Smart Sensing Systems for the Daily Drive

When driving, you might sometimes wonder, "Are there any disruptions on my regular route that might delay me, and will I be able to find a parking space when I arrive?" Two smartphone-based prototype systems can help answer these questions. The first is ParkSense, which can be used to sense on-street parking-space occupancy when coupled with electronic parking payment systems. The second system can sense and recognize a user's repeated car journeys, which can be used to provide personalized alerts to the user. Both systems aim to minimize the impact of sensing tasks on the device's lifetime so that the user can continue to use the device for its primary purpose. This department is part of a special issue on smart vehicle spaces

Situation fencing: making geo-fencing personal and dynamic

Geo-fencing has recently been applied to multiple applications including media recommendation, advertisements, wildlife monitoring, and recreational activities. However current geo-fencing systems work with static geographical boundaries. Situation Fencing allows for these boundaries to vary automatically based on situations derived by a combination of global and personal data streams. We present a generic approach for situation fencing, and demonstrate how it can be operationalized in practice. The results obtained in a personalized allergy alert application are encouraging and open door for building thousands of similar applications using the same framework in near future

Mobile networks and internet of things infrastructures to characterize smart human mobility

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.This work has been supported by FCT–Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. This work has also been supported by national funds through FCT–Fundação para a Ciência e Tecnologia through project UIDB/04728/202

Citizens as Sensors for Crisis Event: Sensor Web Enablement for Volunteered Geographic Information

A set of developments within the field of geosensors is to engage citizens to act as sensors, thus providing so-called Volunteered Geographic Information (VGI). There is a long tradition of non specialists contributing to the collection of geo-referenced information. Furthermore thanks to recent convergence of greater access to broadband connections, the availability of Global Positioning Systems at affordable prices, and more participative forms of interaction on the Web (Web 2.0) vast numbers of individuals are able to create and share geographic information. The potential of up to 6 billion human sensors to monitor the state of the environment, validate global models with local knowledge, contribute to crisis situations awareness and provide information that only humans can capture (e.g. emotions and perceptions like fear of crime) is vast and has yet to be fully exploited. However, integrating VGI into Spatial Data Infrastructures (SDI) is a major challenge, as it is often regarded as insufficiently structured, documented or validated according to scientific standards. Early instances of SDIs used to have limited ability to manage and process geosensor-based data (beyond remotely sensed imagery snapshots), which tend to arrive in continuous streams of real-time information. The current works on standards for Sensor Web Enablement (SWE) aim to fill this gap. This paper shows how such SWE standards can be applied to VGI, thus converting it in a timely, cost-effective and valuable source of information for SDIs. By doing so, we extend previous works describing a workflow for VGI integration into SDI and further advance an initial set of VGI Sensing and event detection techniques. In particular, an example of how such VGI Sensing techniques can support crisis information system is provided.JRC.DDG.H.6-Spatial data infrastructure

THE ARCHAEOLOGY OF THE POSTINDUSTRIAL: SPATIAL DATA INFRASTRUCTURES FOR STUDYING THE PAST IN THE PRESENT

Postindustrial urban landscapes are large-scale, complex manifestations of the past in the present in the form of industrial ruins and archaeological sites, decaying infrastructure, and adaptive reuse; ongoing processes of postindustrial redevelopment often conspire to conceal the toxic consequences of long-term industrial activity. Understanding these phenomena is an essential step in building a sustainable future; despite this, the study of the postindustrial is still new, and requires interdisciplinary connections that remain either unexplored or underexplored. Archaeologists have begun to turn their attention to the modern industrial era and beyond. This focus carries the potential to deliver new understandings of the industrial and postindustrial city, yet archaeological attention to the postindustrial remains in its infancy. Developments in the ongoing digital revolution in archaeology and within the social sciences and humanities have the potential to contribute to the archaeological study of the postindustrial city. The development of historical GIS and historical spatial data infrastructures (HSDIs) using historical big data have enabled scholars to study the past over large spatial and temporal scales and support qualitative research, while retaining a high level of detail. This dissertation demonstrates how spatial technologies using big data approaches, especially the HSDI, enhance the archaeological study of postindustrial urban landscapes and ultimately contribute to meeting the “grand challenge” of integrating digital approaches into archaeology by coupling reflexive recording of archaeological knowledge production with globally accessible spatial digital data infrastructures. HSDIs show great potential for providing archaeologists working in postindustrial places with a means to curate and manipulate historical data on an industrial or urban scale, and to iteratively contextualize this longitudinal dataset with material culture and other forms of archaeological knowledge. I argue for the use of HSDIs as the basis for transdisciplinary research in postindustrial contexts, as a platform for linking research in the academy to urban decision

