World of IoT – Part 4
 

Just a recap, in my previous post, I had taken a deep dive into the growth and trends in the IoT space. This will be the concluding post for this series where we will discuss the Industries where IoTs have been successfully implemented.

According to Internet of Things spending data and forecasts, published early 2017 by IDC, the 3 main industries in terms of IoT spending in 2016 were, respectively, manufacturing, transportation and utilities. Consumer Internet of Things spending ranked fourth.

While globally in the period until 2020, manufacturing will remain the major industry (except in Western-Europe) there will be global changes in this top 3. Among the fastest growing industries in the period until 2020 are insurance, healthcare, retail, consumer and, as mentioned, cross-industry initiatives.

Obviously, there is a difference between Internet of Things spend and number of Internet of Things projects.

A report by IoT Analytics, really a list of 640 real-life Internet of Things projects, indicates that from the perspective of number of projects connected industry ranks first but is closely followed by smart city implementations (where we mentioned the report), which rank second.

  1. Internet of Things in MANUFACTURING

The Manufacturing industry has always taken the lead in the implementation of IoT, given the origins of IoT i.e., RFID. Hence the most early typical use cases have kept this industry in the lead but not for long. In 2015, it was estimated that there were 307 million installed units in the manufacturing industry where systems with sensors have always been embedded into manufacturing and the automation processes. And that it would reach $98.8 billion by 2018 in manufacturing operations through efficiency optimization and connecting the automated areas. By and large the 3 top IoT use case in this industry are listed below.

A majority of manufacturers has deployed devices to collect, analyze/measure and act upon data. More than 34.6 percent of these companies had already implemented devices and sensors to gather this data and another 9.6 percent were about to implement IoT devices within a year. Only 24 percent from manufacturing industry had no plans to implement devices to collect, analyze and act upon data.

Retailers are working with the Internet of Things for several innovative and immersive approaches, ranging from virtual closets and self-checkouts to smart shelves (inventory accuracy) and connected vending machines.

  1. The Internet of Things in the RETAIL business

Retail is moving up fast, both in operations and customer-facing circumstances. The emphasis is primarily on efforts to digitize the consumer experience. It is mainly in the optimization of processes and of logistics that the Internet of Things offers immediate benefits to retailers. However, obviously the customer-facing and inventory-related aspects matter a lot too. The use of the Internet of Things in retail, among others, changes customer experience, leads to better customer insights, enables new collaborations and business models and further blurs the line between digital and physical in an in-store context.

Retailers are working with the Internet of Things for several innovative and immersive approaches, ranging from virtual closets and self-checkouts to smart shelves (inventory accuracy) and connected vending machines.

 

  1. The Internet of Things in GOVERNMENT AND CITIES

The Internet of Things is already used across several government activities and layers the sector is a very vast ecosystem and so are the many IoTs use cases in government. Probably the best-known usage of the Internet of Things in a government context concerns smart cities, in reality mainly smart city applications.

Smart city projects are what people hear about most and they get a lot of attention, among others because smart city applications are close to the daily lives of residents. Another reason why smart cities are often mentioned is that defacto smart city projects account for a big portion of Internet of Things deployments. Think about smart waste management (often a local matter), smart parking and environment monitoring.

Another area where we see the Internet of Things popping up is in citizen-facing public services. To a large extent smart city uses cases overlap with Internet of Things use cases in public services as one of the key tasks of a city is to serve the citizens. However, with public services we also go beyond the local/urban level but also includes smart energy. The degree of overlap depends on the way government services are organized in a particular country or region.

Improving citizen satisfaction is the main objective when considering or implementing the Internet of Things and other emerging technologies. Moreover, governments have a role in public health which can be enhanced by taking initiatives using the Internet of Things and in collaboration with private a state-sponsored partners. The same goes for public safety by the way. An example: collaborations between governments and insurance firms, leveraging telematics.

There are really hundreds of ways in which governments leverage and can leverage the Internet of Things to improve citizen experience, realize cost savings and, not to forget, generate new revenue streams.

The latter is quite important as many IoT projects have an impact on the funding of cities. A simple example: if you have a perfectly working smart parking solution in a city, you lose revenues for all the obvious reasons. So, it’s not just a matter of technologies but also of finding creative ways to turn enhanced citizen experience and citizen services in a global picture that is beneficial for everyone.

This takes time, planning and, as you can imagine, given the complexity of the government ecosystems, lots of alignment and coordination.

  1. The Internet of Things in BUILDING AND FACILITIES

     

The Internet of Things plays an important role in facility management, among others including data centers and smart buildings. The integration of IT (Information Technology) and OT (Operational Technology) plays an important role in this regard. Smart buildings are among the fastest growing cross-industry Internet of Things use cases in the period until 2020. Moreover, research indicates that data collection from buildings and other structures such as HVAC is already high. Last but not least, the market and evolutions of the BMS (Building Management System) are strongly impacted by the Internet of Things.

As the graphic below indicates, building management systems are becoming the centers of connectivity in a world of ever more endpoints in buildings, data analytics and actionable data play a key role in the evolution of building design, the connected building and the building management. As data collection from end point increases and next generation technologies make analytics and insights key in building systems, the connected BMS becomes a center of visualization, insights and actions.

Leveraging data from IoT-enabled facility assets, along with new Internet of Things platforms and facility management, with embedded capabilities, are leading to possibilities and benefits in building management areas such as:

  1. Smarter building security systems.
  2. Smarter Heating, ventilation and air conditioning (HVAC).
  3. Safer and more comfortable/healthy workplaces and buildings.
  4. Facility service quality optimization.
  5. Cost reductions, also in a green building context and in reduction of energy and water consumption.
  6. Better planning, operational efficiencies and enhanced resource allocation.
  7. Predictive maintenance and facility maintenance planning.
  8. Facility equipment control, configuration and regulation.
  9. Building management and building automation.
  10. Energy efficiency.
  11. Light and room control, comfort.

This list is far from comprehensive. As there are various sorts of buildings, each with their own challenges, infrastructure, technologies and most of all goals the landscape of building automation and management is very broad. In light and room control alone there are several controls such as blind controls, AC unit controls and literally dozens more.

