Sections

The Future Of Sensors: Business In High Definition

Kai Goerlich

All change begins with the ability to measure. For millennia, humans relied on our five senses to gauge the world around us in order to survive and thrive.

As civilization advanced, however, we started to use technology to expand those natural capabilities. We began building tools to measure time – first sundials and then sophisticated ones like the sky disc of Nebra and the Antikythera mechanism. Early maps on the walls of the Lascaux caves charted the night sky while the ancient Greek Anaximander drew the first map of the world. Beginning with telescopes and microscopes in the sixteenth and seventeenth centuries, and continuing today with the CERN particle collider, we’ve developed increasingly advanced tools to examine aspects of the universe beyond human perception.

Today, thanks to the explosion of low-cost sensors and high-powered processing and analytics capabilities, we are on the cusp of the next wave of magnifying our natural ability to assess the world around us and stretching the limits of human perception – if we can open our minds enough to let them.

The tiny engines driving the digital revolution

Sensors come in a variety of form factors and with wide-ranging functions: wearables like fitness and health trackers, infrared imaging and night vision sensors, motions sensors such as gyroscopes, chemical and biological sensors, accelerometers and torque sensors, light sensors, gestural sensors. Increasingly, we’re seeing combination sensors that are capable of gathering multiple types of data from the world.

Experts predict that the universe of sensors will grow exponentially in the near future, up to 100 trillion sensors by 2030, depending upon which estimate you believe. These tiny bits of technology are driving everything from robotics to self-diagnosing appliances.

A number of advancements are colluding to make these increasingly ubiquitous sensors both cheaper and more capable every day. Imagespeech, and voice recognition will advance to near 100% accuracy by 2025, according to the latest published research. Today, a passive RFID tag costs between seven and 15 cents to produce. While active tags are more expensive, the cost of these is also rapidly dropping. Emerging 3D printers will enable lower cost production of sensors (and nano-sensors) to embed in day-to-day items like glasses or apparel. These sensors will quickly make their way as standard issue into many places, including the 111 million new cars and the 2 billion smartphones that will be purchased in 2020. If you have one of the latest smartphones, you already have several sensors on board, including a magnetometer, barometer, thermometer, gyroscope, proximity sensor, accelerometer, and light sensor. Indeed, many future sensors will be practically invisible to us.

Perhaps more importantly, the analytics capabilities required to make sense of the staggering amounts of new sensor data – we could be talking brontobytes, or 1,000,000,000,000 petabytes – are also rapidly advancing. The speed of analytics will intensify thirty-fold by 2030, with 95% of queries answered in mere milliseconds, according to SAP estimates. That will be critical in transforming this truly big data into smaller, digestible bites of information. The question is whether or not we can cope with it. As Professor Dr. Yvonne Förster of Luephana University in Luneburg, Germany, points out, our devices already process and deliver information much faster than our human perception can track. As most of these technology-induced rhythms run outside our awareness, it will be interesting to see how we adapt to it.

Widening the doors of perception

Our innate biological senses and nervous systems are truly amazing. The human eye contains 2 x 108 sensors, the ear 3 x 104, and the nose 3 x 107. But with an expanding network of increasingly sophisticated and embedded sensors we’ll be able to expand our perception far beyond our human capabilities. Ultimately, we’ll be able to create an intelligent matrix of sensors and analytic tools to measure, detect, and analyze more data from the world around us. Looking beyond 2025, we will advance beyond data analysis as a distinct activity to more directly experiencing data as an additional aspect of life around us. We will experience the world in much finer detail using virtual reality and other technologies that tap into our biological senses at their roots.

Ultrasound, infrared, low frequency, and position sensors will increase our vision and hearing. Chemical sensors will amplify our ability to smell and taste. Mechanosensors will intensify what we can feel. Medical and biological sensors will monitor the health and status of humans, animals, and plants. And the mix of all the above sensors will be used to monitor a wide spectrum of parameters that are critical to the operation of machines, building, and living things.

Finally, there will be sensors that help us scan our environment for more precise navigation, logistics, weather prediction, agricultural planning, and pollution management. Sensors to watch for here include voice, facial recognition, chemical, biological, and 3D imaging sensors. Occipital Inc.’s 3D sensor provides a spatial view of the environment to be used in virtual and augmented reality and 3D scanning and printing.

We’ll certainly develop algorithms and analytics necessary to process sensor data in an increasingly automated and real-time fashion. But will our minds be able to grasp it all?

An approach that keeps the human at the center might prove helpful as we adapt to the new world of high-powered sensors. According to Professor Förster, we tend to consider technology as an enhancement of our biological nature and believe we can choose which types of technology we allow into our system. But when devices and sensors are ubiquitous, technology becomes like the air we breathe, rather than being a separate part of life, explains Förster. Thus the function of sensors should be to introduce new data streams that are compatible with our existing biological and value systems.

