What is Smart Infrastructure?

Smart infrastructure refers to smart automation systems that are enabled by advanced hardware and software working together to create intelligent, real-time decisions. Smart infrastructure combines sensors, Internet of Things (IoT) devices, building information models (BIMs), real-time data analytics, and other application-specific technologies to monitor physical infrastructure and optimize its performance.

With smart capabilities, physical infrastructure can run a lot more efficiently, improve its performance, and produce fewer emissions. Examples of smart infrastructure in society involve public transport, energy, utility, smart building technology, and smart city infrastructure.

The capabilities of smart infrastructure are only possible due to its fundamental building blocks, including the following elements:

Sensors

Sensors are the cornerstone of smart infrastructure. From simple temperature and humidity sensors to advanced IoT sensors, they are responsible for collecting data about their environment. Without this data, the wider smart technology system would not be able to make any real-time or informed decisions as it would have no understanding of its surroundings.

Alongside more traditional sensors, imaging cameras are used to record videos, recognize assets, and track objects in an environment. These cameras can be attached to poles in outside environments and walls in internal environments, as well as on drones, satellites, and other aircraft to monitor infrastructure on a large scale. Whereas more traditional sensors track environmental stimuli, imaging cameras provide a visual picture of the environment.

Wireless Communication

Smart infrastructure hinges on all hardware and software components communicating with each other in real time. Without efficient communication technologies, smart infrastructure (and smart technology in general) would not be possible. Wireless networks are now driven by 5G communications, connecting sensors, imaging cameras, and IoT devices to central control systems where the software analysis is performed.

Building Information Models

BIMs produce 3D models of buildings, utilities, or traffic environments by combining geometric data with the design properties for the intended infrastructure (material data, cost, etc.). The data contained in a BIM allows real-time monitoring and predictive maintenance operations to be performed to make infrastructure safer, more sustainable, and optimally placed.

BIMs are not new technologies but have become more advanced in recent years, with digital twins providing more information on the life cycle of physical infrastructure and how it is likely to age, as well as how it can be optimally run.

Reality Capture and Mapping With Geographic Information Systems

Combining BIMs and reality capture tools, such as laser scanning and photogrammetry, with geographic information systems (GISs) allows more context to be added to the information in the environment. This improves the system’s decision-making by being location-aware, sensitive to different contexts, more precise, and more efficient. Examples of information that can be contextualized with a GIS include:

• Where buildings should be situated based on terrain and elevation data
• What types of utility lines and transportation networks need to be situated around building infrastructure

This contextualized information is important because it’s easier to preemptively determine the geographical and environmental factors before siting infrastructure. If construction has started but there are zoning restrictions or issues with utility connection, it makes it a lot more difficult and costly to remedy any planning issues at that point.

Many types of smart infrastructure exist today, all of which use different technologies to monitor and optimize their placement and day-to-day operations. Here we look at some of the main types:

Smart Grids

Smart grids are changing how the electrical grid produces and manages energy. The digitization of the grid is improving energy efficiency, energy consumption, and sustainability in the grid and enabling the wider energy ecosystem to become more closely connected. A lot of old grids only have one-way communication between utility companies and consumers, but smart grids now provide two-way communication. On top of this, smart grids have multiple sensors and IoT devices (that can be retrofitted on legacy equipment) located around the grid to manage energy loads from distributed energy resources (DERs). These DERs include renewable energy sources (RESs) and electric vehicles (EVs) that intermittently add and remove localized energy, respectively.

Decentralized control systems facilitate the flow of energy at peak times through real-time data collection and monitoring of assets in the grid. This makes it easier to predict downtime, quickly spot power outages and faults on transmission lines (without the need for manual help), get power back online more rapidly after an outage, and integrate renewables into the grid.

For load demand, smart grids can spot localized spikes from EVs and other energy drawers. Smart grids can also identify if too much energy is being introduced from renewable sources causing localized bottlenecks on the transmission lines. By spotting the load change in real time, power can be rerouted to optimize the transmission network and either remove power from a line or add power, depending on the load requirements, so everyone still has access.

Smart Traffic Management Systems

Traffic management systems are another example of smart infrastructure. They are time- and schedule-based and will determine the flow of traffic lights based on anticipated traffic at any given time of the day. However, traffic flow varies day by day, and if any accidents occur, it can completely change traffic dynamics. To accommodate unexpected situations, smart traffic management systems have advanced scheduling capabilities that can perform real-time dynamic traffic control.

Using a combination of advanced cameras, antennas that constantly count the number of vehicles at every stop, and advanced algorithms, the signals can be dynamically changed to ensure a better flow of traffic. This also helps to better ensure pedestrian safety as crosswalk time can be adjusted.

In the future, it might also be possible to integrate real-time traffic sensor systems into autonomous vehicles (AVs) where both the vehicles and the traffic signals can communicate with each other. This could be part of a wider smart transportation system and smart city urban environments where everything is even more connected than the smart systems today.

Smart Water Management Systems

Smart water management systems are also a key smart infrastructure element and can be used to address a number of issues regarding the delivery of water and maintenance to existing piping infrastructure. Sensors are now being implemented by utility companies to better measure, manage, and understand any potential issues and rectify them before they turn into bigger problems. Smart water management systems can be used to:

• Identify any potential leaks (and accurately pinpoint their location) and address them before they worsen, enabling consumers to get water back on more quickly.
• Measure levels of pH, turbidity, and contaminants in the pipes to ensure that the water remains potable.
• Check for any pump failures and filter clogs by measuring the quality of the water.

Smart Building Management

The next generation of buildings integrated with advanced sensing technology will have a lower environmental impact due to the smart technology monitoring the internal environment based on whether certain rooms of the building are occupied — making smart buildings more energy-efficient. From automated light control and adjusting HVAC settings to control the air quality and humidity to measuring internal temperature and CO2 levels, smart buildings also provide a more comfortable living environment and quality of life for occupants.

