Three laws of the next Internet of Things – the new platforming evolution in computing

By Mark Skilton, Global Director at Capgemini

There is a wave of new devices and services that are growing in strength extending the boundary of what is possible in today’s internet driven economy and lifestyle.   A striking feature is the link between apps that are on smart phones and tablets and the ability to connect to not just websites but also to data collection sensors and intelligence analytical analysis of that information.   A key driver of this has also been the improvement in the cost-performance curve of information technology not just in CPU and storage but also the easy availability and affordability of highly powerful computing and mass storage in mobile devices coupled with access to complex sensors, advanced optics and screen displays results in a potentially truly immersive experience.  This is a long way from the early days of radio frequency identity tags which are the forerunner of this evolution.   Digitization of information and its interpretation of meaning is everywhere, moving into a range of industries and augmented services that create new possibilities and value. A key challenge in how to understand this growth of devices, sensors, content and services across the myriad of platforms and permutations this can bring.

·         Energy conservation

o   Through home and building energy management

·         Lifestyle activity

o   Motion sensor Accelerometers, ambient light sensors, moisture sensors, gyroscopes, proximity sensors.

·          Lifestyle health

o   Heart rate, blood oxygen levels, respiratory rate, heart rate variability, for cardiorespiratory monitoring are some of the potential
that connecting Devices

·         Medical Health

o   Biomedical sensing for patient care and elderly care management,  heart, lung, kidney dialysis,  medial value and organ implants, orthopaedic implants and brain-image scanning.   Examples of devices can monitoring elderly physical activity, blood pressure and other factors unobtrusively and proactively.  These aim to drive improvements in prevention, testing, early detection, surgery and treatment helping improve quality of life and address rising medical costs and society impact of aging population.

·         Transport

o   Precision global positioning, local real time image perception interpretation  sensing, dynamic electromechanical control systems.

·         Materials science engineering and manufacturing

o   Strain gauges, stress sensors, precision lasers, micro and nanoparticle engineering,  cellular manipulation, gene splicing,
3D printing has the potential to revolutionize automated manufacturing but through distributed services over the internet, manufacturing can potentially be accessed by anyone.

·         Physical Safety and security

o   Examples include Controlling children’s access to their mobile phone via your pc is an example of parental protection of children using web based applications to monitory and control mobile and computing access.  Or Keyless entry using your  phone.  Wiki, Bluetooth and internet network app and device to automate locking of physical; door and entry remotely or in proximity.

·         Remote activity and swarming robotics

o   The developing of autonomous robotics to respond and support exploration and services in harsh or inaccessible environments. Disabled support through robotic prosthetics and communication synthesis.   Swarming robots that fly or mimic group behavior.  Swarming robots that mimic nature and decision making.

These are just the tip of want is possible; the early commercial ventures that are starting to drive new ways to think about information technology and application services.

A key feature I noticed in all these devices are that they augment previous layers of technology by sitting on top of them and adding extra value.   While often the long shadow of the first generation giants of the public internet Apple, Google, Amazon give the impression that to succeed means a controlled platform and investment of millions; these new technologies use existing infrastructure and operate across a federated distributed architecture that represents a new kind of platforming paradigm of multiple systems.

Perhaps a paradigm of new technology cycles is that as the new tech arrives it will cannibalize older technologies. Clearly nothing is immune to this trend, even the cloud,   I’ll call it even the evolution of a  kind a technology laws ( a feature  I saw in by Charles Fine clock speed book http://www.businessforum.com/clockspeed.html  but adapted here as a function of compound cannibalization and augmentation).  I think Big Data is an example of such a shift in this direction as augmented informatics enables major next generation power pays for added value services.

These devices and sensors can work with existing infrastructure services and resources but they also create a new kind of computing architecture that involves many technologies, standards and systems. What was in early times called “system of systems” Integration (Examples seen in the defence sector  http://www.bctmod.army.mil/SoSI/sosi.html  and digital ecosystems in the government sector  http://www.eurativ.com/specialreport-skills/kroes-europe-needs-digital-ecosy-interview-517996 )

While a sensor device can replace the existing thermostat in your house or the lighting or the access locks to your doors, they are offering a new kind of augmented experience that provides information and insight that enabled better control of the wider environment or the actions and decisions within a context.

This leads to a second feature of these device, the ability to learn and adapt from the inputs and environment.  This is probably an even larger impact than the first to use infrastructure in that it’s the ability to change the outcomes is a revolution in information.  The previous idea of static information and human sense making of this data is being replaced by the active pursuit of automated intelligence from the machines we build.   Earlier design paradigms that needed to define declarative services, what IT call CRUD (Create, Read, Update, Delete) as predefined and managed transactions are being replaced by machine learning algorithms that seek to build a second generation of intelligent services  that alter the results and services with the passage of time and usage characteristics.

This leads me to a third effect that became apparent in the discussion of lifestyle services versus medical and active device management.  In the case of lifestyle devices a key feature is the ability to blend in with the personal activity to enable new insight in behavior and lifestyle choices, to passively and actively monitor or tack action, not always to affect they behavior itself. That is to provide unobtrusive, ubiquitous presence.   But moving this idea further it is also about the way the devices could merge in a become integrated within the context of the user or environmental setting.  The example of biomedical devices to augment patient care and wellbeing is one such example that can have real and substantive impact of quality of life as well as efficiency in cost of care programs with an aging population to support.

