Leveraging entangled quantum states to develop consensus mechanisms in blockchain networks for smart forestry applications

Abstract

Blockchain's evolution has revolutionised data integrity and decentralised processing, impacting diverse sectors, including environmental monitoring. However, conventional blockchains face hurdles in scalability, energy efficiency, and security. This research presents QuantumForest, a consensus algorithm tailored for smart forestry, using verifiable quantum random numbers and entanglement principles. Using enhanced transaction throughput, consensus time, and energy efficiency for real-time forest data from IoT devices, QuantumForest underwent simulations on a blockchain network with nodes ranging from 50 to 500. The evaluation considered factors such as network latency, data size, and environmental noise. The performance exhibited a nonlinear correlation with the number of nodes, influenced by the size of the network and the complexity of the data. Consensus time logarithmically increased with node numbers, while energy consumption demonstrated a sublinear increase. QuantumForest signifies a promising step forward in blockchain, particularly for environmental applications such as smart forestry. By integrating quantum entanglement, it fortifies security, decentralisation, and enhances transaction processing and energy efficiency. This study sets the stage for sustainable, efficient environmental monitoring through blockchain, with far-reaching implications.