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Future Of Affective Computing

According to new market research report the global affective computing market to increase from USD 12.20 billion in 2016 to USD 53.98 billion by 2021, at a Compound Annual Growth Rate (CAGR) of 34.7%. The affective computing market is growing rapidly, owing to the increasing need for data archiving tools to organize the data generated from varied end-use sectors.

Facial feature extraction software is expected to grow during the forecast period

The research study for the global affective computing market encompasses the analysis of the market on the basis of software, which is further segmented into speech recognition, gesture recognition, facial feature extraction, analytics software, and enterprise software. The deployment of facial feature extraction software is mainly driven by the increasing demand expression recognition technique, used by various end-use sectors, especially, healthcare & life sciences and media & entertainment

The healthcare and life sciences sector is expected to hold the largest market share

The affective computing end-users are segmented into academia & research, media & entertainment, government & defense, healthcare & life sciences, Information Technology (IT) & telecom, retail & e-commerce, automotive, and Banking, Financial Services, & Insurance (BFSI). The healthcare and life sciences sector holds large scale application areas for affective computing technology, which include facial expression recognition for the specially-abled children (autism & dyslexia) and detection of psychological disorders, thereby holding the largest market share among other end-use verticals studied for the market analysis.

Asia-Pacific is expected to be the most lucrative market in 2016

The research study encompasses regional market analysis for North America, Europe, Asia-Pacific (APAC), and the Rest of World (RoW), along with some of the major countries in specific regions. North America is expected to hold the largest share in the affective computing market in 2016, which may then overshadowed by the APAC region, by the end of forecast period.

The rapid developments in infrastructure and higher adoption of digital technologies are the two major drivers that increase the demand for the affective computing market. Furthermore, the U.S is the most technologically-advanced region, with the presence of different business verticals in this region, such as BFSI, healthcare, and retail & e-commerce.

The prominent players in the affective computing market are Google Inc. (California, U.S.), IBM Corporation (New York, U.S.), Microsoft Corporation (Washington DC, U.S.), Saffron Technology (North Carolina, U.S.), Softkinteic System S.A. (Brussels, Belgium), Affectiva (Waltham, U.S.), Elliptic Labs (Oslo, Norway), Eyesight Technologies Ltd. (Israel), Pyreos Ltd. (Edinburgh, U.K.), Cognitec Systems GmbH (Germany), Beyond Verbal Communication Ltd. (Tel Aviv, Israel), Numenta (California, U.S.), GestureTek (Canada), and SightCorp (Amsterdam, the Netherlands).

Kai Goerlich is Research Director, IoT, Supplier Networks, and Digital Futures for SAP

1. McKinsey Global Institute, The Internet of Things: Mapping the Value Beyond the Hype (McKinsey & Company, June 2015), https://www.mckinsey.de/sites/mck_files/files/unlocking_the_potential_of_the_internet_of_things_full_report.pdf
2. “A Guide to the Internet of Things,” Intel Corp., accessed April 14, 2016, http://www.intel.com/content/dam/www/public/us/en/images/iot/guide-to-iot-infographic.png
3. SPB Global, A Trillion Sensors Is the Equivalent of 150 Sensors per Human on Earth. September 26, 2014 http://spb-global.com/uncategorized/trillion-sensors-equivalent-150-sensors-per-human-earth/
4. Julio Bezerra, Wolfgang Bock, François Candelon, Steven Chai, Ethan Choi, John Corwin, Sebastian Digrande, et al. The Mobile Revolution: How Mobile Technologies Drive a Trillion-Dollar Impact (The Boston Consulting Group, January 2015), ch. 2, https://www.bcgperspectives.com/Images/The_Mobile_Revolution_Jan_2015_tcm80-180510.pdf
5. Cisco, Global Cloud Index (GCI), 2015 http://www.cisco.com/c/en/us/solutions/service-provider/global-cloud-index-gci/index.html
6. IDC, The Internet of Things and Digital Transformation: A Tale of Four Industries, 2016, http://www.digitalistmag.com/executive-research/internet-of-things-and-digital-transformation-tale-of-4-industries
7. IDC, The Internet of Things and Digital Transformation: A Tale of Four Industries
8. SPB Global, A Trillion Sensors Is the Equivalent of 150 Sensors per Human on Earth

The Importance of the Internet of Things : Live Business

The Internet of Things (IoT) is not merely a step along the path to digital transformation; it is the driving force.

