10 research outputs found
Location Based Indoor and Outdoor Lightweight Activity Recognition System
In intelligent environments one of the most relevant information that can be gathered about users is their location. Their position can be easily captured without the need for a large infrastructure through devices such as smartphones or smartwatches that we easily carry around in our daily life, providing new opportunities and services in the field of pervasive computing and sensing. Location data can be very useful to infer additional information in some cases such as elderly or sick care, where inferring additional information such as the activities or types of activities they perform can provide daily indicators about their behavior and habits. To do so, we present a system able to infer user activities in indoor and outdoor environments using Global Positioning System (GPS) data together with open data sources such as OpenStreetMaps (OSM) to analyse the user’s daily activities, requiring a minimal infrastructure
Crowdsourcing Crisis Management Platforms: A Privacy and Data Protection Risk Assessment and Recommendations
Over the last few years, crowdsourcing have expanded rapidly allowing citizens to connect with each other, governments to connect with common mass, to coordinate disaster response work, to map political conflicts, acquiring information quickly and participating in issues that affect day-to- day life of citizens. As emerging tools and technologies offer huge potential to response quickly and on time during crisis, crisis responders do take support from these tools and techniques. The ‘Guiding Principles’ of the Sendai Framework for Disaster Risk Reduction 2015-2030 identifies that ‘disaster risk reduction requires a multi-hazard approach and inclusive risk-informed decision-making (RIDM) based on the open exchange and dissemination of disaggregated data, including by sex, age and disability, as well as on easily accessible, up-to-date, comprehensible, science-based, non-sensitive risk information, complemented by traditional knowledge. Addressing the ‘Priority Action’ 1 & 2, this PhD research aims to identify various risks and present recommendations for ‘RIDM Process’ in form of a general Privacy and Data Protection Risk Assessment and Recommendations for crowdsourcing crisis management. It includes legal, ethical and technical recommendations
An Agent-Based Variogram Modeller: Investigating Intelligent, Distributed-Component Geographical Information Systems
Geo-Information Science (GIScience) is the field of study that addresses substantive questions concerning the handling, analysis and visualisation of spatial data. Geo- Information Systems (GIS), including software, data acquisition and organisational arrangements, are the key technologies underpinning GIScience. A GIS is normally tailored to the service it is supposed to perform. However, there is often the need to do a function that might not be supported by the GIS tool being used. The normal solution in these circumstances is to go out and look for another tool that can do the service, and often an expert to use that tool. This is expensive, time consuming and certainly stressful to the geographical data analyses. On the other hand, GIS is often used in conjunction with other technologies to form a geocomputational environment. One of the complex tools in geocomputation is geostatistics. One of its functions is to provide the means to determine the extent of spatial dependencies within geographical data and processes. Spatial datasets are often large and complex. Currently Agent system are being integrated into GIS to offer flexibility and allow better data analysis. The theis will look into the current application of Agents in within the GIS community, determine if they are used to representing data, process or act a service.
The thesis looks into proving the applicability of an agent-oriented paradigm as a service based GIS, having the possibility of providing greater interoperability and reducing resource requirements (human and tools). In particular, analysis was undertaken to determine the need to introduce enhanced features to agents, in order to maximise their effectiveness in GIS. This was achieved by addressing the software agent complexity in design and implementation for the GIS environment and by suggesting possible solutions to encountered problems. The software agent characteristics and features (which include the dynamic binding of plans to software agents in order to tackle the levels of complexity and range of contexts) were examined, as well as discussing current GIScience and the applications of agent technology to GIS, agents as entities, objects and processes. These concepts and their functionalities to GIS are then analysed and discussed. The extent of agent functionality, analysis of the gaps and the use these technologies to express a distributed service providing an agent-based GIS framework is then presented.
