the financing and risk, and works with the user to provide continued satisfaction and development. Both of these steps can go a long way to realizing ambitious city dreams.

            These partnership-oriented approaches, however, fit poorly with established vendor-management practices, which tend to focus on RFPs for projects limited to a single product or service. Developers will need to adjust their mindset, at least for the more ambitious integrated developments, for both financial and operational reasons.

            To fully realize these possibilities, it’s not enough for city governments and private developers to evolve toward this more integrated, partnership-based approach. Vendors must as well, and move beyond specific areas, such as design, IT, or mechanical. To make integration work, vendors must be able to speak the language of architects, construction contractors, and engineers. They have to make the business and the technical case for the project at the same time, with the help of an ecosystem of industry partners.

Integration in the Real World

What does this holistic approach mean in actual urban development? For example, the island city of Maui, Hawaii, is rethinking its energy infrastructure. Most electricity comes from expensive imported fossil fuels. Municipal officials wanted to build a few large solar power plants, to take advantage of the abundant sunshine. Then they expanded their view and considered transportation dynamics. They realized that most vehicles in the future would run on electricity, not oil. Instead of centralizing electrical production, it would be more efficient to locate it where people would likely charge their cars. With this holistic perspective, Maui officials are shifting their energy investments and licensing. They’re looking for help from sensors that can track evolving patterns of consumption. By preparing the island for charging stations, they’ll reduce not just oil imports but also air pollution.

Mixed-use urban projects are a major opportunity for businesses, especially in the burgeoning cities of Asia. These projects range from single buildings to clusters

of towers with millions of square meters of floor space. Despite those projects’ enormous scale, the owners are working to integrate smart services in energy, water, telecommunications, predictive maintenance, video analytics, security, traffic, and parking. Everything will run on a single IoT-driven platform and command center—even projects that include office, retail, hospitality, and residential areas. Embedded sensors and analytics capabilities will enable property managers to continually adjust and optimize building operations and the ongoing resident experience. Expected to open in 2021 and to serve 60,000 people daily, it will be a demonstration site for existing sites as well as greenfield applications. (Hitachi Consulting is assisting on the project.) The developers expect to deploy many of these smart services to existing properties throughout their international portfolio.

            Southeastern Australia is another case in point. Sydney and Melbourne are two of the most expensive cities in the world. In response, people are sprawling out to faraway suburbs, which damage both the environment and quality of life. To address these issues, private enterprise in partnership with government is considering the creation of eight new densely settled cities between these two metropolises, which are about nine hours apart by car. High-speed rail would connect the eight cities with the two endpoints, so each one would be no more than an hour’s ride from either Sydney or Melbourne. The satellite cities would have all of the amenities and efficiencies of urban life, while reducing energy use and aggravation and preserving the environment.

The worldwide pressures for urbanization are powerful, and the opportunities from smart, integrated infrastructure are compelling. Over time, we expect holistic urban development to become the norm, facilitated by cities, developers, and vendors taking the long view.  Companies that stay with the old approach to urbanization will lose out.

About Andrew Hamilton

  • Andrew Hamilton is a Global Client Partner for Hitachi Consulting. He is responsible for Key Clients focusing on social innovation projects, runs Social Innovation Business for APAC and provides on the ground project support and industry expertise.
  • He has run projects in Asia Pacific, Middle East and Europe in the infrastructure, telecom, media and power sectors.
  • Andrew has over 30 years of project experience with 23 years of experience with infrastructure projects, vendors and management consulting firms in SEA, India and China. Experience includes very large international infrastructure program management in Asia and the Middle East, healthcare, supply chain, pharma, national infrastructure recreation, national distribution networks, mobile phone company launch programs and contract negotiations, Sarbanes Oxley Act (SOX), manufacturing, large IT deployments, and international logistics programs with APEC.

[1] “Urbanization and the Mass Movement of Peoples to Cities,” by Bret Boyd, Grayline, Jan. 17, 2017. https://graylinegroup.com/urbanization-catalyst-overview/

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9 Articles on IoT and Blockchain

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