The overall building automation and management landscape exists since far before the Internet of Things existed and is composed of various specializations, each with their standards (e.g. KNX in room control or BACnet in building management systems), certification programs for green buildings (ecology and energy/ecology regulations are key drivers) and for OT channel partners, technologies, networks, solutions and of course goals (the goal of an IoT-enabled office space, building or even meeting room is not the same of a hospital, even if there are always overlaps) .

However, with the Internet of Things these worlds are converging (and the standards already evolved to IP). This is a challenge and opportunity for the various players who all have their skill sets but rarely are able to offer the full picture.

5. The Internet of Things in HEALTHCARE

The Internet of Things has been present in healthcare in many forms and shapes since several years.

With remote healthcare monitoring and medical/hospital asset tracking, monitoring and maintenance as typical examples of these initial applications, the face of the Internet of Things in healthcare is changing fast.

Among the evolutions and drivers of the Internet of Things in healthcare:

  • An increasing consciousness and engagement from the consumer/patient side leads to new models, leveraging personal healthcare devices.
  • In a more integrated perspective, data from biosensors, wearables and monitors are used in real-time health systems and to save time for caregivers, detect patterns, be more aware and increase quality of care.
  • A broad range of innovations in fields such as smart pills and ever better delivery robots help in making healthcare more efficient and in saving resources, while also increasing quality of care.

This glorifies the importance of remote monitoring as the main use case in healthcare from a spending perspective until 2020 and ongoing growth in the years after that with some vital sign monitor devices, followed by ways how healthcare providers and healthcare payers plan to leverage the Internet of Things and, finally smart healthcare market growth data.

Some evolutions and forecasts in healthcare IoT in numbers:

 

 

 

 

 

 

  • Research shows that by 2019, 89% of all healthcare organizations will have adopted IoT technology
  • Among the main perceived benefits of healthcare IoT in the future are increased workforce productivity (57%), cost saving (57%), the creation of new business models (36%) and better collaboration with colleagues and patients (27%). The key benefits as reported in March 2017, however, are increased innovation (80%), visibility across the organization (76%) and cost savings (73%).
  • Other research shows that wearables will play a key role in health care plans, clinical IoT device data will free up clinician’s time significantly by 2019 (up to 30%) and there will be an increasing role for IoT-enabled biosensors and robots for medication and supplies delivery in hospitals by 2019.
  1. Internet of Things in UTILITIES AND ENERGY

Facing huge challenges and transformations for several reasons, utility firms have 299 million units installed according to Gartner. On top of utilities in the traditional sense there is also a lot happening in oil and gas and in energy.

Among the many typical use cases in utility firms: smart meters to improve efficiency in energy, from a household perspective (savings, better monitoring etc.) and a utility company perspective (billing, better processes and of course also dealing with natural resources in a more efficient way as they are not endless) and smart grids (which is about more than the Internet of Things).

  1. The Internet of Things in AUTOMOTIVE

Connected cars and all the other evolutions in the automotive industry are driving the market as well. Again, connected vehicles is the hottest US market in the overall picture. The connected car is one of those typical examples where the Consumer Internet of Things and Industrial Internet of Things overlap.

  1. The Internet of Things in OTHER SECTORS

Other industries include healthcare, transportation (where “smart devices” and sensors have existed for quite some time), logistics, agriculture and more. Add to that the consumer context and you know why it is such a hot topic. 

In summary the biggest drivers for IoT projects are listed below

This is the last blog in the series on the World of IoT and the related space. Hope you all enjoyed reading through the posts as much as I enjoyed putting them together. Stay tuned while I come back with yet another series on a technology topic

Please feel free to review my earlier series of posts 

World of IoT – Part 3
 

Just a recap, in my previous post, I had emphasized primarily over the key definitions and approaches to the Internet of Things. In this post, we are going to take a deep dive into the growth and trends in the IoT space.

The exact predictions regarding the size and evolution of the Internet of Things landscape tend to focus on the number of devices, appliances and other ‘things’ that are connected and the staggering growth of this volume of IP-enabled IoT devices, as well as the data they generate, with mind-blowing numbers for many years to come.

It makes it look as if the Internet of Things is still nowhere. Make no mistake though: it is already bigger than many believe and used in far more applications than those which are typically mentioned in mainstream media.

At the same time it is true that the increase of connected devices is staggering and accelerating. As we wrote the first edition of this Internet of Things guide, approximately each single hour a million new connections were made and there were about 5 to 6 billion different items connected to the Internet. By 2020, Cisco expected there would be 20 billion devices in the Internet of Things. Estimations for 2030 went up to a whopping 50 billion devices and some predictions were even more bullish, stating that by 2025 there will be up to 100 billion devices. The truth is that we will have to wait and see and that by the time we have written about recent predictions, new ones are already published.

Regardless of the exact numbers, one thing is clear: there is a LOT that can still be connected and it’s safe to assume we’ll probably reach the lower numbers of connected devices (20-30 billion) by 2020. Moreover, it’s not that much the growth of connected devices which matters but how they are used in the broader context of the Internet of Things whereby the intersection of connected and IP-enabled devices, big data (analytics), people, processes and purposeful projects affect several industries.

Also the data aspect is critical (again with mind-blowing forecasts) and how all this (big) data is analyzed, leveraged and turned into actions or actionable intelligence that creates enhanced customer experience, increased productivity, better processes, societal improvements, innovative models and all possible other benefits and outcomes. The impact of the IoT from a sheer data volume and digital universe perspective is amazing. And the Internet of Things will surpass mobile phones as the largest category of connected devices with 16 billion connected devices being IoT devices

There are numerous reasons for the growing attention for the Internet of Things. While you will often will read about the decreasing costs of storage, processing and material or the third platform with the cloud, big data, smart (mobile) technologies/devices, etc. there certainly is also a societal/people dimension with a strong consumer element.

A factor that has also contributed a lot to the rise of the Internet of Things, certainly in a context of the industrial Internet of Things and smart buildings, to name a few, is the convergence of IT and OT (Operational Technology) whereby sensors, actuators and so forth remove the barriers between these traditionally disconnected worlds.

