Smart cities: using data to shape our urban environments

Smart cities: using data to shape our urban environments

Organisations in Australia and overseas provide insights into how they are using information to build more intelligent cities

Rio Operations Centre: The incident commander's view provides a summary of everything happening around the city on a video wall, including surveillance cameras, maps, simulations, news updates, resources and information about incidents

Rio Operations Centre: The incident commander's view provides a summary of everything happening around the city on a video wall, including surveillance cameras, maps, simulations, news updates, resources and information about incidents

Scarce resources, an ever-growing population, natural disasters and many other factors mean we need to be smart about the way we manage the environments we live in.

CIO Australia spoke to several organisations in Australia and abroad to get insights into how they are tapping into advanced analytic tools, data modelling, machine learning, Internet of Things and and machine-to-machine communications to help build smarter, data-driven cities.

Creating smart transport systems

Port Botany’s rail freight operation was experiencing capacity and congestion issues so the organisation considered investing in new infrastructure.

A team at National ICT Australia (NICTA) collected real-time data from trains and shipping containers and interviewed various stakeholders to build a computer model of trains coming in and out of Port Botany. They were able to use clever scheduling to show the rail line didn't need to be upgraded for another 10 or 20 years, saving hundreds of millions of dollars.

“This is an area of say 300 hectares, and it can move up to 1 million containers per year. We have a forecast of 3 million containers until 2030. So the first reaction from everybody would be ‘we have to build new infrastructure’. That means $100 million just for new infrastructure because you would also have to build new railways, new terminals, etc,” says Thomas Vitsounis, project leader, total port logistics at NICTA.

“We said ‘let’s see how we can make it 2 million with the infrastructure as it is’. So we need to change the layout, we need to change the operational rules, we need to change the flow of goods in and out, etc.”

The team also changed the length of the train carriages, and looked at each interaction within the supply chain from the loading of the containers through to train schedules to better optimise the whole network.

“Looking at the whole system in something as complex as a port can yield important insights. The state-of-the-art model we developed [showing] how all the parts interact showed that the rail infrastructure does not appear to be the main bottleneck. That is very forward thinking of the port [workers] to ask us to analyse the system in this way,” says Dean Economou, technology strategist at NICTA.

“The conventional techniques for analysis just don’t reveal the subtlety in the interactions. Now it’s actually possible to get visibility of the entire supply chain, whereas before that was quite difficult.

"You know where stuff is and you can see two stages up the supply chain if there’s a delay. Because you know what’s happening further up the chain, you can actually adapt your own situation.”

The NICTA team is also working on optimising Canberra's bus network because there's a shortage of bus drivers and services to support growing demand, particularly on weekends.

Instead of the government throwing more money at the problem, the NICTA team looked at how the transport system could be transformed to create efficiencies. Using a new model, the system showed that people could get to their destination faster without having to pay more for their ticket.

“You get a taxi to pick you up and take you to the bus hub. Then you get on a high frequency bus, go to the next bus hub and get on another taxi. You’re thinking ‘that’s very expensive’. But it turns out that because of the savings you make by having the buses running nearly full, keeping the buses fully utilised, you actually have enough money to pay for the taxis at either end,” says Economou.

“And instead of just waiting at the bus stop where you have a service say every two hours, you can just ring up a taxi with 15 minutes warning and say ‘I’d like to catch the bus at this bus stop’. Yeah, you do have to change [mode of transport], but you don’t have to wait as much.”

NICTA has sent a proposal to the ACT government to trial the new system.

“It’s the ability to build these detailed models with lots of understanding of the interactions and the costs; and now using more advanced mathematics and computation, you can actually run scenarios and understand them,” says Economou.

NICTA is also doing machine learning and predictive analytics in addition to conventional simulation planning for a new light rail in George Street, Sydney. The team looked at historical data to build a model that can predict how the traffic will behave under certain conditions, and build future action plans based on that data.

“We are looking at how to complement and extend it with machine learning [using] the counters from under the road. So there are these little things that detect cars, and those things are constantly counting … and inferring how to adjust the green, red and amber cycles to try and get through as many cars as possible,” says Economou.

“We built a model of how the Sydney CBD is working and then from that, made predictions on what would happen when George St was closed.”

