Modern storage technology allows for substantial amounts of data to be written and read quickly. Typical household personal computers can store terabytes of data and be relatively compact and power-efficient. Even some mobile devices and portable memory solutions are capable of carrying impressive amounts of information while being small and light (“CFexpress,” n.d.). While these solutions can enable most users to store and work with uncompressed files, such as RAW images or high-bitrate video and audio, specific scenarios require maximum data-handling efficiency. Unmanned vehicles that have to operate for prolonged periods without manual maintenance and are bound by tight power and space restrictions need ways to optimize their data storage.
Data compression algorithms exist in many different forms that are utilized for various applications. Formats such as MP3 are designed for music, JPEG is made for images, and ZIP is used for all types of files (Hemmendinger, n.d.). Data compression can be divided into two types – lossless and lossy, with the former conserving all the data, and the latter strategically removing some of it (“Data Compression,” n.d.). Both methods can be used on a crewless vehicle, and the choice depends on the specific use case of the equipment. Autonomous cars though technically not unmanned, gather vast amounts of data, but only use the relevant parts of it to train AI, thus incorporating lossy compression (Billington, 2018). Scientific operations might not benefit from the same techniques, as researchers need all information to be recoverable, thus necessitating the use of lossless compression (Sayood, 2018). Such data treatment methods do not offer as many savings in terms of storage but ensure that all the original details are preserved, which can be critical for sensor output or text logs.
References
Billington, J. (2018). Finding solutions to the challenge of data storage in autonomous vehicles. Web.
CFexpress. (n.d.). 2020, Web.
Data Compression. (n.d.). 2020, Web.
Hemmendinger, D. (n.d.). Data compression. 2020, Web.
Sayood, K. (2018). Introduction. In Introduction to Data Compression (pp. 1–10). Web.