As we move towards the age of digitalization, data is being rightly called the ‘king’, as it is essential for taking better and informed decisions. With smart cities becoming the buzzword, the significance of data has only grown as it enables decision-makers to plan, build and maintain cities in a better way. Cities around the world are looking to function efficiently through connected networks to increase transparency, by allowing open access to data.
In such a scenario, mobility is an area which produces enormous data every second. As per a research report by ABI, the numerous vehicles commuting and connecting people to their destinations have huge potential of data generation that can boost the economic growth of smart cities by more than 3 percent and lead to additional benefits worth $20 trillion by 2026.

Importance of mobility data

Mobility data is generated from public transit agencies, private mobility solution providers and citizens. It is either derived in a primary manner through an organization’s own sensors, or through user applications. While collecting data from primary sources, it is often assumed that data is valuable and collecting more of it can provide benefits in the future. The other method is the secondary method, in which data is collected by acquiring existing datasets from other parties, with intent defined well in advance. In this case, only that data is acquired which is of use.
Mobility data is of great importance as it unlocks the maximum value that can help cities become smarter and provide better transport facilities to its citizens. For example, it can inform citizens about real-time information of arrival and departure of trains and buses, help them to choose options for last mile connectivity and help in reducing travel time by informing them about areas with heavy traffic and suggesting alternative routes. It also helps in reducing traffic congestion due to cars looking for parking space as it can provide parking availability information.
Mobility data also creates efficiencies for delivery vehicles by identifying the most efficient time slots and routes, and adjusting traffic/ parking rules during major events. Furthermore, this data can also be used for identifying road safety and security hotspots, thus enabling quick response and understanding the issues of those areas and how they can be rectified.
This data can also help city administrators to better design and maintain routes, public transit and mobility infrastructure. For example, analyzing traffic and commute patterns can help planners to decide where to build infrastructure and add transit routes to ease stress in heavy traffic areas. Through the flow of traffic, the structural health of transportation infrastructures such as bridges and overpasses can be monitored.
Mobility data also helps in effective enforcement of regulations, develop new and modify existing regulations to ensure smooth functioning of system. This data can allow regulators to see where violations occur frequently and collect tolls and parking fees efficiently.

Challenges in optimizing mobility data

Despite having great importance, there are numerous problems that block the proper utilization of mobility data. The first one is the lack of data sharing: companies still work in silos and the reasons for this are competition and privacy concerns. Thus, there needs to be a common platform where all data is available so that anyone can use it for better city management and decision-making.
On the other hand, data standardization is another challenge that obstructs data sharing. Cities are still struggling to establish a standard for data sharing for efficient management. Therefore, a proper data sharing mechanism is a must for using this data efficiently.