Remote sensing with a difference. That’s what Ellen Christopherson, CEO and founder of clearGrid, is here to talk about. Their unique way of collecting radio frequency (RF) data makes them a valuable partner for utility and energy companies that do any type of meter readings and billings. Ellen’s background in aviation engineering gives her an edge to see how technology can deliver efficiency in this space.
It’s a massive task to get data from a meter back to the office in a format that the utility company then can use for their operations. Typically, there is a meter installed in a building (or somewhere that can send data), but the signal can be obstructed from different types of objects. Sometimes the exact location of the meter is unclear.
Companies have two ways around these challenges:
Basically what this looks like is a person drives around and collects data. In order to do this successfully the signal from the meter needs to penetrate the built environment and make it to the road where the data can be collected from a vehicle. This model also assumes that the location of the meter is known in order to optimize the collection path but this is not always the case.
The meters of the network talk to each other or a central node. It takes years to set up a system like this, if at all possible because it’s only viable for utilities that have a denser population ̶ cities. Electric utilities tend to look into this because of the capital required to set it up, especially on the IT side. It needs an overhaul of the entire IT system to be able to handle that kind of data coming in.
From 4500 feet above the ground, you get an entirely different viewpoint on a meter than you would from the ground with obstructions, buildings, or trees. Planes pass by within a certain distance of an address and pick up readings. The signals are then triangulated. Every time a meter is heard, the location and the signal strength are recorded, and a 3D map of that RF environment is created. A physical address becomes less of a concern because its own coordinates are now established, and a smart flight route in 3D space can be planned to hear that meter.
What about All the Other RF Signals out There? Isn’t That Space Crowded Already?
Technology has made it possible to filter out signals and handle all of the meters chirping in at once. Each meter has a unique identifier that’s attached to the rest of the data, making it easier to sortthrough it later. Meters are categorized by their identifiers, and this becomes their data point to associate everything else with. You can tie this back to a particular utility and keep the data separate if you need to.
The meters don’t have location data in them. The guestimate on where the meter is located comes from the triangulation, grabbing the signal data from multiple angles. Not only does this pinpoint where the meter is, but it also reveals its environment and what’s potentially blocking it. If it’s blocked, the signal can only come from straight above, while if it’s wide open, it’s possible to get a signal from 190km away. Triangulationgives data a powerful context.
What’s the Collected Data Like? What Can You Do with It?
After collection, you end up with a unique data set. A set unlike other sets out there. It provides a smart flight path so that next time the information can be collected as efficiently and quickly as possible.
You can also take the data and see what the RF environment looks like. You get a detailed picture of a planned mesh network with specifics on potential interference. You also get to see where the signals arenot located and understand what buildings or structures are impeding RF signals in that area.
Definitely. Changes happen all the time. Other RF signals can enter your space. For example, you keep adding more and more devices into your smart home, and eventually, you change the whole RF environment. Or there could be temporary structures erected and taken down the next month. Every time a flight takes place, these changes are recorded.
Surprisingly, foliageis not a big problem. Some RF signals can be affected by foliage, but with the ranges ClearGrid uses, it’s not an issue.
It depends on the meter.
Some transmit all the time, or at least at regular intervals, while others need to be pinged and woken up to transmit. There are many types of meters and manufacturers out there, but ClearGrid is flexibleand works with what’s given. It’s best to use the same type of meters for a system to be efficientand to avoid bottlenecks.
Data collection this way is applicable for all utilities, yes. The only assumption is that the meters in place are all RF capable meters. The system is agnostic, and therefore, it’s useful in so many other areas.
In the energy industry, anti-corrosion is a critical part of maintaining the infrastructure. This technology can help cathodic protection systems on pipelines without sending people into dangerous and far away areas on foot to take measurements by hand. Works with abandoned wells, too, via down wall monitoring and grabbing the data and tracking from the air.
Sensors can be customized and outfitted with communication devices that are used on our planes. In a pipeline scenario, to get as much life out of the battery as possible, these customized industrial sensors are woken up to send signals when it’s time to collect data in the area. In the meantime, they are programmed to collect information at appropriate intervals and keep the data.
It could very well be in the future. But for now, lack of connectivity is an issue, especially in rural areas. It limits both mesh networks and IoT.
Another issue is that once you set up a mesh network, what do you do with the data that’s coming in, without overwhelming your system and your people? It’s not just a matter of connecting everything together. Your data has to be channeled and appropriately analyzed. This is a huge roadblock, and a massive overhaul needs to be implemented on the IT side of your business so that the information collected is useful to the people sitting at your end. Artificial Intelligence can be an excellent tool, but with utilities, it’s not there yet.
The biggest challenge is regulation. Think about a utility service territory. It’s a vast area, it could even be nationwide, and you need to cover it every month. Regulations for drones vary from country to country. Most of the time, it’s limited by line of sight. If it’s not, then there is a further limitation to airspaces, international airport spaces, military zones, or flying along borders. Drones are not welcomed in many airspaces right now.
On the technology side, you need a drone that can handle more extended missions and cover sizable areas of ground. Larger drones can handle this. They have enough power to stay up in the air and accommodate the incoming data flows. Diamond Aircraft (DA42) have full conversion kits to unmanned, and they’re capable of providing the power necessary for the task with ease. Until they hit another regulatory roadblock or limited airspace, that is. However, the current regulations focus on small drones, so they face more regulatory challenges.
Remote sensing is a vague definition.
It’s always best to narrow down the mission and not overwhelm people with the technology that’s delivering it. The mission should be solving problems, not talking about technology. People who aren’t in the remote sensing industry should understand what we offer, which is so much more than just collecting data.
Do you agree with Ellen’s visionary marketing strategy in drawing in non-tech GIS crowds to understand what problems they solve? As someone who loves all shiny and techy things, I tend to agree. How else do you think we can make GIS more accessible to laypeople?
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WHAT IS OPEN SOURCE SOFTWARE? It’s software thatshares the actual instruction code, and the binary you run on your computer. There are different versions and variants of how that sharing happens. Essentially, you get access to the underlying recipe of the software. You can modify it and adapt it for your needs. This episode is all about building a business based on open source GIS software.
On one side, we have the promise of personalization of being seen and understood, provided we share our data about how we interact with the world. That data can be used to make things better. On the other side, we risk being exposed or being manipulated and treated like a product instead of the customer. In terms of data privacy, location plays a massive role. We, the geospatial community, play a role in this conversation.
Artists, mathematicians, and scientists think about their work as a structure that already exists. Their job is to chip away at the detritus. They clear the noise and the content that distracts. They dig up the bones of a fossil and work on revealing a structure that’s already there.
Take Michelangelo, who, by his own admission, was onlyfreeing David from the surrounding marble.
Mapmakers let the geographic content ̶ the data and the layers ̶ communicate.