It’s become a cliché to say that data is the new oil. Like oil, remotely sensed data can be a driver of enhanced mobility and environmental health. And that has to be worth something.
In the 20th century, oil enabled mobility through vehicles with the internal combustion engine. In the 21st century, data is delivering intelligence and insights to a new generation of vehicles as part of smart city planning.
Beyond mobility, data is also increasingly factored into urban planning as the Internet of Things applications gathers pace, and remote sensors begin to proliferate throughout Australia.
In what was likened to a Fitbit tracking device for cities, as many as 70 environmental sensors were installed in a new residential development in Sydney’s north-west to monitor noise, temperature, and air quality.
Melrose Park sites on a 25-hectare site and will soon comprise around 5,000 units. It is also shaping as something of a test case for the planning of future suburbs.
A digital windsock will provide real-time information on weather conditions, including air quality and the UV index. At the same time, sensors placed in buoys in the nearby Parramatta River will monitor water quality.
This data will be made available on a dashboard on the local council’s website. It will be analyzed to understand the impact on the surrounding areas, improve long-term livability, and serve as a blueprint for future developments.
In another IoT application, the “T” could refer to “trees” as quickly as it does to “things.”
German startup Dryad has responded to the bushfire disaster of early 2020 with an application that comprises a network of sensors that claims to detect wildfires in under 60 minutes, even in remote locations.
Current technology uses satellites and cameras, detecting smoke plumes. With the Dryad solution, solar-powered sensors are mounted on trees and AI to detect bushfires at an early stage, when they have begun to smolder.
The data is sent via wireless, satellite, or wired internet to a cloud-based dashboard, which delivers a general overview of the situation from the “intelligent forest.”
The result, it is claimed, will be rapid detection and response, which can save trees, property, and lives — both human and animal.
Gentle social distancing
The project is entirely different, but the IoT is also being used in a small public transport trial, which began in Victoria this month to deliver real-time data on crowding.
Occupancy data on trains, buses, and trams will be collected by passenger counting sensors and gives a pilot group of 50 passengers information on how busy their public transport mode is. The aim is to help passengers comply with social distancing.
Remote sensing in transport issues was also up for discussion recently at a webinar for local council authorities in the Australian state of NSW.
Hosted by connected mobility solutions provider Intelematics, the theme of the event was “Smart Mobility, Utilising Data to Enhance Mobility within your City, Council, or Region.”
The aim was to demonstrate, with tangible examples, how data can be used in local government areas to overcome challenges of movement and flow and ultimately improve the quality of life for residents while contributing to a more vibrant business environment.
The attendees’ top priorities were road safety and traffic congestion and flow, which were nominated by a respective 32% and 18% in an audience poll.
So how can data help? Traffic flow data is now collected on an ongoing basis and can be accessed through a dashboard that combines traffic data, weather conditions, and pollution factors with information collected through IoT devices and road cameras and updated at 15-minute intervals.
It can show how a particular intersection, for example, is turning into an accident hotspot and can also identify the causes behind it.
Traffic flow data shows average speeds traveled by vehicles over particular road sections, and that can be layered over incident and congestion data to understand how the hotspot is occurring and the dynamics behind it.
Not only can this data be used to validate measures such as “traffic calming,” but it can also prove whether the measures are having the desired impact.
Road safety is the primary concern, and addressing it successfully lies in using data to understand the cause and effect, but what about congestion?
In one case study, data analysis suggested that new clearways should be installed on a particular road in Sydney’s west at specific times to ease congestion during peak hours.
Post-implementation, the data showed a notable increase in average vehicle speed, combined with a flattening of the curve for vehicle volume. This showed that the traffic had thinned out and was moving more freely, effectively validating the project and delivering measurable outcomes.
Another priority of the group was infrastructure planning to facilitate mobility, cited by 14% of the audience.
Intelematics’ John Cardoso put the dilemma this way: “On an average trip, 50% of that trip’s duration accounts for only 20% of the distance traveled.”
This is the time it takes to circle the block, looking for a parking space, and then walk to the destination, which is too far away because there were no parking spaces in the immediate area.
Already, the City of Melbourne is piloting an app to show where free parking spaces are — red and green lights in some car parks — but beyond that, data can play into planning to deliver solutions in the design phase.
If planners of a new shopping center, for example, know where the congested traffic in the immediate vicinity is coming from, then they can improve the transport options and traffic flow from those routes.
In a modern city, this is a combination of pedestrian, bicycle, public transport, and vehicle options, all informed by an aggregated data analysis.
It might not be rocket science or fit in with the idea of data being the new oil, but the good news is that all these efforts might save on oil — while we are still using it — by making our cities smarter and more efficient.
Image credit: iStockphoto/Sandra M