Frameworks for Evaluating Affective Design and Managing Prosumer Community Groups Using Blockchain and ML

Abstract

This dissertation presents two novel frameworks. Increasing Greenhouse Gas (GHG) emission is a question for future environmental sustainability. Viewing agriculture and land use management as a sink to greenhouse gases, this dissertation introduces a novel concept of “agro prosumer community group framework” which is potentially an effective way for locals to participate in carbon reduction mechanism while trading carbon-tokens and providing food traceability platform for local market.This research framework proposed four sub-framework to solve management and carbon assessment issues. The solution framework provides trust and transparency in network by using blockchain concepts as a design guide. Another study propose a social media analytical framework, namely SMAF that utilizes consumer opinion data from social media in order to measure affective qualities in new product. The SMAF is integrated with fuzzy regression to predict affective quality; fuzzy regression is used to evaluate uncertainty which exists in users’ affective quality perceptions. The mechanism of the proposed framework is demonstrated by a case study on affective design of automobiles.