Artificial Intelligence and Blockchain-Based Trading Framework for Satellite Images

The convergence of artificial intelligence (AI) and the space industry is a crucial step towards advancing humanity. It has the potential to create innovative technologies and services, revolutionize existing practices, and provide valuable insights to space researchers. Many private investors and government organizations possess high demand for satellite images for various reasons, including weather forecasting, global disaster management (e.g., floods, earthquakes, and tsunamis), space object location, land records, geolocations, and international shipment management. However, the traditional centralized economic model for space business is costly to implement in terms of infrastructure, deployment, security risks, ownership, and marketing of the data. Additionally, the initial acquisition of satellite images is usually retrieved in a raw format without any authentication or interpretation. Consequently, the integration of AI and the space industry has the potential to revolutionize the existing model by unlocking new avenues to monetize satellite data by introducing automated processes that are more secure and cost-effective. In this paper, we aim to use deep learning models that are capable of automatically analyzing and classifying raw satellite images into valuable and actionable formats. Furthermore, we are inspired to design a blockchain-based solution to make satellite image datasets available to private and government agencies through a user-friendly and secure marketplace. The proposed solution will focus on a decentralized socio-economic model using blockchain to increase the security of transactions. Blockchain networks facilitate the fair exchange of transactions using smart contracts that will execute and enforce agreement rules among the blockchain participants. The proposed research will mainly focus on the efficient design of smart contracts for satellite data blockchain. In addition, our integrated image quality assessment method is built and tested to accurately group high-quality satellite images into valid categories to make the trading and marketing process more efficient.