Authors: Ivano Ortis

Alessandro Della Monica

Key Contributors:Carlos Arteaga

Eduardo Pelegri-Llopart

TURNING THE INTERNET OF THINGS FROM TECHNOLOGY CHAOS TO BUSINESS FOUNDATION:

A PRACTICAL GUIDE.

January 2016

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Executive SummaryThe Internet of Things will have a profound impact on every industry and promises not just to augment but to completely transform the business, consumer and public ecosystem. Leveraging tens of billions of connected devices (or things) and the associated real-time data flows, companies, institutions and people will achieve unparalleled opportunities through new paradigms.

In the future a symbiotic interaction between the real/physical world, and the digital/virtual world will be the norm: things become context aware as they can sense, communicate, interact, exchange data, information and knowledge leveraging an open ecosystem of interconnected platforms.

Learning from past developments in the communication industry, and considering the complex, open nature of IoT, “actionable interoperability” represents the biggest challenge to ensure success. Considering that there is no single nor a best communication protocol for IoT - now and in the future - the required technology platform will have to cope with multiple communication protocols (interoperability), while ensuring a standard, real-time way to communicate the changes in the state of things to billions of distributed services, devices, users (actionability).

The objective of this White Paper is to provide business and IT executives who already have some familiarity with IoT, with a practical guide on how to execute IoT transformations successfully, what are the key requirements and business case considerations. Emphasis is on the the central role of the IoT platform as the key enabler of both short-term vertical use cases and longer term business ecosystem developments.

Readers will find in this paper a comparison of architectural and deployment options, and our effort has been to clearly link every technology consideration with a business reason and business value. An introduction to an innovative and native IoT platform by AMTECH is also provided.

The key findings of this White Paper are:

• Objective. The ultimate goal of IoT deployments is the creation of an open, orchestrated ecosystem that goes beyond the four walls of the enterprise, to generate smart services across industries that will increase IoT value to all stakeholders, while driving competitive advantage for your company. Think of it as achieving inter-system communications and inter-operation across vertical silos (for example smart energy, smart home, connected vehicles, smart health, legacy systems). This will enable full value chain collaboration and benefits in an open IoT ecosystem.

• Business Models. While initial vertical use cases will support achieving investments’ payback and initial financial benefits, stronger business returns of IoT implementations are driven by Product-as-a-Service business models, where the product becomes a platform to deliver new and recurring business outcomes, enlarging the addressable customer base, gaining a greater intimacy with customers, unlocking innovative and more effective product development models.

• Technology Platform. The foundation of any IoT strategy should be a full-stack IoT platform providing embedded, end-to-end capabilities across all of the following: device communication, device management, integration with enterprise systems and consumer-grade applications leveraging a Domain Application Protocol (DAP) and a Platform as a Service (PaaS); business orchestration, activity monitoring and service management through a semantic action engine; real time, endless data management and analytics thanks to a big data real-time architecture; end-to-end security management.

• Vision. We foresee the following evolutionary paths for IoT: the internet of smart objects - where some things will embed smarter features leading to the development of purpose-specific categories of objects; new algorithms for predictive, context aware interactions; new service discovery agents in highly distributed big data environments; action engines empowered by artificial intelligence and cognitive computing to automate the evolution and optimisation of smart services; development of meshed IoT networks to create activity-based, on-demand peer networks among IoT nodes, empowered by semantic search, discovery, service composition and distributed - yet governed - self-orchestration.

Just as today you can’t consider an application project without considering mobile, in the near future, applications will need to be equally adaptable to IoT. The AMTech Platform provides a unique solution to address the needs of IoT applications that require real-time data.

Eduardo Pelegri-Llopart VP of Technology, Progress

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Agenda

What to look for

The Internet of Things as a Singularity

The platform is the foundation of any IoT strategy

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• Cross industry capabilities

• Open ecosystem

Foundational capabilities for any enterprise across industries. Quick summary of specific industry use cases.

The enablement of a truly open ecosystem beyond the four walls of the enterprise is fundamental to generate smart services that will increase IoT value to all stakeholders.

Approach / How to do it

Path to implementation: How to unlock the IoT paradigm?3

This section supports executives that are defining implementation roadmaps and selecting IoT platforms by comparing available options and approaches with the objective of enabling a rapid, scalable and cost-effective deployment path.

• Architectural approaches

• IoT Platform - Key technology requirements

• AMTech

Vision

Call to action

About the Authors

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A vision for IoT, its long term impact and the active role enterprises can have in the disruptive transformation.

Key actions and recommendations.

Business case options / ROI4

• Beyond traditional elements

• Focus on incremental revenues, new revenue opportunities

• Key pillars for successful business case assessments and ROI opportunities identification

Main considerations to make in order to start right with IoT opportunity investment.

Maximizing IoT ROI will require a focus on “unconventional” or new revenue opportunities.

• IoT paradigm

• Enterprise archetypes

• Essentialfiguresanddata

Disruption at a glance.

Full-stack platform vs. multiple components.

IoT in action.

Market Visionaries, Fast Followers and Late Followers.

Market relevance in a nutshell.

Much has been written on what IoT is and how it will fundamentally transform our world. Why will it be? Essentially because disruptive Internet of Things - enabled businesses, industries and societies, will benefit from:

There are dozens of definitions of the Internet of Things. Since we like to keep all comments on applications and benefits as separate topics, the simplest and clearest we adopt and recommend is the one from Harvard: “IoT is a collection of smart, connected devices or products that, when pieced together well, can yield new functionality, reliability, utilization, and capabilities that were previously not deemed possible”.

It is also interesting to note how developments in different industries and fields over the past few years held to the Internet of Things paradigm, converging concepts and technology: Internet of Everything (IoE), Industrial Internet of Things (IIoT), Forth industrial age, Internet of Objects, Physical Internet, Ubiquitous Computing, Ambient Intelligence, Machine to Machine (M2M), Industrial Internet, Web of Things, Connected Environments, Smart Cities, Pervasive Internet, Connected World, Wireless Sensor Networks, Situated Computing, Future Internet and Physical computing. The essence of the Internet of Things (IoT) is creating new opportunities for companies to gain business insight, improve business process, and differentiate their offerings. Connecting Machines, Sensors, Systems and People brings companies closer to their customers and improves relationships while delivering huge financial opportunities.

• Real time data-driven intelligence from connected things, people and devices giving unprecedented insights into the way our business and ecosystems work

• New revenues and profit stream, laying on innovative “as-a-service” business models

• Improved brand loyalty

• Distributed and flexible operating ecosystem, able to self-optimise, self-configure and self-diagnose its assets

IoT Paradigm - Disruption at a glance

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Electricity changed nearly everything about the way we l ive and work and that scale of transformation is possible with the Internet of Things.

