Crowdsourcing and Crowdsensing as Smart Rural Service Platform Technology

Shengfeng Qin, Xiaojing Niu

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter first clarifies the urgent need for a smart rural service platform and then describes crowdsourcing technologies for service design crowdsourcing and crowd-based service outsourcing including incentive mechanisms, crowds’ qualification, task assignment, workflow management, quality control, crowds’ structure, and information communication and sharing. After that, a crowdsourcing platform prototype for ‘remote diagnosis of crop diseases’ is developed as a demonstrator. It integrates crowdsourcing mechanisms to create an all-in-one platform able to support the effective deliveries of requested services dynamically and flexibly. With information accumulation on the platform and AI technology, it can help optimize the allocation of local manufacturing/service/agricultural resources and capabilities, and it also helps create win–win service-centered business ecosystems with better service traceability. The developed crowdsourcing platform was qualitatively evaluated through the case study ‘remote diagnosis of crop diseases’, and we found that it helped platform actors gain more values from personalized services with improved user experience although some improvements such as privacy protection are still required to be made.
Original languageEnglish
Title of host publicationDigital Transformation with AI and Smart Servicing Technologies for Sustainable Rural Development
EditorsShengfeng Qin, Hongan Wang, Cuixia Ma
Place of PublicationBoca Raton, US
PublisherCRC Press
Number of pages23
ISBN (Electronic)9781032686691
ISBN (Print)9781032686677, 9781032686684
Publication statusPublished - 27 Jun 2024

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