Time Series Is out of This World: Data in the Space Sector
While humans have yet to develop light-speed travel, teleportation or lots of the other cool things we see in movies or read in books, that doesn’t mean we aren’t making progress. Advances in technology are starting, ever so slowly, to blur the lines between science fiction and reality when it comes to outer space.
There are many different types of technology that make space industries “go,” but virtually all of them rely on time series data in some capacity. This article highlights several industries within the space sector that use time series data. Then, we’ll look at some of the sources that produce the data for these organizations. Finally, we’ll consider some of the challenges that exist when focusing business interests in outer space.
Uses for Time Series Data in Outer Space
We’ve long relied on satellites to relay communications around the world. Whether we’re talking about a phone call or a live broadcast on television, everyone has benefitted from satellite-based communications at some point.
Thales Alenia Space designs and delivers satellite systems to power telecommunications, navigation, Earth observation, environmental management, exploration, science and orbital infrastructures.
Just like you’ve probably been to places with spotty reception for your mobile phone, communications companies monitor signal quality from their satellites. Using time series data, these organizations can track changes in signal strength and quality over time and use that data to optimize performance.
Satellite operators also need to constantly be aware of the physical locations of their devices. Combining time series data with radar, signal Doppler and laser reflector data helps pinpoint satellite location and movement over time.
Furthermore, time series data is critical for predicting signal interference and the effects of space weather. Having the ability to anticipate space phenomena like solar flares or meteor showers can have a significant impact on satellite performance.
Earth Observation and Remote Sensing
It’s not enough to simply watch the watchmen, so to speak. While it’s important to ensure that space equipment like satellites is in good working order, the type of work these devices do also makes heavy use of time series data. Loft Orbital provides space infrastructure as a service and collects telemetry data on all its equipment in orbit to ensure everything functions properly.
Remote sensing devices can monitor environmental changes over time. Whether that’s sea levels, the area of polar ice caps or changes in the sizes of the planet’s forests, there are almost endless environmental elements to track.
A common use case for time series data is studying climate patterns and weather forecasting. Having accurate and timely climate data can affect human safety. That’s why this data is also useful for assessing natural disasters and formulating emergency response and restoration efforts when crises occur.
Space Exploration and Navigation
Thanks to sci-fi, exploration is the most common thing we think about when it comes to outer space. Mission planning and execution rely heavily on accurate data and monitoring systems.
First, there’s the actual spacecraft needed to get into orbit. Time series data is critical for trajectory planning, setting thresholds and spacecraft telemetry for launches. Of course, the need for data doesn’t end after a successful launch. Data streams enable monitoring spacecraft health and many other performance metrics for space missions.
The recent deployment of the Webb space telescope highlights another use of time series data in space, which is analyzing and predicting celestial events. Not only are scientists able to see things in greater detail than ever before, but they are also able to track these events in greater detail.
While these examples aren’t exhaustive, they paint a consistent picture of how critical data is for monitoring and understanding aspects of the space sector.
Time Series Data Sources in Space Industries
We’ve touched a little bit on data sources, but it’s worth going a bit deeper to highlight the variety of tools and technology used in the space industries.
Satellite sensors and instruments are some of the most common data sources we see. Public and private organizations alike use a wide range of devices to track events in space and on Earth. The data received from imaging sensors, like optical or infrared sensors, helps us visualize and track phenomena. Spectroscopy sensors help with many aspects of space exploration, like measuring radiation from the sun to understand solar events. These sensors can also track the movements of distant objects, providing a more thorough glimpse of the far reaches of the universe.
Radar and Lidar sensors measure distances using radio waves and lasers, respectively. Astronauts used Lidar to map the surface of the moon. These sensors have wide applications for outward-facing initiatives, as well as inward, Earth-facing goals. For example, weather monitoring systems rely on these and other sensors to monitor space environments, to predict and mitigate the effects of space weather on spacecraft and to monitor and forecast radiation levels in space.
Plenty of ground-based data sources help spur space exploration as well. Telescopes and observatories collect data on and monitor objects and events in space. For example, the Vera C. Rubin Observatory uses time series data to keep its equipment in good running order. These Earth-based devices and systems augment devices in orbit, or even those further afield, to expand the area of the cosmos that humans can monitor. They also help track space debris and identify potential collisions.
Challenges in Handling Time Series Data in Space Industries
While time series data is critical for space industries, managing that data is not always straightforward. This is especially true for devices in or beyond Earth’s orbit. Doing routine maintenance on satellites isn’t possible because the cost of sending a crew up for repairs would break almost any company’s budget. Therefore, these data-producing devices need built-in redundancies and automated processes for managing data.
One challenge with time series data is that sources generate a lot of it. High-volume data is fine when you have cloud infrastructure, but if you need to collect data on a device and then transmit it, you need to make sure you have enough resources to handle that data.
It’s not like you can simply swap out a larger hard drive on a satellite. So organizations need to make sure their devices have sufficient storage and compute power. The latter is key because, while you may want to transmit data from orbital sources to storage on Earth, you likely want to process that data to clean and optimize it before transmitting. This cuts down on total data throughput.
Of course, device malfunctions or space weather events may affect a device’s ability to transmit data. In these events, organizations need to be sure that they have tools on the device and in their central data hub that can handle transmission delays and late-arriving data. A time series database like InfluxDB provides solutions for many of these challenges.
It is available for on-device deployment and can collect and process data at the point of origin. A feature like edge data replication creates a durable queue so that connectivity issues don’t cause you to lose data. Instead, that data automatically gets pushed to a cloud instance of the database once connectivity returns. InfluxDB upserts late-arriving data to ensure you have as complete of a dataset as possible.
Businesses are just starting to scratch the surface when it comes to leveraging space. As more companies explore the possibilities in space, InfluxDB will be there to provide the tools and capabilities that enable observation outward toward the cosmos and inward to the Earth.