Getting under our skin

Researchers are already developing sensor technologies that are far more embedded than in the past. And they won’t just go into “things” like smart tennis rackets or ceiling fans. Nano-engineers at the University of California, San Diego, have developed a temporary tattoo that could enable non-invasive glucose testing. The FDA has accepted an application for the first digital drug-device that combines a pill for mental illness embedded with an ingestible sensor to track data on patients. MIT scientists have introduced a “Band-Aid of the future” that incorporates temperature sensors, and tiny, drug-delivering reservoirs.

In the future we will see more sensors embedded in humans, animals, plants, and all kinds of everyday items. But how much data do we actually need – and how much can we digest? Much of this data will exist in the background where algorithms will separate the insight from the noise, while new types of sensors will allow us to interact directly with our environment.

Company leaders should consider how they could benefit by combining existing data with the new sensor data that will soon be available. They should monitor the development of sensor technology with an emphasis on where sensor technology threatens to either bypass or optimize traditional business processes, and where new sensor capabilities widen the scope of what we can measure today. And they should keep an eye outside of their own domains for sensor advances that could transform their own businesses in different ways.

There’s no doubt that our five senses will soon be supplemented by these man-made sensors numbering in the billions and capable of measuring anything that we deem to be worthwhile. But deriving business value from them will require us to open our minds to the new possibilities.

Download the executive brief: Making Sense of Sensors

Sensors thumbnail

To learn more about how exponential technology will affect business and life, see Digital Futures.

Comments

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Idea Director of Thought Leadership at SAP. His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

Comments

Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

Comments

The Robotics Race

Stephanie Overby

As robotic technologies continue to advance, along with related technologies such as speech and image recognition, memory and analytics, and virtual and augmented reality, better, faster, and cheaper robots will emerge. These machines – sophisticated, discerning, and increasingly autonomous – are certain to have an impact on business and society. But will they bring job displacement and danger or create new categories of employment and protect humankind?

We talked to SAP’s Kai Goerlich, along with Doug Stephen of the Institute for Human and Machine Cognition and Brett Kennedy from NASA’s Jet Propulsion Laboratory, about the advances we can expect in robotics, robots’ limitations, and their likely impact on the world.

SAP_Robotics_QA_images2400x16002

qa_qWhat are the biggest drivers of the robot future?

Kai Goerlich: Several trends will come together to drive the robotics market in the next 15 to 20 years. The number of connected things and sensors will grow to the billions and the data universe will likewise explode. We think the speed of analytics will increase, with queries answered in milliseconds. Image and voice recognition – already quite good – will surpass human capabilities. And the virtual and augmented reality businesses will take off. These technologies are all building blocks for a new form of robotics that will vastly expand today’s capabilities in a diversity of forms and applications.

Brett Kennedy: When I was getting out of school, there weren’t that many people working in robotics. Now kids in grade school are exposed to a lot of things that I had to learn on the job, so they come into the workplace with a lot more knowledge and fewer preconceptions about what robots can or can’t do based on their experiences in different industries. That results in a much better-trained workforce in robotics, which I think is the most important thing.

In addition, many of the parts that we need for more sophisticated robots are coming out of other fields. We could never create enough critical mass to develop these technologies specifically for robotics. But we’re getting them from other places. Improvements in battery technology, which enable a robot to function without being plugged in, are being driven by industries such as mobile electronics and automotive, for example. Our RoboSimian has a battery drive originally designed for an electric motorcycle.

qa_qDo you anticipate a limit to the tasks robots will be able to master as these core technologies evolve?

Goerlich: Robots will take over more and more complex functions, but I think the ultimate result will be that new forms of human-machine interactions will emerge. Robots have advantages in crunching numbers, lifting heavy objects, working in dangerous environments, moving with precision, and performing repetitive tasks. However, humans still have advantages in areas such as abstraction, curiosity, creativity, dexterity, fast and multidimensional feedback, self-motivation, goal setting, and empathy. We’re also comparatively lightweight and efficient.

Doug Stephen: We’re moving toward a human-machine collaboration approach, which I think will become the norm for more complex tasks for a very long time. Even when we get to the point of creating more-complex and general-purpose robots, they won’t be autonomous. They’ll have a great deal of interaction with some sort of human teammate or operator.

qa_qHow about the Mars Rover? It’s relatively autonomous already.

Kennedy: The Mars Rover is autonomous to a certain degree. It is capable of supervised autonomy because there’s no way to control it at that distance with a joystick. But it’s really just executing the intent of the operator here on the ground.

In 2010, DARPA launched its four-year Autonomous Robotic Manipulator Challenge to create machines capable of carrying out complex tasks with only high-level human involvement. Some robots completed the challenge, but they were incredibly slow. We may get to a point where robots can do these sorts of things on their own. But they’re just not as good as people at this point. I don’t think we’re all going to be coming home to robot butlers anytime soon.

