There are a number of ways in which IoT is revolutionising water management. These efficient new solutions both current and in the making have come at the right time given the current challenges that the global water industry now faces due to an increasing population, eco-system pollution, and water rights amongst many more.

In the current climate, making sure that water usage is being properly regulated, and consumed efficiently is critical, says freelance writer Jocelyn Brown. This is all the more pressing considering the current estimate that 70% of the world’s population will be living in cities by 2030, and almost half will experience water scarcity issues.

Fortunately, however, this has come at a time of rapid growth in the technology industry, with the IoT bringing great new advantages to many industries. This article will look at some of the new technologies available for improving water management, that will help contribute towards tackling these forthcoming global issues.

Harvesting rainwater for toilet flushing

Looking at more sustainable solutions that involve working with nature and recycling old materials is a great way forward where possible. With this in mind, a popular water saving solution idea is to harvest rainwater to use for flushing toilets.

Underground vs. Overground systems

There are two options for a rainwater harvesting system, the most conventional approach is to go for an underground system, however this isn’t always possible as it involves a lot of power, maintenance and a large underground excavation. The other option would be an above ground gravity fed system, which can also double up as garden irrigation system, given that the tank is at the right level above the garden.

There are a few important considerations to take into account however when installing an overground system such as the need to install an air gap to combat atmospheric pollution, taking measures to minimise hydraulic losses, and removal of the flow restrictor in any downstream float valve. An overground system is also not a good idea in areas that are at risk of freezing.

Automated garden irrigation systems

There are some fantastic new smart systems for your garden such as ‘Gardena’, which gives homeowners maximum and streamlined control over their garden through a smart app. Their products include a robotic lawnmower, garden lights, sprinklers and soil moisture trackers.

An upgrade from more conventional systems

The smart moisture sensors are a water saving upgrade over and above conventional systems, as they will only activate when the soil moisture gets below a certain level, whereas their less advanced cousins will water the plans like clockwork regardless.

Beyond this, the smart sensor provides further optimal watering solutions by taking into consideration factors such as the soil type in the garden, the type and amount of plants, as well as their locations. Small water saving solutions such as these mount up and make a huge difference over time.

If you happen to be a fan of water features, having an indoor water fountain is much more economical on water saving than a garden one, not only that, they also make for an impressive and eye-catching display.

Water leak detectors

Flooding in the home is a very common cause of property damage, even for homeowners that don’t live in an area prone to weather induced floods. The fact is, it come from a number of different sources such as a clogged toilet, a broken supply line under the sink, a split hose connected to the washing machine, a burst pipe or a failing water heater.

The damage caused by such incidences, not to mention the water loss, can be significant, so it is important for any homeowner to be prepared for this eventuality. There is now a range of water leak detectors for smart homes that will alert you at the earliest signs of a leak.

Some of the latest models will also alert you to high humidity levels or freezing temperatures that can lead to other problems, and in the event that you are not at home and a leak is detected, many of the newer sensors will shut off the water supply to prevent any imminent damage.

The security of IoT implementations continues to be the leading impediment to deploying IoT initiatives in the construction industry. In addition to a reliance on mobile devices such as smartphones and laptops, the construction industry is increasingly adopting new technologies like IoT to improve productivity, efficiency and safety. IoT sensors are useful because they provide real-time monitoring and data collection, while virtual reality can create simulations of building designs. Additionally, IoT sensors can be used to access data, the causes of physical malfunction of physical infrastructure, building information modeling (BIM), digital twins and geographic information systems (GIS).

Integrated project delivery through IoT technologies opens a world of safety, training and efficiency opportunities, but also increases vulnerabilities of attacks from malicious actors. The characteristics of the construction industry make it a challenging environment to implement ubiquitous technologies like IoT. First, the construction industry’s workforce is fluid; many construction industry employees work in the field — using laptops, smartphones, and tablets — rather than traditional office environments. Second, reliance on subcontractors can present unique challenges, including training. Finally, the completion of any project typically involves dozens of companies the sharing of vast quantities of confidential data including bids, blueprints, employee records and financial information.

Forward-looking construction companies now rely heavily on cloud infrastructure to manage project blueprints and sensitive customer data needed for multi-million-dollar projects across wide geographical areas. As the adoption of IoT technology continues to grow rapidly, security teams have to consider new approaches to detect stealthy insiders and respond to sophisticated threats across a dispersed digital infrastructure. In addition to the worksite challenges faced by construction companies, additional hurdles include the lack of adequately skilled staff, inadequate budgets and change management issues. In particular, top management in the sector underestimates the threats and risks that arise because of IoT deployments. They lack guidance on particulars and scope to enable them to assess threats and manage risk.

The construction sector is impacted by cyber risks that arise from enterprise-system technology and project-specific technology. Enterprise-related risks (IT or OT security) are well understood and include the loss of client data or confidential project information data, intellectual property and sensitive commercial material, employee data, subcontractor and supply chain management data and/or financials and outage or disruption related to critical software, applications, data or networks. IoT security falls under project-specific technology. Project-specific technologies could relate to asset management and control systems, site access, concrete maturity monitoring, structural health monitoring systems or other operating systems.

