Learning from the information network of life
Life is network based. Millions of years of evolution have allowed the natural world to develop what can be argued to be the most tried, tested and optimized protocols in existence: biological networks. The ability for Internet of Things (IoT) market stakeholders to interpret and effectively apply principles derived from the study of biological networks will lead to increased asset and resource productivity, as well as greater system resilience.
Networks that are extremely resilient, decentralised and yet connected, able to self-repair, and designed to grow and scale without complexity issues are standard in the natural world. Food webs, mutualism networks, neuronal networks, and gene regulation and metabolic networks have been optimised over millions, if not billions of years. Biomimicry – the practice of emulating life’s solutions – can provide a very useful set of principles for how to design systems within, and set guidelines for, the evolution of the IoT market.
Biological networks are already being used as a base reference for systems and network design. For instance, bio-inspired computing looks at how individual biological agents communicate with one another to optimally complete various processes. The study of Swarm Intelligence (SI) – where social, decentralised, self-organised organisms such as ants, bees, flocking birds and bacteria, are interacting locally to achieve intelligent ‘global’ behaviour – is being applied across a variety of sectors such as energy, transportation, telecommunications, medicine, defence and space. Within telecommunications, companies like British Telecom (BT) are currently using a subset of SI, Ant Colony Optimisation (ACO), to optimise things like scheduling, telecommunication, data network routing and process optimisation. Furthermore, companies such as ReGen Energy, an electrical energy demand management and automated demand response solutions provider, are applying ACO algorithms to optimise energy usage within the built environment.
Looking ahead, the proliferation of intelligent assets and IoT will further enhance our understanding of both what we have and what we are losing. From a circular economy perspective, intelligent assets-enabled information about what assets and resources we have is likely to be tremendously important. Within today’s market place, current practice requires individuals to upload information onto the internet, to show prospective users that a specific asset is available for sharing. With the proliferation of assets capable of real-time sensing and responding, a sharing platform of the future may no longer require human intervention but rather the assets making themselves available for use in real-time. This is a development that could increase asset and resource utilization tremendously, and enable new innovative business models within the sharing economy. Looking further ahead, there is potential to develop objects that are able to sense when they are no longer needed and self-disrupt (or disassemble), much like how a cell or organism would decompose in nature.
Intelligent assets will also guide decision-making about waste and discards by providing more knowledge than ever before about what assets and resources we are losing. The tagging and tracking of assets and resources enables businesses to know exactly where materials end up, and thus unlocks the possibility of closing material loops. Going a step further, technological developments making objects increasingly self-aware, will lead to reduced resource losses before the end of a given use-cycle. One example of this is Platelet Technology, developed by Breaker Technology Inc, which is designed to stop water leakage in pipelines throughout drought stricken California. Imagine the savings in resources such as oil, natural gas and methane through leakage prevention, if all our pipelines were intelligent enough to heal themselves. Another space to watch is the development of intelligent buildings, automatically adapted to changing of seasons. Building materials that can sense and respond to environmental conditions (awnings can already open and close dependent on sun exposure – ‘mimicking’ a flower) can start to make resource use within them extremely efficient as well as more comfortable for their users.
The application of many technologies enhancing our understanding of what we have and what we are losing is currently cost prohibitive – and the challenge is to pay for complexity and interconnectivity. In the natural world, you have complex, interconnected material systems built out of cheap building blocks, which can respond to external stimuli. In the example of the flower, the sunlight triggers the opening of the flower head. Within our awning example however, a large range of unrelated technologies may need to be combined. The sensor is made of one set of technologies, the material that is being opened and closed is another set of technologies and then the motor to open and close this material is yet another, rendering the overall system highly costly.
Even though in many instances an elegant, bio-mimicking ‘solution’ already exists – for example in the awning case electro-active polymers sensitive to everything from UV light to change in pH levels, to an electrical impulse – it is still at academic or early R&D scale. It is of course hard to say when such new technologies will commercialise. But current developments in enabling technologies such as 3D printing – which will begin to allow us to be able to embed functionality within a single material – will likely accelerate progress in this area.
Resilient IoT market evolution, as well as our ability to find out exactly what we have and what we are losing, can all be informed through observation and study of life in our natural world. The way in which natural systems access, store, and share information about themselves can – and should – be considered in order to design intelligent assets that harness maximum asset and resource productivity.
As part of an ongoing collaboration between the Ellen MacArthur Foundation, McKinsey & Co. and the World Economic Forum called Project MainStream, a new report, Intelligent Assets: Unlocking the circular economy, was launched analysing the potential of pairing the circular economy with the Internet of Things.