Ian Goldin, Director of Oxford Martin School

The Internet of Things as a Singularity 1

Today companies are asked to decide on how to deal with IoT potential, analyzing carefully the costs associated with the delays in adopting the new paradigm, effectively facing the challenge of driving pilots at speed while building a solid foundation for the future.

In the next sections we will discover the magnitude of the opportunity, what are the key elements to consider and analyze, how to start an IoT journey and, finally, some considerations and guidance on the business cases and ROI calculation.

The Internet of Things can be a game-changer for the world’s economies, accelerating productivity, overcoming infrastructure gaps and driving innovation.

Chris Al len Vein, Chief Innovation Officer for Global ICT

Development, World Bank

The price of sensors and actuators has come down over the past few years, making it cost effective for manufacturers to incorporate them as part of a product design.

Among the hundreds of IoT strategic acquisitions and startups that are arising, Google bought smart thermostat maker, Nest Labs, for $3.2 billion, and Samsung purchased connected home company SmartThings for $200 million.

According to Forbes, The IoT is only going to grow: currently less than 0.1% of all the devices that could be connected to the Internet, are connected to the Internet. According to McKinsey, most of the IoT data collected today are not even used at all or not fully exploited. in several applications, less than 1 percent of the data being generated by sensors is currently used to make decisions, but only for real-time control or anomaly detection.

A great deal of additional value remains to be captured. There’s a tremendous potential and limitless opportunities this brings for business and society.

According to a survey from The Economist, 76% of executives worldwide are already exploring IoT today, 95% of them expect their company to use IoT within the next three years and 63% of executives believes the IoT offers them a competitive advantage and if they don’t implement IoT solutions they will fall behind competition. A fundamental factor for the Internet of Things is that is one of the few technology-enabled transformations ever that is pushed by both consumers and enterprises in a fairly symmetric manner. This further accelerates IoT adoption, pressing society and institutions to follow the pattern and contribute from a policy standpoint.

The Industrial Internet Consortium (IIC) established in March 2014 by GE, Cisco, Intel, AT&T and IBM – now counting on more that 130 member organizations - is indicative of the widespread interest that exists with regard to cross-company cooperation to test smart services in use.

As a matter of fact, we are witnessing an intense dialogue between government, business, the research community, social partners and civil society. Industry clouds - the optimal place for collaboration - are blossoming, together with digital ecosystems (Smart Products Marketplaces, Smart Services, High performing infrastructures).

In 2015, we already have 4.9 billion connected things. What are the predicted trends:

Essential Data & FiguresMarket relevance in a nutshell

• The number of connected devices in 4 years will be between 20B and 40B. Cisco predicts that by 2020, the number of Internet-connected things will reach or even exceed 50 billion

• Already In 2015, over 1.4 billion smart phones have been shipped and by 2020, according to Ericsson (Ericsson Mobility Report, November 2015) we will have a staggering 6.1 billion smartphone users

• According to Machina Research, global M2M market to grow to 27B devices, generating 1,6 Trillion $ by 2024

• In 2015, global market for wearable devices has grown 223%

• According to Gartner, by 2020 a Quarter Billion Connected Vehicles Will Enable New In-Vehicle Services and Automated Driving Capabilities

• According to Acquity Group, mass consumer adoption of connected technology is expected within the next five years

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“The biggest challenge IoT faces is the enablement of seamless interoperability between each connection. Addressing this challenge is essential to unlocking the full potential of IoT”. (IoT Survey report, Progress 2015) Simplifying is key to succeed and choosing a performing platform is critical to answer the challenges every corporation faces when building a connected device strategy, from capturing sensor data in the field, to discovering and provisioning devices, to enabling and securing network connectivity, to providing developers with the tools to integrate APIs into the fabric of complex apps, to giving business stakeholders the tools to process and analyze and monetize the captured data.

Other examples with hundreds of leading members are the Open Internet Consortium, the AllSeen Alliance, the Thread Group and many others. They are coordinating vast ecosystem initiatives to connect and integrate objects with people, processes and data using common architectures, interoperability and open standards. This all is creating the basis for the widespread acceptance and the birth of a global ecosystem. So, whatever the angle, the opportunity is huge and hectic activities show that we are already crossing the chasm.

Data are current or projected by 2017,2018 or 2020.

FIG.1 A COMPLEX ECOSYSTEM

Forrester believes that “the IoT trend is about to enter a second stage in its development that will focus on software application platforms that provide prebuilt connectivity, security, management, and analytics capabilities…” and again “...the IoT focus shifts away from devices and networks toward platforms and applications...”.

Forrester, Predictions 2015: Software Platforms Drive Internet-Of-Things Adoption, How The Connected World Will Advance, November 13, 2014.

Everything should be made as simple as possible, but not simpler.

Albert Einstein

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This section Illustrates some key considerations on the behaviour of different type of organization when dealing with a new technology adoption like IoT and some take-aways from the authors.

Enterprises’ identities come often from far and not all companies are requested to lead the scene; nevertheless, when dealing with market-changing opportunities, now IoT, it is fundamental to have a systemic view of the implications of engaging Vs not-engaging in time, because often technology transitions become singularities where everything changes. The real risk of ignoring them is to disappear.

Enterprise Archetypes(Market Visionary / First Mover, Market Innovator / Fast Follower, Late Followers)

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Companies are going to decide what archetype they want to belong to and evolve, if necessary, accordingly. From the table, from a cost/benefit perspective, it emerges a fairly clear advantage of being a Fast Follower: First movers have already shown up on the market and filtered the wrong practises out, but there’s still a lot of value to grasp from adopting the new technology, once overcome some entry barriers.

Good opportunities breed competition like flies, therefore we expect a considerable number of companies to enter the IoT space in the next 18 to 24 months. A good Fast Follower, usually, takes simplicity seriously, stripping out what is unnecessary in order to “zero in on what matters”. Effective prototyping on the best platforms is probably the best way to kick off an IoT initiative.

Enterprise Archetypes

MainFocus

Organizational Culture

Aspiration Information to Engage

Pros Cons

Market Visionary First Movers

Market Innovators Fast Followers

Industry revolution

Experimenting unexplored patterns

Customization

Profitable change

Benefits

Benefits

Competitive advantage

Risk mitigation

Standardization

Late Followers Status quo exploitation

Cost minimization

Risk avoidance

Change when unavoidable

Systemic innovation

Experimentation/Research/Test

everything

Project effectiveness

Fail fast

Business transformation

Executive commitment

Long term mindset

Industry leaders

Cultural supremacy

Academic referrals

Social influence

Performance

Evolution

Industry leaders

Performance

Sustainable “transparency”

Being “OK”

Safety of the status quo

Trends

Research publications

Proof of concept

Mockups of the available innovative technologies

External /Internal

analysis

Proof of concept

Cross-sector

reference customer

at any stage

External/Internal

available analysis (@ no cost)

Vertical reference

Customers with

proven benefits

Competitive pressure

Set Industry Rules/Standards

Technology leadership

Learn how-to early

Competitive advantage

Control of resources

Set entry barriers

Fine tune Industry

Rules/Standards

Informed decisions

Early benefits

Competitive advantage

Targeted business transformation

Project efficiency

No failure

Lower cost

No risks associated with

technology adoption

Enter a

consolidated market

Passive participation to

Industry bodies’

initiative

Let the innovation happen

Person-centered

innovation

Mortality of initiatives (47% average failure rate) /Cost associated

Spend on education

Be sure to have resources to sustain initial benefits

Slow ramp up of benefits

Mortality of initiatives (8% average failure rate) /Cost associated

Overcome entry

barriers

Lower benefits

Everything to be made as fast as possible.

