Hamouma Moumen

This article focuses on improving fault tolerance and optimizing energy consumption in the context of a mining prospection mission conducted by a swarm of autonomous robots. Two major contributions are proposed. The first aims to reduce communication between robots in order to increase the system’s robustness in the presence of failures. The second focuses on minimizing the trajectory of a deminer robot to reduce overall energy consumption. To address these goals, two reinforcement learning-based algorithms are proposed: Deep Q-Network (DQN) and Federated Reinforcement Learning (FRL), both derived from the Q-learning algorithm. Simulation results examining the impact of the exploration rate α on the number of detected mines show that, with 10 autonomous robots of the same architecture and 30 randomly placed mines over 30 experiments, the FRL algorithm provides better fault tolerance and ensures that the main prospection mission is accomplished even in the presence of some robotic failures or errors. Furthermore, a second series of 60 experiments involving the integration of the deminer robot, focused on optimizing energy consumption, demonstrates that the DQN algorithm is more effective in reducing energy usage, due to improved a better optimization of unnecessary deminer movements, while successfully resolving deadlock situations that the latter may encounter. These findings open the door to the development of a hybrid algorithm combining the strengths of DQN and FRL to ensure both system robustness and minimal energy consumption.

Blockchain technology has emerged as prominent player in supporting the United Nations’ Sustainable Development Goals (SDGs), by providing transparent, decentralized solutions across various sectors. However, the inherent transparency of blockchain raises significant privacy concerns, particularly in sensitive fields such as healthcare, finance, and supply chains, where confidentiality is essential. To address these challenges, we delve into emerging privacy-preserving techniques such as Ring Signatures, Zero-Knowledge Proofs (ZKPs), Secure Multi-Party Computation (SMPC), Trusted Execution Environments (TEEs), and mixers, examining their implementation, effectiveness and limitations in safeguarding user data without compromising blockchain’s core features. Additionally, we provide a deep technical analysis of next-generation blockchain platforms, which implement these techniques to balance privacy, scalability, and interoperability. By offering a deep dive into the architectures and privacy mechanisms of these platforms, this paper contributes to understanding how blockchain can be leveraged to achieve SDG objectives while addressing the critical issue of data privacy.

Since its inception, Blockchain Technology, the underlying technology of Bitcoin has gained a lot of popularity and interest in various industries, varying from the healthcare industry, Internet-of-Things, smart grid, and supply chain management. Sports is one industry where blockchain can have significant breakthroughs where it can reshape the way the sports industry works by providing reliable athlete data management, secure mechanisms for data sharing, reforming the event management practices, collectibles traceability, and many more, but so far its impact is overshadowed by the hype surrounding the use of fan tokens and Non-Fungible-Tokens (NFT) collectibles. This paper aims to provide a systematic review of the ongoing research on the application of blockchain in the sports industry. this work shows that many studies have proposed different use cases for the application of blockchain in the sports industry on and off the field and targeting different stakeholders. However, we inferred a lack of adequate prototype implementations to evaluate the effectiveness of these proposed use cases. We further highlighted the technical details of the implementation of these blockchain-based applications, their limitations, and challenges, and proposed some solutions to support the integration of blockchain in this domain. The findings of this work will be beneficial for researchers, policymakers, and practitioners in the sports industry.