Ten Axioms of IoT
Thought Leadership, Digitization, Energy/Utilities, Mobility
Globally, society is currently going through a critical inflection point. Until now, all decisions were made by people, our brains. However, our capability is beginning to plateau. No matter how much effort or time we spend to increase our brain performance, we will only ever achieve a fraction of a percent improvement. Conversely, we are concurrently experiencing a massive unfolding opportunity where technology, specifically compute, network and storage performance, is improving annually at almost exponential rates. There is an obvious divergence in capability improvement between computing (“machines”) and the human brain. At the same time, we are generating more data than ever – zettabytes per annum. The proliferation of mobility, cloud and the internet of things (IoT) is accelerating data production. Fortunately, the research conducted over the last five decades in artificial intelligence (AI) can now become both useful and powerful. Previous obstacles for AI, such as insufficient data and performance, are rapidly disappearing. We can now generate the data and have the required IT performance at a reasonable and justifiable cost. Therefore, society is primed and ready to move through this inflection point from “human scale” to “machine scale”.
Axiom #1: As global economies increasingly adopt and deploy technologies that enable digitisation, they are transitioning from ‘human-scale to machine-scale’. Businesses are doing this in order to leverage the power of technology and software which already do what no human can match in terms of speed, cost, efficiency and/or precision. Cisco is already, and has been for over 10 years, playing a crucial role in digitisiting the physical world and securely connecting anything that can be digitally connected. This is a critical part of the digital supply chain, as without connectivity, computers would not be able to access, process or act on the data. There are three outcomes we seek from digitisation and IoT: human augmentation, automation and prediction.
Axiom #1 – Expected Outcomes from IoT:
Axiom #2: Automation involves eliminating or re-engineering human involvement in a specific process. Automation requires three critical ingredients – measurement (to generate data), computation (to process the data) and action (to do something with the data). These are also the three basic functions of Cisco’s Intent-Based Networking (IBN) [NW]. This ‘closed loop’ concept has been an integral part of engineering control systems (eg SCADA) for decades. What is new, is the volume of data and powerful technology that is now available at an affordable cost.
Axiom #2 – Key Ingredients of IoT:
Axiom #3: There are two key components required to measure the physical world and enable automation: sensing and connectivity. Sensing may be in the form of a sensor, a camera, a Lidar or a processor. Connectivity is the means of transferring the data measurements produced to a computation device. Sensing and connectivity provide data that enable a product to externalise its capabilities and provide a range of new opportunities and services. For example, an intelligent connected car can generate data to make it safer, more reliable (through predictive maintenance data) or find faster routes.
Axiom #3 - IoT is not about the ‘thing’ or connections, it is about the data and the collections.
Corollary: In less than a decade, the cost of connecting to a thing will be zero
Axiom #4: Basic mathematics theory says that the more data points a statistical analysis is provided with the more accurate and reliable the analysis will be. Digital and IoT takes advantage of this notion by generating far more data points (measurements) than was ever possible, even just a few years ago! The more data points generated, the more accurate can be the statistical result. By combining the power of computing with large volumes of the right data, we are thus able to provide more reliable and better outcomes (see Axiom #1).
Axiom #4 - Predictions can be improved by averaging the predictions of many. (Ensemble Principle)
Axiom #5: According to Einstein, “The formulation of the problem is often more important than the solution”. While amassing data may seem important, the critical question to ask is ‘what do you need the data for?’. Most organisations already have more data than they can manage, yet most often don’t have the right data. If they did, would they know what to ask of the data? If they are able to formulate the problem, how would they go about finding the answers needed within the data? Digital leaders thoroughly understand these three questions and typically leverage computers in conjunction with AI and machine learning to find the answers.
Axiom #5 – Right question, right data, right method.
It is not about having plenty of data, or big data. The key is knowing:
Corollary: By 2025, 40% of data will never get to the cloud.
Axiom #6: Cyber security crime is already at an all-time high and negatively impacting global economies by upwards of one percent of GDP [Hath]. We are becoming more mobile, we are using more cloud services and we are expanding IoT deployment to tens of billions of connected things, thereby expanding exploitation and attack opportunities. Our situation will inevitably get worse if we don’t take the right precautions. Most of the new IoT solutions coming to market are from vendors with little or no cyber security ability or expertise. Cisco continues to invest billions of dollars in developing cyber security solutions that enable organisations to continue taking advantage of the benefits of digitisation through trusted mobility, cloud and IoT technologies.
Axiom #6 – If you don’t secure it, don’t connect it.
Axiom #7: Cisco has played a crucial part in the development and global deployment of internet version 1.0. However, as the world inexorably connects more people and things, we believe that several traditional methods and technologies will no longer work efficiently or cost-effectively. For example, securely connecting 50 billion things (by 2020) is a different challenge to connecting 50 million people (in the nineties). Factors such as power, distance, mobility, spectrum, latency, response time and cost were addressed in the first version of the internet, however they are now having to be reviewed and often re-invented for internet version 2.0, especially as Cisco predicts that the world will connect 500 billion things by 2030.
Axiom #7 - The first generation of the internet is not fit for the second.
Axiom #8: Cisco has found that most IoT projects are failing, despite the enthusiasm and optimism for the opportunity it represents [Cisco]. The inaugural phase of IoT is charaterised by numerous point solutions from a multitude of new (often startup) vendors. Typically, these solutions have been designed to solve a particular societal problem such as lighting or parking. In each case, a complete IT stack needs to be built in support of the solution. Eventually, customers find themselves with multiple siloes from multiple vendors that don’t interoperate, are not cyber secure, use different protocols and generate more complexity at greater cost. This is why Cisco is building the foundation for “IoT Phase 2”. This phase is characterised by an “IoT platform” that incorporates modularity and functionality to address multiple different sensors from different vendors while supporting multiple different applications and data interchange from different vendors. Other factors behind failed projects include a lack of qualified skills, no cyber security, poor project definition, governance and support.
Axiom #8 - Three-quarters of IoT projects are failing.
Axiom #9: Almost overnight (seventy years is not long in the history of humankind) computers have developed at an astounding rate. Our brains on the other hand, are physically not discernably different from the human brains of several thousands of years ago. What is exciting is that both computers and software are changing and advancing in a manner that is increasingly resembling the performance, physical architecture and operation of our brains [Muhge].
Axiom #9 - Computer science and neurology are converging.
Axiom #10: Innovation can be a double-edged sword. Just like the adoption of fire helped to keep humans warm, it also burns down houses. There are several new challenges that we face, which have been brought about by digitisation and IoT technology. These new challenges, often referred to as ‘economic dislocation’, include unemployment, increasing cyber-crime and risk, algorithmic accountability and loss of (human) attention and cognitive ability due to increasing dependence on smart phones. Therefore, when we consider the exponential opportunities that digital and IoT may provide, we as humans, need to think about why we are doing it and for whom.
Axiom #10 - A person consists of two ingredients, a body and a soul. Bodies are nothing but ordinary machines, but the soul is not subject to scientific law (Descartes).