An Overview of IoT Security

IoT security is the protection of the confidentiality, integrity and availability of an IoT solution or device. IoT security is a journey which starts by making sure the organization has enough knowledge on what devices/solutions to buy, how to perform secure integrations, how to ensure that the solution or device operates smoothly and efficiently at scale and how to enable safe and secure communications. It’s about making sure the IoT device/solution operates as expected, communicates securely and has enough resilience to absorb attacks. Beyond that, good IoT security practices ensure that no rogue devices connect to the IoT infrastructure and prevents the user of a solution/device from doing anything unintended by the designers of the device or owners of the data, whether by accident or malice. IoT security is about making everything work as expected and keeping unauthorized users and authorized users who could be a threat from potentially doing anything that compromises the IoT system.

IoT is the best space to launch an attack. The systems are usually less mature in terms of security than server and PC systems. The remoteness of some of the devices allows for the attackers to be physically present and manipulate hardware at their leisure which would not happen in a secure office setting.

The best approach to IoT security is built around the “before/during/after” approach. Before: prevent system compromise and unauthorized access. During: monitor and detect a breach as quickly as possible. After: quickly assess and minimize damage. IoT security focuses on the following broad areas; device security (the physical destruction or attack on terminal devices such as sensors and RFID tags), data security (data loss or tampering), access management (privacy and confidentiality) and active security (maintenance of control).

Every organization that deploys IoT solutions must have a plan to ensure trust, identity, privacy, protection, safety and security of devices and people. It’s important to recognize that an IoT device or solution is likely to be attacked or compromised at some point in its lifecycle. Leading organizations treat security as a manageable risk to be considered and countered along with all other risks they manage.

IoT Risk Management and Best Practices

The first step in managing cyber risk is to identify sources of potential risk. Construction companies should conduct audits that gauge employee access to and use of critical and sensitive data, including personally identifiable information and proprietary corporate assets. This audit should determine who has access to such information and critical systems and take stock of existing capabilities for monitoring inappropriate system access and potential security events.

Once completed, businesses should develop formal, written policies regarding the use of corporate networks, and ensure that access to sensitive data is restricted only to parties that require it. While IoT security practices are still evolving, a set of best practices is emerging:

1. Security From Start to Finish

Make IoT security inherent in the IoT process from the start. Use hardware that incorporates security features beyond encryption or physically secure critical technologies. Laptops, smartphones, tablets and portable media devices — along with emerging technologies that are often present on construction sites, such as wearable devices — can present significant data security threats if lost, stolen or hacked.

2. Prioritize Security Across Teams

Make security a priority for everybody involved with the organization. Educate, share and discuss IoT security best practices. Stay abreast of developments in IoT security and regularly update employees, partners and vendors on how to identify, avoid and report potentially malicious activity on corporate networks. The most effective way to handle IoT security is to treat it as a journey; be smart and proactive when it comes to IoT risks. Make security a top priority for everybody in the organization as well as outside partners and vendors. Don’t be naive and appreciate that there are many reasons somebody would hack your IoT solution ranging from thrill, political statements, an act of war or terror, expectations of financial gain by stealing data or trade secrets for competitive advantage, hobble you as a competitor, disrupt your business strategy or an employee attempting to exact revenge.

You should reward users who find and report bugs especially defects likely to expose zero-day exploits. The construction industry is heavily decentralized and involves several stakeholders. Without thorough and regular training and buy-in from all personnel, even the most robust cyber risk management plans can be rendered ineffective. Businesses should also implement strong internal controls, including the resetting of passwords every 90 days, multi-factor authentication and randomized default passwords.

3. Monitor and Upgrade Your Infrastructure

Use the most current operating system and libraries with updated firewalls and security patches. Despite the added expense, investing in a robust set of firewalls that require user authentication can be beneficial. Businesses should also institute secure file sharing, advanced email and web filtering and separate WiFi networks for subcontractors, architects and engineers. Use automatic updates to fix and patch bugs and vulnerabilities in field devices.

4. Continually Evaluate Your Vendors’ Vulnerabitilies

Closely monitor third-party risk. Assess the cybersecurity processes of any third parties that access or retain critical data. Seek to build favorable hold harmless agreements into contracts with third-party vendors. Also, establish procedures to evaluate any third-party service providers (if applicable) and, as discussed, review their agreements, limiting as much liability to your company as possible, and assess their cybersecurity processes.

5. Have a Contingency Plan

Develop detailed data breach response plans. Planning can enable an organization to act swiftly, decisively and effectively to minimize damage from a breach and any resulting claims or regulatory actions.

6. Cyber Insurance is a Real Thing

Purchase cyber insurance. A cybersecurity breach is not a matter of if but when. Having insurance coverage against cyberattacks makes business sense. Understand that IoT doesn’t have a security silver bullet. The scope and variety of IoT solutions effectively prevent the emergence of faultless security defense. IoT technology is fluid, the solutions are continually evolving and so too are the threats and attack vectors. IoT solutions are constantly evolving and so should your IoT defense strategy. While cyber insurance policies have historically been most often associated with data and privacy breaches, today’s cyber policies cover the failure of technology and the resulting interruption or loss of revenue.

