Cooperative Intelligent Distributed Systems for Indoor Localization

无线传感器网络中的定位被定义为测量节点和物理对象之间的空间关系的技术的集合。定位是确定一个对象相对于另一个对象的位置的问题。路由信息作为无线传感器网络的重要组成部分，通过本地化得到了增强。许多现实世界的应用现在需要跟踪或监控封闭环境中的物理对象，如医院、矿山、机场和地铁。虽然全球定位系统(GPS)似乎是一种显而易见的跟踪解决方案，但GPS仍然相对昂贵、耗电，而且在室内使用时性能会降低。无线传感器网络是解决执行广域监视和监视问题的一种解决方案。在大型系统的监控和跟踪中，结合射频识别(RFID)是必不可少的。实体，从物体到用户，都配备了WSN和RFID标签来收集它们的上下文信息。在WSN中使用代理的唯一标识提高了网络的可管理性和可扩展性。*我的研究目标是开发一个新的、智能的、高效的、自主的、有效的室内定位服务系统，将代理与WSN和RFID相结合。这种多方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/没有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；4)进行密集的模拟和开发工作原型。*为了实现我们的目标，我们首先将研究和开发高效、可扩展的能耗感知定位协议。其次，我们将减少估计的运动目标位置与实际位置之间的误差，并将仔细检查不同距离/距离自由协议的定位协议的性能。第三，我们将测试不同的网络拓扑，并根据所需的真实应用程序提出建议。最后，随着我们研究计划的进展，我们将继续评估和提高我们所有提出的算法的性能。*人工智能与无线通信的融合将带来一种处理定位和监控环境的新方法。我们的成果将有利于加拿大的许多应用领域，如制造业、地理跟踪和医疗保健。例如，在医疗保健方面，拟议的方法将为开发集成系统以更好地监测和管理健康状况提供基础。这项研究还将推进将代理与WSN和RFID一起用于仓库、商场、机场、火车和地铁站等室内定位系统以及采矿业的技术。

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.