Data collection enabled by existing FMM systems lacks 1) the top-down information solicitation on facility conditions, such as crowdsourcing task division, and 2) geo-referenced occupant feedback. Mobile crowdsourcing has great potential to improve current FMM practice, especially in terms of timely data collection. In this context, this paper explores the feasibility of mobile crowdsourcing for FMM data collection and highlights the associated opportunities and challenges. A survey is carried out on a university campus in order to gain an understanding of the human, data, system, geospatial, and automation characteristics of mobile crowdsourcing for FMM data collection on post-secondary campuses. The survey results are analyzed to reveal the challenges and recommendations for mobile crowdsourcing for user-centered FMM. A conceptual framework is proposed to apply mobile crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges, opportunities, and a framework of mobile crowdsourcing-based data collection for FMM.
Application of an occupant voting system for continuous occupant feedback on thermal and indoor air quality – case studies in office spaces