7. Implement Consistent Authentication Schemes

Be smart and practice good cyber hygiene practices: use secure passwords from password generators and implement multi-factor authentication among other standard security measures. Most security breaches take advantage of well-known vulnerabilities that haven’t been addressed despite ample alerts and most attackers are known to you: employees, contractors or partners.

8. Systems Are Only Secure if Their Security Is End-to-End

Deploy end to end security, from the device to the cloud. Collaborate with partners and vendors as a security strategy. Choose the best partners and build security into your IoT ecosystem from the start e.g. Darktrace, Intertrust, Device Authority, Sectigo, Rubicon Labs, Kudelski Security, Patreon, Ockam and Blackridge Technology are IoT security-focused companies among others. IoT security isn’t something you should tackle alone. Find and collaborate with partners inside and outside your organization. Extend IT security architecture to OT and then augment it with specific security needs, issues and concerns in mind.

9. Learn From the Industry

Go to IoT security conferences, especially events where your peers showcase practical implementations being deployed and share best practices.

10. Use Security Standards Across the Stack

Adopt industry-supported standards everywhere they’re available. Treat proprietary solutions with caution. Be guided by standards bodies and trade associations. E.g. IEEE, ITU Study Group 20, oneM2M Consortium, IIC, Open Connectivity Foundation, Open Fog Consortium, etc. The IoT industry is increasingly coming together to drive common security standards and best practices.

11. Trust Security Veterans

Seek top management support for security initiatives. Make them aware that IoT security is another business-critical challenge they need to consider.

12. Automate Security

Automate and monitor IoT security end to end. Manual efforts cannot keep pace with the volume of events in an IoT ecosystem. Co-create solutions with IT vendors to expand software capabilities to handle IoT security vulnerabilities.

Investment in IoT security has to be commensurate with the likelihood of risk and the potential value of the loss or damage. Different types and levels of vulnerability produce different threats with the potential for different damage. The best way to protect your organization is to start with solid risk identification, assessment and management.

Securing the Future of Construction Industry IoT Solutions

Like all businesses, construction companies must adopt a robust cybersecurity risk management strategy and take the time to understand the exposures associated with IoT deployments. IoT technology can be a source of strength, but any breach or technology interruption that disrupts critical workflows and operations can lead to project delays and substantial losses for the business and other project stakeholders. However, security is not a technology issue. Deploying IoT means your organization is becoming a digital enterprise which needs an integrated, companywide security strategy and risk management plan that involves employees at every level. More emphasis has to be placed on security policies, best practices and tools that autonomously prioritize, contain and defeat attacks based on sound risk management as part of everything the company does.

Separation of systems or staying offline as a security strategy is no longer imaginable and neither is it the most effective approach of operating a modern business. Without seamless interoperability and integration, there is little improvement in business outcomes and hence no reason for IoT.

5G is finally here. This year, we’ve seen the first 5G networks going live for consumers in the US, UK and South Korea. It’s the first generation of cellular network technology designed with IoT applications in mind and will make a big difference in the medium to long-term. But, for anyone planning an IoT project right now, what are 5G’s benefits – and is it truly a viable option?

The Advantages of 5G for IoT

It’s worth noting that some of the big advantages of 5G for consumer applications – the higher connection speeds and greater capacity – aren’t of much relevance for IoT, which typically uses a large number of devices, each sending a small amount of data. The extra capacity could theoretically be a boon to IoT because it allows for a much greater density of devices within a region, but in truth, it’s very rare to find a use case today where the density is too high for existing networks.

The biggest gain lies in its lower power usage. When we say 5G was built with the IoT in mind, this is what we mean. Previous cellular technology was designed on the assumption that it would be used predominantly by mobile phones with batteries which are charged once a day, and each generation has consumed more power than the last. But 5G is much better optimized for devices sending small amounts of data, reducing the overhead of signalling and payload for any particular bit of data.

The benefits of lower power consumption – either smaller batteries or longer battery life – are huge for IoT and connected devices. Smaller devices allow for greater flexibility in how an IoT solution is deployed, while extended life means devices can be left in the field for longer without requiring costly maintenance.

Alternatives to 5G

However, while 5G has now started to roll out, it’s unlikely to be ready for most IoT use cases today. The networks are still geographically limited, and you also have to consider the availability of 5G-compatible devices and all of the systems integration steps that come along with that.

In truth, waiting for 5G could mean waiting for a significant time. And there are other solutions available right now that can solve most of the same IoT problems.

The most notable is LoRa, a low-power wide-area network (LPWAN) technology based on an unlicensed public spectrum which was first developed in 2009 but has started to see widespread adoption in the past 12-18 months. It’s specifically designed to send very small amounts of data with very low overhead.

There are limitations, of course. A LoRa module gives around 10 kilometres of coverage in open space, which confines it to use cases with static devices operating in a fixed area. Public LoRa networks also exist, but these only cover major urban areas unlike cellular networks, where a device can reliably connect in almost any city on earth.

Whether it’s the right technology depends on the specific requirements of your use case, including location, bandwidth and security. Alternatively, your needs may be better served by using current cellular technology and accepting larger batteries in the short term or by some combination of technologies.