Overcome big entry

barriers

Executive commitment

Long term mindset

Business commitment

Short term mindset

FIG.2 ENTERPRISE ARCHETYPES

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The biggest challenge for IoT is that it requires a highly innovative, business transformation culture and it is not enabled in a traditional IT manner. Approaching a disruptive business opportunity with traditional methods will most likely fail or result in unnecessary costs and business limitations. Initial implementations of IoT have been geared around specific vertical use cases that drive short-term operational efficiency gains or enable new service models, typically leveraging a minimal set of technology components that deliver the scenario. Whilst these approaches help support a short-term business case for IoT projects, some significant gaps will rapidly emerge aiming to unlock the full value promise of IoT. New services, new devices, more interactions and billing models will be added. Open and closed ecosystems will converge, data volumes and scalability requirements will grow exponentially, and intelligent automation capabilities will be even more fundamental to thrive.

When executing an IoT strategy, the following key questions should be addressed:

From the above, it appears evident that just a middleware or an API platform will not suffice, unless you want to raise implementation complexity hence costs significantly, by interconnecting and managing multiple modules devoted to a specific capability area. A comparison of architecture approaches is provided in the following section.Therefore, the essential requirement is to be found in an IoT platform that serves as the foundation of your IoT strategy. Bringing flexibility from application development, through deployment, to maintenance over time.

Selecting the right IoT platform running on an elastic infrastructure is the key enabler of both short term requirements and the longer term roadmap. The IoT platform of choice should essentially provide the following capabilities:

Regardless of industry scenarios and use cases, any IoT implementation should start considering the following foundational capabilities:

• How can the multi device, multi machine, multiple things and humans interactions paradigm be truly achieved?

• How to effectively orchestrate existing and new services and resulting actions on demand, in real time and as required using smart data and automatic discovery?

• How can the marginal costs involved in scaling up smart service business models be much lower compared to traditional IT-enabled business models?

• Things - devices, sensors, objects, either machine, physical or human-based. In other words, means to an end. Some owned, most things owned by third parties.

• Communication protocols enabling a seamless interconnected ecosystem for any type of thing.

• Orchestration. Activity monitoring, diagnostics and action engine driving observation, discovery and configurable, resource-based action orchestration.

• Integration with enterprise systems and consumer-grade platforms and applications (e.g. social, apps) at the same time.

• Endless data. Real-time data management and analytics capabilities.

• Embedded security management across all of the above.

• A Platform-as-a-Service (PaaS) for the creation, deployment and management of activity monitoring solutions in the cloud, leveraging the Internet of Things (IoT) and for the integration with existing systems and applications.

• A collaborative environment for software development, focused on workflow management regardless of the data source being used for the application given the extendable and “open system” nature of IoT.

• An application protocol allowing the communication and actions between things in a highly distributed system. This protocol must leverage existing web standards and device management/MDM protocols to guarantee standard compliance and interoperability hence easier deployment.

The platform is the foundation of any IoT strategy

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• ConfigurableIoTsemantics assigning resources and actions to things in its broadest meaning, e.g. not just devices, but also physical objects or humans.

• Big data architecture, allowing for data management and analytics on the PaaS data layer in real-time.

• End-to-end, scalable security management.

On this basis, it will be possible to quickly enable specific vertical use cases, new applications and service models. Figure 3 provides some examples of specific industry use cases.

The ultimate goal is the creation of an open, orchestrated ecosystem that goes beyond the four walls of the enterprise, granting access by default to all foundational capabilities (integration, security, analytics, activity monitoring and actionability). This is fundamental to generate smart services across industries that will increase IoT value to all stakeholders, while driving competitive advantage for your company. Such a converged ecosystem allowing rapid simulation, test & deployment of IoT use cases will benefit from the platform-based architecture highlighted in this chapter. The following section analyses in more detail IoT platform requirements and capabilities and provides an overview of AMTech’s innovative IoT approach.

FIG.3 SPECIFIC INDUSTRY USE CASES

Industry Operational

Efficiency New Services Open Ecosystems

Self-optimised, on-demand supply chain

Products as a service platformProduction optimizationDistribution optimization

Manufacturing & Logistics

Autonomous carsConnected roads

Vehicle to human service monetization

Telematics, vehicle to machine,

smart plantAutomotive

Connected pharma R&DSmart hospitals (assets, patients,

buildings), automated data collection and diagnosis

Remote diagnosticsClinical trial monitoringLifestyle management

Healthcare

Intelligent retail-home-supply chain ecosystems

New customer experienceSupply chain optimizationRetail

Intelligent transitSmart safetyTrafficoptimizationGovernment

Connected bankingTelematics based servicesInsurance/Banking

Connected home, car, health, bank services

End-users access to IoT servicesInfrastructure monitoring & predictive maintenance

Communication

Smart grid optimizationSmart meteringPredictive maintenanceConnected worker safety

Energy

Smart shipPredictive maintenanceFuel consumption optimisation

Transportation

Intelligent homeWearables servicesIntelligent buildingsConsumer

Predictive customer habits &cross-sale opportunities

Connected trains, buses, planes,

subways.

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The number of available software platforms, tools and technology offerings is rapidly increasing as IoT adoption grows. This section supports executives that are defining implementation roadmaps and selecting IoT platforms by comparing available options and approaches with the objective of enabling a rapid, scalable and cost-effective deployment path.

Before delving into the essential technology requirements, and especially given the distributed, open nature of IoT ecosystems, it is firstly important to assess architecture options and then select technology platforms accordingly.

Broadly speaking, an IoT architecture should define how the following capabilities are enabled and governed: device communications and device management, service enablement, service orchestration, data management, enterprise integration, security and industry applications. An additional important element to consider from a M2M perspective is configurable intelligence at the edge for discovery, centralized management and protocol smoothing/filtering. The chosen architecture should allow for both configuration and software development capabilities across the previous elements, as well as intelligent big data binding abilities, enabling synchronised integration of distributed data sources.

Two major architectural deployment options exist, namely a full-stack IoT platform approach versus using multiple IoT components. In this paper we focus on native, IoT-specific architecture/platform approaches, thus we are not discussing general-purpose approaches that may be adapted to an IoT context.