As companies increasingly started investing in Internet of Things technologies and scalable Internet of Things deployments instead of just pilot projects it quickly became clear that the Internet of Things as a term covered completely different realities which have little in common. The majority of the Internet of Things hype focused on consumer-oriented devices such as wearables or smart home gadgets. Yet, we can’t repeat it enough, there is a huge difference between a personal fitness tracker and the usage of IoT in industrial markets such as manufacturing where the IoT takes center stage in the vision of Industry 4.0 (you can for instance think about IoT-connected or IoT-enabled devices such as large industrial robots or IoT logistics systems). That’s why a distinction was made between the Industrial Internet of Things and the Consumer Internet of Things to begin with.

The Industrial Internet of Things (IIoT): is ‘machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes”. The main value and applications are found in the so-called Industrial Internet of Things or IIoT. In all honesty one of the main reasons why we started talking about the Industrial Internet of Things is to distinguish it from the more popular view on the Internet of Things as it has becoming increasingly used in recent years: that of the consumer Internet of Things or consumer electronics applications such as wearables in a connected context or smart home applications.

Typical use cases of the Industrial Internet of Things include smart lightning and smart traffic solutions in smart cities, intelligent machine applications, industrial control applications, factory floor use cases, condition monitoring, use cases in agriculture, smart grid applications and oil refinery applications.

It’s important to know that the Industrial Internet of Things is not just about saving costs and optimizing efficiency though. Companies also have the possibility to realize important transformations and can find new opportunities thanks to IIoT.

Those who can overcome the challenges, understand the benefits beyond the obvious and are able to deal with the industrial data challenge have golden opportunities to be innovative, create competitive benefits and even entirely new business models

The Consumer Internet of Things (CIoT)

About 5 years ago, consumers rarely saw what the Internet of Things would mean to their private lives. Today, they increasingly do: not just because they are are interested in technology but mainly because a range of new applications and connected devices has hit the market.

These devices and their possibilities are getting major attention on virtually every news outlet and website that covers technology. Wearables and smart watches, connected and smart home applications (with Google’s Nest being a popular one but certainly not the first): there are ample of you know the examples.

Although it is said that there is some technology fatigue appearing, the combination of applications in a consumer context and of technology fascination undoubtedly plays a role in the growing attention for the Internet of Things. That consumer fascination aspect comes on top of all the real-life possibilities as they start getting implemented and the contextual and technological realities, making the Internet of Things one of those many pervasive technological umbrella terms. Obviously, the Consumer Internet of Things market is not just driven by new technology fascination: their manufacturers push the market heavily as adoption means news business possibilities with a key role for data.

Below are some consumer electronics challenges to tackle first:

  • Smarter devices. Consumers are waiting for smarter generations of wearables and Internet of Things products, which are able to fulfil more functions without being too dependent from smartphones, as is the case with many of such devices today (think the first generations of smartwatches, which need a smartphone).
  • Security. Consumers don’t trust the Internet of Things yet, further strengthened by breaches and the coverage of these breaches. Moreover, it’s not just about the security of the devices but also about, among others, the security of low data communication protocols (and Internet of Things operating systems). An example: home automation standard Zigbee was proven easy to crack in November 2016.
  • Data and privacy. On top of security concerns, there are also concerns regarding data usage and privacy. The lack of trust in regards with data, privacy and security was already an issue before these breaches as we cover in our overview of the consumer electronics market evolutions.
  • A “compelling reason to buy”. The current devices which are categorized as Consumer Internet of Things appliances are still relatively expensive, “dumb” and hard to use. They also often lack a unique benefit that makes consumers massively buy them.

Whereas the focus of the Industrial Internet of Things is more on the benefits of applications, the Consumer Internet of Things is more about new and immersive customer-centric experiences. As mentioned, the Consumer Internet of Things typically is about smart wearables and smart home appliances but also about smart televisions, drones for consumer applications and a broad range of gadgets with Internet of Things connectivity.

The Internet of Everything (IoE) : brings together people, process, data and things to make networked connections more relevant and valuable than ever before-turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries.

It focuses too much on the things and, as mentioned, is also very broadly used. It’s why some started distinguishing between the just mentioned Consumer Internet of Things and the Industrial Internet of Things.

Cisco and other prefer to use the term Internet of Everything, partially because of that umbrella term issue, partially because of the focus on things and partially to provide context to their views and offerings. But it’s not just marketing. The Internet of Everything or IoE depicts crucial aspects of IoT, namely people, data, things and processes; in other words: what makes a business. It’s this mix that matters. Moreover, the classic illustration of the Internet of Everything also made clear what, for instance, machine to machine or M2M is all about.

We’ve based ourselves on that classic depiction and added the dimensions of value and data analysis.

The relevant four key drivers for IoE are listed below

The Internet of Robotic Things (IoRT): is a concept where intelligent devices can monitor events, fuse sensor data from a variety of sources, use local and distributed intelligence to determine a best course of action, and then act to control or manipulate objects the physical world, and in some cases while physically moving through that world

One of the major characteristics of the Internet of Things is that it enables to build far stronger bridges between physical and digital (cyber) worlds. You see it in all IoT use case and in the Industrial Internet of Things you see it in what’s called the Cyber Physical Systems.

Yet, in most case, the focus is predominantly on the ‘cyber’ part whereby data from sensors essentially are leveraged to achieve a particular outcome with human interference and with a focus on data analytics and ‘cyber’ platforms. The way it happens, as ABI Research, who came up with the IoRT concept (which is real today) puts it is that essentially many applications and business models are built upon passive interaction. The Internet of Robotic Things market is expected to be valued at USD 21.44 Billion by 2022

By adding robotics to the equation and turning devices (robots) in really intelligent devices with embedded monitoring capabilities, the ability to add sensor data from other sources, local and distributed intelligence and the fusion of data and intelligence in order to allow these devices determine actions to take and have them take these actions, within a pre-defined scope, you have a device that can control/manipulate objects in the physical world.

With collaborative industrial robots), warehouse automation (Amazon Robotics) and even personal robots for cleaning and so forth make it more tangible. It’s still early days for the IoRT but the projects and realizations in this next stage are real. IoRT is not tied to the consumer and industrial IoT distinction, it’s ever-present.

The Internet of Things is used in various industries for numerous use cases which are typical for these industries. On top of that, there is a long list of Internet of Things use cases that is de facto cross-industry. As the Internet of Things is embraced and deployed at different speeds throughout consumer and industrial sectors, we take a look at some of the main industries and use cases which drive the Internet of Things market and Internet of Things projects.