Preventing incidents with smart safety and emergency services

There were 1,188 road deaths let alone crashes in the year ended March 2014, according to Bureau of Infrastructure,Transport and Regional Economics.

John Wall, manager of road safety technology at Transport for NSW, reflects on an incident from a few years ago that stands out in his mind: A young women was driving in severe wet conditions, hit a wet patch on the road and crashed into a pole.

At the time, Wall asked: How could smart, connected technologies help prevent crashes like this, as well as make the job of emergency services easier?

Wall says gathering weather data, as well as information about the driver and car through an opt-in form, could be used to encourage drivers to avoid certain roads during severe wet conditions or to take public transport when they are planning their journeys.

“In the future, hopefully we will prevent those kids from getting on the road in the first place. The driver who hit this pole was a P-plater, she was in an old vehicle, and the weather was absolutely terrible. She hit a very wet patch of road in really heavy rain, and lost control,” says Wall.

“If the system was able to know a little bit more about the driver, perhaps the journey systems could of taken into account all of this information on the weather plus the fact she was young, driving a car that doesn’t have stability control and recommend she go by train or bus.”

Connected vehicles also have a role in preventing crashes on the road. The idea is to have sensors on the wheels that detect a sharp bump in the road or a when the wheels start to get slippery so that information can be relayed to other connected vehicles behind and warn the drivers to slow down, Wall says.

“The car could even prepare itself to hit that wet patch by getting its breaking systems ready, and electronic stability control. So it’s not just being able to warn the driver, it’s also warning the vehicle management systems that control the breaks and the accelerator and steering – all of those sorts of things – that there’s a potential hazard ahead.”

The NSW Centre for Road Safety is trialling a Cooperative Intelligent Transport Initiative (CITI) where trucks are fitted with anti-collision devices. Information such as the truck’s position and speed is sent from the truck to roadside devices. The devices then send alerts, such as warnings about potential crashes, back to truck drivers.

“The Dedicated Short Range Communication radios that we will have installed in some trucks in the Illawarra from July are doing this 10 times a second – sending information out to other vehicles if they detect hazards that are on the road,” says Wall.

“The vehicle talks to the driver only when the situation becomes more urgent or critical … because we don’t want drivers getting 10 messages a second. The system itself that sits in the vehicle takes care of that information and then decides through business rules what it should actually advise the driver on.”

Transport for NSW is also working on Automatic Crash Notification technology that lets a connected vehicle automatically call emergency services and inform staff of its location once it has crashed.

“In the US, there are a number of people who have been working at George Washington University and they have taken it one step further. They have also looked at sensor systems within the vehicle to determine how many passengers are in it. It’s the kind of sensors that cause a light to flash when you are not wearing your seat belt. So [emergency services] can plan for the number of causalities that may be at the crash scene,” Wall says.

“I have been to a number of night time crashes … where vehicles have gone over cliffs and those sorts of things, and it’s been very difficult to find where these people are. We have heard of people who have crashed not being found until the following morning, and they maybe would have survived if we got early notification of exactly where the crash happened.”

Getting to the crash scene as quick as possible can also be assisted by connected vehicles. Wall says in the near future traffic systems will be able to detect an emergency vehicle coming towards an intersection and readjust the traffic flow to give the vehicle a green light. The emergency vehicle could also talk to other vehicles nearby to alert drivers to give way.

“When the emergency vehicle arrives on scene, then we have to look at things like where’s the best place to cut through parts of the car to rescue a person trapped in a vehicle.

"If they had information at their fingertips, maybe through Google Glass and augmented reality, they would be able to look at the vehicle and know where potential hazards are, where they can’t cut because there’s a high voltage cable that runs in a particular compartment or there’s an airbag that hasn’t gone off that’s at risk of going off,” Wall says.

The NICTA team did an analysis on how fast they could get all people residing in Sydney safely evacuated during a flood. The team looked at which Sydney regions they would evacuate first, which modes of transport should be used first and where.

The analysis found that the current algorithms would not get 40 per cent of the population out in time, whereas the new model showed it can get everyone out safely. “And that it is still possible to do so even if the population increases by 40 per cent,” says Economou.

Next page: Building smart utilities

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