Figure 4 compares the high-level pros and cons of the two architectural approaches.

A full-stack platform is a single IoT platform providing embedded, end-to-end features across the capability stack, e.g. device, service, data, integration and security management. Typically industry applications are built on top of the platform as stand alone applications that leverage the platform core components to enable specific industry scenarios. By contrast, a multiple IoT components architecture leverages different software components from different vendors, for example a device management software, a service and business engine management component from a second vendor, a data management system from a third supplier.

Architectural approaches

Path to implementation: How to unlock the IoT paradigm?3

Architectural Approach

Full stack IoT platform (PaaS)

Pros Cons

Higher scalability

Certifiedperformancewithbuilt-insimulation tools

Faster time to market/speed to value

End to end security management

Quicker, richer IoT services development/management leveraging embedded tools, technology, libraries and

APIs

Configuration-basedservicecreationtested

and deployed across the entire stack

•

•

•

•

•

•

Platform vendor “lock-in”•

Multiple IoT components Flexibility to integrate with heterogeneous IoT components

Configuration-basedservicedesign(tobeintegrated and tested with multiple components)

•

•

Higher costs (implementation,

maintenance)

Complex versioning management of components from multiple vendors

API-only integration

Complex security management across the technology stack

•

•

•

•

FIG.4 ARCHITECTURAL APPROACHES

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Common enterprise IT architecture management employs device management, protocol management, and other necessary components. In turn, IoT is different in such a way that device management cannot be separated from the rest of the stack. This is due to the fact that protocols and device management need to have “embedded” communications to achieve IoT goals, because device status & changes need to be immediately and consistently available to the platform. A key resulting benefit of such an integrated architecture is the ability to ensure failure-free operations once a device or a resource fails and the business application stays uninterrupted. Regardless of whatever happens to billions of devices’ state changes.

The result of our analysis, backed up by end user cases and developers’ preference, shows that a full-stack IoT platform is the clear winner, from initial pilot to full scale deployment of real-time IoT ecosystem operations. Selecting the right platform partner is crucial given the long term nature of the implementation and the central role of the platform.

What are the key technology requirements of a full-stack IoT platform?

IoT have unique data requirements, semantic and workload models which prevents the use of many traditional enterprise-grade tools when building out the architecture based on a full-stack platform.

The specific characteristics that make practical IoT implementations different than other types of large-scale data applications are:

IoT Platform - Key Technology Requirements

• Higher velocity, higher volume, continuous data ingestion, storage and analysis. IoT is largely based on machine-generated data whereas web, enterprise and social media systems are mostly human-generated data. This precludes the use of many traditional database/data-warehouse platforms as well as in-memory databases. The requirement is a distributed platform that can reliably process and store high data volumes per second.

• Context, resources, complex entities. How sensor measurements are aggregated and turned into a picture of what is happening in the real world requires the aggregation of data attributes into complex entities within their specific context. As a result, it is necessary to perform joins and operations across resources and data sources following the IoT semantic model, which in turn required a native IoT platform.

• Real-time operational queries and analytics. Fundamentally different from data warehouse performance (e.g. fast queries on stored data) and fast storage for batch processing. IoT requires instant queries on live, real-time data and historical data with minimal latency, on a much larger scale. The required analytics are processing the IoT-data model illustrated in the previous bullet, which again makes it impractical to use many of the available tools developed for other purposes.

• Interoperability. Interoperability is a key element to ensure the promise of a fully open, adaptable and rich IoT ecosystem. While initial implementations focused on vertical integration, e.g. integration of resources and systems for vertical industry applications, maximum value for all stakeholders has to be found in vertical plus horizontal integration. With the latter we mean achieving inter-system communications and inter-operation across vertical silos (for example smart energy, smart home, connected vehicles, smart health, legacy systems). This will enable full value chain collaboration in an open IoT ecosystem.

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loT-A, the European Lighthouse Integrated Project has addressed for three years the Internet-of-Things Architecture, and created the proposed architectural reference model (see Figure 5). Source: Internet of Things Architecture, Deliverable D1.5 – Final architectural reference model for the IoT v3.0.

The IoT architecture is defined as follows: “IoT architecture views are the physical view; context view; functional view; information view; deployment view. The focus point of any IoT architecture is the context view also called the ‘IoT Domain Model’ which introduces the main concepts of the Internet of Things like Devices, IoT Services and Virtual Entities (VE), and it also introduces relations between these concepts.” In other words, the IoT domain model provides a core IoT abstraction layer that is completely independent from specific technologies and use cases, and as such will remain valid throughout the long term roadmap of any IoT implementation.

In addition to the domain model abstraction which needs to be implemented in a specific IoT platform, an high level of interoperability needs to be reached at the communication level as well as at the service and even information level. Considering that there is no single nor a best protocol for IoT - now and in the future - the required platform will have to cope with multiple communication protocols, while ensuring a standard way to communicate the changes in the state of things to distributed services, devices, users.

FIG.5 FUNCTIONAL DECOMPOSITION VIEWPOINT OF THE IOT REFERENCE ARCHITECTURE

Following the discussion logic, the business value of a Domain Application Protocol (DAP) as a core element of an IoT platform becomes evident to ensure scalable, interoperable, future-proof, richer IoT communications and actions between things. In addition to solve the interoperability challenge and provide the IoT-specific building blocks in a scalable manner, DAP brings additional benefits:

Platform-as-a-Service (PaaS) include the tools, technology, and APIs designed for developers to build custom apps. Examples of these tools and APIs are: RESTful APIs for mobile apps, geolocation support, metadata, automated testing frameworks, and integration with source code control. An IoT PaaS should provide:

As you can see from the above, IoT require developers to shift from focusing on devices to focusing on services based on user data, and PaaS provides the required platform support and capabilities.

IoT Platform Requirement #1 Domain Application Protocol

IoT Platform Requirement #2 Platform-as-a-Service

• Centralised management, thus making the IoT platform truly acting as the IoT command center.

• Extendable and better suited for IoT integration requirements. APIs have a “function” signature by functionality. DAP has a well defined set of resource types specific to an Application Domain and can be extended without defining new “signatures” and thus without binding to a specific communication protocol. As simple as defining a new resource type.

• From a technical standpoint, DAP should leverage existing web standards like Linked Data, Resource Description Framework and REST. On the latter, developers agree that in the IoT context IoT, RESTful Web Services have many advantages over arbitrary Web Services (i.e., SOAP), such as less overhead, less parsing complexity, statelessness, and tighter integration with HTTP.

• The ability to leverage and interact with ecosystem services. This is not only useful for developers to make new services available through app marketplaces or to leverage existing services. It represents a value growth opportunity also for enterprises to offer their own services for consumption.

• A collaborative environment throughout the development process.

• Multi-Tenant Infrastructure as a Service (IaaS) and fully managed cloud database.

