Real-time asset tracking is an emerging trend that is gaining popularity throughout North America, and as a result, we are seeing the consumption of live data streams from dynamic asset tracking and telemetry (data collection from sensors on vehicles) growing as well. Tracking snowplows, maintenance and delivery vehicles and any other moving assets can produce massive amounts of temporal and spatial data that have a great potential to help organizations better understand their business and make better decisions.
What is dynamic asset tracking?
Fleet and dynamic asset management and tracking tools include the physical tracking and sensing devices themselves as well as the orchestrating software. The devices include GPS technology and telemetry devices that gather important information about the vehicle’s activities. Take snowplows as an example, this can include sensors that identify the ground cover (snow, ice, pavement), thermometer to measure the temperature, whether the plow arm is up or down, the speed of the vehicle or the amount of salt distributed. The software runs on the devices, creates temporal data streams, and can also provide asset or work-order management functionalities.
While this technology has been around for a long time, we are seeing it implemented more broadly, notably by municipalities. These tools and software produce large amounts of valuable data – while they all have their strong points, most miss some key functionalities. Right now, there is no one software that responds to all the needs of an organization when it comes to real-time asset tracking.
While the collection of high-quality tracking data can benefit any organization, leveraging it comes with a new set of challenges. Some of the main challenges we are seeing and questions that are being asked include:
Data storage: how to decide what to store, where and how?
Data streams from fleet and dynamic asset tracking can produce enormous amounts of temporal and spatial data. One of the biggest challenges is how to store that data – but it is not only a question of which kind of database or what structure to store the data in. It is also a question of: what timeframe to keep? What level of precision? Do we keep data from the last 20 days or the last 20 months? On a daily, hourly, or down-to-the-second basis? In some cases, there may be legal requirements to keeping vehicle tracking data for a certain amount of time, such as in the case of a road accident. These situations must be considered when making decisions around data storage.
Reporting and Dashboarding: requirements for creating data reports that go beyond the software’s capabilities.
Often, software for dynamic asset tracking is limited in its ability to produce customized reports and dashboards. The way that the data is presented is not necessarily tailored to the customer’s specific needs and requirements. It can be a challenge to process large amounts of spatial data and quickly generate the kinds of time-sensitive reporting required to exploit the true value of the data and benefit the organization.
Connecting to other systems and/or combining data streams: data can be output in multiple streams and there can be advantages to connecting the data directly with other systems within or outside the organization.
The value of the data also lies in combining it with other systems or data streams. Depending on the structure and availability of the data, it can be a challenge to make those connections. The software available for dynamic asset tracking usually does not natively provide the ability to make all necessary connections – it can only be done with the help of APIs and restructuring the data. It can be a challenge to identify and build these bridges between data streams and other enterprise systems.
Pathways to solutions
As this is an emerging trend, solutions are emerging as well. Two different but complementary solutions that are currently gaining popularity in managing and leveraging the flux of dynamic asset tracking data are the FME Platform by Safe Software and Esri’s ArcGIS Velocity and GeoEvent Server.
ArcGIS GeoEvent Server and ArcGIS Velocity are Esri’s solutions for monitoring dynamic assets that are constantly changing location. The main difference is that GeoEvent Server is on-premises and Velocity is in the Cloud. They can connect to data streams and perform some transformation and analysis. They are THE way to get data into Esri’s Big Data Store. They do real-time data analytics, tracking and geo-fencing and integrate seamlessly with the rest of Esri’s platform.
FME Server and FME Cloud are another way to connect to any data stream – you can make calls or set up webhooks to process a constant stream of incoming data. You can also orchestrate a series of triggers and actions to implement business processes, transform data into custom reports or dashboards and connect directly with a plethora of other systems and databases. The advantage to using FME is the flexibility for data transformation and the ability to interface seamlessly with a multitude of formats, databases, and systems.
Once you have decided how you want to use your dynamic asset-tracking data, here are some relevant questions to ask yourself which might help decide which solutions are right for you:
- What is the structure and format of the incoming data?
- How am I going to transit the data? Which time frames of data do I need?
- Where am I going to store and archive the data, and which cuts of it will I keep?
- What is the end point, how do I need to manipulate it to get there?
We have been involved in implementations of one or both solutions – the perfect recipe will come down to the specifics of your needs, existing tools, software and what you need to do with the data.