White PaperIoT: A New Digital Revolution
Behind the scenes at the world’s leading cities and enterprises, a profound revolution — a digital revolution — is underway.
Within the industry, there are three concepts are driving this new paradigm.
Can be defined as the use of technology to radically improve performance or reach of an enterprise. Modern innovations in machine intelligence, big data, and connected networks can help businesses completely rethink the customer experience, operational processes, and business models.
This concept focuses on the end-to-end digitization of physical assets and their integration into digital ecosystems. These developments are poised to fundamentally change individual companies while transforming market dynamics across a whole range of industries. Seamlessly collecting, analyzing and communicating data are fundamental attributes of the gains promised by Industry 4.0.
Internet of Things (IoT):
Proliferation of sensors and ultra-low-cost connectivity, combined with powerful analytics are transforming services and business models across a broad range of industries. By bringing machines and assets into the connected world, IoT provides new ways of monitoring and managing the numerous moving parts that comprise businesses and communities – creating an economic impact of between $2.7 trillion and $6.2 trillion annually by 2025.
Some of the most promising uses are in infrastructure and public-sector services—helping society tackle some of its most significant challenges. For example, the ability to monitor and control power grids, city infrastructure, and water systems can have a considerable impact on energy conservation and greenhouse gas emissions. By using sensors to streamline operations, public-sector functions can become much more productive – leading to a reduction in resources used, increased productivity, and more efficient use of existing resources, or a combination of the three.
However, before these changes can become a reality, businesses need to recognize and tackle the complexity of IoT solutions to ensure secure, scalable, and interoperable deployments.
Having a technology foundation that reliably, efficiently, and quickly integrates physical assets into enterprise processes is going to be a critical challenge for cities and companies wishing to make customers happier, optimize operations, and make better decisions.
Driving quantum leaps in performance.
PWC’s 2016 Industry 4.0 Survey, with over 2,000 participants from nine major industrial sectors and 26 countries, concluded: “digitization will drive quantum leaps in performance.” The survey found that “high levels of cost reduction are expected in every industry sector” and “on average, companies expect to reduce operational costs by 3.6% p.a.” while survey participants “expect additional digital revenues of 2.9% p.a. until 2020.”
Another study conducted by the World Economic Forum (WEF) and Accenture found that “digital initiatives could generate an estimated $100 trillion in economic value over the next decade.”
These studies and others strongly suggest that tremendous economic value are possible by leveraging technologies like IoT, big data, advanced analytics, and machine learning to hyper-personalize customer experiences, reduce operational inefficiencies, and innovate business models.
While the tactical executions are unique to different sectors, the framework for a vast majority remains similar – increasing revenue while decreasing costs. There are numerous examples of public and private organizations reducing costs or generating incremental revenue with digital initiatives:
- Manufacturers that have more in-depth visibility across their supply chains can charge a premium for rapid product delivery or can change product focus more nimbly than their competitors.
- Cities that sense parking and traffic can dynamically change parking rates to meet changing demand, modify traffic patterns based on congestion, and increase retail revenue — all from the intelligent use of real-time and historical parking data.
- Companies that can orient their business around real-time sensing and predictive maintenance often develop the ability to disrupt traditional business models.
Finally, businesses can use the granular information to design and develop new products with digital features to augment their existing portfolios – leading to new revenues and improved operating margins.
The New Competitive Landscape
Regardless of industry vertical, the pressure to transform will only continue to grow.
Government agencies are being driven by increased pressures to reduce costs and deliver a better quality of services. At the same time, governments will be strongly influenced by the open data movement to increase transparency and citizen demands to provide personal data privacy and protections.
Private sector companies are being pressured by their shareholders and their competitors to adopt approaches to business transformation. Whether the drivers are cost-cutting and efficiency, or pressure to increase revenue, the market will reward companies that make use of these new tools to innovate and transform themselves and their industries.