The vast majority of IoT applications are viable on currently available technology. Implement it correctly, and you’ll be ready to transition to 5G once its coverage is more ubiquitous and hardware is more affordable.

To learn more about 5G and other IoT connectivity options that can interconnect everyone, everything, everywhere, read “Managing IoT Connectivity for Tomorrow: Growing your connected device business” and join the SAP Digital Interconnect Community.

There are several options for developing a message broker with full duplex functionalities and various supporting features. Some of these options are the use of a raw TCP socket, a raw UDP socket, AMQP and CoAP. Most of these alternatives have more limitations and complications than benefits, especially when compared to MQTT. This is where MQTT becomes the most appropriate, efficient and convenient choice, especially when building our own Internet of Things platform.

Remember that all of these protocols can coexist, and we could deploy them on the same cloud instance, if necessary. This means that, in the future, if you decide to use AMQP as well as MQTT, it’s possible to integrate some or all of them. More importantly, we can link these channels with an additional plugin program so that there’s a seamless communication from an application’s and device’s perspective.

Using an MQTT Broker

Fundamentally, MQTT is an asynchronous protocol and thus enables duplex communication with a lightweight burden on systems. It allows systems to run on low bandwidth and low power. Conversely, HTTP and similar protocols require relatively high bandwidth and power and are request-response in nature, which means that the client must always initiate communication.

In places where you want either party (server or client) to initiate communication, MQTT is the best choice. Moreover, if systems need to run on low data consumption, especially on batteries, for a long period, it’s prudent to use MQTT. If the device needs to send or receive data frequently and at random, then MQTT also makes sense because it reduces a significant HTTP overhead.

If bandwidth and power is not a concern, then HTTP may be a better choice. It could also be a better choice when data sending or receiving frequency isn’t high, which can block the resources sooner in the process.

Why and When to Use MQTT For IoT Messaging

In an application where live control or monitoring is required, MQTT is an obvious choice because it provides duplex, two-way communication abilities with the least amount of overhead.

You must be mindful of the fact that the workload of an MQTT-based the system can grow parabolically, which means that for each device added to the MQTT speaking network that has n devices in total, the load on the system becomes n squared n*n. The figure below explains this concept graphically.

MQTT-based platform loads increase by n-squared. For example, let’s assume an extreme scenario where there are two clients in which each subscribes to all possible topics. When a client publishes a message, the broker needs to receive a message and another client needs to receive the message too. This means one message sent could result in two transmissions. The same goes for the other client, making it four messages in total for a two-client system.

For a three-client system, this number becomes nine messages in total, (i.e. three messages per client). Simply having 10 devices connected means that the message broker should be capable of handling 10*10 (i.e. 100 messages, and so forth).

When the number of MQTT clients starts to grow, the load on the message broker, overall system and platform will grow almost exponentially.

Always keep this in mind as you scale any IoT platform that’s based on MQTT in the later stages or add more devices to it.

The data collected by sensors and IoT devices in the smart city have to, somehow, be used. Information can provide insights to spot patterns and trends. If you have enough of it, aka big data, you can get a pretty accurate picture of whatever it is you’re exploring. For example, smart grids, with enough information at hand, can use data to determine peaks and troughs in electricity need and to then adjust output. This optimizes the use of energy, helping in the drive to sustainability.

Decision Making with AI & ML

Optimization decisions can be enhanced using technology such as Machine Learning (ML), which is a subset of Artificial Intelligence (AI). ML takes the data generated by health apps, smart meters or internet-enabled cars, etc., and uses these data to spot patterns and learn how to optimize the given service. For example, NVIDIA has developed smart video which handles big data analytics and applies machine learning to video streams. They’ve partnered with 50 AI city partners to utilize the technology to improve areas such as smart transport. There are expected to be 1 billion of these intelligent cameras by 2020. That’s an awful lot of data generated, analyzed and acted upon. The system will replace human interpretation, replacing it with machine learning algorithms – with an expected improvement in accuracy and speed. This city brain will process a lot of our personal data, including visual data about our movements.

As mentioned above, Machine Learning requires data to spot patterns and trends. The analysis of big data gives city services the information needed to be highly responsive to the needs of its citizens. It also uses these data in services to build more optimized responses to service use, helping to enhance the experience and improve sustainability. One area that’s being explored as suitable for AI and Machine Learning is in the personalization of services. This requires that personal data is collected and aggregated before being used as a profiling tool.

How AI and ML Can Personalize Smart City Services

ML tools that personalize experiences are already in use in marketing, for example. Here they’re used to tailor online sites, displaying products that users are expected to like from their predicted profile. In a smart city, the same type of algorithm can be used for other purposes. For example, a study by three UK universities looked at the application of various ML algorithms for cycling and weather as a means of creating personalized services within a smart city. This was based on the collection, aggregation and analysis of big data. The study concluded:

“[a] combination of ML, IoT and Big Data, offers great potential to developers of smart city technologies and services.”

Importantly, this study was done without the need for data that could directly identify an individual. That isn’t to say that with effort, correlated data, perhaps using GPS from mobile devices, could be used to re-identify individuals. Also, it’s not too big of a leap to imagine that even more tailored personalization, or more accurate results, could be obtained by using directly identifiable information.

