A significant proportion of the population has become used to sharing private information on the internet with their friends. This information can leak throughout their social network and the extent that personal information propagates can depend on the privacy policy of large corporations. In an era of artificial intelligence, data mining, and cloud computing, is it necessary to share personal information with unidentified people? Our research shows that deep learning is possible using relatively low capacity computing. When applied, this demonstrates promising results in spatio-temporal positioning of subjects, in prediction of movement, and assessment of contextual risk. A private surveillance system is particularly suitable in the care of those who may be considered vulnerable.

A large proportion of the population has become used to sharing private information on the internet with their friends. This information can leak throughout their social network and the extent that personal information propagates depends on the privacy policy of large corporations. In an era of artificial intelligence, data mining, and cloud computing, is it necessary to share personal information with unidentifiable people? Our research shows that deep learning is possible using relatively low capacity computing. The research demonstrates promising results in recognition of human geospatial activity, in prediction of movement, and assessment of contextual risk when applied to spatio-temporal positioning of human subjects. A private surveillance system is thought particularly suitable in the care of those who may, to some, be considered vulnerable.

From parks to shopping areas, smart technologies are being used throughout our cities to inform, guide and even persuade us into certain experiences. In terms of the technologies (and their usage), the emphasis is now very much on the mobile device and mobile applications that provide us with the digital media time to interact and share. Moreover, what we are increasingly witnessing and experiencing is how this mobile experience can fully absorb and disconnect us from the environment around us. The authors of this paper want to re-focus the actual role of the environment in the design of the smart city experiences. Integrating site-specific artworks with smart technologies, the goal of this research is to put the emphasis back into the environment as a place where everyone can engage and enjoy regardless of ability and/or disability. This paper reports on the early conceptual stages of the Cardiff Bay Barrage project. It will highlight how the work (thinking and feeling) of artists, computer scientists, writers and engineers in alignment with the needs of industrial partners Cardiff Council and Philips Lighting Ltd. can bring 'inclusivity' to the experience of all/any visitors to Cardiff Bay Barrage. This paper presents the 'pattern making' process involved in the preparation for gathering and validating of initial requirements to support the overall design for this inclusive experience.

Where Cartesian philosophy distinguishes the perceiving and perceptual mind from the body, phenomenology constitutes the experiential/experiencing body as the subject, giving rise to the affective potential of art. An immersive world of digital connections, smart cities and the Internet of Everything dramatises the centrality of relationship, the intertwining of Self and Other, in the lived environments of human experience. This article addresses the contextual, disciplinary and practical challenges encountered in developing an ambitious interactive public art project embedding SMART technology on the coastal fringes of Cardiff, the capital city of Wales (UK). It examines the processes and problems involved in delivering a stimulating aesthetic experience in and on a complex site, for a complex audience profile. It traces, in particular, the dependence of a multi-disciplinary project team on the theoretical and practical effects of affect in their ongoing effort to produce engaging, provocative, socially inclusive interactive public art, in and through human-centred design techniques.

A simulated annealing based algorithm is presented for segmenting a river centre line. This process is required for the purposes of river symbolization that is often required when generalizing (simplifying) a large scale map to produce a map of smaller scale. The algorithm is implemented and then tested on a number of data sets. A gradient descent based alternative is also implemented. Simulated annealing is shown to produce significantly better results.

The work presented here investigates the usefulness of Ant Colony Optimisation to solving network schematization problems. This is a well-established problem domain and a number of solutions have appeared in the literature previously. In this paper an Ant Colony System (ACS) based algorithm is presented, together with experimental results and performance analysis. The aim is to provide an algorithm that produces better results and is more efficient (in terms of execution times) than previous solutions. Throughout the paper, ACS is tested and evaluated empirically - that is, experiments are performed and observed, these observations are recorded and subsequently analysed. In order to perform the experiments, a software implementation of the algorithm is constructed and then applied to test data sets. No attempt has been made here to perform a theoretical analysis of ACS. The results presented demonstrate that ACS can be used as an effective means of providing solutions to network schematization problems. In particular, ACS is shown to outperform a previous Simulated Annealing based solution.