The real value of the IoT doesn’t come from all the connections it creates but from the data it generates. With real-time data analytics, the IoT becomes a live communications network for fostering insights and improvements. It will also become the foundation of Live Business, in which companies will be able to sense and respond to customers in the moment.

Sensors are the messengers of the IoT, and by 2030 there will 1 trillion of them.³ By putting sensors on everything around us – even inside of us – we will be able to exchange information and participate in a global data network. The IoT will become ubiquitous.

New Interactions Between People, Things, and Machines

We will see many new interactions between people, things, and machines that today seem like science fiction (see Figure 1). Many of the things in our daily lives at home and work will interact with each other, enabling us to use them in new ways. In this connected world, having access to things like cars will become more important than owning them.

At the human-to-machine level, we will be able to gauge the status of machines, receive warnings when they need maintenance, and control their roles in production at any given moment. The IoT will also enable us to control robotic extensions of our bodies, such as replacements for lost or disabled limbs or suits to improve our strength and other capabilities. And humans and machines will work together as teams, communicating through the IoT.

Using the IoT, machines will coordinate and communicate with other machines to create large armies of automated bots capable of acting together in swarms, as ants do in nature. Machines will also be able to monitor one another for potential problems and perform repairs without human intervention.

While mobile made people a part of the digital revolution, the IoT enables everything else to be part of that transformation. Because the IoT will affect so many different aspects of the economy, its generated value will exceed that of mobile.

Mobile started in 1990 with 2G, got more serious in 2000 with 3G, and finally kick-started the smartphone with 4G in 2010. With each technical leap, mobile’s social and economic impact increased in areas such as healthcare, finance, and education.⁴ The Internet may have connected many people in the world, but mobile gave them true global access. Mobile also allowed individuals and small and midsize enterprises to join a global economy that had long been dominated by big companies.

Mobile had a direct economic impact of $3 trillion on a global value chain in 2014, created 11 million jobs in the global value chain, and resulted in billions of R&D investments and startups.⁵ This transformation was the result of a huge investment from many players within IT and telecommunications that developed the core technologies, infrastructures, mobile networks, apps, and devices.

While behind mobile, the IoT is following a similar path. It started as a concept around 2000, is now in its second wave of development, and is experiencing exponential growth. Not only are IT and telecommunications companies investing in the IoT; so are players from outside the classical digital markets.

The IoT won’t remain behind mobile, however. It will spark a transformation that will exceed mobile’s by connecting everything together. We expect nothing less than a reinvention of interactions, communications, and services on a global scale, creating new jobs and opportunities.

As stated earlier, the IoT’s real value isn’t in the connections but in the data it creates. This massive digitization allows us to gather data and information and come up with decisions in the moment. When the IoT is integrated into the overall business strategy, a company has the opportunity to become a Live Business – when the entire business focuses on sensing and responding to customers in all the moments that matter most to them. Only companies that embrace the culture of a Live Business will take full advantage of the IoT.

How do you embrace that culture and create a live IoT strategy? Here are five steps to building that strategy.

Strategic Asset Management

Most companies today don’t have a real-time information repository of their assets, yet fixed assets can account for as much as one-third of all operating costs. Even in a highly automated manufacturing process, then, strategic IoT-based asset management can help save costs and resources and define a new path for innovation. With the IoT, businesses can monitor and evaluate asset usage patterns and maintenance routines, estimate current asset values, and find new ways to optimize asset use. Moreover, companies can share their assets with business partners, which will drive down costs and potentially uncover new business models. Companies can manage their assets with the IoT by optimizing routing for cars and trucks involved in logistics services, reducing machine downtime through remote maintenance and predictive analytics, and improving logistics and production planning by combining data from the IoT with demand and logistics.

Customer Experience

Digitization is radically changing the customer experience. By using the IoT as a direct feedback loop throughout the customer journey, businesses can enhance every purchase and interaction experience to transform passive consumers into live interactive partners and co-innovators. The true benefit of the IoT in this case is to offer a personalized and contextualized experience for customers in the moment.

Product and Service Experience

The IoT is enabling businesses to deliver more proactive and interactive products and services, which improves the brand experience and customer loyalty. Moreover, businesses can use the IoT to improve their products and services and co-innovate with customers, while remaining constantly in touch with them to understand their changing needs and wants.

