With governments around the world agreeing to significantly reduce humanity’s carbon footprint, industry and investors are stepping up to deliver sustainable changes to how we live. Transport is one of the largest creators of carbon emissions yet is essential for modern living. As such, solutions must be found that meet emissions reduction goals through supporting while not reducing quality of service.
This is the goal of smart transport networks, which leverage new technologies, such as level 3 and level 2 charging station networks, and the potential of large-scale data analysis and modeling to create more efficient and environmentally friendly infrastructure. Some of these advances include:
- Cold chain freight transport: Cold transportation is a vital cog in the global supply chain, but due to on-board refrigeration, it consumes 20% more fuel than standard trucks. However, the widespread use of IoT sensors to monitor temperature, maintenance requirements, and product integrity are making the cold chain transport more efficient and improving delivery results.
- Smart traffic management: Real-time data collection is already a major part of most major cities’ traffic management. This data is analyzed in real time by traffic control centers to keep drivers informed and traffic flowing as efficiently as possible, reducing journey times and emissions.
- Autonomous vehicles: As driverless electrified public transport becomes an increasingly popular solution to both urban congestion and emissions, data sensors on vehicles and road sides are critical for ensuring safe, secure delivery of services for users.
- EV charger station installation: Electric vehicles (EV) are significantly reducing the transport sector’s creation of carbon emissions, and automotive executives predict that EVs will make up the majority of car sales by 2030. To support this and to increase buy-in from consumers, there needs to be effective EV charging station installations in areas that have the infrastructural capacity and are convenient to drivers.
Smart transport networks: Challenges and solutions
For smart transport networks to reach their potential, they must still overcome a number of challenges. These relate to how data can be collected and used correctly, adhering to national and international regulations, as well as the physical task of installing modern network architecture. Here are some of the biggest challenges facing smart transport networks and how they can be overcome:
Data analysis capacity
Smart transport networks rely on very large amounts of data being collected from thousands of IoT sensors, smart transport cards, and GPS data among other sources. Collecting this data from edge sources, bringing it together and analyzing it, and then providing that data to decision-makers in real-time requires highly streamlined data operations. To achieve this, smart transport DataOps are working with data virtualization tools that don’t require the movement of data for analysis and help data scientists to locate data easier through automatic metadata cataloging.
Time to install
While new technologies are being developed all the time, the paradigm with physical transport infrastructure has been built around slow planning and implementation processes. This slow pace of change is causing more emissions to be released unnecessarily. To overcome these issues, infrastructure planners are combining multiple stakeholders to allow potential smart transport and electrical system improvements, such as smarter planning for electric car charging stations, to gain approval from all necessary parties within a single application, significantly reducing the time to install a robust EV charger network.
There are a number of major regulations governing the collection, processing, and sharing of data, especially that containing personally identifiable information. This is a problem for smart transport networks, as they require large-scale data sharing between different stakeholders to reach their most efficient potential. However, these issues can be overcome by ensuring that all analysis of shared data is performed in trusted execution environments within a context where data administrators are given extensive access management tools, with each user’s data never actually leaving their control.
EV charger station installation: A smart transport grid use case
Germany, one of the biggest automobile manufacturers in the world, is a leading nation in the rollout of EVs and smart transport infrastructure. This is complicated, however, by the dispersed nature of its utility market, where there are over 800 distribution service operators (DSOs), 16 different state governments responsible for infrastructure and charger installation rollouts–and strict data regulations under the EU’s GDPR.
Digikoo, a subsidiary of E.ON SE, one of the largest utilities in the world, has worked to solve these issues by deploying Cleangrid as a data operations toolkit. Digikoo was tasked with aggregating grid data from DSOs in order to coordinate with planners around EV charger station installation to reduce installation costs. This process required several inputs from various stakeholders, such as identifying potential user needs and integrating that with utility infrastructure and load capacity. This gave EV charger station installation planners a clear insight into where charger stations were needed and how feasible they were, allowing them to gain faster planning permission and reducing project planning cycles by up to 90%.
All of this was achieved while simultaneously ensuring compliance with data regulations through the enforcement of strict access controls over all datasets, allowing various stakeholders to collaborate freely without fear of breaching regulations.
The smart transport networks of the future will harness large-scale data collection and analysis to deliver a greener and more efficient transport infrastructure, such as EV charger station installation and dc fast chargers. However, achieving this future means overcoming challenges in terms of capacity for real-time data analysis, regulatory compliance, and physical planning processes.
The solution is to improve DataOps capacity to bring together diverse datasets from multiple stakeholders through secure data virtualization platforms. Intertrust Platform has been doing exactly that through the Cleangrid toolkit and many other use cases across the world. To find out more about how Intertrust Platform and the Cleangrid toolkit are empowering smart transport networks and infrastructure you can read more here or talk to our team.