Automation of map generalization requires facilities to monitor the spatial relationships and interactions among multiple map objects. An experimental map generalization system has been developed which addresses this issue by representing spatial objects within a simplicial data structure (SDS) based on constrained Delaunay triangulation of the source data. Geometric generalization operators that have been implemented include object exaggeration, collapse, amalgamation, boundary reduction and displacement. The generalization operators exploit a set of primitive SDS functions to determine topological and proximal relationships, measure map objects, apply transformations, and detect and resolve spatial conflicts. Proximal search functions are used for efficient analysis of the structure and dimensions of the intervening spaces between map objects. Because geometric generalization takes place within a fully triangulated representation of the map surface, the presence of overlap conflicts, resulting from indi...

This article describes results from a research project undertaken to explore the technical issues associated with integrating unstructured crowd sourced data with authoritative national mapping data. The ultimate objective is to develop methodologies to ensure the feature enrichment of authoritative data, using crowd sourced data. Users increasingly find that they wish to use data from both kinds of geographic data sources. Different techniques and methodologies can be developed to solve this problem. In our previous research, a position map matching algorithm was developed for integrating authoritative and crowd sourced road vector data, and showed promising results (Anand et al. 2010). However, especially when integrating different forms of data at the feature level, these techniques are often time consuming and are more computationally intensive than other techniques available. To tackle these problems, this project aims at developing a methodology for automated conflict

Geographic features change over time, this change being the result of some kind of event. Most database systems used in GIS are relational in nature, capturing change by exhaustively storing all versions of data, or updates replace previous versions. This stems from the inherent difficulty of modelling geographic objects and associated data in relational tables, and this is compounded when the necessary time dimension is introduced to represent how these objects evolve. This article describes an object-oriented (OO) spatio-temporal conceptual data model called the Feature Evolution Model (FEM), which can be used for the development of a spatiotemporal database management system (STDBMS). Object versioning techniques developed in the fields of Computer Aided Design (CAD) and engineering design are utilized in the design. The model is defined using the Unified Modelling Language (UML), and exploits the expressiveness of OO technology by representing both geographic entities and events as objects. Further, the model overcomes the limitations inherent in relational approaches in representing aggregation of objects to form more complex, compound objects. A management object called the evolved feature maintains a temporally ordered list of references to features thus representing their evolution. The model is demonstrated by its application to road network data.

Mapping is a way of visualizing parts of the world and maps are largely diagrammatic and two dimensional. There is usually a one-to-one correspondence between places in the world and places on the map, but while there are limitless aspects to the world, the cartographer can only select a few to map (Dorling, 1996). Map generalization is required when there is a need to represent geographic information that is captured at large scale in a derived form at a smaller scale (Buttenfield and McMaster, 1989). The potential applications, and hence importance, of automated map generalization has increased tremendously with the advent of digital geographic datasets. Much work has been carried out in recent years, and considerable progress has been made. This is evidenced by the many academic papers published on the subject (e.g. Weibel, 1995; Weibel and Jones, 1998; Jones and Ware, 2005), the various working groups that have been set up (e.g. ICA Commission on Generalisation and Multiple Representation) and the increasingly advanced and useful generalization functionality now being found in commercial GIS software. However, many tasks associated with map generalization have proven difficult to automate and many research challenges remain.

This paper explains a ray tracing method which is applied to prediction and visualization of diffracted and reflected GPS signals in dense urban areas. Reflected and diffracted signals can have a detrimental effect on GPS positioning accuracy especially in highly built‐up areas. The ray tracing technique implemented in this paper is specially geared to LiDAR height pole data at 1‐m spatial resolution and 2D building footprints in raster and vector format, respectively. Such a simple data format allows for rapid implementation of 3D ray tracing in a GIS without further processing so that detailed 3D urban models in vector format are not required. Issues of spatial uncertainty in the data used are also addressed in relation to the identification of multipath signals. Some preliminary results obtained from fieldwork are presented and analysed in detail.

