How can big data be optimised to effectively manage increasing urbanisation, congestion and complexity associated with smart cities?
Cities around the world feature different cultures, cuisines and tourist attractions, but most of them face similar challenges in relation to increased urbanisation, congestion and complexity.
With the United Nations estimating that more than half the world’s population now live in urban areas – this number is expected to rise to 60% by 2030 – civic authorities need to find solutions to these challenges now if they’re to effectively address this trend in the long-term.
Unfortunately, as a result of the rapid rise in urban habitation, it’s inevitable that some public services will be impacted as authorities attempt to deliver a consistent quality of experience to a growing population.
For citizens, one of the most obvious areas they will notice this is in the provision of public transport, where it’s hard to overlook the effects of increased traffic congestion and transport-related pollution. And it’s in this area that many see the smart city model as the best practice approach to address these issues.
Saudi Arabia, for example, recently announced NEOM, an ambitious $500 billion project which will see a new smart city economic zone developed over 26,500km. The transnational city will use smart, sustainable and connected technology in areas such as security, logistics and care-giving to improve the lives of residents, visitors and businesses – helping the region flourish beyond its traditional oil export economy.
While smart city technology promises a lot, the concept itself is relatively new. As a result, there are a number of challenges that need to be addressed if its implementation is to deliver the desired result. For instance, just as a starting point, full integration of digital assets is required in for real-time operational visibility of networks.
In addition to this holistic approach to network design and management, there are five other key IT capabilities transport authorities require to deploy and integrate effective smart city technologies:
Planning for and overcoming transport challenges using the smart city approach heavily depends on collecting and processing large volumes of data – all while attempting to navigate day-to-day challenges, legacy systems and conflicting business goals.
Optimisation is critical to managing this complexity, as it automates manual processes to maximise efficiencies and speeds in storing, retrieving and prioritising data.
Irrespective of where data originates from – whether it’s between government departments, or any number of IoT sensors on vehicles, road or track side – effective optimisation helps authorities differentiate between and prioritise tasks, and then identify the best approach to address these.
For example, Amsterdam’s public transport provider, GVB, uses optimisation to manage a range of special circumstances such as disruptions, demand spikes, and even the preferences of every tram, bus and metro driver. By having greater and faster visibility, GVB can redeploy and reallocate resources more flexibly and efficiently to keep its one million passengers moving.
Given smart city data won’t be limited to the public transport network, it’s vital to draw insights from other sources such as surrounding towns, local events, and even the weather, which can impact public transport performance.
Optimisation grants authorities with the ability to respond in real-time, propose new solutions and quickly adapt and incorporate the knowledge of experienced city planners.
Behind any big cities, there exists a complex array of public sector departments and civil servants, as well as numerous private sector organisations and services, working together to keep the lights on. Typically, this approach results in disrupted information flows and the emergence of data silos.
These silos occur when city data is generated and stored on isolated platforms, inaccessible to other departments that might find it useful.
Ultimately, while having the right data is important, running it through a centralised and single platform so that it can be analysed alongside information from other parts of the city is what will generate actionable insights. This interconnectedness is at the heart of any smart city, and is vital for integrated planning, operations and predictive analytics.
In Australia, Queensland Rail has adopted this model to unify its approach to rail management. Completed in 2016, the organisation’s new management centre features a 24 metre-long screen projecting the entire city network – helping manage its growing fleet and the complexity of monitoring a metropolitan rail network.
By better integrating its various operations, Queensland Rail can deliver more dynamic timetabling, smarter fleet allocation and more effective responses to incidents should they occur.
This kind of integrated platform is the key to breaking down data silos and enabling effective communication between different departments, planning teams and employees. And real-time integration provides the fuel for continuous optimisation.
It’s commonplace today for transit agencies to capture data generated by passengers, equipment and infrastructure. Even so, many struggle to realise the value of this data, failing to find ways of using it to improve operations. Data alone is of little value unless it’s capable of providing actionable insights that support decision-making.
By creating feedback loops, data can be collected and the impact of decisions can be seen instantaneously, allowing measurement of results and informing further refinements. An example might be analysing real time data against historical records covering time spent stationary at scheduled stops to optimise service schedules or further improve maintenance window durations.
Using advanced analytics can enable even deeper insights into performance over longer timeframes. Self-learning technology can feed specific data segments back to the planning teams for review, allowing them to update the most critical segments of their planning datapool to improve the accuracy of the process.
Whether it’s looking at how crowding can affect passenger behaviour, or how special events will impact network usage, planners can link data with passenger journeys and trip satisfaction to improve future plans.
Prediction capabilities of advanced analytics can play an essential role in simulating changes to a network and assets, and evaluate the effect of those changes in real-time. In a truly smart city, data from both external and internal sources can be used to see how transport infrastructure demand may change in the future.
Using sources, such as census data to understand how a population is changing, or hospital records to get an aggregated view of the future demands on assisted emergency transport services, can make the difference between success or failure in the eyes of a city’s inhabitants.
The ability to compare ‘what-if’ scenarios is critical to understanding the long-term effects of investments or changes to public transport operations. It also supports planning teams by presenting clear options for contingency planning.
Despite limited government resources, civil servants can be more efficient and more responsive to citizen needs by using predictive analytics to harness the massive volume of available data.
Ultimately, data-driven and IoT powered predictions will not only improve government responsiveness and results, but also create conditions more conducive to innovation by reducing risks associated with future changes to infrastructure.
The public transport sector employs approximately 13 million people around the world, and in European cities like Madrid, Paris or Berlin, these organisations are typically the largest employers.
With large and disparate workforce, it’s critical public transport providers empower employees through mobile technologies, allowing drivers, maintenance and support staff to instantly access the information they need while also becoming more accessible to citizens.
In the same way citizens rely on having instant access to scheduling and delay updates, mobile solutions are becoming an essential tool for employees of all industries worldwide.
When implemented correctly, mobile applications can act as a window onto a city’s whole transport infrastructure, regardless of the device being used, saving time and money for those that keep it running or rely upon it. Fewer applications should be tied to a desktop computer in a smart city.
Becoming a smart city in 2018
There’s no avoiding that transforming into a smart city will be a significant undertaking but a number of cities are already realizing the benefits and beginning down that path. For example, Singapore is building a system that will virtualise the buildings, infrastructures, green spaces and almost every aspect of life in the city-state and then display the results as an interactive, 3D replica.
Regardless of whether a city is continuing or just starting down a smart city ‘journey’ in 2018 – a word that’s important, as becoming a smart city is never truly a destination – these five IT capabilities provide the foundation. And of all the cross capability smart city initiatives, effective provision of transport services will be a major measure of success, impacting the environmental, economical and personal lives of citizens.
The public transportation of the future will be built around commuters who expect little-to-no waiting time, smart ticketing, real-time information, travel comfort and personal security.
Cities like Helsinki in Finland are working to make this a reality by transforming their existing public transport network into a comprehensive, point-to-point ‘mobility on demand’ system by 2025 – hoping to make car ownership a thing of the past. Similarly, Transport for London is making its 12,500 strong workforce more multi-functional through optimising its rostering; meaning staff are no longer restricted by their role when it comes to addressing commuters needs.
By taking an integrated approach to technology, and ensuring solutions providing these five IT capabilities deployed, cities can transform transport for the better provide a better service today, and prepare for increased urbanisation tomorrow.
Source: Information Age
This article is culled from daily press coverage from around the world. It is posted on the Urban Gateway by way of keeping all users informed about matters of interest. The opinion expressed in this article is that of the author and in no way reflects the opinion of UN-Habitat.