Showing papers in "ACM Transactions on Spatial Algorithms and Systems in 2021"
TL;DR: This research presents a probabilistic procedure for estimating spatial distributions of data of natural phenomena using different spatial interpolation techniques and shows good results for estimating the distribution of noise in urban areas.
Abstract: Spatial distributions of data of natural phenomena can be estimated by using different spatial interpolation techniques. These techniques can be used for the purpose of developing urban noise pollu...
10 citations
TL;DR: This article conducts a thorough analysis of how this widely used method to estimate predictability in human mobility works by looking into two different metrics that are easier to understand and, at the same time, capture reasonably well the effects of the original technique.
Abstract: Predicting mobility-related behavior is an important yet challenging task. On the one hand, factors such as one’s routine or preferences for a few favorite locations may help in predicting their mo...
5 citations
TL;DR: The unprecedented rise of social media platforms, combined with location-aware technologies, has led to continuously producing a significant amount of geo-social data that flows as a user-generated stream as mentioned in this paper.
Abstract: The unprecedented rise of social media platforms, combined with location-aware technologies, has led to continuously producing a significant amount of geo-social data that flows as a user-generated...
5 citations
TL;DR: In this paper, a scalable approach for range and k nearest neighbor queries under computationally expensive metrics, like the continuous Frechet distance on trajectory data, is presented, based on clustering for met...
Abstract: We present a scalable approach for range and k nearest neighbor queries under computationally expensive metrics, like the continuous Frechet distance on trajectory data. Based on clustering for met...
5 citations
TL;DR: The proliferation of GPS-enabled devices has led to the development of numerous location-based services as discussed by the authors, which need to process massive amounts of streamed spatial data in real-time.
Abstract: The proliferation of GPS-enabled devices has led to the development of numerous location-based services. These services need to process massive amounts of streamed spatial data in real-time. The cu...
5 citations
TL;DR: An optimal algorithm for 2D trajectories using a model with unbounded acceleration but bounded velocity, and an algorithm for any model where consistency is “concatenable”: a consistent subsequence that ends where another begins together form a consistent sequence are described.
Abstract: Trajectories are usually collected with physical sensors, which are prone to errors and cause outliers in the data. We aim to identify such outliers via the physical properties of the tracked entit...
3 citations
TL;DR: In this article, the authors considered real-world travel (road-network topology, speed speed, etc) and proposed an algorithm to optimize itineraries for agents to visit multiple targets.
Abstract: The Vehicle Routing Problem (VRP) is an NP hard problem where we need to optimize itineraries for agents to visit multiple targets. When considering real-world travel (road-network topology, speed ...
3 citations
TL;DR: With the ubiquity of spatial data, vertexes or edges in graphs can possess spatial location attributes side by side with other non-spatial attributes.
Abstract: With the ubiquity of spatial data, vertexes or edges in graphs can possess spatial location attributes side by side with other non-spatial attributes. For instance, as of June 2018, the Wikidata kn...
2 citations
TL;DR: This work considers a scenario when sensing requests are originated from sensor aware applications that are host aware and when the applications themselves are not sensor aware.
Abstract: Integration of sensor and cloud technologies enable distributed sensing and data collection. We consider a scenario when sensing requests are originated from sensor aware applications that are host...
2 citations
TL;DR: In this paper, a novel square equal area map projection is proposed, which combines closed-form forward and inverse solutions with relatively low angular distortion and minimal cusps, a combination of pr...
Abstract: A novel square equal-area map projection is proposed. The projection combines closed-form forward and inverse solutions with relatively low angular distortion and minimal cusps, a combination of pr...
1 citations
TL;DR: In this article, the quality-of-position (QoP) assessment problem is studied in an offline manner, which aims to assess the localization accuracy that can be obtained by a user that aims to localize using a fingerprint map.
Abstract: Internet-based Indoor Navigation (IIN) architectures organize signals collected by crowdsourcers in Fingerprint Maps (FMs) to improve localization given that satellite-based technologies do not operate accurately in indoor spaces where people spend 80%–90% of their time. In this article, we study the Quality-of-Position (QoP) assessment problem, which aims to assess in an offline manner the localization accuracy that can be obtained by a user that aims to localize using a FM. Particularly, our proposed ACCES framework uses a generic interpolation method using Gaussian Processes (GP), upon which a navigability score at any location is derived using the Cramer-Rao Lower Bound (CRLB). We derive adaptations of ACCES for both Magnetic and Wi-Fi data and implement a complete visual assessment environment, which has been incorporated in the Anyplace open-source IIN. Our experimental evaluation of ACCES in Anyplace suggests the high qualitative and quantitative benefits of our propositions.
TL;DR: GloBiMap is proposed, a randomized data structure, based on Bloom filters, for modeling low-cardinality sparse raster images of excessive sizes in a configurable amount of memory with pure random access operations avoiding costly intermediate decompression.
Abstract: In the last decade, more and more spatial data has been acquired on a global scale due to satellite missions, social media, and coordinated governmental activities. This observational data suffers ...
TL;DR: Zhang et al. as mentioned in this paper proposed a multi-source variable rate (MSVR) signal reconstruction mechanism for road topology map inference using a three-stage approach, which incorporates a novel Multi-source Variable Rate signal reconstruction scheme.
Abstract: The amount of GPS data that can be collected is increasing tremendously, thanks to the increased popularity of Global Position System (GPS) devices (e.g., smartphones). This article aims to develop novel methods of converting crowd-sourced GPS traces into road topology maps. We explore map inference using a three-stage approach, which incorporates a novel Multi-source Variable Rate (MSVR) signal reconstruction mechanism. Unlike conventional map inference methods based on map graph theory, our approach, to the best of our knowledge, is the first use of estimation theory for map inference. In particular, our approach addresses the unique challenges of vehicular GPS data. This data is plentiful but suffers from noise in location and variable coverage of regions. This makes it difficult to differentiate between noise and sparsely covered regions when increasing coverage and reducing noise. Due to the asynchronous, variable sampling rate, and often under-sampled nature of the data, our MSVR approach can better handle inherent GPS errors, reconstruct road shapes more accurately, and better deal with variable GPS data density in empirical environments. We evaluated our method for map inference by comparing to Open Street Map maps as ground truth. We use the F-Measure, Precision, and Recall metrics to evaluate our method on Tsinghua University’s Beijing Taxi Dataset and Shanghai Jiao Tong University’s SUVnet Dataset. On these datasets, we obtained a mean F-Measure, Precision, and Recall of 0.7212, 0.9165, and 0.6021, respectively, outperforming a well-known method based on Kernel Density Estimation in terms of these evaluation metrics.
TL;DR: The cavity decomposition problem is a computational geometry problem, arising in the context of modern electronic CAD systems, that concerns detecting the generation and propagation of electromagne... as mentioned in this paper, and it is a well-studied problem.
Abstract: The cavity decomposition problem is a computational geometry problem, arising in the context of modern electronic CAD systems, that concerns detecting the generation and propagation of electromagne...