# An Overview of CubeSat Missions and Applications
## 8 The Use of CubeSats in Novel Technology Demonstration Missions
### Communications, AI, and Automation Technology Demonstration  
Moving on to demonstration missions involving communication technologies, one notable mission is the Pathfinder Technology Demonstrator-4 (PTD-4) [305]. Part of the PTD series, this 6U CubeSat was launched in August 2024, with the primary mission of demonstrating the Lightweight Integrated Solar Array and anTenna (LISA-T), which is essentially a deployable and high-power solar array with an X-band antenna combination. This system provides both enhanced power generation and high data rate communication, essential characteristics for extended missions. The PTD-4 CubeSat with its deployed arrays can be seen in Figure 23. Initial flight data has confirmed the proper function of on-board electronics; however, some challenges are observed in the full extension of the solar power and communication arrays [306]. This in-orbit demonstration provides useful insight regarding the performance as well as the challenges related to this type of deployable system. Figure 23: Pathfinder Technology Demonstrator-4 (PTD-4). Image credit: Terran Orbital Corporation [307]. One other ground-breaking mission was \(\Phi\)-Sat-1 (PhiSat-1) mission developed by ESA in collaboration with Ubotica Technologies (Dublin, Ireland) [308]. Launched in September 2020, this 6U platform was part of the Federated Satellite Systems (FSSCat) mission, with the main objective of demonstrating how Artificial Intelligence (AI) can be used on-board an Earth observation satellite. To validate the usage of AI for the detection of clouds in observation images, a feature that reduces the unnecessary data sent to ground allowing for more efficient and fast data delivery, it utilized an Intel(r) Movidius(tm) Myriad(tm) 2 vision processing unit (Intel, Santa Clara, CA, USA) and a deep convolutional network, known as CloudScout. It was validated that this combination of hardware and AI is feasible, since the data was processed in-orbit and then sent back to Earth, with a much-reduced data volume and high accuracy in cloud detection. \(\Phi\)-Sat-1 also demonstrated that integrating AI in on- board decision making in CubeSat operations can reduce their ground control dependence. Built upon this mission's success, ESA developed \(\Phi\)-Sat-2 (PhiSat-2) [309]. Launched in August 2024, this 6U CubeSat's innovation is the implementation of a convolution autoencoder image compression algorithm, tailored to the computational constraints of the CubeSat platforms, used for on-board image compression. The OBS was tested in three environments, a graphic processing unit (GPU), a vision processing unit (VPU), and a central processing unit (CPU), with the VPU-models requiring lower power but more time in comparison with the GPU-models. \(\Phi\)-Sat-2 successfully validated the AI compression algorithms, both reducing the transmission load and the computational load for in ground processing. One mission demonstrating automation technologies in CubeSats is the Starling mission, by NASA's Ames Research Center, in collaboration with Stanford University, Blue Canyon Technologies and CesiumAstro (Austin, TX, USA) [310]. Using four 6U CubeSats, that were launched in July 2023 aboard a Lab Electron Rocket, this mission had four objectives: the Mobile Ad-Hoc Networking (MANET), the Distributed Spacecraft Autonomy (DSA), the Starling Formation-Flying Optical Experiment (StarFox), and the Reconfiguration and Orbit Maintenance Experiments Onboard (ROMEO). Each CubeSat was equipped with deployable solar panels, star trackers, reaction wheels, GPS and S-band antenna, a cold-gas propulsion system (HAMLET), a Xiphos Q75 processor, and a CesiumAstro CommPack crosslink radio. In MANET, CubeSats formed a network that could achieve >90% reliability and could support data transfers up to 50 kB. During DSA, CubeSats coordinated autonomously data collection for studying the ionospheric electron density variations and dynamically adjusted the measurement strategies.