Stephen: It’s extremely difficult to program robots to behave as humans do. When we trip over something, we can recover quickly, but a robot will topple over and damage itself. The problem is that our understanding of our human abilities is limited. We have to figure out how to formally define the processes that human beings or any legged animals use to maintain balance or to walk and then tell a robot how to do it.

You have to be really explicit in the instructions that you give to these machines. Amazon has been working on these problems for a while with its “picking challenge”: How do you teach a robot to pick and pack boxes the way a human does? Right now, it’s a challenge for robots to identify what each item is.

qa_qSo if I’m not coming home to a robot butler in 20 years, what am I coming home to?

Goerlich: We naturally tend to imagine humanoid robots, but I think the emphasis will be on human-controlled robots, not necessarily humanshaped units. Independent robots will make sense in some niches, but they are more complex and expensive. The symbiosis of human and machine is more logical. It will be the most efficient way forward. Robotic suits, exoskeletons, and robotic limbs with all kinds of human support functions will be the norm. The future will be more Iron Man than Terminator.

qa_qWhat will be the impact on the job market as robots become more advanced?

SAP_Robotics_QA_images2400x16004Goerlich: The default fear is of a labor-light economy where robots do most of the work and humans take what’s left over. But that’s lastcentury thinking. Robots won’t simply replace workers on the assembly line. In fact, we may not have centralized factories anymore; 3D printing and the maker movement could change all that. And it is probably not the Terminator scenario either, where humanoid robots take over the world and threaten humankind. The indicators instead point to human-machine coevolution.

There’s no denying that advances in robotics and artificial intelligence will displace some jobs performed by humans today. But for every repetitive job that is lost to automation, it’s possible that a more interesting, creative job will take its place. This will require humans to focus on the skills that robots can’t replicate – and, of course, rethink how we do things and how the economy works.

qa_qWhat can businesses do today to embrace the projected benefits of advanced robotics?

Kennedy: Experiment. The very best things that we’ve been able to produce have come from people having the tools an d then figuring out how they can be used. I don’t think we understand the future well enough to be able to predict exactly how robots are going to be used, but I think we can say that they certainly will be used. Stephanie Overby is an independent writer and editor focused on the intersection of business and technology.

Stephanie Overby  is an independent writer and editor focused on the intersection of business and technology

To learn more about how humans and robots will co-evolve, read the in-depth report Bring Your Robot to Work.

Download the PDF

Comments

Tags:

What Is The Key To Rapid Innovation In Healthcare?

Paul Clark

Healthcare technology has already made incredible advancements, but digital transformation of the healthcare industry is still considered in its infancy. According to the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare, the possibilities and opportunities that lie ahead for the Internet of Healthcare Things (IoHT) are astounding.

Many health organizations recognize the importance of going digital and have already deployed programs involving IoT, cloud, Big Data, analytics, and mobile technologies. However, over the last decade, investments in many e-health programs have delivered only modest returns, so the progress of healthcare technology has been slow out of the gate.

What’s slowing the pace of healthcare innovation?

In the past, attempts at rapid innovation in healthcare have been bogged down by a slew of stakeholders, legacy systems, and regulations that are inherent to the industry. This presents some Big Data challenges with connected healthcare, such as gathering data from disparate silos of medical information. Secrecy is also an ongoing challenge, as healthcare providers, researchers, pharmaceutical companies, and academic institutions tend to protect personal and proprietary data. These issues have caused enormous complexity and have delayed or deterred attempts to build fully integrated digital healthcare systems.

So what is the key to rapid innovation?

According to the Connected Care eBook, healthcare organizations can overcome these challenges by using new technologies and collaborating with other players in the healthcare industry, as well as partners outside of the industry, to get the most benefit out of digital technology.

To move forward with digital transformation in healthcare, there is a need for digital architectures and platforms where a number of different technologies can work together from both a technical and a business perspective.

The secret to healthcare innovation: connected health platforms

New platforms are emerging that foster collaboration between different technologies and healthcare organizations to solve complex medical system challenges. These platforms can support a broad ecosystem of partners, including developers, researchers, and healthcare organizations. Healthcare networks that are connected through this type of technology will be able to accelerate the development and delivery of innovative, patient-centered solutions.

Platforms and other digital advancements present exciting new business opportunities for numerous healthcare stakeholders striving to meet the increasing expectations of tech-savvy patients.

The digital evolution of the healthcare industry may still be in its infancy, but it is growing up fast as new advancements in technology quickly develop. Are you ready for the next phase of digital transformation in the global healthcare industry?

For an in-depth look at how technology is changing the face of healthcare, download the SAP eBook Connected Care: The Digital Pulse of Global Healthcare.

See how the digital era is affecting the business environment in the SAP eBook The Digital Economy: Reinventing the Business World.

Discover the driving forces behind digital transformation in the SAP eBook Digital Disruption: How Digital Technology is Transforming Our World.

Comments

Paul Clark

About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.