• Underlying enabling technologies such as localization, security, and entity management, which are all required for rich business services.

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The additional fundamental requirement of an IoT platform is not only to be a PaaS for software development, but also provide business activity monitoring and an IoT-specific action engine enabling complex actions management and business scenario creation via simple user configuration. In essence the semantic action engine should be capable of:

IoT Platform Requirement #3 Semantic Action Engine

• Defining semantic leveraging Internet standards.

• Configuring every available resource.

• Providing the “configuration logic” by interpreting resource semantics and exposing the logic using binding concepts.

• Defining new resources, types of resources, notification, observations, actors.

• Facilitate the development, configuration, discovery of services including the possibility to expand their features.

In summary, the identified five key requirements of an IoT platform will enable the selection of an interoperable and scalable platform embedding a Domain Application Protocol, a domain specific actions engine capable of maintaining Big Data real time data views for low latency applications, enabling communications with M2M networks, sensor networks and devices as well as other existing enterprise or consumer systems in real time. All while offering native, extendable IoT semantics and architecture that can be fully configured by high level users.

It is important to remark that the IoT platform must work at the “speed layer”, processing streaming data in real time and applying reduce techniques and intelligence, combining observations from things, things status and executing actions configured by things and humans. In other words, the IoT platform must work at the speed layer of the Big Data.

Data Management should respond to low latency and higher latency application requirements at the same time. A proven guideline to respond to IoT requirements is the Lambda Architecture, a framework for the design of big data applications in distributed data processing environments like IoT. A platform implementation based on a Lamba architecture provides the following key capabilities:

IoT Platform Requirement #5 End-to-end Security

IoT Platform Requirement #4 Big Data Real-Time Architecture

• A full security schema across resources, actions and users.

• Complete entity management and not just identity or device management.

• Real-time big data management (speed or realtime data layer) — the purpose of the real-time data layer is to generate real-time views from new data.

• A batch processing layer to generate batch views from all of the available data.

• A serving layer that aggregates indexed batch views with real-time views to provide low latency responses to ad-hoc queries.

• Fault-tolerance, linear scalability, extensibility.

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AMTech (Activity Monitoring Technologies) is an innovative technology company specializing in the Internet of Things and providing a full-stack Platform-as-a-Service for the easy creation, deployment and management of activity monitoring solutions, specifically built for operating within the Internet of Things (IoT) paradigm.

AMTech’s mission is to solve everyday problems enhancing existing systems and making a difference globally in Enterprises, Institutions and Communities.

Among the founders, Carlos Arteaga is distinguished: CTO and well known technologist with a undisputed standing in the Internet of Things, made particularly interesting because of his deep knowledge and experience with Enterprise Software architectures, Big Data Architectures, Networks of sensors, location-aware computing together with real time intelligence and complex event processing. All these competences together have made possible, under his guidance, the creation of an end-to-end full stack Platform-as-a-Service, designed and created for scaling and performing in any size of Enterprises. With his background of CIO, CTO, IT Architect and Technology Consulting leader, he knew from the inside of the company what it was really missing to unleash the IoT potential, a solution native for IoT and Big data together.

The company employs a team of world-class engineers, mathematicians and professionals, active in the IoT community via open source contributions, lectures and more than 10 patents in different areas such as data collection, M2M, sensor network, location awareness and RFID.

This combination of knowledge, experience and vision is probably the core enabler for developing the lean and complete AMTech end-to-end IoT Platform, focussed on rich functions and Services, Performance and high usability together, as it is illustrated in the next sections. From a capital structure standpoint, having on board a successful long standing team allowed for thoroughly supporting the full PaaS development with Shareholders’ equity and Seed Capital, giving the freedom to the Team to keep faith to the original setting, which wanted to leverage exclusively the best available standards, foundational technologies and architectures.

As stated in the previous paragraphs, a Platform-as-a-Service (PaaS) can be defined as a computing platform that allows the creation of Web applications quickly, easily and without the complexity of buying and maintaining the software and infrastructure underneath it. According to Salesforce, PaaS must provide a fully managed infrastructure that can scale beyond a company’s current needs. They defined, at the infrastructure, developer and business level, 8 core services that must be in place in order a vendor to be able to define its platform as a true PaaS:

AMTech – The Company AMTech – IoT in Action

1. Fully Managed Cloud DB

2. Multi-tenancy

3. Open API, Tech Libraries, IDE, Sandbox and ALM tools for app management, Mobile ervices

4. Multi-language development

5. Mobile SDK

6. Point and Click App Building for Business Users

7. Social & Mobile Built-in

8. Cloud App marketplaces

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FIG.6 CLOUD COMPUTING STACK

AMTech is an IoT full-stack Platform as a Service (PaaS) following a complete PaaS Business model as defined above, with the following additional capabilities:

As it’s been articulated in the previous sections of this paper, new opportunities require new approaches and tools.

AMTech has been architected and implemented for cloud clustered environment; it runs on Lambda architecture and executes at the speed layer of Big Data, having been built natively for Big Data and IoT together.

Full-Stack Platform – A full accountability

Architecture – Natively designed for IoT and Big Data together

• Targeting specific domains that IoT Integrates.

• Orchestrating a wide array of specific core services in a completely different way with respect to a traditional API approach.

• Offering also a Software-as-a-Service (SaaS) experience to Business Analysts and profiled guests, who will be focusing on configuring business logics, subscribing to services and receiving/managing alerts or notifications. Twitter, Facebook, WhatsApp do not typically run on top

of J2EE engines and tools from big SW vendors. This is because no one of the latter has architected their solutions for Big Data and clusters in the cloud. ERP vendors, for instance, run 90% of the business rules on tools that run 100% on top of RDBMS. Following that approach it’s impossible to deal with Big Data, clusters, NoSQL, M2M, Sensor Network Semantic, etc, that are the standard components of today’s IoT ecosystem. Big Data is new, it requires new tools, new architectures, new ways of thinking. This is the reason why the open source community released a new architectural approach for the Big Data, such as the Lambda framework already described and adopted by AMTech.

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FIG.7 BIG DATA LAYERS

FIG.8 LAMBDA ARCHITECTURE

It should be clear at this point that IoT applications require a standard protocol to communicate the meaning of the changes in the state of the Things that build the IoT ecosystem and that a Domain Application Protocol (DAP) is needed in order to allow the communication and actions between things. It should also be now an accepted requirement that this protocol must leverage existing Web standards, like Linked Data, Resource Description Framework (RDF) and REST. AMTech core and integration layer is the DAP (Domain Application Protocol) with integrated security. AMTech DAP are RESTful APIs that allow clients to drive the execution of a domain application protocol without binding to the protocol itself. It is extensible by defining new Things and Events (as defined below, “Observations”) to communicate with each other leveraging existing Web standards like Linked Data and RDF.AMTech DAP exposes 9 core resources types specific to the IoT Domain:

Communication Protocol, Resources and Services – The semantic heart

Thing (IoT thing)

Observation (the event)

Topic (it publishes observation)

Observer (it configures the observation execution in real time)

Activity (it packages a set of IoT Resources and provides a BAM solution)

Reasoner (Action engine)

Notification(notification template initiated and sent by the Reasoner)

Action (configuration for executing an action over an IoT resource)

Actor (contains the configuration information needed to enforce access control to a Thing)

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9.