Environmental Scanning

Sensor technology is constantly improving, which will allow more devices and machines to proactively monitor their environments and deliver a live view of the world around us at a much higher resolution. Companies will be able to use sensors to scan the environment to improve navigation, logistics, city planning, weather prediction, agricultural planning, and pollution management, for example. By combining real-time IoT information with existing data, organizations can react faster to change, create new insights, and develop new products and services.

Advanced Cooperation

Many devices and daily things around us will be enabled to interact with humans and with each other, creating a totally new experience in the physical world. We are already exploring connected and interactive cars and various forms of wearables.

As a Service

The move from products to services has been under way for some time, but digitization will speed up the transition, as the IoT allows companies to more directly serve their customers. The IoT will also help companies meet increasing customer demand for live service. Companies should use the potential offered by the IoT to develop new services along the product lifecycle and look for ways to create services using existing capabilities within the organization.

Resource-Optimized Innovation

Using the IoT, companies can make their products more interactive. They can monitor the actual use of their products, getting live feedback from customers and gathering data about longevity and performance. Products will no longer be designed once but will go through multiple iterations as part of a continuous, real-time innovation process. Not only will products become better over time, but customer loyalty will also be improved.

Omnichannel Customer Experience

Today’s digital customers demand a seamless shopping experience in all channels. Retailers and consumer-product companies must close any gaps between offline and online experiences. The digital IoT-driven channel will improve the brand experience and create opportunities for co-innovation.

Business Awareness

Today’s businesses are operating in a 24-hour real-time environment. Combined with a live-data analytics strategy, the IoT can be used as an antenna to reveal business changes. By getting faster and better information about demand changes and altered buying behavior, by predicting potential disruptions, and by identifying opportunities, companies will significantly increase their resilience in the marketplace.

Steps to Big Data Success

By Sudhi Sinha, Vice President of Product Development, Building Technology & Services, Johnson Controls

A great convergence occurred several years ago in information technology, with the cost and capacity of computer storage, processing, and networking all improving at the same time. This trifecta brought us to an inflection point where new technologies such as Hadoop could unlock unprecedented volumes of data and deliver new business value. That is the essence of the much-talked-about phenomenon known as “big data.”

In practical terms, big data means it is now feasible to collect, store, and use all available data, leading to new insights derived from ever-more sophisticated analytics. This presents a great opportunity to increase the value of existing data while also preparing the ground for the deluge of additional data expected to be unleashed by the Internet of Things, or IoT— the network of information generated by people, objects, and the environment.

How did we get to this place? Historically, large data sets needed to be structured and stored in a very specific way in order to then apply queries and analytics. From the columns and rows of what conceptually was much like a vast spreadsheet, deriving insights was an inflexible process where the very structure of the data was predefined and tended to make the range of conclusions all but inevitable.  In that environment, out-of-the-box thinking was almost impossible.

Today, big data technologies have overcome the limitations of past practices by breaking data sets into multiple components, distributing and analyzing those components on different processors, and then aggregating the results to deliver a meaningful picture of the whole that is not constrained by a specific, preordained order or structure.

As the ability to use all that data and run analytics on it has increased and improved, businesses are suddenly able to access new types of insights. It is the “art of the possible” for data.  Furthermore, now that the analysis encompasses all the data rather than just samples, the results are more accurate and   you can look at data in connection with more scenarios, sources, geographies, and applications. Your view of what is possible starts to broaden.

Combining Big Data and the IoT

Big data technologies are maturing, and they are widely applied across many industries. In automotives, for example, a manufacturer can incorporate data from warranty and maintenance activities or even a customer’s visit to the auto body shop to better understand patterns of failure.

Collecting data from dealers in different states is not new. But big data takes this activity to the next level. For example, marrying the actual weather data in a region to vehicle failure information allows manufacturers to begin developing predictive analytics. Somewhat simplistically, cars in Massachusetts may be found to suffer more cold-induced battery failures while vehicles in Texas may see more problems with air-conditioners.  But folding in other data streams flowing from the Internet of Things enables more nuanced predictions. Think how the somewhat obvious prediction that cars in cold climates suffer from battery failures and in hot climates experience air-conditioner problems can be enhanced by factoring in local traffic information, say, or sensor data from the car itself.

