Data is generated and captured in every aspect of our daily lives these days. As individuals, the phones in our pockets, watches on our wrists, our televisions, and even the cars we drive. On the industrial scale, we have the burgeoning Internet of Things (IoT), with myriad sensors deployed on everything from building sites to monitor material movement, to water gauges on farms to monitor rainfall and soil moisture.
This data is being generated from what is broadly called, cyber-physical systems (CPS), the intersection of the physical world with digital devices, sensors, computation, control and networking.
Like the internet connected people to information, these CPS are connecting information to the physical world. CPS are what underpins our transition to the 4th Industrial Revolution.
Founding executive editor, Kevin Kelly wrote in WIRED magazine of a world where “someday soon, every place and thing in the real world—every street, lamppost, building, and room—will have its full-size digital twin in the mirrorworld.”
This mirrorworld “will reflect not just what something looks like but its context, meaning, and function. We will interact with it, manipulate it, and experience it like we do the real world.”
Technologies such as digital twins will form the basis of the mirrorworld, creating a living 3D metaverse that mimic the real-world environment. Loaded with sensors streaming data from everywhere, these digital avatars will provide infinite analytical possibilities, allowing humans and machines to diagnose, optimise, and predict in ways never before dreamt of.
Much of the data generated by CPS has never existed before, providing many exciting opportunities to gain fresh insights about our natural and built worlds. However, transforming data at the scale required comes with many challenges.
Of most concern is our inability to cope with the data flowing from CPS. A typical data scientist will lay awake at night worried about the three V’s: Volume (amount of data); Velocity (the speed at which data is generated); and, Variability (differences in data types, quality, programming languages). With the onslaught of data coming down the pipe from CPS, the size of problems caused by the three V’s are beyond most data scientists’ capability to control.
It seems incongruent to say that the existence of CPS is the culmination of centuries worth of research and technological innovation, yet they appear to have snuck up on us, given our unpreparedness to cope with the data explosion they have caused .
Fortunately, there are many researchers, data scientists, and organisations collaborating to harness CPS to generate quantum leaps in the way in which we interact with our natural and built worlds.
Take for example the groundbreaking work undertaken by Australia’s preeminent research organisation the CSIRO. Within their cyber-physical systems unit, they are strapping microsensors to bees to better understand what factors are affecting colonies and pollination to reverse the unprecedented decline in bee populations globally.
One of the largest scale CPS programs in the world is Singapore’s smart nation initiative. Along with digitising all government services, the program is focussed on creating interconnected systems for urban living, mobility, and health. For example, town planning is linked to transport design to plan for the seamless integration of autonomous vehicles into their society.
We believe in the potential that CPS has to positively reshape our world, and are committed to solving the many data problems inherent in translating raw sensor data into meaningful, actionable insights about our natural and built worlds.
The idea of a mirrorworld is interesting, but right now, we’re not quite sure what’s looking back at us. If we have anything to do with it, that’s about to change.
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Authors | Steve Taitoko |
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