This repository sem_analysis contains the code of the paper published in the 2023 Fifth International Conference on Blockchain Computing and Applications (BCCA).

If you are using this code in full or in part, please cite our work as:

@inproceedings{cowlishaw2023automating,
    title={Automating and decentralising satellite-based emergency mapping},
    author={Cowlishaw, Robert and Boumghar, Red and Arulselvan, Ashwin and Riccardi, Annalisa},
    booktitle={2023 Fifth International Conference on Blockchain Computing and Applications (BCCA)},
    pages={76--81},
    year={2023},
    organization={IEEE}
}

The quantity and diversity of stakeholders in space is increasing and centralised management of their assets is becoming more complex. New technologies in Web3 such as Decentralised Autonomous Organisations (DAOs) can bridge the communication gap with neutral and automated systems, and distribute currently centralised processes that are inherently decentralised by nature. One of these processes is Satellite-based Emergency Mapping (SEM) for Disaster Response Management (DRM). With automated decision strategies and transparent ledgers, a fairer and more accessible system can be built to handle the increase in stakeholders as well as the increasing number of natural disasters occurring. A DAO also address' the key issue with the current SEM process, such as decreasing the current three days wait, required to produce the necessary processed and analysed data for end users, after the disaster occurs. Moreover, with fleets of satellites belonging to different governmental and private organisations, a specific central authority cannot be identified to manage the process in an efficient and equitable way. The paper discusses the need for a more decentralised and automated system for DRM by presenting evidence of current bottlenecks and lays the foundations of the first DAO for on-orbit assets management and demonstrates which Web3 technologies could further improve SEM in this first phase of charter activation.

The work was produced by Robert Cowlishaw of the Intelligent Computational Engineering Laboratory (ICE Lab) of the University of Strathclyde, UK.

This repository smart_contracts contains the code of the paper published in the Proceedings of the 2023 conference on Big Data from Space (BiDS’23).

If you are using this code in full or in part, please cite our work as:

@inproceedings{cowlishaw2023proof,
  title={Proof of optimality for a decentralised EO data processing architecture},
  author={Cowlishaw, Robert and Riccardi, Annalisa and Arulselvan, Ashwin},
  booktitle={2023 conference on Big Data from Space (BiDS’23)},
  year={2023}
}

Earth Observation (EO) data is large and often processed in a very centralised manner. Through the decentralisation and distribution of data processing, a more neutral and automated system can be created, while incentivising a more diverse set of data sources. This can help lower the initial barrier for new data providers and help with decreasing the time it takes for data to be created for systems such as Satellite-based Emergency Mapping. Building such architecture on a decentralised network comes with difficulties, such as merging centralised data sources together, building trust or reputation on a trustless system, and building processes and methods that require low enough computational cost to be executable on distributed networks. This paper discusses how to offload and on-load data onto a distributed network to overcome these computational challenges.

The work was produced by Robert Cowlishaw of the Intelligent Computational Engineering Laboratory (ICE Lab) of the University of Strathclyde, UK.

The repository orbit_consensus_propagation is to study the time it takes for consensus to be reached on-orbit across satellites to provide a way to make fault-tolerant decisions in space. Multi-Objective Optimisation including a Genetic Algorithm is used to generate results. This repository is currently under development...