1,053 research outputs found

    Understanding and Personalising Smart City Services Using Machine Learning, the Internet-of-Things and Big Data

    Get PDF
    This paper explores the potential of Machine Learning (ML) and Artificial Intelligence (AI) to lever Internet of Things (IoT) and Big Data in the development of personalised services in Smart Cities. We do this by studying the performance of four well-known ML classification algorithms (Bayes Network (BN), Naìˆve Bayesian (NB), J48, and Nearest Neighbour (NN)) in correlating the effects of weather data (especially rainfall and temperature) on short journeys made by cyclists in London. The performance of the algorithms was assessed in terms of accuracy, trustworthy and speed. The data sets were provided by Transport for London (TfL) and the UK MetOffice. We employed a random sample of some 1,800,000 instances, comprising six individual datasets, which we analysed on the WEKA platform. The results revealed that there were a high degree of correlations between weather-based attributes and the Big Data being analysed. Notable observations were that, on average, the decision tree J48 algorithm performed best in terms of accuracy while the kNN IBK algorithm was the fastest to build models. Finally we suggest IoT Smart City applications that may benefit from our work

    A Geo-Spatial Information Model for Rurban Planning

    Get PDF
    The Indian context of planning primarily focuses on urban settlements comprising approximately 30% of our land area. The rest two-thirds are composed of spatially isolated rural communities which lack access to adequate infrastructure, services and connectivity for which the absence of a standardized planning methodology is a pertinent reason. Since a spatial entity is never disconnected from its context, planning is most effective when undertaken in the context of a region, joining settlements in need of physical, economic and social connectivity. Within a region, the availability of a multihierarchical geo-spatial database is fundamental to spatial planning, and research identifies that it requires conspicuous attention in our rural planning strategy. The proposed paper addresses this lacuna of data infrastructure at the micro-regional level. An example of micro-region is the rurban cluster, comprising several village settlements around a central town, displaying potential for spatially integrated development. The rurban cluster is in compliance with the Shyama Prasad Mukherji National Rurban Mission (SPMNRM), a flagship programme initiated by the Ministry of Rural Development (Government of India) in 2016. The planning, implementation and execution of this scheme also sufferes due to the lack of geo-spatial database management. Borrowing from past experiences in the country and abroad, this paper constructs a model for geo-spatial planning of rurban clusters. The model takes care of all the stages of rurban cluster planning such as delineation of the micro-region, database design and management, analysis, evolution of alternative scenarios and finally implementation and monitoringthrough geo-spatial information systems. Once developed and applied, it objectively evaluates the corresponding stages of the SPMNRM (non-spatial) and the new model (geo-spatial), to demonstrate how the latter adds value to the planning process and produces superior results on ground

    Museum Mobile Guide Preferences of Different Visitor Personas

    Get PDF
    Personalising museum mobile guides is widely acknowledged as being important for enhancing the visitor experience. Due to the lack of information about an individual visitor and the relatively limited time of his or her visit, adapting the user interface based on a museum visitor's type is a promising approach to personalisation. This approach first requires a mechanism to identify the visitor type (‘persona’) and, second, knowledge of the preferences and needs of different types to apply personalisation. In this article, we report a face-to-face questionnaire study carried out with 105 visitors to Scitech, a science and technology visitor centre. The study aims to investigate the main facts required to identify a visitor persona and to explore the preferences of different visitor personas for particular mobile guide features. We limited our concern to the user interface features of the guide (e.g., whether it provides recommendations for related items to view) rather than what content and services the guide provides (e.g., what related items are recommended). We found that we can reliably identify the visitor persona using two multiple choice questions about visit motivation and perceived success criteria. In addition, we found that visitors have significant preferences for particular features such as presentation media, venue navigation tool, object suggestions, details level, accessing external links, exhibit information retrieval method and social interaction features such as voice communication, instant messaging, group games and challenges. Some features were found to be preferred differently by different personas such as the challenges feature, some were found to be preferred by personas differently to the overall preference such as in presentation media, and some were found to be preferred by some personas with no particular preference for others such as a venue navigation tool. Instant messaging was found to be significantly not preferred by all personas. The results provide a basis for personalisation of museum guides and services using a personas approach, which is a solution where data about individual users may be limited and where the individual configuration of a user interface may not be practical or warranted

    Network of excellence in internet science: D13.2.1 Internet science – going forward: internet science roadmap (preliminary version)

    No full text

    The Role of Self-congruity in Consumer Preferences: Perspectives from Transaction Records

