DC-39 - Time-of-Arrival (TOA) Localization for Indoor GIS

Indoor geographic information system (GIS) opens up a new frontier for identifying, analyzing and solving complex problems. In many indoor GIS-driven applications such as indoor wayfinding and logistics planning and management, determination of location information deserves special attention because global positioning system (GPS) may be inaccessible. Alternative methods and systems have emerged to overcome this hurdle. The time-of-arrival (TOA) measurement is one of the most adopted metrics in numerous modern systems such as radar, acoustic/ultra-sound-based tracking, ultra-wide band (UWB) indoor localization, wireless sensor networks (WSN) and Internet of things (IoT) localization. This topic presents the TOA technique and methods to solve the localization and synchronization problem. We also introduce variants of the TOA system schemes, which are adopted by real-world applications. As a use case of the TOA technique realized in practice, a UWB localization system is introduced. Examples are given to demonstrate that indoor localization and GIS are tightly interconnected.
FC-08 - Time
Time is a fundamental concept in geography and many other disciplines. This article introduces time at three levels. At the philosophical level, the article reviews various notions on the nature of time from early mythology to modern science and reveals the dual nature of reality: external (absolute, physical) and internal (perceived, cognitive). At the analytical level, it introduces the measurement of time, the two frames of temporal reference: calendar time and clock time, and the standard time for use globally. The article continues to discuss time in GIS at the practical level. The GISystem was first created as a “static” computer-based system that stores the present status of a dynamic system. Now, GISystems can track and model the dynamics in geographical phenomena and human-environment interactions. Representations of time in dynamic GISystems adopt three perspectives: discrete time, continuous time and Minkowski’s spacetime, and three representations: ordinal, interval, and cyclical. The appropriate perspective and representation depend on the observed temporal patterns, which can be static, oscillating, chaotic, or stochastic. Recent progress in digital technology brings us opportunities and challenges to collect, manage and analyze spatio-temporal data to advance our understanding of dynamical phenomena.