Thus, a general agent-based framework for GIS and a novel agent-based architecture for a specific part of GIS, the variogram, to examine the applicability of the agent- oriented paradigm to GIS, was devised. An examination of the current mechanisms for constructing variograms, underlying processes and functions was undertaken, then these processes were embedded into a novel agent architecture for GIS. Once the successful software agent implementation had been achieved, the corresponding tool
was tested and validated - internally for code errors and externally to determine its functional requirements and whether it enhances the GIS process of dealing with data. Thereafter, its compared with other known service based GIS agents and its advantages and disadvantages analysed
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Designing a human-centred, mobile interface to support real-time flood forecasting and warning system
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThere is a demand for human-centred technology which improves the management of flood events. This thesis describes the development, design and evaluation of a mobile GIS-based hydrological model. The application provides hydrological forecasts and issues flood warnings. The thesis reports on the usability and practicality of the application. The application, a mobile-based hydrological modelling system, permits the integrated handling of real-time rainfall data from a wireless monitoring network. A spatially distributed GIS-based model integrates this incoming data, approximating real-time, to generate data on catchment hydrology and runoff. The data can be accessed from any android-based mobile computer or mobile phone. It may be further analysed online using several GIS and numerical functions. A human-centred approach to design was taken. Design guidelines for a user-centric application were developed and deployed in the first prototype. There was intensive consultation with potential users. Particular attention was paid to the ease of use of the mobile interface. Users’ needs and attitudes were relevant in the achievement of a highly functional but intuitive interface. The first prototype underwent intensive testing with users. After the initial testing of the first prototype an interactive approach was taken to development. This generated a high-fidelity prototype which was matched to the taxonomy from a user’s mental model. Users were interrogated under controlled laboratory conditions as they performed predefined tasks which were selected to generate data across all aspects of the system and to identify weaknesses. Subsequent to this work there was a major prototype re-design. User test data, identified issues and an improved mental taxonomy closer were used to further refine the application. Of particular note was new functionality which aligned with user expectations and enhanced the applications credibility. The final evaluation of the system was undertaken with diverse subjects. Overall, the subjects considered the system efficient and effective. Users said the system was easy to learn and integrate into their work. Task completion rates were satisfactory. The final interviews with users confirmed that the application was ready to proceed to the implementation phase
A location-aware GIServices quality prediction model via collaborative filtering
The quality of GIServices (QoGIS) is an important consideration for services sharing and interoperation. However, QoGIS is a complex concept and difficult to be evaluated reasonably. Most of the current studies have focused on static and non-scalable evaluation methods but have ignored location sensitivity subsequently resulting in the inaccurate QoGIS values. For intensive geodata and computation, GIServices are more sensitive to the location factor than general services. This paper proposes a location-aware GIServices quality prediction model via collaborative filtering (LAGCF). The model uses a mixed CF method based on time zone feature from the perspectives of both user and GIServices. Time zone is taken as the location factor and mapped into the prediction process. A time zone-adjusted Pearson correlation coefficient algorithm was designed to measure the similarity between the GIServices and the target, helping to identify highly similar GIServices. By adopting a coefficient of confidence in the final generation phase, the value of the QoGIS most similar to the target services will play a dominant role in the comprehensive result. Two series of experiments on large-scale QoGIS data were implemented to verify the effectivity of LAGCF. The results showed that LAGCF can improve the accuracy of QoGIS prediction significantly
A value alignment smart city stakeholder model
The concept of a Smart City has evolved over the last three decades and has attracted the increasing interest of the scientific research community. Unfortunately, many Smart City projects and initiatives do not provide the value expected by all the stakeholders. Many of the reasons for this relate to a lack of data management, data integration, data access and stakeholder participation. People are an integral part of any city’s ecosystem, and the Smart City concept was introduced to address the challenges of an ever-growing global population leading to the risk of depletion of economic, environmental and social resources. The problem addressed in this study is based on the challenges preventing the creation of the value of smart cities or stakeholders. Limited research has been published on the status of Smart City initiatives or on the impact of various success factors on the potential value creation for stakeholders including citizens. Studies on initiatives in developing countries, such as South Africa are even less. Whilst some challenges and constraints related to smart cities in Africa have been reported, there are no studies reporting on initiatives across the data value chain that consider all types of stakeholders, nor the impact of these initiatives. This study addressed this gap in research and designed a theoretical Value Alignment Smart City Stakeholder (VASCS) Model based on a Systematic Literature Review and a review of related theories. The model has important components that should form part of any Smart City project or Smart City initiative. These five main components are: 1) nine Smart City dimensions with related success factors; 2) four stakeholder roles (enablers, providers, utilisers and users); 3) the data value chain; and 4) the five phases of stakeholder benefits/value realisation that can be linked to; 5) stakeholder value alignment. This study applied the VASCS Model to Smart City initiatives in two case studies in the Eastern Cape Province of South Africa, which were the Nelson Mandela Bay and Buffalo City to investigate and understand the status of such initiatives and the alignment of value thereof. The stakeholder interviews were conducted in two rounds with various stakeholders of Smart City initiatives, referred to as cases in the two case studies. An expert review of the VASCS Model was conducted with eight experts in the field of Information Systems and Smart Cities. The findings of this review served to confirm the components of the model, with only minor improvements