One of the other concerns about machine learning and AI is the possibility of default bias built into the very algorithms that are supposed to improve accuracy. If the training set itself is skewed towards a specific expected outcome, then the result will itself be skewed – in fact, the resulting bias may well be amplified. There have been several studies in this area including, “Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints”. This study looked at how training sets contain gender bias; this bias then becomes amplified when used in an AI situation.

Bias and Privacy Concerns Around AI and ML

The use of bias in AI might also amplify privacy concerns. An example of where this type of bias and control has crept in was the use of Microsoft’s ‘Tay’ chatbot which was trained using real-world tweets. The problem arose when people started tweeting racist and misogynist comments to Tay who then played back those sentiments. Similarly, privacy issues could arise from biased training sets. Privacy is about more than the exposure of personal data; privacy is about the exposure of our very being – our beliefs, our views, our political leanings and so on.

Privacy in the smart city is about so much more than revealing your name…

Azure IoT Hub is a managed Internet of Things (IoT) service hosted on the cloud. Brought out by Microsoft’s cloud, this service enables a two-sided conversation between IoT applications and the devices they’re connected to. Recently, Microsoft announced reduced subscription costs for Azure, making it easier for small businesses and large enterprises to adopt IoT technology. Best of all, as customers advance in their IoT journey, they can upgrade their subscriptions to perform more specialized capabilities.

We bring to you some real-world examples of how Azure’s IoT Hub is being used for improved efficiency and business benefits:

1. Thyssenkrupp Elevators

Wanting to get ahead of the competition, Thyssenkrupp Elevators decided to focus on making their elevator cabs much more efficient and reliable, giving customers something they truly need. They did this by leveraging the potential of IoT and Microsoft Azure’s capabilities. Data related to the elevator usage is transferred to the cloud using sensors and software systems. This information is converted to useful business intelligence. Using this information, ThyssenKrupp has been able to make vast improvements in their operations, take pre-emptive measures and make on-time maintenance checks for seamless use through the year.

Here’s a video of Azure at work for Thyssenkrupp elevators.

2. EcoLab’s Water Management System

Here are some interesting facts shared by Ecolab. While individual conservation of wateris a big talking point, it’s important to look at the larger picture. It takes about 55 gallons of water to make the coffee you drink every day, and over 700 gallons of water to make your shirt. Ecolab is on their way to solving this problem by identifying ways to produce everyday items using much less water. Ecolab is using Microsoft’s cloud services to bring much-needed insights for their water management solution. Together, they have devised a solution that addresses the problem on a much larger scale and with much deeper impact. Microsoft’s solution helps convert customers in two ways: firstly, by gathering data related to the wastage of water, and secondly, by providing alternatives to factory processes that will make more business sense.

Watch this video made by EcoLab.

3. Oil and Gas Supply Chain Management by Rockwell Automation

It takes numerous machines, transport systems, and logistics teams who work seamlessly together in order to provide a constant supply of petroleum to those in need. Each of these processes is elaborate and requires the usage of expensive capital assets. Any glitch in the supply chain will lead to huge losses. Identifying this market gap, Rockwell Automation is using the capabilities of IoT to build new forms of intelligence and transform the petroleum supply chain process. Rockwell Automation has added sensors throughout the system in order to evaluate health and wellness in real-time. From collecting fuel from oil wells to smart gas pumps, Rockwell Automation is ensuring safety, automation, and control for the entire supply chain.

4. Johnson Control’s Greener Buildings

As temperatures rise and pollution increases, there’s an increased need to regulate air quality in apartments and housing complexes. Johnson Controls is one of the leading companies in the modern building automation and sustainability segment. As data points, sensors, and information grew, Johnson Controls decided to use the Azure IoT suite to manage their data sets. This was the best alternative to reduce costs and to improve performance, security, and core data infrastructure. Moving to IoT has helped building managers maximize operational efficiency and minimize expenses and energy costs, ensuring a more sustainable environment.

Why is 5G one of the most anxiously awaited technologies in recent memory, and why is it so geopolitically consequential? Because 5G has the potential to change the world.

Between 2018 and 2025, operators and investors will bet about $1 trillion globally on 5G becoming the de-facto wireless communication standard worldwide. This bet is certainly a safe one for multiple reasons, and many of them have to do with the changes that 5G heralds for the Internet of Things.

Here are six ways 5G will change the IoT for the better:

1. Far Easier Setup

The promised 100-fold increases in speed — although considerable — won’t be the only obvious way 5G improves current-generation protocols.

You can think of 5G as a kind of next-generation Wi-Fi. You’re used to using a central router in your home or workplace that sends out radio waves to any devices in the vicinity so that they can use Wi-Fi to connect to the internet. Desktops, laptops, telephones, smart home devices, watches, bathroom scales, refrigerators and all our other internet-connected items currently use these routers to function.

Instead, 5G connectivity will let each device connect wirelessly, individually and directly to your internet service provider. We’ll want to use routers for a while yet as carriers further develop our 5G infrastructure and electronics companies make devices that can maintain connectivity while using little power.