Last, but not least, AMTech, in the light of offering a complete, ready-to-use PaaS and reduce to the minimum the Time to Market of the IoT solution, created 16 key core Services essential for IoT deployments: examples are Geo-location, complete EPC integration covering RFID at any granularity, Device Management, Identity Access Management securing multi-tenancy and protecting IoT real time view data hosting, UX configuration, M2M Bridge, proximity location - leveraging proximity concepts and technologies like RFID, beacons, Wi-Fi Aware and others, App Marketplace and more.

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FIG.9 AMTECH DAP SCHEMA

The AMTech configuration is done through a user-friendly experience, completely oriented towards Business Analysts. AMTech configuration tools allow to configure and reuse each and every resource mentioned above, not just the Reasoner (Action Engine); the “configuration logic” interprets semantics and exposes configuration using binding concepts. Moreover, AMTech approach makes no difference between configuring a Thing “device”, a Thing “truck”, a Thing “ERP” or a Thing “existing Data feeds”. There are just Things that consume and/or produce Observations that have been semantically defined. This is hugely important when integrating external entities.

WhyisConfigurationsoimportant?

With AMTECH’s approach to IoT, which grants by default all foundational capabilities, IT departments, leveraging AMTech Platform as PaaS, will be able to focus on their core priority of building Services and Apps, while Business Analysts and Entrepreneurs, leveraging AMTech Platform as a SaaS, will be focusing on configuring Business Logics and subscribe to Services.Either one or the other will serve seamlessly the new defined Business models, eventually delivering big value to the business.

Among the several customer programs on going and deployed on the AMTech technology, the following examples are a simple and easily understandable set of Customer cases, addressing one single big issue, with huge benefits from a financial and/or Service Level standpoint. It’s important to restate that, thanks to the peculiarities of AMTech Technology and its Platform maturity, the typical first deployment time has been in the order of days.

Configuration–IoTas“Plug&Use”

AMTech – A selection of simple and practical IoT Customer examples deployed on AMTech IoT PaaS

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FIG.10 CUSTOMER EXAMPLES

Below you can find some examples of the direct implications, value-wise, of leveraging AMTech as IoT Platform provider. They are simple examples among the several more that a vertical deployment grafted into AMTech foundational technology will be able to grant.

AMTech – Why it is an enabler to accelerating value creation

FIG.11 AMTECH VALUE CREATION

AMTech Differentiating Element

Full stack IoT platform (PaaS)

Comments Contribution to Value Creation

It allows the configuration of unlimited business monitoring activities with zero programming, in a

user friendly context, reducing the time-to-market

of any new business model supported by the loT paradigm, providing unconventional new revenues.

AMTech unlimited scalability (architecture-e-reusability), reduces the Marginal Cost of data and services, making them a rich profit center.

•AMTech, it´s not an API, it´s not a web service or

SDK, it is a real platform for the loT. There is no integrated tool in the market that goes from defining semantics via web standards to

configuration.

AMTech is the only PaaS able to securely integrate, orchestrate and reuse loT specific

services.

Domain Application Protocol (DAP):Standard, extensible and “Thing” agnostic

Adding new things and monitoring activities is so simple that it will allow you to quickly innovate without the concerns of mounting capital expenses, complexities and delays.

It future-proofs any loT strategy without having to

worry anymore about evolving protocol standards or hardware barriers.

Easy to Integrate From ideation to production in days instead of

months, reducing the time-to-market of any new business model supported by the loT paradigm.

In AMTech PaaS there is no difference between configuring a Thing “device”, a Thing “truck”, a

Thing “ERP” or a Thing “Existing Data Feed”. There are things that consume and/or produce observations that have been semantically defined.

Multi-tenant / Multi-user Resources can be shared or restricted very easily, accelerating the loT adoption.

Low risk of security breaches.

AMTech offers secure native multi-tenancy and protected loT real time view data hosting.Actors have access to things, observations and notifications strictly depending on their access roles.

Simulating Capabilities The resulting intelligent action will immediately be able, reducing costs and complexity of deployments of any size.

Users are able to model and simulate processes more efficiently, and easily integrate new devices and data without having to physically touch or

see devices, sensors or data feeds.

Integrated Services 16 Core Services available

Thanks to the focus on Business Processes and speed, innovation accelerates and associated costs drop.

According to Progress (IT Survey 2015), although the vast majority of developers are excited about

loT, they say no vendor is able to offer loT integrated services: For example Google offering a map and set of API’s, including some geoloca-tion, doesn’t provide integration with loT. Without

integrated services, trying to manage data sets for contextualized loT Apps, such as location-based apps, becomes overwhelming.

AMTech platform integrates core services in order

to fill that gap and provide the missing bridge.

Open Source License costs associated vanish.

Complete freedom with AMTech’s 100% open source platform. More over, there are no limita-tions of third party components (for example maps that don’t currently scale when receiving thousands of petitions).

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Selecting the IoT platform and tools is difficult, because of the vastity and diversity of the offering available on the market.

The complex nature of IoT and its required resilience to the long term is coupled with a certain degree of ambiguity resulting from Vendors’ use of the same keywords to describe technology components that have a completely different sensitivity, meaning and usage in the IoT world.

For this reason, in order to put some clarity and, at the same time, wrapping up most of the key concepts that have been presented throughout the paper, the following table compares the various technology approaches with AMTech Platform. The analysis identifies the level of coverage of the different approaches against the key criteria, along with high level snapshots characterizing each approach.

AMTech’s technological, methodological and architectural elements position their Platform as a strong contender to drive IoT operations and innovation, offering all Core Services needed to fulfill the foundation of any deployment, guaranteeing to enterprises, system integrators and other third parties the ability to quickly integrate, develop and reuse Vertical Services or Business Models that can contribute to the companies’ competitive advantage and overall performance.

Comparing Technology Approaches - IoT Criteria Coverage Matrix

FIG.12 IOT CRITERIA COVERAGE MATRIX

t’s not easy to talk about IoT Benefits within the ante-IoT paradigm. Yes, costs and benefits need to be identified and captured as per the ROI liturgy, but new categories of “benefits” and “costs” need to be created, connected with new, unprecedented and extraordinary data flows and finally regularly fed.

Recalling a simile made at the beginning of this paper, once an electrical infrastructure began to proliferate, new disruptive inventions such as radio and television emerged; and it’s already happened many times, also with the Internet. in Innovation science this is called the “multiplier effect”, typical of enabling technologies and paradigms, as also IoT represents today.