Patterns and shifts in the vertical industry and Internet of Things use case spend

Note that the biggest and/or fastest growing use cases are not always related to the biggest and/or fastest growing industries in terms of Internet of Things spending.

While it is expected that in terms of use cases there will be high growth in consumer-related use cases such as personal wellness and smart home applications, the largest majority of spending is and will be done by enterprises. The main reasons for this shift are below

  • The costs and scope of the investments. A full-blown, enterprise-wide Internet of Things project in industrial settings such as manufacturing or logistics is far more expensive than a smart home implementation.
  • The shifts in the major Internet of Things use cases and industries. Remember that the Internet of Things mainly started as an industrial and business sector phenomenon. Industries with many existing physical assets can realize fast cost savings and efficiencies of scale. That’s why today they spend more in Internet of Things projects than consumer segments where we see more ‘new’ devices, rather than existing assets.
  • The Consumer Internet of Things catching up. As industries keep leading the current waves of Internet of Things spending until 2020, the fact that they started first and the advent of ever more consumer use cases and better (safer and more useful) solutions means that gradually consumer Internet of Things catches up with Industrial Internet of Things spending.
  • The rise of cross-industry Internet of Things applications and of scenarios whereby consumers and businesses meet each other in business-driven initiatives (for instance, the push for telematics in insurance, the push for smart meters in utilities) has a leveling effect on the adoption of the Internet of Things and on spending.

Stay tuned…. Part 4 of this foray, we will look into the 8 best example usages of the world of IoT.

Please feel free to review my earlier series of posts 

Authored by Venugopala krishna Kotipalli

World of IoT – Part 1
 

In this series of posts, I will emphasize primarily over the world of IoT (Internet of Things). We’ll start with looking at the origins of IoT, its common elements and approaches, look at the market growth and trends for IoT in the industry. We will also touch base with the newer extensions of IoT like IIoT (Industrial IoT), CIoT (Consumer IoT), IoE (Internet of Everything) and IoRT (Internet of Robotic things).

IoT is an umbrella term for a broad range of underlying technologies and services depending upon the use cases and in turn are part of a broader technology ecosystem which includes related technologies such as AI, cloud computing, cyber security, analytics, big data, various connectivity/communication technologies, digital twin simulation, Augmented reality and virtual Reality, block chain and more.

The Origin

The idea of the Internet of Things goes back quite some time. The RFID has been a key development towards the Internet of Things and the term Internet of Things has been coined in an RFID context (and NFC), whereby we used RFID to track items in various operations such as supply chain management and logistics.

The roots and origin of the Internet of Things go beyond just RFID. Think about machine-to-machine (M2M) networks. Or think about ATMs (automated teller machine or cash machines), which are connected to interbank networks, just as the point of sales terminals where you pay with your ATM cards. M2M solutions for ATMs have existed for a long time, just as RFID. These earlier forms of networks, connected devices and data are where the Internet of Things comes from. Yet, it’s not the Internet of Things.

The Role and Impact of RFID

In the nineties, technologies such as RFID, sensors and a few wireless innovations led to several applications in the connecting of devices and “things”. Most real-life implementations of RFID in those days happened in logistics like warehouses and the supply chain in general. However, there were many challenges and hurdles to overcome (mainly warehousing and industrial logistics as RFID was still expensive).

An example of an RFID application – electronic toll collection. The use of RFID became popular in areas beyond logistics and supply chain management: from public transport, identification (from pets to people), electronic toll collection (see image), access control and authentication, traffic monitoring, retail outdoor advertising. That growing usage was, among others, driven by the decreasing cost of RFID tags, increasing standardization and NFC(Near Field Communication).

Journey of RFID to IoT

The possibility of tagging, tracking, connecting and “reading” and analyzing data from objects would become known as the Internet of Things around the beginning of this Millennium.

It was obvious that the connection of the types of “things” and applications – as we saw them in RFID, NFCs – with the Internet would change a lot. It might surprise you but the concepts of connected refrigerators, telling you that you need to buy milk, the concept of what is now known as smart cities and the vision of an immersive shopping experience (without bar code scanning and leveraging smart real-time information obtained via connected devices and goods) go back since before the term Internet of Things even existed. Th attention for IoT in numerous other areas without a doubt has led to the grown attention for it as you’ll read further.

Coining of IoT Term

According to the large majority of sources, the term Internet of Things was coined in 1999 by Kevin Ashton at MIT.

RFID existed years before talked about the Internet of Things as a system, connecting the physical world and the Internet via omni-present sensors. Team there wanted to solve a challenge as wired reports: empty shelves for a specific product. When shelves are empty, obviously no one can buy what’s supposed to be there. It’s a typical problem of logistics and supply chain. The solution was found in RFID tags, which were still far too expensive to be able to put them on each product. Once the benefit was realized, there were many who invested in the expensive RFIDs to derive the benefits. The rest is a standard system, solving miniaturization challenges, lowering RFID tags prices and…history.

Definition of IoT

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Physical devices are either designed for the Internet of Things or are assets, including living beings, which are equiped with data sensing and transmitting electronics. Beyond this endpoint dimension with devices, sensors, actuators and communication systems, the Internet of Things is also used to describe what is effectively done with the data acquired from connected things.

The Internet of Things describes a range of applications, protocols, standards, architectures and data acquisition and analysis technologies whereby devices and items (appliances, clothes, animals,….) which are equipped with sensors, specifically designed software and /or other digital and electronical systems, are connected to the Internet and/or other networks via a unique IP address or URI, with a societal, industrial, business and/or human purpose in mind. As you can read below, data and how they are acquired, analyzed and combined into information value chains and benefits are key in it. In fact, the true value of the Internet of Things lies in the ways it enables to leverage entirely new sources and types of data for entirely new business models, insights, forms of engagement, and ways of living and societal improvements

The Internet of Things is not a thing. Data which is acquired, submitted, processed or sent to devices, in most cases travels across the Internet, fixed lines, across cloud ecosystems or via (tailored) wireless connectivity technologies which are developed for specific applications of IoT

Bridging digital, physical and human spheres through networks, connected processes and data, turned into knowledge and action, is an essential aspect in this equation. In recent years the focus in the Internet of Things has shifted from the pure aspect of connecting devices and gathering data to this interconnection of devices, data, business goals, people and processes, certainly in IIoT.

