The Smart Networked Systems (SNS) Multidisciplinary Research Group (MRG)

Invariably the information communicated from these edge devices ends up to the cloud. Once the data gets to the cloud, it gets processed and it may trigger an action, such as sending an alert or automatically adjusting the sensors/devices. In certain applications, users are also informed of the data, or are recipients of solutions stemming from information gathered by the devices.

The recent technological developments in all the architectural components described above, make IoT suitable for meaningful deployment as part of the infrastructure and services comprising a Smart City. This is where IoT devices will be embedded into the city’s infrastructure monitoring all sorts of activity and collecting all sorts of data. The data will then have to be transported to an operation center where it will be processed and actions will be taken.

For example IoT devices may collect information about parking space availability in private or public parking lots and streets. Other sensors may offer information on road traffic conditions. This information can be utilized by a smart parking application and inform the users of the best possible parking given the time of day, and a number of other parameters of interest to the user. Artificial intelligence algorithms can even make predictions of traffic conditions and suggest alternative parking spots or routes. There are numerous such examples of the way IoT can make our everyday lives easier. 

The SNS MRG has developed a prototype of a Smart Parking Application and we are working towards deploying it at the Municipality of Nicosia.

By monitoring environmental conditions (temperature, humidity, pollution) the city can inform certain groups of citizens on courses of best action (elderly people and children can stay inside in periods of extreme temperatures, asthmatic people can know if pollution or dust is in the atmosphere, people with allergies can avoid certain areas with high pollen concentration). By monitoring ambient light and traffic conditions, a city may find ways to dim roadside light fixtures and save on electricity. By accurately measuring energy consumption and production, a district can find ways to share energy and reduce their carbon footprint.

For us, at the SNS MRG, the most interesting part of IoT is the extension of Internet connectivity into physical devices and everyday objects. As far as the network operation is concerned, it is extremely difficult, if not impossible, to extract any deterministic behavior from the Internet and the Cloud Infrastructure. Given the push for Mobile-Access Edge Computing (MEC) – the concept that cloud operations can and will be pushed towards the edge of the network (ie the gateway) or even the devices themselves – we concern ourselves to providing Reliability, Performance Control and Security to the “local network” part of the of Things

Towards this end, we are actively developing an Intrusion Detection System for IoT and Low-power and Constrained Node Networks. We have started by creating a tool for monitoring the individual nodes and the network, which we call Remote Monitoring Tool (RMT. Then, we have started employing statistical analysis and machine learning techniques, like Binary Logistic Regression (BLR), Support Vector Machines (SVM), Fuzzy Logic (FL) and Self Organizing Maps (SOM) to define normal and abnormal behavior and classify attacks in IoT networks.

As part of RISE and the team working on Smart Cities and the creation of the Digital Twin what do you hope to achieve with the implementation of this project? What is to you the most important aspect of the impact it will have?

We see our work in Smart Cities and the iNicosia Flagship as being part of the work done in RISE’s strategic research focus of Smart Environments.  The definition we give is the following:
“A Smart Environment is a part of the physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives (down to nanoscale), and connected through a continuous network. The continuous connectivity enables the smart devices to access pertinent services anywhere and anytime, self-organize, and manipulate/publish complex data. The aim of that world is to make peoples’ lives more comfortable by advancing an otherwise passive environment to become an active partner of its users. Humans augment this world by carrying smart devices in different formats (mobile phones, wearables, body-embedded medical devices). The smart world may also be, in part, virtual, thus allowing the cyber and the physical domains to interact.  The interaction of humans with the environment leads to the need to understand how perception can be linked to appropriate actions (AI) and how a system can be linked with its users (HCI).”

While the concept of a digital twin has been around since 2002, it’s only thanks to the Internet of Things (IoT) that it has become cost-effective to implement. It is so imperative to business today, it was named one of Gartner’s Top 10 Strategic Technology Trends for 2017. Quite simply, a digital twin is a virtual model of a process, product or service. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations. Thanks to IoT sensors, a digital twin receives continuous, real-time data from the twin’s real-world object or asset. This unique, one-to-one correspondence makes it possible to test future scenarios, including potential performance enhancements, and proactively anticipate maintenance faults. Digital twins also mean that building construction can be monitored remotely. A digital twin can be understood as a bridge between the physical and digital world. First, smart components that use sensors to gather data about real-time status, working condition, or position are integrated with a physical item. The components are connected to a cloud-based system that receives and processes all the data the sensors monitor. This input is analyzed against business and other contextual data. Lessons are learned and opportunities are uncovered within the virtual environment that can be applied to the physical world.

We expect that the implementation of the iNicosia Flagship and the realization of the Digital Twin of Nicosia will offer a multitude of opportunities that will move away from creating simple data-consumig mobile or web applications that serve the general public, but also influence the way the city is developed. The municipality’s different departments will be able to use the data for better urban planning, more efficient urban mobility solutions, faster urban waste flow design etc. The biggest impact will be on the quality of living of the city’s inhabitants and visitors.

When did you take your first steps towards this Research focus area? How/Why?

As far as IoT is concerned, my group’s involvement dates back to 2010 when we started looking info different problems and solutions in wireless sensor networks. In that context we have dealt with congestion and overload control, mobility management, dynamic topology control, and security. The work in IoT is a natural evolution in the sense that we are still interested in low-power networks, constrained nodes and energy- and communication load-aware protocols.
We employed our solutions in different setting, ranging from industrial networks to home environments. In the second setting, we have started in 2015, to explore the application of IoT and edge computing in Home Energy Management.

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