Intelligent Infrastructure: How to Make Cities & Buildings Smart

Intelligent Infrastructure connects physical assets comprising a critical infrastructure and a purpose-built IoT platform that includes Edge AI and operational Digital Twins. Intelligent Infrastructure can substantially increase an IoT investment’s ROI while increasing the efficiency, safety, and sustainability of cities, states, and facilities. In this blog post, we’ll explain what Intelligent Infrastructure looks like in practice.

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Summary:

Intelligent Infrastructure connects physical assets comprising a critical infrastructure and a purpose-built IoT platform that includes Edge AI and operational Digital Twins. It is central to the concept of smart cities and buildings.
Achieving Intelligent Infrastructure can substantially increase an IoT investment’s ROI while increasing efficiency, safety, and sustainability.
Critical assets are the components of a critical infrastructure and can include everything from machines in a retail store to oil and gas plants to railroad crossings to solar farms.
Once critical infrastructure is connected via an IoT platform and hydrated with data from the Edge, a no-code application can put command and control functionality into the hands of operators.
A key mistake in achieving ROI with Intelligent Infrastructure is stitching together hundreds to thousands of point solutions.
Operators can be empowered to monitor and control assets without coding using a Digital Twin connected to critical infrastructure and reflective of real-time status.
Practical applications of AI in IoT can provide critical information to ensure an infrastructure runs as efficiently, safely, and sustainably as possible.

Explore Intelligent Infrastructure in more depth:

What is Intelligent Infrastructure?

First, let’s look at the term “critical infrastructure.” It brings to mind energy grids, water supply systems, fiber internet lines, highways, food supply chains, and mobile phone service. These are critical to life today and can benefit immensely from Intelligent Infrastructure. Critical infrastructures can also include the physical operations of businesses, from transportation to retail to energy to buildings. What can comprise a critical infrastructure? Let’s explore.

Critical Assets: Components of a Critical Infrastructure

Critical assets are things that business has that needs to be tracked and monitored.

Critical assets are things that a business has that need to be tracked and monitored.

A critical infrastructure consists of critical assets that need to be tracked. They are things that the business owns that need to be monitored. This can include machines in retail stores, pallets of goods, heavy-duty equipment, vehicles, trains, ships, factories, and buildings. To effectively monitor critical assets, data must be accessed and analyzed to answer questions such as:

How is it performing?
What is its location?
Who is using the asset?
Is it operational?
Does it need maintenance?

When critical assets are leveraged effectively, they can reveal a great deal about our critical infrastructure’s status, for example:

A convenience store operator knowing the status of slushie machines across a national chain of 1,000 stores.
A solar farm operator tracking the efficiency of solar panels to know if they are performing optimally or require maintenance.
A goods manufacturer knowing the location of an expensive pallet of products.
An oil and gas operator knowing the location and status of workers on oil platforms to ensure their safety. Or knowing the location and status of oil tankers as they travel through dangerous waters.

The question might change for different roles or situations within an organization. When deployed correctly, Intelligent Infrastructure successfully ties together critical assets throughout a business, facility, city, or state but is flexible enough to answer new questions as they arise.

IoT of Intelligent Infrastructure: Brownfield or Greenfield Assets

When businesses need to monitor assets, this can include Brownfield or Greenfield assets. According to Machine Daily, Brownfield assets are “legacy equipment or software that perform discrete functions in isolation,” while Greenfield indicates “a situation where no preexisting equipment or assets are present on the shop floor.”

Brownfield and Greenfield assets will comprise a heterogeneous equipment ecosystem from which data can be gathered. Each asset can be monitored, commanded, and controlled when connected to an IoT-powered operational Digital Twin of this asset ecosystem.

Intelligent Infrastructure: Where Physical Assets & Software Meet

Intelligent Infrastructure converges our physical world’s critical infrastructure with purpose-built IoT, Edge AI, and connected Digital Twins to increase efficiency, safety, and sustainability. We’ve covered the physical aspect, things or assets that comprise a critical infrastructure, now let’s look at the software side of the equation.

Infrastructure on the Edge: Taking Control of Assets

Edge computing has a vital role in Intelligent Infrastructure. It can engage with legacy protocols coming off sensors and equipment. These protocols include Modbus, BACnet, OPC UA, or any legacy enterprise or industrial protocol. The Edge can also engage with wireless protocols such as LoRa, BLE, or Zigbee.