    Get PDF
    Personalised marketing is more persuasive than traditional techniques aimed at the masses, however marketers do not always have access to consumers’ private attributes in order to apply these insights. The effect of personalisation is based on an established theory in consumer psychology – self-congruity theory – which posits that individuals prefer products, brands and advertisements that embody characteristics that match with their self-concepts. Self-congruence not only enhances marketing effectiveness, it can also be used to improve consumer well-being. While it has been established that consumers who spend in a way that is more congruent with their personality are happier, clarifications around the types of individuals who are more or less likely to engage in self-congruent spending, as well as the moderating effects on the benefit in happiness from such consumption could inform policy for improving happiness at a collective level. This thesis contributes to a growing body of research which attempts to understand how consumption patterns are related to consumers’ characteristics, its applications in advertising, as well as consumer well-being. By using a dataset containing more than 1 million transactions recorded over a period of 12-months, the thesis demonstrates the value of the digital footprint in the form of bank transactions for enriching our understanding of key questions in consumer research, underpinned by the theory of self-congruity. This thesis combines methods from computational social science with personality psychology to test research questions on consumer preferences. Two components of the thesis focused on the predictive utility of transaction records in inferring consumer attributes with which to personalise advertising, as well as the use of transaction records in examining self-congruence in overall consumption patterns and its relationship with happiness. Through five empirical studies, this work suggests that consumer attributes such as age and financial distress can be reliably inferred from consumption patterns reflected in transaction records (Chapter 3 and 5). The inferred age can be used to personalise advertisements in order to increase their appeal (Chapter 4). Using an objective measure of self-congruence in overall consumption pattern computed from transaction records and panel ratings, the thesis shows that individuals differ in their tendency to spend in a way that is congruent with their personality based on their levels of materialism and financial distress (Chapter 6). As the most important predictor of self-congruent spending, financial distress moderates the relationship between self-congruent spending and happiness (Chapter 7). These findings contribute insights into how consumption patterns are related to consumer attributes and usefulness for personalisation in marketing, as well as policy recommendations for improving well-being by targeting consumption patterns in financially distressed individuals. In addition, this thesis also showcases the value of machine learning and large-scale behavioural field data in the study of consumer psychology. Privacy and ethical concerns surrounding automated profiling and microtargeting are also cautioned

    Efficient, sustainable and secure use of smart city resources

    Get PDF
    The rapid advancement and increased use of technology has introduced the concept of smart cities, driving cities around the world towards developing a wide variety of smart systems, solutions and services. While these smart components provide improvements to various city operations, from increased resource efficiency and sustainability to general quality of life enhancements, they also introduce many challenges that must be dealt with in order to ensure future success. The purpose of this thesis is to determine the necessary measures both current and future smart cities should take in order to use their resources in an efficient, sustainable and secure manner. This was primarily achieved through extensive theoretical research, using a wide variety of information sources, from various scientific publications to different web-based resources. In addition, a simulated model of a smart waste management system was designed in this thesis in order to aid the development of the Salo smart city project. Resource efficiency and sustainability are integral to successful smart city implementations, as they ensure that smart cities can continue to prosper and develop more and more advanced solutions and services in the future. Consequently, the importance of solutions such as smart energy, smart waste management and smart mobility will only continue to increase in the future. Moreover, smart cities must be prepared to deal with various challenges presented by the use of advanced technologies and smart systems - from security, privacy and service availability to people- and ethics-related challenges. In the final parts of the thesis, the aforementioned topics were discussed from the perspective of the Salo smart city project. The use of different security measures and cheaper smart solutions, such as the smart waste recycling centre designed in the thesis, were given as recommendations to guide Salo towards a more resource efficient, sustainable and secure future

    The Ethical Balance of Using Smart Information Systems for Promoting the United Nations’ Sustainable Development Goals

    Get PDF
    The Sustainable Development Goals (SDGs) are internationally agreed goals that allow us to determine what humanity, as represented by 193 member states, finds acceptable and desirable. The paper explores how technology can be used to address the SDGs and in particular Smart Information Systems (SIS). SIS, the technologies that build on big data analytics, typically facilitated by AI techniques such as machine learning, are expected to grow in importance and impact. Some of these impacts are likely to be beneficial, notably the growth in efficiency and profits, which will contribute to societal wellbeing. At the same time, there are significant ethical concerns about the consequences of algorithmic biases, job loss, power asymmetries and surveillance, as a result of SIS use. SIS have the potential to exacerbate inequality and further entrench the market dominance of big tech companies, if left uncontrolled. Measuring the impact of SIS on SDGs thus provides a way of assessing whether an SIS or an application of such a technology is acceptable in terms of balancing foreseeable benefits and harms. One possible approach is to use the SDGs as guidelines to determine the ethical nature of SIS implementation. While the idea of using SDGs as a yardstick to measure the acceptability of emerging technologies is conceptually strong, there should be empirical evidence to support such approaches. The paper describes the findings of a set of 6 case studies of SIS across a broad range of application areas, such as smart cities, agriculture, finance, insurance and logistics, explicitly focusing on ethical issues that SIS commonly raise and empirical insights from organisations using these technologies

    AI Affordances Perception for the Transformation of Mobility Ecosystems

    Get PDF
    Artificial Intelligence (AI) can transform organisations, industries, and ecosystems. However, how different organisations in a given ecosystem perceive the action potentials of AI (i.e., AI affordances) has not been researched. To advance the AI affordances research and develop a nomological net of organisational and ecosystem factors that influence the AI affordances perception, this paper contributes a conceptual framework with the context of the mobility ecosystem transformation. The framework draws from two theories: the affordances theory and the social cognitive theory. The paper presents an in-depth interpretation of these theories for the perception of AI affordances and develops propositions to explain two distinct types of affordances perceptions: vicarious and autonomous. Our conceptual work offers a foundation for developing models for prediction and opens new avenues of investigating AI affordances perception. Future research could further test and validate the framework
    • …
    corecore