An interesting side effect of these trends is the cultural dilemma these devices and sensors bring in the intrusion of personal data and privacy. Yet once the meaning and value of if this telemetry on safety , health or material value factors is perceived for the good of the individual and community, the adoption of such services may become more pronounced and reinforced. A virtuous circle of accelerated adoption seen as a key characteristic of successful growth and a kind of conditioning feedback that creates positive reinforcement.     While a key feature that is underpinning these is the ability of the device and sensor to have an unobtrusive, ubiquitous presence this overall effect is central to the idea of effective system of systems integration and borderless information flow TM (The Open Group)

These trends I see as three laws of the next Internet of things describing a next generation platforming strategy and evolution.

Its clear that sensors and devices are merging together in a way that will see cross cutting from one industry to another.  Motion and temperature sensors in one will see application in another industry.   Services from one industry may connect with other industries as combinations of these services, lifestyles and affects.

Iofthings1.jpg

Formal and informal communities both physical and virtual will be connected through sensors and devices that pervade the social, technological and commercial environments. This will drive further growth in the mass of data and digitized information with the gradual semantic representation of this information into meaningful context.  Apps services will develop increasing intelligence and awareness of the multiplicity of data, its content and metadata adding new insight and services to the infrastructure fabric.  This is a new platforming paradigm that may be constructed from one or many systems and architectures from the macro to micro, nano level systems technologies.

The three laws as I describe may be recast in a lighter tongue-in-cheek way comparing them to the famous Isaac Asimov three laws of robotics.   This is just an illustration but in some way implies that the sequence of laws is in some fashion protecting the users, resources and environment by some altruistic motive.  This may be the case in some system feedback loops that are seeking this goal but often commercial micro economic considerations may be more the driver. However I can’t help thinking that this does hint to what maybe the first stepping stone to the eventuality of such laws.

Three laws of the next generation of The Internet of Things – a new platforming architecture

Law 1. A device, sensor or service may operate in an environment if it can augment infrastructure

Law 2.  A device, sensor or service must be able  to learn and adapt its response to the environment as long as  it’s not in conflict with the First law

Law 3. A device, sensor or service  must have unobtrusive ubiquitous presence such that it does not conflict with the First or Second laws

References

 ·       Energy conservation

o   The example of  Nest  http://www.nest.com Learning thermostat, founded by Tony Fadell, ex ipod hardware designer and  Head of iPod and iPhone division, Apple.   The device monitors and learns about energy usage in a building and adapts and controls the use of energy for improved carbon and cost efficiency.

·         Lifestyle activity

o   Motion sensor Accelerometers, ambient light sensors, moisture sensors, gyroscopes, proximity sensors.  Example such as UP Jawbone  https://jawbone/up and Fitbit  http://www.fitbit.com .

·          Lifestyle health

o   Heart rate, blood oxygen levels, respiratory rate, heart rate variability, for cardiorespiratory monitoring are some of the potential that connecting Devices such as Zensorium  http://www.zensorium.com

·         Medical Health

o   Biomedical sensing for patient care and elderly care management,  heart, lung, kidney dialysis,  medial value and organ implants, orthopaedic implants and brain-image scanning.   Examples of devices can monitoring elderly physical activity, blood pressure and other factors unobtrusively and proactively.  http://www.nytimes.com/2010/07/29/garden/29parents.html?pagewanted-all  These aim to drive improvements in prevention, testing, early detection, surgery and treatment helping improve quality of life and address rising medical costs and society impact of aging population.

·         Transport

o   Precision global positioning, local real time image perception interpretation  sensing, dynamic electromechanical control systems. Examples include Toyota  advanced IT systems that will help drivers avoid road accidents.  Http://www.toyota.com/safety/ Google driverless car  http://www.forbes.com/sites/chenkamul/2013/01/22/fasten-your-seatbelts-googles-driverless-car-is-worth-trillions/

·         Materials science engineering and manufacturing

o   Strain gauges, stress sensors, precision lasers, micro and nanoparticle engineering,  cellular manipulation, gene splicing,
3D printing has the potential to revolutionize automated manufacturing but through distributed services over the internet, manufacturing can potentially be accessed by anyone.

·         Physical Safety and security

o   Alpha Blue http://www.alphablue.co.uk Controlling children’s access to their mobile phone via your pc is an example of parental protection of children using web based applications to monitory and control mobile and computing access.

o   Keyless entry using your  phone.  Wiki, Bluetooth and internet network app and device to automate locking of physical; door and entry remotely or in proximity. Examples such as Lockitron  https://www.lockitron.com.

·         Remote activity and swarming robotics

o   The developing of autonomous robotics to respond and support exploration and services in  harsh or inaccessible environments. Examples include the NASA Mars curiosity rover that has active control programs to determine remote actions on the red planet that has a signal delay time round trip (13 minutes, 48 seconds EDL) approximately 30 minutes to detect perhaps react to an event remotely from Earth.  http://blogs.eas.int/mex/2012/08/05/time-delay-betrween-mars-and-earth/  http://www.nasa.gov/mission_pages/mars/main/imdex.html .  Disabled support through robotic prosthetics and communication synthesis.     http://disabilitynews.com/technology/prosthetic-robotic-arm-can-feel/.  Swarming robotc that fly or mimic group behavior.    University of Pennsylvania, http://www.reuters.com/video/2012/03/20/flying-robot-swarms-the-future-of-search?videoId-232001151 Swarming robots ,   Natural Robotics Lab , The University of Sheffield , UK   http://www.sheffield.ac.uk/news/nr/sheffield-centre-robotic-gross-natural-robotics-lab-1.265434

 Mark Skilton is Global Director for Capgemini, Strategy CTO Group, Global Infrastructure Services. His role includes strategy development, competitive technology planning including Cloud Computing and on-demand services, global delivery readiness and creation of Centers of Excellence. He is currently author of the Capgemini University Cloud Computing Course and is responsible for Group Interoperability strategy.

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