“Efficiency gains of the magnitudes uncovered by these surveys have the potential to change the competitive landscape within in a very short period. If even half of the expectations outlined become realized, some companies might find themselves unable to compete. In an increasingly cost-competitive market, no industrial company can afford to lose out in operational efficiency against their market peers. The next two to three years will be crucial for companies looking to catch up.”
PWC: 2016 Global Industry 4.0 Survey
The Challenges of IoT at Enterprise Scale
Forward-looking businesses are beginning to realize that tremendous value can be harnessed by exploring the increasingly blurred space between the connected world of digital information and the physical world where we live and work.
With IoT pilots and experiments proliferating, even the most established and well-run companies often underestimate the challenges in implementing IoT solutions for business-critical, large-scale, real enterprise scenarios.
Scale of data and integration complexity
Connected devices create volumes of data, which are unprecedented in traditional enterprise systems. It is estimated that the total volume of data generated by the Internet of Things will reach 600 Zettabytes per year by 2020, which is 275 times higher than projected traffic going from data centers to end users/devices (2.2 Zettabytes) and 39 times greater than total projected data center traffic (15.3 Zettabytes).
Understanding data of this size in the context of enterprise transactions and transforming it into actionable information mandates a data storage, integration, and analysis infrastructure that is designed from the ground up to handle these volumes, cut across silos, and produce results within time spans that deliver an advantage to the business.
Fast moving data and decision latency
In addition to being large-scale, device data moves rapidly. Enterprise systems that were traditionally designed to handle thousands of simultaneous user transactions may now have to respond to millions of device events.
To remain efficient, systems must be capable of ingesting data moving at much higher velocities while business processes need to be redesigned for faster decisions and quicker reaction time.
Real world conditions and sensing accuracy
In most applications, the only way to accurately sense a physical event or condition is to use learning algorithms that can be individually tuned to the surroundings of a particular device in a network that may contain thousands of similar programmable devices. To add further complication, environmental conditions may change over time, requiring constant adjustments to maintain accuracy.
Sustained accuracy and reliability is only achievable by enabling the sensing algorithm to learn and evolve with environmental conditions and business context.
Location Specific Power Constraints
Many urban, industrial, and agricultural IoT applications envision devices in areas where providing power can be a challenge. Additionally, power consumption can be a crucial element in the successful implementation of a remote IoT system. Sensors and actuators installed in underground or remote pipelines, inside road beds, inside containers, etc. are all examples of devices that must depend on either battery power or must somehow harvest enough energy from their environment.
In either case, these devices must be designed to be extremely efficient in their use of power. Many of these applications can only be served by low data-rate, low-power edge devices that have been specially engineered to operate in such environments, as communications are often the largest single factor in an edge device’s power consumption.
Similar to power constraints, wired network connectivity is not feasible in many scenarios, requiring IoT solutions to rely on wireless networks that have an extremely low-power footprint. Poorly designed protocols, bloated messages or inefficient encodings can all prove to be difficult engineering hurdles.
Moreover, industrial and urban environments are often affected by radio/electromagnetic noise or physical obstructions. Industrial IoT networks must be designed to adapt to such noisy conditions while providing redundant communication paths without compromising system power efficiency.
Often, the information an IoT application requires cannot be confirmed by just one device. For instance, to detect a blockage in a sewage system, information from multiple sensors must be read collectively.
IoT systems must enable this type of concurrent collaboration between edge devices. Sometimes this communication is direct, over physical channels like radio, at other times it may require coordination at a central server. Direct communication may be instantaneous but can come at a significant power cost. Centralized collaboration may help reduce power consumption and enable cooperation between devices, but may increase latency.
Direct vs. central collaboration can present a range of trade-offs between power consumption, latency, and cost. A modern solution must empower applications that can prioritize any of these factors based on the appropriate business need.
Maintaining Numerous Distributed Devices
Building, installing, and operating a network of connected things with thousands of geographically distributed devices can present unique logistical challenges. Ensuring quality of service requires a system that can precisely track the entire life-cycle of each device from manufacturing to recycling.