This paper describes an automated method for predicting the number of satellites visible to a GPS receiver, at any point on the Earth's surface at any time. Intervisibility analysis between a GPS receiver and each potentially visible GPS satellite is performed using a number of different surface models and satellite orbit calculations. The developed software can work with various ephemeris data, and will compute satellite visibility in real time. Real-time satellite availability prediction is very useful for mobile applications such as in-car navigation systems, personal navigations systems and LBS. The implementation of the method is described and the results are reported.

At the heart of any geographic information system (GIS) is a database system. Data representing geographic entities and spatial features are stored in these GIS and manipulated and visualised according to the user’s input. The rapid emergence of GIS has demanded the evolution of database systems to support these spatial data, and to provide powerful analysis operations and functions to assist in decision support, projections, predictions, and simulations in a wide variety of problem domains. The research reported on in this paper investigates a specific area of interest in geospatial database systems, that of the management and representation of evolving features. Features in a GIS group together entities or areas that are of particular interest from a specific viewpoint, such as counties, population, or in this case, roads.

For the purposes of this paper, a schematic map is a diagrammatic representation based on linear abstractions of networks. With the advent of technologies for web-based delivery of geospatial services it is essential to develop map generalization applications tailored for the same. This paper is concerned with the problem of producing automated schematic maps for web map applications. The paper looks at how previous solutions to the spatial conflict reduction can be adapted and applied to production of automated schematic maps for web services.

Geographic features change over time, this change being the result of some kind of event or occurrence. It has been a research challenge to represent this data in a manner that reflects human perception. Most database systems used in GIS are relational, and change is either captured by exhaustively storing all versions of data, or updates replace previous versions. This stems from the inherent difficulty of modelling geographic objects in relational tables. This difficulty is compounded when the necessary time dimension is introduced to model how those objects evolve. There is little doubt that the object-oriented (OO) paradigm holds significant advantages over the relational model when it comes to modelling real-world entities and spatial data, and we believe that this contention is particularly true when it comes to spatiotemporal data. In this paper, we describe a generic, object-oriented model for representing spatiotemporal geographic data, called the Feature Evolution Model (FEM), based on a 'state-event-state' approach. The model exploits the expressiveness of OO technology by representing both geographic entities and change as objects, and the potential complexities introduced by the temporal elements of change are minimised by subtyping. The conceptual model is represented using UML and has the advantage of being implementable by any OO programming language and database development environment. The generic model is applied to real-world geographic data, that of OS MasterMap Integrated Transport Network (ITN) data.

The advent of high‐end miniature technology, together with the increasing availability of large scale digital geographic data products, has created a demand for techniques and methodologies that assist in the automated generation of maps specifically tailored to mobile GIS applications. This paper concerns itself with the problem of automatic generation of schematic maps. Schematic maps are diagrammatic representations based on linear abstractions of networks. In the context of mobile mapping they are seen as being a particularly useful means of displaying transportation networks. This paper describes an algorithm that automates the production of schematic maps. The algorithm makes use of the simulated annealing optimisation technique. An implementation of the algorithm is also presented, together with experimental results.

This paper aims to investigate how 1m LiDAR data and 2D building footprints can be used to predict GPS multipath effects in urban areas. A ray tracing model is implemented in order to model reflected and diffracted GPS signals. Some preliminary results are presented and explained in detail.

This paper looks at how human factors requirements can be considered in the context of graphic conflict reduction for mobile GIS applications. Currently this reduction is achieved by using schematic mapping techniques. With the advent of high-end miniature technology as well as digital geographic data products like OSMasterMap and OSCAR, it is essential to devise proper methodologies for map generalization specifically tailored for MobileGIS applications. This paper is concerned with the problem of producing schematic maps suitable for rendering on mobile display devices (e.g. PDAs). The application of schematic mapping can be thought of as a data reduction technique for large scale datasets to make it suitable for rendering in mobile applications. These techniques have been based on computation and have not incorporated any understanding of how the simplification affects the ease of use of the maps. It is therefore desirable to devise suitable generalization techniques incorporating human factors considerations for generating schematic maps from large scale datasets for display on small display devices to be used for MobileGIS applications