Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4903
Title: PoHMChain: A Sustainable Cryptocurrency Platform with Proof of Human Mobility Consensus Algorithm D.M.H.P. Dissanayake M.S.W. Salgado S.N.S. Wickramasinghe 2025
Authors: Dissanayake, D.M.H.P.
Salgado, M.S.W.
Wickramasinghe, S.N.S.
Issue Date: 28-Jun-2025
Abstract: Abstract Along with the positive impact, blockchain technology also has negative impacts on the environment, climate, and energy consumption. Algorithms like Proof of Work was tend to consume a great amount of energy, hence alternative methods such as Proof of Stake, Proof of Space have come into play. This dissertation focused on the newly introduced human mobility-based consensus algorithm known as Proof of Human Mobility and its practical implementation. This sustainable, proof-based, leader selection algorithm uses human mobility as the trust factor. A desktop application was implemented for blockchain connectivity, along with a mobile application, which is used to generate tickets proving human mobility. Furthermore research and evaluations were carried out in the following areas. In regard to choosing a better short-range communication method, the practical limitations of the integration of Bluetooth, Near Field Communication, and Wi-Fi Direct is discussed, and an alternative method to address those issues is given for the implementation. To make the Proof of Human Mobility (PoHM) more scalable evaluation were carried out on 8 different scenarios and calculated the average decreasing percentage and transaction per second metrics. Brotli compression with a validator group mechanism had the lowest average decreasing percentage of 26% which showcased the best strategy among all scenarios to work with, when the number of nodes increases. To identify the optimal sensor set to detect fraudulent movements evaluation were conducted on 10 sensor combinations using Random Forest Classifier with captured smartphone sensor data. The GPS + Accelerometer combination achieved 91.73% accuracy, selected as the optimal set for its higher accuracy and lower power consumption.
URI: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4903
Appears in Collections:2025

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