Elements of IoT

Most IoT definitions have several aspects in common. Here are the elements they have in common:

  1. Internet of Things Connectivity

All IoT definitions include the connectivity and network aspect: a network of things, devices, sensors, objects and/or assets, depending on the source. It’s pretty clear that a dimension of networks and connectedness, we would even say hyper-connectedness, needs to be present in any decent IoT definition.

2. The Things in the Internet of Things

IoT-enabled assets, devices, physical objects, sensors, anything connected to the physical world, appliances, endpoints, the list goes on. They are all terms to describe what an essential part of a network of things. Some add words such as smart or intelligent to the devices. Let’s say that they contain technology that grants them an additional capability of ‘doing something’: measuring temperature or moisture levels, capturing location data, sensing movement or capturing any other form of action and context that can be captured and turned into data.

3. The Internet of Things and Data

This is part of that intelligent notion but it also brings us far closer to the essence. You can define the Internet of Things by simply describing all characteristics (“what it is”) but you also need to look at its purpose (“the why”).

4. Communication in the Internet of Things

Data as such is maybe not without value but it sure is without meaning unless it is used for a purpose and it is turned into meaning, insights, intelligence and actions. The data gathered and sensed by IoT devices needs to be communicated in order to even start turning it into actionable information, let alone knowledge, insights, wisdom or actions.

5. Internet of Things, Intelligence and action

We just touched upon this aspect. However, in most definitions we see that intelligence is attributed to just the network(s) and/or the devices. While we certainly need, for instance, ‘intelligent networking technologies’ in many cases and while connected devices have a capacity of action, the real intelligence and action sits in the analysis of the data and the smart usage of this data to solve a challenge, create a competitive benefit, automate a process, improve something, whatever possible action our IoT solution wants to tackle.

6. Automation

There is always a degree of automation, no matter the scope of the project or the type of Internet of Things application. Most IoT applications are essentially all about automation. And that often comes with costs and benefits. Industrial automation, business process automation or the automatic updating of software: it all plays a role, depending on the context.

7. Ecosystem

Meaning and hyper-connectedness is what we miss in many answers on the questions regarding what the Internet of Things is. We stay too descriptive and focused on just the technologies and don’t look at purpose and intelligent action enough

While the above mentioned elements come back in all Internet of Things definitions there are a few we miss that are essential in the evolving views regarding the Internet of Things as it moves from devices and data to outcomes and actionable intelligence, and ultimately to a hyper-connected world of digital transformation (DX) and business.

The aspect of hyper-connectivity and integration often lacks. In a context of a reality whereby devices, people, processes and information are more interconnected than ever before; an Internet of Things definition and approach just needs to mention these aspects as the Internet of Things is part of something broader and is more about data, meaning and purpose than about objects. A key element of that hyper-connectivity in the Internet of Things sphere is that sometimes mentioned ongoing bridging of digital and physical environments, along with human environments, processes and data as the glue, enabler and condition to create value when properly used for connected purposes.

Then there is also the possibility to create new ecosystems where connected device usage by groups of people can lead to new applications and forms of community ecosystems. Last but not least and we’ve mentioned this often before: no Internet of Things without security.

Stay tuned…. Part 2 of this foray, we will look into key definitions and approaches for IoT.

Please feel free to review my earlier series of posts 

AI / ML – Past, Present & Future – Part 6
 

Just a recap, we learnt in my last update, the different ways to harness the new age machine to enhance market competitiveness of your products and services. In this excerpt we are going to dwell upon the different ways to harness the new age machine in by and large the innovation quotient that we need to invest upon.

As we have seen throughout this series of posts, the innovation related to the intelligent systems and digital economy is both a catalyst for and an outcome that will allow your organization to discover opportunities that were never before visible or addressable. Innovation being the center stone, it can’t be a side project which is nice-to-have but its central to remaining relevant in the great digital build-out that we are experiencing and of course lies ahead of us. While machines will do more and more of our work, the process of innovation will allow us to discover entirely new things to do that are impossible to imagine and hard to predict but they will be at the core of what we do in the future.

Today, a new economy is emerging with a flurry of job categories that even a few years ago would have been hard to predict; social medial consultants, search engine optimizers, full stack engineers, content curators, and chief happiness officers. These all jobs that the tech economy’s equivalent to the Charles Babbages of the early starters would have imagined. AI is changing our world already, but in reality we have only begun to scratch the surface of where it will take us over the next 20, 50, 100 years. Your job is to imagine the new forms of value you can create with the new machines of the new revolution. Institutionalizing the role and importance of being open to the fruits of innovation is a hugely important role that you as a leader of the future need to play. The openness to innovation is not just a job of the company’s formal R&D department. It has to be a culture of innovation that each and every one of you should exhibit.

We have learned right through this series that the new machine will be your platform of innovation. Once you are instrumenting, automating, tracking and analyzing the core operations of your business an applying machine learning, innovation opportunities will be consistently unearthed. Innovation is thus a rich term with many different attributes and applications. It can be applied to many areas including some I have listed below.

With product innovation, team will gain continual insight as to how your products are being used, also what customer frustrations points exist, and where the obvious areas for improvement exist. These inputs definitely can’t be gauged without a thorough AI system in place. Once you have automated, instrumented and enhanced your company’s activities, the associated AI engines can be applied to innovation. The team will get greatly enhanced by the application of the new machine, primarily because it radically accelerates the scale and speed of the innovation process. As such, when the new machine is soon widely adopted, the rate of human progress in the 21st century (as defined by the cumulative growth of human knowledge and he pace of the innovation) will be at least 1000 times the average rate of the 20th century. Obviously the general factors affecting innovation in the organization (opinions, ideas, emotions, organization’s inertia etc) can bring down above prediction to may be by two orders of magnitude. Still the innovation quotient of 10 times is way higher than traditional R&D ways.

One of the core principle in these posts is that machines can do many things but that practical application should be focused on specific business processes and customer experiences. When you are making discovery investments, start at the process and experience level and imagine how the process can be restructured and reinvented with digital.