73 percent of companies are already investing more than 20 percent of their overall technology budget on big data analytics (Industrial Internet Insights Report for 2015, GE and Accenture).

65% of IoT applications today already generate revenues, even though Business models have not kept pace yet with technology advances (IoT Survey report, Progress 2015). This is the real gigantic evolutive opportunity IoT is offering to the Business World and Society.

The main control points for the digital Value chains reside in the software-defined and service platforms, where big figures will be generated by smart services.

Companies will be able to establish entirely new product and service hybrids that disrupt their own markets and generate fresh revenue streams.

Very simple examples are:

Beyond traditional elements

Focus on incremental revenues, new revenue opportunities

• Pay-as-you-use (Pay as you drive, just for instance.

• Advisory subscription services (drive better, saving fuel, drive on snow/rain, etc).

• Product-as-a-service (no more one-time sale, but recurring revenue model, like grocery services).

• Data re-marketing: data coming from the products will be packaged and sold to third parties: the revenue coming from this activity will more that offset the cost of the product, without considering that the marginal costs of the data is almost zero.

Business Case OptionsReturn on Investment4

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Moreover, the costs involved in scaling-up smart service business models are much lower than within a traditional paradigm. We are probably fairly familiar with the “as-a-service” or “value-in-use” model and we know it is often significantly performing more than the equivalent “ownership” model. But when we talk about Product-as-a-Service or Product-as-a-Platform we need to make some clarification.

Offering a layer of premium services on top of a traditionally sold product is not equal to offering a Product-as-a-Service: The first focuses on simple up sell potential, while the relation with customers gets little affected. Product-as-a-Service is a different business model, where the product becomes a platform to deliver business outcomes and tangible value, helping to increase addressable customer base, gaining a greater intimacy with customers; which eventually helps achieving a Linear economic model, stabilizing financial flows.

The Internet of Things is blurring the boundaries between virtual and physical objects, enabling entirely new market segments and business models.

Amit Jasuja Senior Vice President of Development,

Java and Identity Management Products, Oracle.

It transforms Service from a standalone function within a manufacturer to an integrated product and service offering that delivers value as the product is in use. This helps customers reduce up-front capital expenditures while affording the manufacturer a continuous service revenue stream, ongoing cash flow and an opportunity to stay closely aligned with the customer, gaining greater intimacy while enhancing product development from closer feedback loops.

What does this has to do with the Internet of Things?

Product-as-a-Service starts with sensor-based products that continuously feed information about product usage and condition to manufacturers, who can then leverage the data for a variety of purposes, from delivering proactive and preventive maintenance to creating entirely new service-oriented business models. Then, machines, systems, factories and people can be easily connected to the Internet via digital platforms, using the “Plug & Use” approach, thus creating entire ecosystems of Services.

So, IoT enables, empowers, simplifies and eventually unleashes the Service Model, truly leaving creativity as the only limit (See Figure 13).

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Statistics show that sellers moving from a physical sale to a recurring service fee get more stable, profitable and larger overall revenue streams than one-time sales Last, but not least, Product-as-a-Service increases the seller’s market size. A buyer’s entry price is reduced with less capital expenditure, therefore expanding the number of customers that can be sold to.

FIG.13 FROM PRODUCT TO IOT BUSINESS SERVICES

And Smart-Service makers will be able either to ask people to pay a service charge for using the marketplace or even charge users for downloading apps.

The real race will be run within the service control track. Whoever controls the service platforms will also gain control of the entire value chain.

Who gains sovereignty over the data and seizing control of value-added control points will ultimately write the new ground rules.

Think about Uber, a company that provides a taxi hiring service without actually having physical assets of its own. Uber uses platforms to scale endlessly its business. Airbnb is another great example. It’s already happened in the retail trade with e-commerce platforms and in tourist industry given the success of vertical portals, which changed the way the Industry works today.

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As we probably have clear now, the opportunities for exploiting the full business potential offered by the IoT paradigm need that we think out-of-the-box and build up, from the new information available and the Plug&Use new paradigm made possible by IoT, what we really want in order to challenge the way we currently operate and deal with customers. In other words, we have today a unique opportunity to design our new Business Models, counting on Carte-blanche, technology-wise.

FIG.14 IOT LEVERAGE RATIOS

IoT leverage: 0-20 Low / 21-50 Medium / 51-100 High

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The complexity of structuring an IoT business case assessment lays in the necessary understanding of what the new IoT paradigm can offer specifically to us, in terms of efficiency, Business growth and competitive advantage; in order to get there, we need to create our specific Value clusters that will be then targeted. Often, when dealing with disruptive innovation, quick Prototyping serves very well to clarify the thinking and modeling, because we need to see technology in action and trust it, before creating a business model around it.

The following figure illustrates the typical high level ROI structure, where “Value Clusters” represent a good indication cross-industries, while activities and KPIs are examples (from Retail Industry) aimed to provide some indications on how to relate metrics with activities.

Best recommendation on IoT, though, is not over-spending energies in creating complex strategies and complete operating models before even starting to move a step within IoT. Instead quick-wins IoT pilots with Partners, excluding without any hesitation at all those that need too long to make it (it simply means platforms are not ready and big integration efforts are necessary) are the cradle of a good IoT program. Based on pilot results, understand the potential, create the vision, the strategy and, finally, the operating model, designing the full scale solution.

This small scale first results, would also enhance the Executive commitment which is absolutely necessary for challenging Business models and for bringing on board the talents needed to carry on a complex suppliers selection, made of a big variety of components, design new processes and business models, all in a multidisciplinary fashion where collaboration will be needed, therefore a top-down mandate is crucial to achieve.

Key pillars for successful business case assessments and ROI opportunities identification

FIG.15 ROI SCHEMA

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What is your IoT Vision?5

McKinsey predicts that IoT has a total potential economic impact of up to $11.1 trillion a year by 2025. The McKinsey study is of particular interest because it analysed not only vertical use cases but also the impact of IoT on larger settings including cities and consumers, thus showing how the interaction of larger ecosystems can lead to greater value in the IoT economy.

Hardware manufacturers state that every device they produce will be connected and open, and even products that you don’t normally expect to see technology in will be connected and interacting with each other. In the future a symbiotic interaction between the real/physical world, and the digital/virtual world will be the norm: things become context aware and they can sense, communicate, interact, exchange data, information and knowledge leveraging an open ecosystem of interconnected platforms.

Lastly, the open nature of IoT ecosystems may benefit in the future from meshed IoT networks to create permanent or most likely temporary, activity-based, on-demand peer networks among IoT nodes, empowered by semantic search, discovery, service composition and distributed - yet governed - self-orchestration.

