Abstract

With the huge volume of location-based point data being generated by Internet of Things (IoT) devices and subsequent rising interest from the Digital Earth community, a need has emerged for spatial operations that are compatible with Digital Earth frameworks, the foundation of which are Discrete Global Grid Systems (DGGSs). Offsetting is a fundamental spatial operation that allows us to determine the region within a given distance of an IoT device location, which is important for visualizing or querying nearby location-based data. Thus, in this paper, we present methods of modelling an offset region around the point location of an IoT device (both static and mobile) that is quantized into a cell of a DGGS. Notably, these methods illustrate how the underlying indexing structure of a DGGS can be utilized to determine the cells in an offset region at different spatial resolutions. For a static IoT device location, we describe a single resolution approach as well as a multiresolution approach that allows us to efficiently determine the cells in an offset region at finer (or coarser) resolutions. For mobile IoT device locations, we describe methods to efficiently determine the cells in successive offset regions at fine and coarse resolutions. Lastly, we present a variety of results that demonstrate the effectiveness of the proposed methods.

Highlights

  • The Internet of Things (IoT) consists of millions of devices that are generating a massive amount of location-based point data on a global scale

  • To exploit IoT data that is embedded in a Digital Earth, a need has emerged for spatial operations that are compatible with the underlying Discrete Global Grid Systems (DGGSs) framework

  • In this paper, we present methods that are more closely aligned with the underlying structure of typical DGGSs to model an offset region around the point location of an IoT device

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Summary

Introduction

The Internet of Things (IoT) consists of millions of devices that are generating a massive amount of location-based point data on a global scale. We do discuss how the proposed methods may be adapted or applied to other DGGSs. It is important to mention that while the offset methods presented in this paper are suitable for any point location that is quantized into a cell of a DGGS, we are motivated by and focus on the point location of an IoT device because of (i) the proliferation of IoT devices and the huge volume of location-based point data that is subsequently being generated and (ii) the growing interest between Digital Earth and the IoT and the subsequent use of DGGSs to meet the important needs of efficient indexing, aggregation, summarization, analysis, and visualisation of IoT data at varying spatial resolutions.

The rHEALPix DGGS
Append all cells in I to C
Multiresolution
Mobile Offset Regions
Results
Multiresolution Method
11. Topic 21
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