Consumer data is central to retail operations and to the airline, ticket, and travel industries. In these instances, you are trying to understand demographics and individual consumers in the context of location, season, trends, and so on. Big data is a powerful tool for bringing together what you know about those factors and integrating new sources of information – for example, sensors in a retail facility or weather for a travel site – to produce deeper insights.

Putting Big Data to Work in Your Business

To realize the value of big data and capitalize on the emerging  Internet of Things, follow this step-by-step approach:

1. Build a Strategy Framework.
  It is vital to develop a clear conceptual understanding of big data and how its potential might map to your own organization’s needs.  This should probably begin with a review of existing business intelligence efforts and data sources. But don’t stop there; look further and see whether there might be other data sources that aren’t being utilized or processes that could be better instrumented to provide valuable data. Remember, big data means BIG. More is generally better.  Think about the kind of insights big data might be able to provide, and then get ready for the next steps, when you will move ahead and engage the organization.

2. Create an “Opportunity Landscape.” 
 If the full potential of big data is a gold mine, the tactical projects that can get you started are gold coins.  The point is to focus initially on a small number of projects or initiatives with the potential for significant payback.  These could be aspects of your business that have not performed as expected and where data is available to potentially change the game.  When you’ve found the gold in those projects, you will be better able to gather resources to finance the gold mine and begin to extract widespread rewards for the organization.

3. Effectively Manage Big Data Projects. 
This means having a good grasp on the learning that may be transferable from other transformation and IT projects, as well as focusing on what is really unique.  Depending on the existing capabilities of your organization, big data may require investments in human capital—the IT experts and data scientists who can help ensure that you get the desired results. Because big data is by definition an evolving activity, having a robust project-management framework can help you keep things on track and moving in the right direction. That approach can also help you steer the initiative toward new and emerging opportunities.

4. Build the Right Technology Landscape. Even if you are an IT professional, the nuances associated with big data may be eye opening.  A big data initiative does not have to “break the bank” but it will likely require some specific investments.  The good news is that big data initiatives are generally less expensive and less complex than the massive data-warehouse projects that some organizations have built using traditional IT tools—a sort of “brute force” attempt to garner more value from corporate data. The best news is that starting small means your initial expenses can be quite low.

5. Build a Winning Team.
 Even in an era where technology is so critical, the human factor can make the difference between success and failure. Big data projects call upon a range of skills. Obviously, some of these are pure IT skills; others have to do with mastering the data science side of big data. But deep business knowledge is also vital – having the ability to dig into operational realities and discern issues that can be attacked with big data. Recruiting the people you will need for your big data projects, and then organizing, managing, and motivating them, is a case of making investments up front that will pay over the long term and yield future success.

6. Manage Your Investments and the Monetization of Your Data.  
The valuation and monetization of data is almost a “secret sauce” aspect of big data.  Having an approach to help you weigh the costs of big data with its benefits can help you make decisions that are most likely to be profitable and meaningful. This inquiry starts at a granular level and helps you develop an appreciation of the true value of data and its costs.  If you take this path you’ll never look at gigabytes the same way again, and you’ll begin to develop a practitioner’s instincts for harnessing information cost-effectively.

7. Effectively Drive Change.
 Your initial big data steps may not rock the boat too much, but over time, big data can upend assumptions, sometimes even assumptions that have been driving the entire business.  With big data, you have the potential to cut through the fog and know the things that have always seemed unknowable.  If that sounds hard to believe, think about how much data is not used effectively now. Add to that the new data that may become available in the near future, through sensors, better use of existing systems, and new external sources. To ensure that all of this data helps the organization, plan to implement change-management practices and start teaching your organization how to be more agile, adapting quickly to new assumptions driven by fresh insights.

8. Communicate Effectively.  
Change can only be mastered with effective communication. This isn’t simply a one-way street.  Listening is vital, too.  For an organization to ride the big data wave successfully, everyone should be “on board.” Only a small percentage of the organization may need new skills, but because big data can alter how business is conducted, everyone needs to be aware that change is afoot and to understand their stake in the future.

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In the final analysis, big data is about opportunity. It is the embodiment of the old adage, “knowledge is power.” By rebuilding your business upon the collection and analysis of big data – data that will expand exponentially as the Internet of Things emerges and matures – you can create a better future.