面向物联网搜索的群智感知关键技术研究

Crowd sensing is a novel and important way to implement comprehensive sensing in the Internet of Things (IoT). It brings about broader, richer, and more timely data source to IoT search, and provides larger improvement space to smart search ability. Considering the requirements of IoT search on extensiveness, timeliness, and location correlation, we focus on three key technologies of crowd sensing, including user incentive mechanism, search task distribution and data collection, and entity location search, from three aspects, including data acquisition, data transmission, and data analysis, respectively. We solve three key scientific problems: 1) the user incentive strategy optimization for extensiveness requirement, 2) the search task distribution and data collection for timeliness requirement, and 3) the trade-off of efficiency, accuracy, and cost of entity location search, through which a serious of original theoretical achievements and key technical breakthrough will be obtained. Moreover, we develop the prototype system of location based IoT search for application verification. The expected project results will enrich the basic theories and implementation technologies of IoT, provide guidance on the application of crowd sensing technologies in the field of IoT search, and support the national strategy of IoT development.

群智感知是实现物联网全面感知的新型重要手段，为物联网搜索带来了更广泛、更丰富、更及时的数据来源，为智能搜索能力提供了更大的提升空间。针对物联网搜索对广泛性、时效性和位置关联性的需求，本项目围绕数据获取、数据传输、数据分析三个层面重点研究用户激励机制、搜索任务分发与数据收集、实体位置搜索三项群智感知关键技术，分别解决满足广泛性需求的用户激励策略优化，满足时效性需求的搜索任务分发与数据收集，实体位置搜索效率、准确性与成本的平衡三个关键科学问题，取得一系列原创性理论成果和关键技术突破，并构建基于位置的物联网搜索原型系统进行应用验证。项目预计成果将丰富物联网的基础理论和实现技术，为群智感知技术在物联网搜索领域的实际应用提供理论指导，有力支撑物联网发展的国家战略。

本项目针对物联网搜索对广泛性、时效性和位置关联性的需求，围绕数据获取、数据传输、数据分析三个层面重点研究用户激励机制、任务分发与数据收集、实体位置搜索三项群智感知关键技术，在用户参与在线激励机制、机会数据收集延迟分析理论、基于群智感知的目标位置识别方法等方面取得一系列原创性或创新性的重要成果，并构建了基于群智感知的目标位置识别系统和协同目标搜寻系统验证平台。成果有效解决了满足广泛性需求的用户激励策略优化，满足时效性需求的搜索任务分发与数据收集，实体位置搜索效率、准确性与成本的平衡三个关键问题，丰富了物联网的基础理论和实现技术，为群智感知技术在物联网搜索领域的实际应用提供了理论指导。.本项目在相关领域期刊和会议上发表和录用学术论文共计17篇，其中SCI检索论文7篇，包括国际一流学术刊物IEEE Trans. on Vehicular Technology（SCI 2区）论文1篇、IEEE Trans. on Human-Machine Systems（SCI 2区，CCF B类）论文1篇，EI检索论文10篇。获得授权中国发明专利3项，申请发明专利3项。项目主持人在承担该项目期间获得了教育部自然科学奖一等奖、中国计算机学会自然科学一等奖和北京市教学成果奖一等奖等奖项。