- Before installation, such a system must track firmware versions loaded on each device, record unique identifiers, generate encryption keys, and record results of manufacturing quality checks.
- During installation, information such as when a device was installed, which team installed it, the exact install location, configuration, and activation time must all be collected.
- In operation, any significant event, maintenance activity, configuration history, firmware version history, suspicious event, etc. must all be tracked to enable future diagnosis and audits.
Flexibility, Adaptability and Risk in Updates
Adopting the Internet of Things is a strategic investment for any enterprise. It is not enough to only consider short-term needs. IoT deployments must adapt to changing requirements while supporting future connected solutions that have yet to be created.
To facilitate these evolutions, over-the-air firmware updates for remotely deployed devices is a critical, yet highly risky operation, traditionally leaving a system open to device failure and security vulnerabilities. A poor implementation may allow for bad updates that may, in turn, render a device inoperable or unable to communicate, or even render an entire IoT device network unusable—requiring costly repair efforts and potentially lengthy downtime.
To be successful, IoT solutions must enable a safe method of efficiently updating remote devices without leaving the business critically vulnerable.
A 2016 paper by the US Department of Homeland Security (DHS), on IoT device security, states that “Many of the vulnerabilities in IoT could be mitigated through recognized security best practices, but too many products today do not incorporate even basic security measures. There are many contributing factors to this security shortfall. One is that it can be unclear who is responsible for security decisions in a world in which one company may design a device, another supplies component software, another operates the network in which the device is embedded, and another deploys the device.”
While it is essential to enforce established enterprise security practices with strict authentication, careful access management, granular network policies, etc., it is also prudent to avoid ad-hoc piecemeal solutions where there is no well-defined owner of security for the entire loosely integrated stack of technologies.
IoT solutions also present many new security challenges. Mainstream authentication and encryption protocols are far too computationally expensive for most low-power wireless devices. Asymmetric algorithms are often impractical, while symmetric encryption presents complex key distribution and key management challenges.
Further, many IoT devices installed in urban and industrial scenarios are not protected by physical boundaries, leaving them vulnerable to tampering. This makes it hard for such edge devices to guarantee safe storage of keys. These challenges make robust key life-cycle management crucial to ensuring unique keys for every device. Additionally, new approaches to detect tampering and take remedial actions are necessary for sustaining a secure and reliable system.
Technology Landscape Fragmentation
There are many IoT solutions available on the market; however, most vendors provide only a subset of the components required to implement an integrated end-to-end solution.
Some vendors provide only edge devices, others provide just the low-power wireless network, while many others sell “IoT platforms” which, in most cases, are merely the centralized software-only server component with management tools.
Often, system integrators cobble together edge devices, wireless networks, and server-only IoT platforms to build a solution. As noted above, such piecemeal solutions often suffer from security issues and implementation challenges due to the logistics of coordinating multiple partners.
Most businesses now have teams experimenting with IoT, yet very few of those teams have experience with large-scale, geographically distributed IoT deployments. This can result in unexpected costs, risks and delays in real enterprise scale projects.
Digital Enterprises require a new kind of IT foundation, one that enables business systems and processes to reliably sense, infer, and act on the physical world. Progressive organizations recognize that the Internet of Things is strategically critical to achieving cost efficiency and consumer centricity. Large-scale IoT projects are for most companies uncharted territory – presenting a plethora of novel, complex challenges that many existing teams aren’t prepared to undertake.
At iSymplify, we help our clients to navigate the daunting task of integrating IoT technologies with existing business processes and systems. Our team has deep expertise assisting IT teams – offering comprehensive solutions that help our customers move ahead of their competition.
Working in close collaboration with industry-leading partners and experts, we provide templates for success that our clients can quickly adopt and take to market.
Our dedication to client success is a core company value. Delivering proven solutions while being a partner, rather than a vendor, is how we bring value to our customers – helping them to gain a strategic advantage in the marketplace.devices. To add further complication, environmental conditions may change over time, requiring constant adjustments to maintain accuracy.
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2270 Bluestone Dr.
St Charles, MO 63303