Smart Systems

Smart Systems

Since the rise of the internet, we have found ourselves living in two seemingly parallel worlds, one the familiar physical world the other this growing world of information. But with the convergence of advanced analytics, cloud computing and the Internet of Things, these two worlds are starting to collide in powerful new ways as the internet starts to come offline into the physical world. Technology that we once thought of as physical tools and machines are no longer so, as a wave of information that started with personal computing and the internet is breaking out into the real world of physical things. Today information is out of its box and it is redefining our technology landscape.

Technology is no longer a one-off object that performs some physical operation, as we network our world placing sensors and actuators in all kinds of objects, technologies are becoming more like systems for executing on algorithms. Phones that just ten years ago were lumps of plastic and electronics with buttons for making calls have become smartphones that are designed to simply run code. Cars are becoming smart cars, whole cities are becoming smart cities with all of this technology increasingly connected up to the cloud where smart systems run analytics, crunching data, learning and feeding it back to the devices to optimize their performance.

As a revolution in information technology unfolds at a fast pace, science fiction appears to be becoming science fact. Within just a couple of short decades, we have gone from the PC to the internet and mobile computing, to today’s world of cloud computing. The age of smart systems is becoming a reality as ever more products and services that we use every day – from search-engine advertising applications to facial recognition on social media sites to “smart” cars, phones and electric grids – are coming to demonstrate aspects of “smartness”.


These smart systems incorporate functions of sensing, actuation, and control in order to describe and analyze a situation and make decisions based on the available data in a predictive or adaptive manner, thereby performing smart actions.1 In most cases, the “smartness” of the system can be traced back to autonomous operations based on closed loop control, machine learning and networking capabilities that enable the system to exhibit adaptive behavior. These smart systems will sit at the intersection of humans and our technology infrastructure as they perform basic control operations for our technology infrastructure and interact with people so as to understand their needs and perform required actions.

The extraordinary capacity of this new stage in the development of information technology is in the convergence of advanced analytics, cloud platforms and the Internet of Things. In every decade we have approximately ten times as many connected devices as we did in the past decade and this will likely continue for the foreseeable future. Everything that used to be dumb and disconnected is becoming smart and connected, as devices and technologies become connected into cloud platform.

Smart systems are software entities that carry out some set of operations on behalf of a user or another program with some degree of independence or autonomy, and in so doing, employ some knowledge or representation of the user’s goals or desires and the environment within which they act in order to achieve those goals.2 Such an agent is a system situated in, and part of, a technical or natural environment, which senses any or some status of that environment, and acts on it in pursuit of its own agenda. Such an agenda evolves from programmed goals. The agent acts to change part of the environment or of its status and influences what it sensed.

The central characteristic of these smart systems are, adaptive capacity, dynamic interactivity, a degree of context awareness and learning capacities. Adaptive: They may adapt as information changes, and as goals and requirements evolve. They may resolve ambiguity and tolerate unpredictability. Interactive: They may interact easily with users so that those users can define their needs comfortably. They can also interact with other processes, devices, and cloud services. Contextual: They may understand, identify, and extract contextual elements such as meaning, syntax, time, location etc. drawing on multiple sources of information, structured and unstructured. Learning: They can reason on data to create new information and use closed-loop feedback to rapidly iterate and learn from the output, meaning they get smarter and smarter.


1. Google Books. (2018). Safety and Reliability. Theory and Applications. [online] Available at: [Accessed 13 Feb. 2018].

2. Wikiwand. (2018). Software agent | Wikiwand. [online] Available at: [Accessed 13 Feb. 2018].

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Systems Innovation

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