On the operational side, smart monitoring systems can also ensure that all aspects of the building — elevators, pumps, electric systems, and more — are always working and schedule predictive and preventive maintenance programs to ensure there’s no unexpected downtime.

Like any new technology, there are always benefits and limitations to implementation and use.

The benefits of smart infrastructure technology are:

• Improved efficiency through reduction of waste and improvement of system performance
• Reduced lifetime costs due to optimized energy, operation, and maintenance management, leading to longer longevity of system components and equipment
• Improved sustainability by reducing energy use and greenhouse gas emissions
• Increased system resilience through more advanced prediction capabilities
• Enhanced ability to monitor and maintain assets in real time and take corrective actions more quickly when there is an issue
• Increased infrastructure safety

On the other hand, the limitations of smart infrastructure technology today are:

• High upfront costs for IoT sensor technology make it difficult to be deployed at scale, where only the communities that can afford to pay those costs will get the technology benefits. This could lead to disparities in infrastructure among neighborhoods until costs come down, potentially fueling social issues.
• Putting all the data on the cloud makes the technology susceptible to cyberattacks. Until standardized components are used across the board with robust cybersecurity protocols, having multiple potential nodes of entry that can communicate over a digitally connected network always presents a cyber-risk.
• There’s the potential for societal backlash due to privacy concerns, with both social and technological barriers needing to be overcome to be implemented on a large scale.

Here we examine types of simulation software and how similar software is being used to further the design and implementation of different smart infrastructure.

Simulating Smart Grids

Simulation software helps design more advanced smart grids, from the component to system level. A few simulation tool examples are included below:

The Ansys Maxwell advanced electromagnetic field solver: This electromagnetics tool is used to design transformers, switch gears, and other power electronics equipment used in smart grids. It investigates the thermal efficiency, amperage, and current through the component to ensure high performance.

Ansys Icepak electronics cooling simulation software: This thermal simulation software assesses how components perform in different temperature environments. From power electronics generating a lot of heat due to high current to any assets exposed to the heat of the Sun for a long time, Icepak software can investigate how components will behave during peak surge conditions to ensure they don’t overheat.

The Ansys Twin Builder simulation-based digital twin platform and Ansys TwinAI AI-powered digital twin software: These software systems build digital twin environments that can look at the smart grid system on a full-scale environment level and design the entire control system algorithm for the grid. This enables the determination of any degradation of components, potential faults, maintenance cycles, and the optimal position and performance of the many sensors used in the smart grid. Digital twins build a virtual environment of the physical grid and can then investigate many potential operational scenarios using real-time data from the physical assets.

Simulating Smart Traffic Management Systems

Sensors and cameras used in smart traffic systems are mounted on poles and need to be durable to survive the elements, such as wind and thermal loads that cause wear and tear over time. Regardless of whether optical cameras, infrared cameras, or standard vision cameras are used, Ansys Mechanical structural finite element analysis software captures the degradation data of those systems and simulates how they will behave over time, as well as in adverse weather conditions, such as fog and rain.

On the other hand, the Ansys SCADE Suite model-based development environment for critical embedded software simulates the embedded software underpinning control system monitoring to see how the camera data is fed into the real-time control system and how the two technologies communicate with each other. This helps to identify and capture all potential edge cases in a traffic management system.

Simulating Smart Water Management Systems

Ansys Fluent fluid simulation software is a computational fluid dynamics (CFD) tool that can simulate the flow of water through a pipe and simulate leaks. Areas of pipes with leaks produce a different noise than healthy pipes, and this noise can be simulated in Fluent software to train smart monitoring devices. Once the algorithms have learned the noise difference, sensors can easily detect if there is a local leak based purely on the noise of the water flow.

Twin Builder software and TwinAI software can also be used to build a virtual digital twin environment of the water pipe network. The digital twin can simulate many environments, including:

• Simulating pipe integrity and the remaining useful life of different pipes
• Measuring the acoustic vibrations in the pipes over time and checking for anomalies that might suggest issues
• Simulating and optimizing the pumps and motors used to move water through the pipes
• Tracking pipe pressure fluctuations in real time
• Looking at how all the aspects of the pipe network work together

Simulating Smart Building Environments

The internal environment of a building can be simulated in various ways. For example, Fluent software can look at airflow patterns inside a building and determine temperature gradients in hallways or rooms. This can be used to simulate how the systems can monitor different rooms and always ensure a comfortable temperature.

For lighting, Ansys Speos CAD integrated optical and lighting simulation software can provide the ideal positioning of lights in the building to achieve the highest luminescence using the fewest light fixtures possible to save energy. More so, Speos software can optimize placements before wiring and fixtures are put into place, as it’s difficult to rectify any issue after the physical placement.

Maxwell software can be used to capture the acoustic vibrations and noise levels in a building that would potentially arise from elevators, centralized air conditioning, and HVAC systems to provide a quieter environment for occupants. The sensors can be trained with the simulation data to pinpoint any potential issues in the ducting based purely on the change of noise in the duct system. Maxwell software can also be used to simulate the control system software and hardware involved in running smart building operations to ensure they don’t short-circuit or overheat during operation.

Both physical and digital technologies have already been developed to effectively manage and monitor different infrastructure systems in different environments. Going forward, a lot of smart infrastructure technology will be driven by artificial intelligence (AI), where all sensor inputs will be read and interpreted by AI algorithms. Similar to software-defined vehicles in the automotive sector, we will soon have software-defined buildings, software-defined traffic information systems, and software-defined water management systems.

If you’d like to discover how you can use simulation to develop more robust smart infrastructure systems, then contact our technical team to find out more.

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