But in a few years, households and businesses will be able to design and roll out complete IoT installations in far less time than before, thanks to direct connectivity.

2. New Business Models

According to Nokia, one of the expected outcomes of wider 5G adoption is the promise of new business models and new ways to deliver service to wireless customers for all of their IoT devices — business locations included.

“Network slicing,” according to Nokia, will bring opportunities that weren’t possible with 4G or earlier technologies. Network slicing involves using the same underlying infrastructure for all customers. However, developers would create highly differentiated and personalized QoS (Quality of Service) tiers and packages of features for different customer types.

In other words, 5G will do away with one-size-fits-all packages for business customers with many types of devices to bring online.

Nokia predicts network slicing could improve operating margins for service providers by 5 percent, and as many as 15 percent of current internet subscribers would be interested in “premium” services. The speed and flexibility of 5G will deliver on that desire.

3. Help Smart Cities Come of Age

Cities have always been our centers of socialization and economic and technological progress. According to the United Nations, 68 percent of the world’s population will live in urban areas by 2050, further cementing the importance of these steel and concrete monuments to the human spirit.

Economists don’t always agree on the best way of growing these economies for the good of Main Street and Wall Street alike. But, one popular argument recommends investing in our infrastructure, our cities and efficient living for all.

About 75 percent of America’s GDP flows from its 100 biggest metropolitan areas, according to the Brookings Institute.

Smart cities are a smart idea, and 5G will help the concept come of age. To create these cities, workers will:

• Use sensors and big data to design towns from the ground up for more efficient vehicle and foot traffic.
• Use wireless technology to help cars communicate with one another and civic infrastructure.
• Provide numerous other ways for businesses and citizens to receive or distribute goods and information or travel from place to place using 5G technology.

Cities everywhere can begin achieving far higher economic competitiveness and inclusiveness by making investments in this technology. The implementation of 5G will facilitate even smoother and more capable networks in cities and will help bring technologies like autonomous vehicles into wider usage.

4. Improve Agricultural Management

Big concepts like the Internet of Things and artificial intelligence seemed to blossom into fully realized products in a few short years.

Microsoft, for example, regularly runs commercials touting the power of their artificial intelligence in helping farmers predict and maximize crop yields and minimize the use of water, pesticides and fertilizers.

This moment is hugely important for such innovations. However, AI is just one piece of the puzzle. IoT is the mechanism acting as the eyes and ears while funneling huge quantities of useful data to environmental sensors and connected farming equipment.

Given that the world’s population will reach 9.6 billion by 2050, it makes sense to invest in IoT now. Then, we can begin reaping insights into soil and environment health and how best to use our resources.

5. Make Resource Management More Effective

Agricultural concerns are only the beginning when it comes to 5G and taking huge leaps in connectivity and functionality. Companies that wish to engage in resource and facility management using IoT will find sensors more cost-effective than ever. They can add these sensors to nearly everything, from material handling and manufacturing equipment to the vehicles moving raw materials between facilities.

The means fully connecting our supply chains will be possible with 5G. Data will be able to flow much more freely between business partners and within organizations.

6. Connecting Underserved Communities

Consumers and companies alike will benefit from 5G technology, and health care delivery is a prime example. Although a substantial portion of the population lives in city centers, outlying communities and rural areas around the world frequently suffer from a lack of access to infrastructure and services — medicine included.

Telemedicine will become a far more viable tool in hospitals and private practices with the power of 5G. Health wearables have demonstrated effectiveness in helping flag health issues in at-risk populations and improving patient outcomes in various ways.

Smoother, no-setup connectivity with 5G could bring even more meaningful functionality to patients and their doctors. For example, 5G could help important data — which could signal future health issues — change hands more quickly.

Having reliable, high-speed wireless internet more widely available will improve the quality of other telemedicine services too, including patient-nurse and patient-doctor video conferences.

Telemedicine reduces unnecessary emergency room visits by almost 7 percent, which is critical for people who live beyond city centers and those who don’t find travel easy or convenient.

5G’s Contributions Set to Continue

In an abundance of ways, 5G is set to bring IoT into the consumer and business mainstream. From there, we’re only beginning to understand its full implications and opportunities.

In a recent manufacturing industry insights survey on artificial intelligence (AI), 44 percent of respondents from the automotive and manufacturing sectors classified AI as “highly important” to the manufacturing function in the next five years, while almost half—49 percent—said it was “absolutely critical to success.”

Critical sounds impressive. Yet, in many cases, AI is hard to comprehend for manufacturers, as the technology industry has painted it with such a wide brush that few actually understand how it becomes instantiated—beyond some omnipotent source delivering better business results.

Manufacturers may actually view AI as highly complex and expensive, requiring end-to-end systems throughout their whole company to work properly, and this translates to a costly overhaul of their entire IT/OT operation. The reality is, AI is much more focused and achievable. AI can work on factory floors with minimal construction and get connected to machines via the Industrial Internet of Things (IIoT).

The first thing OEMs need to understand when it comes to implementations of AI is the type of use case to zero in on. The majority of edge machines on the manufacturing floor are being retooled to send data through wireless sensors as part of IoT. That data then feeds into software suites for “crunching.” The data feeding process becomes an ongoing one to create an ever-expanding web of data. All this data can be stored in the cloud to harvest insights, making AI-driven models possible.

