In recent times, data harmonisation is one of the biggest and most frequently spoken about topics in the data world. When data is ingested from various sources in different formats and frequencies, it places a lot of pressure on engineers and analysts to prepare the data first, to generate insights later. Part of what we do here at Intelematics is precisely that, harmonising and standardising the data to ensure all the prep work is done, and you can start visualising your insights immediately. 

So, exactly where does our data come from? 

Traffic Flow and Congestion 

Our traffic flow data comes from a variety of probe vendors. These include private and commercial fleets with a range of vehicle types with collections as rapid as per second frequencies. Furthermore, the accuracy of our flow data is then validated and calibrated in real-time to determine the most appropriate level of congestion in the area. All the data we collect and publish is anonymous with no personally identifiable information which may unknowingly compromise a user’s security.


As explained in a previous case study, our incidents data comes from a vast array of sources such as the road authorities, emergency services and direct feeds into our traffic reporting channel. This creates a whole new level of complexity than Flow and Congestion as some messages and feeds don’t follow any standard formats. So to remain competitive and utilise our knowledge fully, we have upped the game by a notch to introduce the application of Artificial Intelligence in our incidents reporting. 


Our weather data consolidate close to 10 years’ worth of historical weather reports all over Australia to provide a detailed representation of atmospheric activities over time. We also collect current location observations and weather forecasts to better assist with various decision-making requirements. These datasets include highly granular precipitation data on minute intervals for very small radiuses all over the country, making it possible to associate weather information up to the property level. We understand that a carefully curated weather dataset not only gives general weather advice, but it will also help in an array of other applications, such as maintenance, environmental protection and many other weather-related works and activities.

As we face these unprecedented times, and the need to work remotely becomes not just idealism but a necessity, having an easy to use and harmonised dataset will be ever more critical to enabling distributed parties to collaborate and communicate on the same wavelength. We believe our data will allow users to derive extremely accurate and insightful conclusions, which will help them drive their businesses to the next level in the challenging times ahead.