Discovery can be a risk. Invest too much in the wrong ideas and you go broke. Wait for somebody else to do it and you can miss the market opportunity of a lifetime. So what’s the best practice for bringing about this new form of innovation? We find too many managers looking for the new “the next great breakthrough” but that doesn’t work. The opposite approach is to ask how the new machine adds the most value – that is, by looking for continuous, incremental improvements or looking to hit singles on a consistent basis. This primarily caters to “change for better” but is implemented as small, continuous improvements that in time have a large impact. Your goal should be to become a Know-It-All business via instrumentation, sensors, big data and analytics. In the real world, organizations should establish a portfolio of initiatives focused on discovery, with a clear life cycle methodology that manages these initiates from inception through o ultimate success or failure. Central to their generative acts will be the belief that something better can be created. The true core of discovery is, after all, hope.

Obviously, please don’t forget that with the Gods come the devils as well. While most part of my posts are ushering in that AI is an age of miracles and wonder of technological marvels but in the hindsight we should also see a world of robots, more powerful human like machines taking over. Thus strike a balance.

In these posts, we have argued that the information technology innovations and investments of the past 4 decades are merely a precursor to the next waves of digitization, which will have truly revolutionary impacts on every aspect of work, society, and life.

As the last S-Curve’s growth rate continues its inexorable journey south, the new S-curve is gather momentum, and so are the companies  poised to lead this new charge. These are the companies that have learned how to master the 3 Ms, how to align the new raw materials of the digital age (data), the new machines (intelligent systems), and the new models (business models that optimize the monetization of data-based personalization).These are the companies that understand how to build and operate a know-it-all-business, that understand that intelligent machines aren’t to be feared but embraced and harnessed, and that are energized by the unwritten future rather than just trying to hang onto the glories of the past.

Below are the few mandatory steps that any organization should embark upon and leaders from organizations should help them implement.

The companies that are getting ahead are the ones acting on these ideas. Some companies we work with emphasizes one ‘play’ over another, while others recognize the holistic connection between all of the plays, automation enables enhancement, discovery uncovers how to achieve excessiveness, and so on. All of them, however, understand the need to act now, to not wait for more certain times ahead, more clarity over exactly what AI is, and what it will become. All of them recognize that the rise of the machine intelligence is the ultimate game changer we face today. All of them know that inaction will result in irrelevance. All of them know that fortune favors the brave and punishes the timid.

This is the last blog in the series on AI/ML and the related space. Hope you all enjoyed reading through the posts. Stay tuned while I come back with yet another series on a technology topic.

AI / ML – Past, Present & Future – Part 5b
 

Just a recap, we learnt in my last update, the different ways to harness the new age machine to enhance human experience and their related processes and analysis. In this excerpt we are going dwell upon the different ways to harness the new age machine in enhancing Market competitiveness.

The loom led to excessive clothing, the steam engine to excessive travel, and the factory model led to excessive refrigerators and televisions finding their way into homes all around the world. Before the revolutions that spurred them, these products were rare luxuries. So the concept of excessiveness is really quite simple, and old – as prices go down, demand goes up. As the new machines drives the price down, markets of excessiveness will be established, driving sales up to unimagined levels. The question now becomes, will you seize the advantage with the new excessiveness that is available or fall victim to it?

In the past, we have used raw materials, new machines, and hybrid business models to support them to create an unprecedented excessiveness that can in turn make it easily for all luxury goods to be easily available for common masses. A very good example of this excessiveness created is the need for heart surgeries that has pushed organizations to throw excessiveness and innovations in and eventually bring the costs down and thereby make it readily available for common masses. The results delivered in the case of cost reduction in heart surgeries is nether by magic nor by cutting corners. Yes, there are salary disparities between India and other countries, but these account for only a fraction of the cost difference. The vast majority of these dramatic savings come from the digitization of key processes. The business models considered here were purely hybrid, viz. some portions must of course remain highly physical – human – centric work performed by medical professionals on an actual patient – whereas others can be significantly digitized, such as monitoring patients and machines. By Breaking down the processes of surgery preparation, operation room management, and intensive care unit operations into discrete processes and experiences and then apply new technologies, hospitals cut costs to the point that it now can provide high quality care to many more people. In this instance, digital is literally saving lives.

The key point to note here is that setting a new price point is not a one-time thing but a continual process. As once automation takes hold of your products creation and delivery transition from being human- based to machine based they will become inherently the centric, and thus able to benefit from the general consensus that the speed and capability of our computers doubles every two years.

At this stage, it’s imperative to wonder how to kick start quickly on the excessive thought process. Below are seven approaches that might lead you to deliver positive results.

Focus on disruptive thinking

Organizations should now focused on new / disruptive thinking, it should keep its eyes and ears open to new companies that are coming after your business. The Key is that this team should be empowered to take an objective view of the tech-based companies that are looking to bring excessiveness into the industry and potentially eat your pie of business. In such cases, you can clearly view that the industry is clearly coming for that portion of your company and you need to marshal an appropriate response right away – whether it be to buy, to build, or to partner to address the threat.

Analyze areas of weakness

The new generation are key to arriving at where the current organization sucks. These fresh thinking blokes can offer a unique and highly valuable point of view regarding your traditional ways of doing business. As a best practice, a sub-group of these fresh thinkers should be focusing on weakness that can put your company out of business

Plan for a future cost reduction model

Leadership must ask had, even painful, questions about the implications of current products and services moving from expensive and rare, to cheap and nearly available everywhere. Of course, nothing will be truly cost less, one way or another, you need to find ways to grow revenue. However it’s healthy to have organizations start conceiving its products and services as the sum of their parts, which will add up to a certain price. All these parts have been be analyzed from a digital perspective to make them costless so as to bring down the cost of the overall product and service.

Innovative profit making

The question of how do we price our products differently, aimed at very different customer segments and entailing very different economics of margins. It definitely does worldly good for companies to start thinking as to how to bring down the cost but still be able to make adequate profits.

Search for Technical prowess

The movement comprises of individuals, teams, and companies enthusiastic about building new devices that live at the intersection of new functionality and low cost. We find such movements around individuals who while holding down their day job, are itching to really focus on their weekend avocation. Don’t look upon such individuals as uncommitted to the work at hand; rather, harness their talents, energy, and passions by putting them in places and positions in which their personal innovations can become your corporate innovations.