Exploring public sentiment and vaccination uptake of COVID-19 vaccines in England: a spatiotemporal and sociodemographic analysis of Twitter data

Objectives: Vaccination is widely regarded as the paramount approach for safeguarding individuals against the repercussions of COVID-19. Nonetheless, concerns surrounding the efficacy and potential adverse effects of these vaccines have become prevalent among the public. To date, there has been a paucity of research investigating public perceptions and the adoption of COVID-19 vaccines. Therefore, the present study endeavours to address this lacuna by undertaking a spatiotemporal analysis of sentiments towards vaccination and its uptake in England at the local authority level, while concurrently examining the sociodemographic attributes at the national level. // Methods: A sentiment analysis of Twitter data was undertaken to delineate the distribution of positive sentiments and their demographic correlates. Positive sentiments were categorized into clusters to streamline comparison across different age and gender demographics. The relationship between positive sentiment and vaccination uptake was evaluated using Spearman’s correlation coefficient. Additionally, a bivariate analysis was carried out to further probe public sentiment towards COVID-19 vaccines and their local adoption rates. // Result: The results indicated that the majority of positive tweets were posted by males, although females expressed higher levels of positive sentiment. The age group over 40 dominated the positive tweets and exhibited the highest sentiment polarity. Additionally, vaccination uptake was positively correlated with the number of positive tweets and the age group at the local authority level. // Conclusion: Overall, public opinions on COVID-19 vaccines are predominantly positive. The number of individuals receiving vaccinations at the local authority level is positively correlated with the prevalence of positive attitudes towards vaccines, particularly among the population aged over 40. These findings suggest that targeted efforts to increase vaccination uptake among younger populations, particularly males, are necessary to achieve widespread vaccination coverage

Using Twitter to learn about the autism community

Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines pertaining to the treatment and management of the disorder is crucial. Yet evidence suggests that policy makers and medical practitioners do not always have a good understanding of the practices and relevant beliefs of ASD-afflicted individuals' carers who often follow questionable recommendations and adopt advice poorly supported by scientific data. The key goal of the present work is to explore the idea that Twitter, as a highly popular platform for information exchange, could be used as a data-mining source to learn about the population affected by ASD -- their behaviour, concerns, needs etc. To this end, using a large data set of over 11 million harvested tweets as the basis for our investigation, we describe a series of experiments which examine a range of linguistic and semantic aspects of messages posted by individuals interested in ASD. Our findings, the first of their nature in the published scientific literature, strongly motivate additional research on this topic and present a methodological basis for further work.Comment: Social Network Analysis and Mining, 201

Citizen-based sensing of crisis events: sensor web enablement for volunteered geographic information

Thanks to recent convergence of greater access to broadband connections, the availability of Global Positioning Systems in small packages at affordable prices and more participative forms of interaction on the Web (Web 2.0), vast numbers of individuals became able to create and share Volunteered Geographic Information (VGI). The potential of up to six billion persons to monitor the state of the environment, validate global models with local knowledge, contribute to crisis situations awareness, and provide information that only humans can capture is vast and has yet to be fully exploited. Integrating VGI into Spatial Data Infrastructures (SDI) is a major challenge, as it is often regarded as insufficiently structured, documented, or validated according to scientific standards. Early instances of SDIs used to have limited ability to manage and process geosensor-based data (beyond remotely sensed imagery), which tend to arrive in continuous streams of real-time information. The current works on standards for Sensor Web Enablement fill this gap. This paper shows how such standards can be applied to VGI, thus converting it in a timely, cost-effective and valuable source of information for SDIs. By doing so, we extend previous efforts describing a workflow for VGI integration into SDI and further advance an initial set of VGI Sensing and event detection techniques. Examples of how such VGI Sensing techniques can support crisis information system are provided. The presented approach serves central building blocks for a Digital Earth’s nervous system, which is required to develop the next generation of (geospatial) information infrastructures