We also foresee an evolution from the internet of things to the internet of smart objects - in addition to interoperability that remains a key issue to be continuously addressed, some things will embed smarter features (e.g. with intelligence at the edge), while others will be made smarter by platform-enabled features. This may lead to the development of different categories of objects depending on their purpose: for example activity-aware objects, policy-aware objects, and process-aware objects.

• Development of an open architecture and standards to maximise interoperability among heterogeneous systems and distributed resources.

• Algorithms that can foster predictive, context aware interactions capabilities with the required level of accuracy, performance and reliability.

• New service discovery agents in highly distributed big data environments.

• Action engines empowered by artificial intelligence and cognitive computing to automate the evolution and optimisation of smart services.

Other notable technology developments that will enable the expansion of the IoT ecosystem includes:

Figure 16 illustrates the IoT vision in time and across maturity stages on the horizontal axis, mapped to the volume and maturity of associated services on the vertical axis, also representative of the level of physical & digital convergence. Interestingly, enterprises will have the opportunity to go beyond initial vertical use cases and unlock a much greater value by participating in consumer and on-demand ecosystems.

Each and every effort in developing IoT as an open platform will make a significant contribution to achieve the high economic impact of IoT and make our world a better world.

Simplicity is the ultimate sophistication.

Leonardo Da Vinci

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FIG.16 IOT VISION

Call to action6

IoT requires new tools, new architectures, ways of thinking, business models in order to unlock its full value promise. it’s important decision makers build an IoT foundation since the beginning and enable the long term roadmap towards an open ecosystem of smart services.

On the basis of the facts, analysis, opinions and examples illustrated in this paper, we recommend IT and business executives to consider the following 5 key actions:

Accelerate - Today 5B devices, in 3/5 years tens of billions of consumer devices, machines, vehicles and wearables will be connected into the smart ecosystem. Notably, enterprises, consumers and institutions are driving IoT adoption simultaneously. Only companies that act fast are going to achieve the benefits available to market innovators and fast followers.

IoT at the Board - Whatever the initial project organization, make sure the IoT initiative sits at Board level, because of the nature of potential business model changes and the need for achieving stakeholders’ consensus at speed. If you are large enough, consider to establish an IoT office.

Foundationfirst- Aim for the full potential - plan and execute in order to unlock the full Value promise of IoT, putting in place all foundational elements before going vertical. It will bring flexibility from use case scenario development through deployment to maintenance over time.

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IoT Platform next - Select a full-stack IoT Platform fulfilling the following criteria:

Agile and rapid deployment through simulation Plan to allocate up to 40% of the investment to strategy, KPI monitoring and process design, 10% to pilot, 50% to business model enhancement and roll out. Based on pilot results built on a performing Platform, simulate, experiment, test in order to understand the potential, create the vision, the strategy and, finally, the operating model, eventually designing the full scale solution in a continuous improvement and result-driven process.

Being a real Platform as a Service (PaaS), allowing IoT developers to shift focus from devices to services based on end-user data, thus enabling richer business services and the ability to create collaborative ecosystems.

Domain Application Protocol for seamless interoperability between things in order to ensure effective integration and scalability governance, minimizing operative costs, while maintaining the system at speed.

Configurable IoT semantic engine - native IoT Business Activity Monitoring and action engine providing semantic-based configuration logic, service discovery and extensibility.

Real time Big Data - Big Data, in IoT, it’s not batch data mining and the IoT platform must work at the “speed layer”, processing streaming data in real time, while combining historical data with minimal latency on a much larger scale.

End-to-end security, enabling full entity management and providing a complete security schema across IoT resources, actions and users.

Full Stack IoT architecture -in IoT this is a pivotal element and is about enablement and governance of all of the fundamental elements listed in the previous bullets. In addition, device management needs to be embedded and seamlessly connected with the rest of the stack in order to enable failure-free operations.

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About the Authors Key Contributors7

Ivano Ortis worked as a Managing Director at Accenture, where he designed and brought to market innovative business services and differentiating value propositions leveraging strategy, consulting, technology, digital and business process outsourcing capabilities. Prior to Accenture, he managed IDC Retail Insights International business unit for EMEA and APAC and led IDC’s consulting practice globally on omnichannel retail and consumer experience strategies. Ivano has been exposed to IoT, RFID and communication-driven innovations as an advisor to business and IT executives throughout 20 years of experience in management consulting, system integration, enterprise software, and telecommunication, with experiences at Nokia, Fiat, Vodafone, Andersen Consulting and Harris semiconductor. Ivano holds a Master Degree in Computer Science & Telecommunication Engineering from Polytechnic University, Milan.

Carlos Arteaga is the CTO at AMTech; under his direct guidance, AMTech Team designed, programmed and brought to market AMTech’s IoT PaaS. Highly accomplished software architect and adept technical leader with over 20 years experience leading global cross functional engineering and software architect teams to design comprehensive software solutions. Prior to AMTech, he was CTO at JitiSoft, Specialist Leader Technology at Deloite Consulting, CTO at RetaLigent; CTO and VP Engineering at Sybase, CTO and VP Engineering at Picsel Technolgies. Carlos has lead the adoption of multiple emerging technologies including the Internet of Things, Mobility, SOA, SaaS, RFID, Cloud Computing, Big Data, M2M, Business Activity Monitoring and Sensor Network. He holds more than 10 patents in different areas such as Data Collection, M2M, Sensor Network, Location Awareness, IoT DAP and RFID. Perceiving a growing chaos within the IoT context, Carlos decided to undertake an entrepreneurial journey, focusing on the foundational gaps affecting the technology, addressed now by the AMTech Platform. He has achieved the latter by gathering a team of world-class engineers, mathematicians and professionals from different geographies, conforming a flexible and fast development team, a task difficult to achieve when working for a large vendor.

Eduardo Pelegri-Llopart is a VP of Technology in the Office of the CTO at Progress. His work focuses in strategic initiatives for Progress, technology trends and on Corporate Development. Eduardo is also interested in Technology Adoption and tries to stay in touch with the new waves of developers through Hackathons, internships and other community interactions. Eduardo joined Progress in November 2013; before that he worked at BlackBerry, Oracle, Sun Microsystems and Xerox PARC. He has CS degrees from UCB and USB (Venezuela).

Alessandro Della Monica is currently a Technology & Enterprise Advisor and Angel Investor. Until recently he has been Vice President of Europe, the Middle East, Africa and the Russian Federation within Tyco Vertical Markets (Nasdaq), focusing on smart device-driven intelligence and Item Level RFID. Prior to Tyco, he was Retail Country Leader and Regional Director at Oracle, where he launched and consolidated the Retail Global Business Unit. Other roles he carried earlier include Divisional responsibility in Planning&Optimization leading European Software house and, before, Strategy consulting. He has 15 years of work experience in retail and Luxury, and over 20 in business management. Alessandro holds a Master of Science in Industrial Technology Engineering from the Politecnico of Milan and a Master in Marketing from the University of Bologna.

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