Here are three use cases that can help erase doubts manufacturers have about the power of AI:

1. Machine Uptime

A consumer goods packaging lines runs 24×7, producing millions of cartons of varied sizes to package differing consumer products. It is crucial to keep producing them without any breakdown or any quality issues. Speed and quality are of highest importance. Manual monitoring is error-prone, costly and inefficient.

Data gathered through an IIoT system provides 24/7 real-time insight about production-line throughput​ ​and ​equipment ​failure ​through ​tailored ​visualization​ ​and​​ alerts. (AI can eventually help you make sense of the troves of data you’ll gather.) This data is processed on an edge gateway for quick identification of anomalies and for sending instant alerts. The larger data is aggregated in a cloud-based IoT platform for further predictive analytics and defined behavior- and rules-based models. The system would provide a custom dashboard and reports with machine idle time, breakdown reason codes, and overall OEE data. This way, management is better equipped to plan the operations to avoid machine idle time and to apply predictive maintenance.

2. Cost Optimization

A US-based sensor manufacturer, SpectraSymbol, has been producing one of the best linear sensors and potentiometers in the industry, addressing the energy market. As a process, across remote oil wells, when oil and water are being pumped into tanks, the level of oil and water needs to be measured. Concerning this oil-drilling operation, the company had an express need for continued cost optimization by leveraging IIoT data to more economically extend the useful lives of marginal oil wells, aka “stripper wells.” Given the oil production volumes are not high, the greatest issue is that the wells don’t produce enough oil to be worth uniform investments in data sensors, and the cost model had to be reduced for them. The wells are also remotely located, adding to the cost and time challenges. Installation costs of sensors at these wells are also extremely high, adding 60 percent to the cost. For smaller operations and more remote end-of-life wells, fast ROI was of the essence to justify IoT implementation.

An IIoT software platform for storing and processing all machine data was put into place for SpectaSymbol’s multiple oil wells. It created a “data lake” where pertinent data is stored in the cloud. The data being analyzed with AI-driven machine learning has been the enabler for a business-focused, custom application expressly designed for assessing well performance, and condition monitoring through AI analytics. As a result, specific reports are available to all stakeholders, and stripper wells are optimized for uptime and performance.

3. Improved Predictive Quality

A chemical company, SRF, wanted to improve their productivity and manufacturing operations through IoT-enabled digital transformation. To achieve this, SRF had to connect critical processes in the manufacturing of their packaging films and technical textiles. The objectives were to improve quality by analyzing parameters critical to the manufacturing process, improve their fuel consumption, and implement a reduction in power consumption, in addition to reducing any line breakages. SRF’s plant productivity could be improved by predicting stoppages using condition monitoring. The resulting “data lake” created from input via the manufacturing process was integrated with SRF’s ERP to close the loop on the entire manufacturing value chain.

AI was central to the project, as machine learning techniques were utilized to support a set of flexible, multivariate statistical analysis. Specifically, real-time machine data was used as a feedback loop to more accurately define the optimum settings of the machine to ensure product quality and machine reliability. The result was SRF’s ability to monitor and analyze parameters that are critical to machine health, and to optimize machine downtime by predicting failure before it occurs.

Start with an Attainable Experiment or Pilot

When it comes to thinking about how exactly AI improves manufacturing intelligence, the key is to start with an attainable direction, as presented in the three use cases here. Whether you are looking to achieve machine uptime, to minimize costs, or to increase operational efficiencies, machine learning through cloud-hosted data can have an important role to play.

Studies show that by 2050, two-thirds of the world’s people will be living in cities. With rapid urbanization, the concept of the smart city has become more and more popular.

Smart cities use modern technology to provide services and to solve different kinds of urban problems, such as air pollution, traffic congestion, and safety issues.

“IN SMART CITIES, DIGITAL TECHNOLOGIES TRANSLATE INTO BETTER PUBLIC SERVICES FOR CITIZENS, BETTER USE OF RESOURCES AND LESS IMPACT ON THE ENVIRONMENT.”
European Commission

In addition, smart city projects can definitely help city governments operate more efficiently and improve the quality of life for residents.

Smart city applications improve some key quality-of-life indicators by 10 to 30 percent (McKinsey Global Institute analysis).

Starting a smart city journey might seem scary and complicated, even for governments. If you are aspiring to become a smart city, to reduce costs or to contribute to sustainability and stand out from the other urban areas not only in your country but worldwide, then you can begin implementing several easy short-term projects.

Here are three of the best examples of “first-step” smart city projects that can be completed by the end of 2019.

1. Smart Benches

Sixty-seven percent of today’s global population has a smartphone, which translates to 5.11 billion unique mobile users. The need to always stay connected is more important than ever before, and that’s why transforming public spaces so residents can have richer experiences is what governments should contemplate.

One of the most common problems city residents have when they use public spaces is needing to charge a low-battery mobile device. Another challenge is when there is no free WiFi hotspot in the city when it’s most needed. Installing smart benches that use solar power can solve all the mentioned issues. Smart benches with solar harvesting provide the functionality to the users, and at the same time, the city government can monitor public space usage and foot traffic to continuously improve public spaces.

