Cooperative Intelligent Distributed Systems for Indoor Localization

室内定位协作智能分布式系统

• 批准号: RGPIN-2017-05113
• 负责人: Shakshuki, Elhadi
• 金额: $ 1.46万
• 依托单位: Acadia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710721
• 关键词: Cooperative; Intelligent; Distributed; Systems; Indoor

Localization in wireless sensor networks (WSN) is defined as the collection of techniques to measure the spatial relationship between nodes and physical objects. Localization is the problem of determining the position of an object with respect to another object. Routing information, a crucial component in WSN, is enhanced by localization. Many real-world applications now require tracking or monitoring of physical objects in closed environments, such as hospitals, mines, airports and subways. While global positioning systems (GPS) would appear to be an obvious tracking solution, GPS is still relatively expensive, power hungry and has degraded performance when used in indoor locations. WSNs are a solution to the problem of performing wide-area monitoring and surveillance. Incorporating radio frequency identification (RFID) is essential in the monitoring and tracking of large systems. Entities, ranging from objects to users, are equipped with WSN and RFID tags to gather their context information. Using agents' unique identifiers in WSN improves network manageability and scalability. My research goal is to develop a new, intelligent, efficient, autonomous system for effective indoor location services, which integrates agents with WSN and RFID. This multifaceted approach has never been achieved before. My research objectives are to: 1) simplify on-demand access to RFID stored information and the integration of WSN; 2) evaluate and develop WSN efficient localization algorithms with/out RFID; 3) facilitate the interaction between WSN and RFID using intelligent agents; and 4) perform intensive simulations and develop working prototypes. To achieve our objectives, firstly we will investigate and develop efficient and scalable power-aware localization protocols. Secondly, we will reduce the error between the estimated and the actual locations of moving targets and we will scrutinize with different ranges/range-free protocols to inspect the performance of localization protocols. Thirdly, we will test different network topologies and make recommendations based on the required real-world application. Lastly, we will continue to evaluate and enhance the performance of all of our proposed algorithms as we progress with our research program. The amalgamation of artificial intelligence with wireless communications will lead to a novel way to deal with localization and monitoring environments. Our outcomes will be beneficial to many application domains in Canada, such as manufacturing, geo-tracking and healthcare. For example, in healthcare, the proposed methods will provide the basis for developing integrated systems for better health monitoring and management. This research will also advance techniques of using agents with WSNs and RFIDs for indoor localization systems such as warehouses, shopping malls, airports, trains and subway stations, and in the mining industry.

无线传感器网络中的定位是一系列测量节点和物理对象之间空间关系的技术。定位是确定一个物体相对于另一个物体的位置的问题。路由信息是无线传感器网络的重要组成部分，通过定位可以增强路由信息。许多现实世界的应用现在需要在封闭环境中跟踪或监控物理对象，例如医院，矿山，机场和地铁。虽然全球定位系统（GPS）似乎是一个明显的跟踪解决方案，但GPS仍然相对昂贵，耗电量大，并且在室内使用时性能下降。无线传感器网络是一个解决问题的执行广域监测和监视。无线射频识别（RFID）在大型系统的监控和跟踪中至关重要。实体，从对象到用户，配备了无线传感器网络和RFID标签，以收集他们的上下文信息。在无线传感器网络中使用代理的唯一标识符提高了网络的可扩展性和可扩展性。 本论文的研究目标是开发一种新型的、智能的、高效的、自主的室内定位服务系统，该系统集成了智能体、无线传感器网络和RFID。这种多层面的方法以前从未实现过。我的研究目标是：1）简化对RFID存储信息的按需访问和WSN的集成; 2）评估和开发有/无RFID的WSN高效定位算法; 3）使用智能代理促进WSN和RFID之间的交互;以及4）执行密集的模拟并开发工作原型。 为了实现我们的目标，首先，我们将研究和开发高效和可扩展的功率感知定位协议。其次，我们将减少移动目标的估计位置和实际位置之间的误差，我们将仔细检查不同的范围/范围自由协议，以检查定位协议的性能。第三，我们将测试不同的网络拓扑，并根据所需的实际应用提出建议。最后，我们将继续评估和提高我们提出的所有算法的性能，因为我们与我们的研究计划的进展。 人工智能与无线通信的融合将为定位和监控环境提供一种新的方法。我们的成果将有益于加拿大的许多应用领域，例如制造业、地理跟踪和医疗保健。例如，在医疗保健领域，所提出的方法将为开发更好的健康监测和管理综合系统提供基础。这项研究还将推进使用代理与无线传感器网络和RFID的室内定位系统，如仓库，商场，机场，火车和地铁站，并在采矿业的技术。