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Transportation IoT joins physical and information highways

As transportation IoT networks improve with connectivity, embedded processing and sensing technology, society will move from point A to point B more efficiently and safely.

IoT has been a game changer for the transportation sector over the past decade in how people and goods move via land, sea and air.

The heightened situational awareness created by complex networks of IoT devices and the seamless exchange of information via the cloud have made new transportation services and applications possible. With the increase in IoT development worldwide, new innovations will further revolutionize transportation IoT.

Transportation IoT is already here

Several transportation IoT deployments currently exist, including a few that have been around for years. One example of a large-scale IoT implementation for transportation is electronic tolling, or e-tolling, which is used extensively across the nation and around the world daily by millions of people. When initially deployed, e-tolling systems started with simple RFID readers installed in the same tolling plazas where human toll collectors worked. However, as time progressed and IoT technology significantly improved, electronic tolling evolved into a sophisticated IoT network capable of handling almost all traffic scenarios -- such as high-speed travel, out-of-state vehicles, missing transponders -- and eventually replaced the need for human toll collectors altogether. Despite the increased capability offered by the latest electronic tolling IoT systems, the basic ingredients for IoT-based e-tolling systems remain the same: an extensive array of sensors, RFID transponders and readers and camera networks, all of which continuously collect unique vehicle identification data, such as license plate information, in real time. The collected data is communicated via a wireless cellular link from each gantry on a stretch of roadway to the cloud for processing by the state motor vehicles department that subsequently bills specific motorists for their usage of the roadway.

Although the e-tolling example highlights the capabilities and advantages of integrating IoT within a transportation environment to provide seamless, reliable and ubiquitous services, many other examples of transportation-centric IoT exist. Examples include public transportation networks, such as subway systems and bus networks, as well as automated intersections that facilitate efficient traffic flow via vehicle sensing using induction loops in the pavement and camera networks mounted on the traffic light poles. In all of these examples, transportation IoT makes use of the latest embedded computing, connectivity and sensing technologies to reliably execute multiple parallel tasks in concert and support the overall objective of the network.

What's next for transportation IoT?

Given the demonstrated success of transportation IoT deployed in real-world scenarios, emerging capabilities in connectivity systems, embedded processing and sensing technology hint at what might be gained from the future of transportation IoT.

Given the demonstrated success of transportation IoT deployed in real-world scenarios, emerging capabilities in connectivity systems, embedded processing and sensing technology hint at what might be gained from the future of transportation IoT.

The communication systems sector has witnessed an explosive level of growth over the past two decades, especially with the rapid evolution of cellular technology from 3G systems in the early 2000s to the 5G networks today. The 5G standard details how IoT devices connect and integrate with each other and the rest of the network, which builds the seamless and ubiquitous flow of information to and from every IoT device across the 5G network. For example, with vehicular IoT communications architecture known as cellular vehicle-to-everything (C-V2X), vehicles can form decentralized IoT networks between each other as well as with stationary roadside units for the purposes of rapid information exchange with minimal latency. For applications, such as self-driving cars, information exchanges are critical for the safe and reliable operation of vehicles because the information provides them with adequate situational awareness.

Embedded computing platforms have evolved into an array of different technology options with a range of computing abilities, form factors, weight, power consumption and cost. One primary driver was the cellular industry, where significant market demand for consumer goods led to production of smartphones on a massive scale. Embedded devices have become more versatile, powerful, energy efficient and cheaper because of the demand and led to their widespread use across domains, such as the transportation sector. Embedded computing takes place across numerous elements of transportation infrastructure -- including intersections, roadways and parking areas. Computing performed locally within the transportation network can increase the level of automation that gives rise to the smart transportation, smart roads, smart intersections and smart parking talked about today and planned for the future.

Sensing technology converts an actual physical phenomenon, such as temperature, and translates it into digital information that an embedded computer can process and then send the results via a cellular connection, such as 5G, to the cloud. At the core of the sensor, a device translates the physical phenomenon into electrical energy followed by an analog-to-digital converter that digitizes that energy into digital information. Although the basics have not changed, advancements have made the technology that performs conversions between the physical world and the digital world more capable of providing higher resolution information about the environment. Within the context of transportation IoT, vision or camera-based systems and lidar have attracted attention given their abilities to acquire information about an environment and enhance the level of situational awareness. Although both technologies have been around for quite some time, recent advances have resulted in new capabilities in gathering environmental information and translating it into a digital form. For example, frequency-modulated continuous wave lidar has expanded the conditions that it can detect objects in. Manufacturers deploy both technologies in self-driving cars to obtain real-time situational awareness on the road and in automated applications, such as smart intersections and traffic flow control.

Challenges that affect transportation IoT deployment

The industry must adequately address several emerging technical challenges to achieve future growth in areas such as transportation. Many challenges result directly from the use of the very same connectivity, embedded and sensing technologies that have yielded the major innovations in IoT. For example, many embedded computing systems used in transportation IoT are susceptible to cyber attacks because of their use of lightweight or nonexistent cryptographic techniques. Although cyber attacks weren't a problem several decades ago, the vulnerability of these devices has significantly increased because of their greater connectivity to the cloud and internet using Wi-Fi, Bluetooth or 5G, which could provide remote access to unauthorized users or software programs. A hacker could compromise the embedded computing devices on board a vehicle and reprogram several of these devices with new code to perform actions, such as cooperative adaptive cruise control, that might affect the safe driving operations of the vehicle and those surrounding it.

Transportation IoT also faces challenges with having enough wireless spectrum to accommodate the growing need for connectivity and larger bandwidths. The industry has made significant strides during 2020 in securing additional spectral bandwidth to accommodate the demand for 5G cellular services. With the recent completion of the Citizens Broadband Radio Service auction and the redesignation of the 6 GHz band to unlicensed access, new opportunities have emerged to meet the growing needs of society for the convenience of 5G access and its associated data rates. Although this is a significant spectrum increase, it will not immediately affect 5G C-V2X, which is still allocated the limited 5.850-5.925 GHz band. As a result, the current spectrum allocation will not likely be sufficient to support a large number of vehicles or vehicles communicating large amounts of data. This could negatively affect critical applications, such as self-driving cars and smart intersections where reliable, low-latency access to the wireless spectrum is imperative to support real-time situational awareness.

Future opportunities of transportation IoT

Despite the challenges with transportation IoT -- such as cybersecurity issues and insufficient spectrum access -- it can be a game changer, particularly for the deployment of autonomous vehicles en masse on public roads driving alongside human-operated vehicles. Given the limited range of situational awareness from the perspective of individual self-driving cars, transportation IoT can offer a sixth sense to vehicles. IoT devices provide vehicles with additional environmental information from a distributed collection of perspectives on the road, which they can use to perform actions that correlate more closely with reality.

Another future transportation IoT application is the realization of a smart roadway that performs intelligent traffic flow control with the intent to lower emissions and greenhouse gases. Certain driving behaviors are more fuel efficient than others. Also, if vehicles can operate in close enough proximity to one another, they can start taking advantage of each other's aerodynamic properties to minimize air resistance and consume less fuel. Intelligently adapting the traffic flow of a stretch of roadway to minimize potential traffic jams and other obstacles that affect efficient transportation means less time spent on the road and less fuel consumption.

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