Personalize Product line

The key to focus on personalizing any product or service to your customer opens up an extremely new horizon of doing business. This is not a function of scale. It’s simply a function of applying the new machine to establishing one-to-one connections with your customers. After all, this had been the first goal so to say, the entire value chains and customer value propositions were focused on this pursuit. For instance, personalization is the new battleground in the apparel industry as we had seen in one of our last post.

Apply Digital Thought

The lowering cost paradigms is all about finding dramatic cost savings to open new markets. How best to find these breakthroughs and apply new technologies of AI to the parts of the sum (overall). It was advanced in past that almost every work activity could and should be broken down into discrete tasks and measured in time, motion and output. More important, performance levels and best practices could be applied to repetitive tasks to make them efficient. This will more or less drive competitiveness at your company.

Applying the above seven levers and making sure organization are actively pursuing each one of them will keep them active, always in search for best practices to enhance and improve their products and services while keeping the cost lower. This will result in obviously at the end of it an enhanced market competitive stature of the organization.

Stay tuned…. Part VI of this foray, we will continue to dwell upon the different ways to harness the new age machine in by and large the innovation quotient that we need to invest upon.

AI / ML – Past, Present & Future – Part 5a
 

Just a recap, we learnt in my last update, the different ways to harness the new age machine through Automation and Instrumentation and their related processes and analysis. In this excerpt we are going dwell upon the different ways to harness the new age machine to enhance human experience.

Let us recognize that all these scenarios in one way or the other are enhancing the human experience. Today driving places is so easy when compared to following directions from a print out. With smart GPS systems, whether as an app on our smart phones or embedded as an instrument in our vehicle’s dashboard, it’s far more difficult to get lost nowadays. The GPS systems we now take for granted provide a preview of coming attractions on how the new machines are enhancing more and more of our work and personal lives.

Below are some scenarios which illustrate how the current intelligent systems are enhancing human experience in each of the areas below. Obviously this is an infinite list

It’s therefore easier to judge this when it comes to personal choices that a vast majority of us will prefer to work with an enhanced human, the one who is equipped with all details from an intelligent system on their side. For these reasons, we see the forces of enhancement as positive and the concerns over automation-driven job substitution as ill-considered. As we outlined earlier, the vast majority of white-collar work won’t be replace by these new machines but will be made better with them. I believe that more than 80% of teaching jobs, nursing jobs, legal jobs, and coding jobs will be mode more productive, more beneficial, and more satisfying by computers – in other words, enhanced

The story of human evolution is, of course, in many ways the story of our tools, from the sharpened stones to the intelligent machine used by deep-learning pioneers today. This is the progression we are witnessing as we move into the digital age. Isn’t it?

One important but often overlooked aspect of enhancing work is to recognize the relationship that exists between enhancing a job/role/process and automating it. In many ways, automation and enhancement exist in a symbiotic, to –sides-of-the-same-coin way. To effectively enhance, one needs to automate. So the winners will be those who continue to believe in the progress created by technology, those who enhance, and those who understand the power of tools and who adapt to using them effectively.

All of us including senior management, need to enhance our current skills when it comes to engaging with others, leading, reasoning and interpreting, applying judgement, being creative and applying the human touch. These behaviors and activities are still far outside the purview of current and near-future technologies and will remain so for years to come, even as the new machines become more capable. By 2020, senior executives project that employees will need to improve their performance in below areas.

Major companies today are proving that even in a world of enhancement solutions, where people and machines work together in new ways, there’s still value in being human. Our work ahead will require us to double-down on the activities where humans have and will continue to have an advantage over silicon.

We are in an incredible time, when technology is significantly extending the envelope of human capability. Intelligent systems now allow us to do things at a level of productivity and profitability that even a few years ago would have seemed far-fetched and implausible. All of these possibilities and many more are being created by the injection of intelligence in to our tools. We have the potential to become smarter because our tools are becoming smarter. It’s these tools that are really at the heart of the progress we have made so far and the progress we will make ahead. Enhancement will be the force that causes the bar to rise for every one of us, in every organization and in every country in the world. If you can enhance the value you generate, you are doing the right things as machines being to do everything. Enhancement also introduces new avenues of opportunity that we need to explore to keep ahead.

Stay tuned…. Part Vb of this foray, we will continue to dwell upon the different ways to harness the new age machine in enhancing Market competitiveness and by and large the innovation quotient that we need to invest upon.

AI / ML – Past, Present & Future – Part 4
 

Just a recap, we learnt in my last update, the different aspects of what constitutes a business model that an organization should follow and how that impacts your overall foray into AI/ML implementation. In this excerpt we are going dwell upon the different ways to harness the new age machine through Automation and Instrumentation

As I have pointed out repeatedly in the previous parts of this blog series on AI/ML, industry is riding on the cusp of a huge new wave of automated work that is going to fundamentally change what millions and millions of people all around the world do, Monday through Friday, 8 hour work day. The attempt at automation of existing parts of your business with the new machine provides an opportunity to change the cost structure of your firm, while at the same time increasing the velocity and quality of your operations. We need to understand what automation actually is, which part of your business are best suited to be automated, which jobs will be most impacted, the benefits you can expect and the problems to avoid.

Automation is the first step in the journey that exhibits the tendency for industrial change to continuously destroy old economic structures and replace them with new ones. This will result in both revenue increase for the industry but more importantly a cost savings overall. Some study on the internet shows the below numbers to back up the generic idea in the different industries where Automation is more prevalent in.

This trend of applying automation technology to lower cost and improve productivity is playing out in nearly every industry. Like it or not, your competitor across the street will soon gain the massive benefit of digital automation of core processes. If you don’t keep pace, your cost structure will soon be unsustainable. Additionally, the saving generated through automation are what will then pay for the coming digital innovations. Fortunately most of us have a running start. We have been consuming automation for a long time, and much as with AI, once used it’s not even noticed. Let us consider some examples for such automations that we come across and still they go unnoticed while we are travelling out of station

  • Automated toll collections through EZ Passes on the highway while we pass through the toll booth without stopping
  • Parking pass generation while you arrive at the airport parking
  • Receipt of the boarding pass and you check-in baggage at one of airport kiosks
  • Getting cash from ATM while walking down to your departure gate

From your house to the airport gate, your trip was at least a half hour faster than in pre-automation days if not lesser. In any organization therefore, such automation are targeted best in the core operations areas, not visible to your customers. What if you could run these functions or processes at half the cost and with double the throughput? With continuous improvements and quality control and with all these aspects – every transaction – full instrumented and recorded? With the new machine you can.