recommended. It was confirmed that all of the components need to be considered in planning Smart City projects. The first round consisted of six interviews with enablers and providers and the second round consisted of 22 interviews with users, utilisers and citizens. The interviews investigated the value and impact experienced by stakeholders of these initiatives, with a particular focus on the users, utilisers and citizens of the cases. The interview data was transcribed and qualitatively analysed by using Atlas.tiand Excel. The data was analysed according to the Technological, Organisational and Environmental theory constructs and other identified themes. The interview analysis findings revealed several drivers for these initiatives, which were primarily cost reduction, integration and quality assurance. The results also highlighted access to resources, such as technical skills as a challenge. Another challenge identified was connectivity related to access to data and the digital and physical divide that can impact decision making. The main benefits of Smart City initiatives highlighted were the provision of infrastructure, education and training and digitalisation. The theoretical contribution of this study is the VASCS Model, which can assist other researchers and practitioners with knowledge of the factors, drivers, challenges and value obtained in Smart City initiatives. The model has two supplementary components: A Stakeholder Classification Model and a Smart City Success Factor Evaluation Template. The practical contribution of this study is the potential use of the VASCS Model by practitioners, city management, researchers and other stakeholders, who can use the model, with the related model and template for planning and evaluating Smart City initiatives. The model can be used to classify the digital activities according to a Smart City’s success factors while evaluating the value created by these activities. The impact of these initiatives can then be assessed through value realisation and alignment for stakeholders. The scientific contribution is the adoption of the model to the cases in the Eastern Cape. To reveal in depth, rich, interview findings that provide important lessons learnt relating to the value created for the stakeholders and the addition of these findings to the body of knowledge.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202
A value alignment smart city stakeholder model
The concept of a Smart Cityhas evolved over the last three decades and has attracted the increasing interest of the scientific research community. Unfortunately,many Smart City projects and initiatives do not provide the value expected byall the stakeholders. Many of the reasons for this relate to a lack of data management, data integration, data access and stakeholder participation. People are an integral part of any city’s ecosystem, and the Smart Cityconcept was introduced to address the challenges of an ever-growing global population leading to the risk of depletion of economic, environmental and social resources.The problem addressed in this study is based on the challengespreventing the creation ofthevalueof smart citiesfor stakeholders. Limited research has been published on the status of Smart Cityinitiatives or on the impact of various success factors on the potential value creation for stakeholders including citizens. Studies on initiatives in developing countries,such as South Africa are even less. Whilst some challenges and constraints related to smart cities in Africa have been reported, there are no studies reporting on initiatives across the data value chain that consider all types of stakeholders,northe impact of these initiatives. This study addressed this gap in research and designed a theoretical Value Alignment Smart CityStakeholder (VASCS) Model based on a Systematic Literature Review and a review of related theories. The model has important components that should form part of any Smart Cityproject or Smart Cityinitiative. These five main components are: 1)nine Smart Citydimensionswith related success factors;2)four stakeholder roles(enablers, providers, utilisers and users);3) the data value chain;and 4)the five phases of stakeholder benefits/value realisation that can be linked to; 5) stakeholder valuealignment. Thisstudy applied the VASCSModel to Smart Cityinitiatives in two case studiesin the Eastern Cape Province of SouthAfrica, which werethe Nelson Mandela Bay andBuffalo Cityto investigate and understand the status of such initiatives and the alignment of value thereof.Thestakeholder interviews were conducted in two rounds with various stakeholders of Smart City initiatives, referred to as casesin the two casestudies. Anexpert review of the VASCS Model was conducted witheight experts in the field of Information Systems and Smart Cities. The findings of this review served to confirm the components of the model, with only minor improvements recommended.It was confirmed that all of the components need to be considered in planning Smart City projects. vThe first round consisted of six interviews with enablers and providers and the second round consisted of 22 interviewswith users, utilisers and citizens. The interviews investigatedthe value and impact experienced by stakeholdersof these initiatives, with a particular focus on the users, utilisersand citizensof the cases. The interview data was transcribed and qualitatively analysedbyusing Atlas.tiand Excel. The data was analysedaccording to the Technological, Organisational and Environmental theory constructs and other identifiedthemes. The interview analysis findings revealed several drivers for these initiatives, which wereprimarily cost reduction, integration and quality assurance. The results also highlighted access to resources,such as technical skillsas a challenge. Another challengeidentified wasconnectivity related to access to data and the digital and physical divide that canimpact decision making. The main benefits of Smart Cityinitiatives highlighted were the provision of infrastructure, education and training and digitalisation.The theoretical contribution of this study is the VASCS Model, which can assist other researchersand practitionerswith knowledge of the factors, drivers, challenges andvalue obtained in Smart Cityinitiatives. The model has two supplementary components: AStakeholder Classification Model and a Smart CitySuccess Factor Evaluation Template.The practical contribution of this study is the potential use of the VASCS Modelby practitioners, city management, researchers and other stakeholders, who can use the model, with the related modeland templatefor planning and evaluating Smart Cityinitiatives. The model can be used to classify the digital activities according to a Smart City’s success factors while evaluating the value created by these activities. The impact of these initiatives can then be assessed through value realisation and alignment for stakeholders. The scientific contribution is the adoption of the modeltothe cases in the Eastern Cape.To reveal in depth, rich,interview findings that provide important lessons learnt relating to the value created for the stakeholders and the addition of these findings to the body of knowledge.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202