The Edge is essential if you’re truly going to engage with the assets in the field as they are today. It’s also instrumental in deploying AI, although that usually occurs after connecting devices and assets and gathering data.

Once connected, the software Edge layer can hydrate hundreds or even thousands of Edge layers to bring data back into a flexible IoT solution via MQTT. From there, the IoT solution can bring and persist data and provide data as a service to third-party data sources or targets. It also provides a cloud function by engineering this information.

Once critical infrastructure is connected via an IoT platform and hydrated with data from the Edge, a no-code application can put command and control functionality into the hands of operators.

No-Code, Connected Digital Twins: Put Operators in the Driver’s Seat

Best-in-class organizations should seek a holistic approach to get the highest ROI out of IoT to achieve Intelligent Infrastructure.

Most businesses have a wide variety of devices and sensors to connect and a variety of point solutions comprising their IoT tech. This may include Edge and application orchestration, data brokering, containerization, cloud data storage, on-premise systems, over-the-air (OTAs), Digital Twins, and AI models.

It’s a Frankenstein-like science experiment. Why reinvent the wheel when tech exists out of the box that includes these capabilities and more today?

Ultimately, stitching together what can be hundreds to thousands of point solutions is not the most efficient path to ROI and Intelligent Applications. Instead, a holistic platform can deliver IoT, Edge, Edge AI, and connected Digital Twin functionality and connect to any device, gateway, cloud, or on-premise solution and convey data using any protocol. By abandoning the science experiments, organizations avoid being mired in years of resource-wasting developmental limbo.

Intelligent Assets: No-Code Connected Digital Twin

From a technology perspective, a holistic platform is ideal and incredibly interesting from an engineering standpoint. However, it’s not often the devs or the coders who are operating machinery, managing facilities, and coordinating transportation operations. Traditionally, there’s been a divide between the folks with their boots on the ground and those solving company problems using software and data science. Adding operational Digital Twins can bridge that gap once critical assets are connected via Edge and IoT solutions.

However, not all Digital Twins are created equal. Operators can be empowered to monitor and control assets without coding using a Digital Twin connected to critical infrastructure and reflective of real-time status.

Adding AI capabilities can make this application even more accessible to operators, delivering intelligence and making it incredibly simple to make critical business decisions.

AI at the Edge: The Smarts in Intelligent Infrastructure

A holistic approach to an IoT solution can get an organization up and running within a few weeks. After that, the possibilities are endless. In the age of AI, data can be used to better understand a city, state, building, facility, or area and make that knowledge actionable.

However, machine data, stored in Brownfield and Greenfield devices, is the most difficult to access. Here, Edge AI can pull data directly from the Edge, process, categorize, normalize, and organize it, and then stream it back in a compressed manner to the cloud or other systems.

That unlocks the ability for the cloud or enterprise tools to aggregate that data to build an AI model. Whether it’s a generative, video or synthetic, neural nets, Bayesian, or another AI model, devices at the edge can hydrate AI models and solve storage limitations.

AI models are generally thought of as living only on the cloud. With Edge, AI models can be moved back down to the asset. An AI model can be run, and the data can be processed at the physical asset level in real-time. When AI is running at the device level, on the Edge, it is called Edge AI. This results in remarkable real-time or near-time insights that can inform machines operating in the field. Practically, Edge AI can:

Predict as a machine drills: Does the pressure or rotation need to change based on the rock’s hardness?
Predict as water is pumped: Are the pumps running optimally? Do they require maintenance? What is the health and cleanliness of water right now?
Predict as energy is generated: Are the solar panels generating optimal power? Do they require cleaning? Do they require maintenance or repair?
Predict bridge and overpass health: Did a vehicle strike a bridge, or was that normal vibration?

Practical applications of AI in IoT such as these can provide critical information to ensure an infrastructure runs as efficiently, safely, and sustainably as possible.

Conclusion

When an organization adopts a platform encompassing IoT, Edge, Edge AI, and Digital Twins, it can leapfrog its capabilities and take advantage of AI technologies faster and more efficiently. The outcome, Intelligent Infrastructure, makes cities, states, buildings, and companies more efficient, safer, and sustainable.