Finding your Process/Automation Targets for immediate automation is the low hanging fruit you should embark upon.

  1. Highly repetitive tasks
  2. Tasks with low level of human judgement
  3. Tasks requiring low level of empathy
  4. Tasks generating and handling high volumes of data

Identification of your automation target will give your teams a clear path to success, but there still remain a significant hurdle in managing change with your organization. You will need to adapt the path depending on the complexity of what you are doing; what follows is a high level walk through, but the seven steps put together below for automating any process or task are basically the same.

I therefore have shown you above that automation is our new loom, our new steam engine. The cost savings generated from these next levels of automation will provide the cash needed to fuel investments in the new markets and new ideas. The data degenerated by automation is at the heart of creating new products, better customer relationships, and more transparency. Leaders who create the ongoing momentum from using automation – every quarter looking for new automation opportunities using the criteria and guidelines I have presented – will ensure they have the fuel needed to win. Also please do realize and remember that automation is not an end in its own right, it is simply a means to an end.

We are slowly moving into the instrumentation zone, where once an automation is instrumented and tracked, an invisible framework of code emerges around the object and this often provides more insight and value than the actual physical item itself. For instance the Amazon and Netflixs know your tastes in literature and movies better than your family and friends do without even coming in touch with you as a consumer. The race is to win through instrumentation, and established companies are changing the rules of competition across many industries.

There are now three key rules of competition when it comes to Instrumentation

Why instrument everything and build solutions around information? Because doing so sets you on the path to being a “Know-It-All” business. With sensors and instrumentation, it’s now possible to collect and analyze information about everything. To know everything about everything

While instrumentation and collection of data from each and every portion of physical thing on your enterprise does pose the vast opportunity to review, analyze and take business decisions, it also exposes the analyzed and sensitive data to hackers. This is where organizations have to be careful so as to keep their internal, important, competition eluding data secured and not misused in the wrong fashion. Some of key hacking horror stories are below and would give you a fair bit of idea why we need to be careful.

Competing with instrumentation is now becoming the default model for our modern economy. Instrumenting everything, accessing data scientists and other big data/analytics talent, and avoiding the dark side of the instrumentation are all tactics you must adopt to get started. Fortunes will be won and lost depending on your organizations ability to leverage the upsides of the instrumentation and mitigate its downsides.

Stay tuned…. Part V of this foray, we will continue to dwell upon the different ways to harness the new age machine through the enhancement to human experience, Market competitiveness and by and large the innovation quotient that we need to invest upon.

AI / ML – Past, Present & Future – Part 3b
 

Just a recap, we learnt in my last update, the making of Data that makes an AI system successful. In this excerpt we are going dwell upon the design and delivery of Digital business models and solutions thereof.

The ‘first wave’ of data creation, which began in the 1980s and involved the creation of documents and transactional data, was catalyzed by the proliferation of internet-connected desktop PCs. To this, a ‘second wave’ of data has followed — an explosion of unstructured media (emails, photos, music and videos), web data and meta-data resulting from ubiquitous, connected smartphones. Today we are entering the ‘third age’ of data, in which machine sensors deployed in industry and in the home create additional monitoring-, analytical- and meta-data.

Given that much data created today is transmitted via the internet for use, ballooning internet traffic serves as a proxy for the enormous increase in humanity’s data production. While as a species we transferred 100GB of data per day in 1992, by 2020 we will be transferring 61,000GB per second. Beyond increases in the availability of general data, specialist data resources have catalyzed progress in machine learning. ImageNet, for example, is a freely available database of over 10 million hand-labelled images. Its presence has supported the rapid development of object classification deep learning algorithms.

In summary, harnessing the power of the new machine alone is not enough. The final piece of the puzzle, and the ultimate determinant of your success, is surrounding it with the right business model.

The traditional retail behaviors of buying from the physical outlet have changed drastically as today, the amazons/flipkarts have changed the retail business models with speed and price (cheaper of course). Hence most of the industrial models are currently too slow, too expensive, and too cumbersome. They crumble under their own weight in the face of digital competition. In most well established organizations these business models and supporting processes make sure that the knowledge work could be harvested, refined and distributed to the right people at the right time and in the right format.

Of course such a buffet scenario sounds absurd. Yet you will soon look back on several aspects of your business with the same disbelief that Buffet views the old newspaper business. With the growing common appearance of the new machine, however, as I have outlined earlier stability is no longer a viable strategy. Competitors, new and old, will not only be able to change the rules of the game from the outside by delivery vastly improved customer experiences through digital with mobile apps. Instrumented products, and advanced analytics for one-to-one customer management. They will also being changing the basis of competition from the inside, using the new machine to rewire core internal processes. Doing so will fundamentally change their cost base, as well as the speed of their operations and their ability to derive insight on all aspects of the business. Truly better, faster, cheaper. Very simply, in the face of the new machine, manually based knowledge processes do not stand a chance. So the question still remains will the winning business model be just digital only. I guess it will be mixture of part physical and part digital. For instance: even if the tomorrow’s airplane carries the much of the passenger experience and flight operations through digital, it still would be a 280 ton, 300 seater physically. So essentially in an organization the decision will be based on which processes will physically remain intact and which processes will go digital and completely unrecognizable and obviously what becomes a mix of physical and digital – and to what degree.

Let us now look at building the winning Mix model of business and there you will come across two big insights in building one.

  1. Four misadventures to avoid
    • Confusion over best way to becoming digital
    • Following the digital leaders in our implementation
    • Going big bang in the digital journey
    • Obstructing a Digital change
  2. 5 ways to Harness the new machine
    • Build Automation
    • Instrumentation
    • Enhance human potential by Machine support
    • Cost effectiveness to compete in market
    • Investment for Innovation

Hence we have to radically rethink and fundamentally affect yet help us return to our humanity. These are the nit bits of all emerging Managements who are doing the hard work to rewire their companies for the fourth industrial revolution, to define and implement the new business models.

Stay tuned…. Part IV of this foray, we will dwell upon the construct of the business model with a focus on the 5 ways to harness the new machine.