2. Smart Lighting

According to the World Bank, street lighting energy consumption is an increasingly significant part of cities’ energy use and a growing burden on municipal budgets.

In most urban areas, the street lamps are turned on even if there is no one in the area and thus the electricity is wasted. Smart lamps can reduce extra costs; they automatically detect movement in the streets and adjust brightness accordingly. If there’s no movement in the area, it can be dimmed to the pre-selected level of brightness, for example, 50 percent. That helps to ensure security while reducing extra costs.

Also, smart lamps can provide security through video surveillance with advanced analytics, as well as an emergency call button. In addition, a smart lamp has integrated charging for electric vehicles and e-bikes. Enhancing security and digital services and analyzing public space usage highlights the value of a smart city and brings public support and involvement.

These features can be integrated into existing lamps and poles. Smart lighting projects have the potential to be highly successful, for example, the “Milan LED” project has reduced energy costs by 51.8 percent and overheads by 31 percent. This resulted in a cost savings of 10 million euros in 2015.

3. City Info Kiosks

Oftentimes, city residents and tourists need information about public transport scheduling or navigation. News about local events and weather forecast are important, too. An efficient way to give all the necessary information can be via an info kiosk, a touchscreen computer terminal for public use, that can perform multifunctional services with multimedia applications. Additionally, the info kiosk can provide public WiFi, charges devices or calls emergency services at the push of a button.

Helping locals and tourists to navigate the city effectively is important not only for big cities, but for small urban areas, too. Often governments of Small towns work tirelessly to keep their city environment attractive to locals and reduce the number of people leaving the small city.

The installation of smart benches, smart street lamps, and city info kiosks will positively affect city image and improve the quality of life of residents. In addition, these are the short-term projects that can be deployed during the next 6 months with a relatively small budget. They don’t require hundreds of thousands or millions of euros to get started. Moreover, city governments in European Union countries can get financial resources from EU structural funds.

Why Do Digital Twins Matter?

First, let’s discuss why digital twins are important in the overall landscape of smart building technology. As is the case in other industries, the Internet of Things (IoT) has caused a proliferation of data in massive quantities. The complexity of this ever-growing set of real-time information is compounded by the variety of data types (IT and OT) and by legacy sources of data. In particular, for industries like commercial real estate, the data landscape is even more complex because of the people, workflows, and processes that have varying touchpoints with these systems and data.

Unlike heavy industrial asset-centric businesses, like aviation, oil and gas, or discrete process manufacturing, the data being captured in a built environment encompasses more than just the physical space but the complex interactions of people within space. So, you need more than just the ability to make setpoint changes to an HVAC system; you need to understand how that HVAC system relates to a floor, a zone, and to a person within that space. The outcomes are also more nebulous in built environments. Rather than predictive maintenance on a single finite asset, it’s a living, breathing organization with people coming and going every day. The assets are dynamic. Digital twins are best able to make sense of this dynamic ever-changing environment to give you more control.

What Are the Characteristics of a Digital Twin Enabled Space?

Digital twins can be useful at every stage of the asset lifecycle. From designing and planning, to construction, development and commissioning. Use cases for digital twins today are concentrated in the operations and maintenance phase. Data is abundant, and owner/operators of space are most interested in the ability to remotely control space. However, only having remote control over space is not achieving a truly digital twin enabled built environment.

True digital twin enabled space delivers benefits from insights about how people utilize space and unlocks new opportunities to reduce or avoid costs based on that new insight. Let’s look at an easy example: energy reduction is not only a sustainability goal but an easy lever for cost reduction. How can building managers take cost-reducing load-shed actions across lighting and HVAC systems without interrupting someone’s workday? When a space is digital twin enabled, a building manager would know who would be impacted by a load shed. More powerful than that, the twin can alert the building manager about the optimal time to take action, and eventually automate this process based on learnings that tune the model over time.

While everyone must first start by bringing together their disparate systems to create the building blocks of a digital twin, a space is not truly enabled until ALL the following use cases are unlocked.

Remote Monitoring of Smart/Connected Assets

• Monitor KPIs like the performance of subsystems
• Respond to the real-time state of building operations
• Know when new systems come online during commissioning

Predictability and Control of Remotely Monitored Smart Connected Assets

• Old answers to new questions – find out how things like weather or tenants impact operations
• Take control of assets with bi-directional changes to the building subsystems

Context-Rich Model to Drive Even Deeper Insights

• Context not only into how your asset is operated today but a historical view of its operations
• Genealogy of your asset from design and operation to a potential future state
• Insight into how your asset is utilized by tenants and their interactions with the built environment

A System of Smart Assets to Drive Smarter Business

• Extend the digital twin to include entire portfolios of assets to drive smarter business decision making
• Think of your assets in the context of smart cities to drive deeper interaction between inside and outside worlds

The Technology to Get You There

These complex relationships are difficult to capture in a relational database; you need technology that’s tuned to model complex ontologies and relationships. The ability to model these relationships will unlock new possibilities to better understand your built environment, both in a historical context and when looking to the future.