Using smartphones in cities to crowdsource dangerous road sections and give effective in-car warnings

The widespread day-to-day carrying of powerful smartphones gives opportunities for crowd-sourcing information about the users' activities to gain insight into patterns of use of a large population in cities. Here we report the design and initial investigations into a crowdsourcing approach for sudden decelerations to identify dangerous road sections. Sudden brakes and near misses are much more common than police reportable accidents but under exploited and have the potential for more responsive reaction than waiting for accidents. We also discuss different multimodal feedback conditions to warn drivers approaching a dangerous zone. We believe this crowdsourcing approach gives cost and coverage benefits over infrastructural smart-city approaches but that users need incentivized for use

Detecting different road infrastructural elements based on the stochastic characterization of speed patterns

The automatic detection of road related information using data from sensors while driving has many potential applications such as traffic congestion detection or automatic routable map generation. This paper focuses on the automatic detection of road elements based on GPS data from on-vehicle systems. A new algorithm is developed that uses the total variation distance instead of the statistical moments to improve the classification accuracy. The algorithm is validated for detecting traffic lights, roundabouts, and street-crossings in a real scenario and the obtained accuracy (0.75) improves the best results using previous approaches based on statistical moments based features (0.71). Each road element to be detected is characterized as a vector of speeds measured when a driver goes through it. We first eliminate the speed samples in congested traffic conditions which are not comparable with clear traffic conditions and would contaminate the dataset. Then, we calculate the probability mass function for the speed (in 1 m/s intervals) at each point. The total variation distance is then used to find the similarity among different points of interest (which can contain a similar road element or a different one). Finally, a k-NN approach is used for assigning a class to each unlabelled element.The research leading to these results has received funding from the “HERMES-Smart Driver” Project TIN2013-46801-C4-2-R (MINECO), funded by the Spanish Agencia Estatal de Investigación (AEI), and the “Analytics Using Sensor Data for Flatcity” Project TIN2016-77158-C4-1-R (MINECO/ERDF, EU) funded by the SpanishAgencia Estatal de Investigación (AEI) and the European Regional Development Fund (ERDF)

Natural Disaster Crisis Communication by FEMA and Red Cross Via Twitter During Hurricanes Harvey, Irma, Lane, Matthew, and Michael

This thesis examined the way disaster relief agencies, FEMA and Red Cross, communicated during natural hazards at the national and regional levels. Using tweets from the weeks of hurricanes Harvey, Irma, Lane, Matthew, and Michael, I assessed how well the agencies communicated with the public in the wake of a storm. This research utilized crisis communication theory and disaster management theory. The tweets were coded according to a standard model of crisis communication and analyzed using SPSS software. The results found that FEMA national was the agency that followed the crisis communication model the best, while Red Cross national had the least content in line with the model

The Future of Digital Spaces and Their Role in Democracy

This is the 13th"Future of the Internet" canvassing Pew Research Center and Elon University's Imagining the Internet Center have conducted together to gather expert views about important digital issues. In this report, the questions focused on the prospects for improvements in the tone and activities of the digital public sphere by 2035. This is a nonscientific canvassing based on a nonrandom sample; this broad array of opinions about where current trends may lead in the next decade represents only the points of view of the individuals who responded to the queries.Pew Research Center and Elon's Imagining the Internet Center built a database of experts to canvass from a wide range of fields, inviting professionals and policy people based in government bodies, nonprofits and foundations, technology businesses and think tanks, as well as interested academics and technology innovators. The predictions reported here came in response to a set of questions in an online canvassing conducted between June 29 and Aug. 2, 2021.In all, 862 technology innovators and developers, business and policy leaders, researchers and activists responded to at least one of the questions covered in this report. More on the methodology underlying this canvassing and the participants can be found in the section titled "About this canvassing of experts.

Police Use of Twitter: 21st Century Community Policing

With the advancement of social media platforms like Twitter increasingly being woven into the everyday activities of society members, police services, in an attempt to stay relevant and reflective, have begun adopting Twitter into their work initiatives. The present study examines the perceptions Canadian police officers regarding their use of Twitter as a community policing tool. Through semi-structured interviews with police officers and administrative staff operating official police Twitter accounts, and constructivist grounded theorizing, this research provides an in-depth examination of the perceptions of police officers who use Twitter as a part of community policing initiatives. Specifically, the study explores the experiences officers have had with adopting and learning to use Twitter, revealing an individualized and decentralized nature reflective of community policing, and also its value for intelligence gathering. Additionally, this research demonstrates how police perceive Twitter to function as a boundary object that transcends physical, geographical and cultural boundaries in order to develop relationships with various community groups. Further, through exploration of officers perceptions and experiences, this study uncovers how Twitter can be challenging for officers do to the lack of training and organizational support, which results in officer having to rely on self-governance and compensate for a lack of service resources. This research contributes to policing literature by providing a rare vantage point from the perspective of officers utilizing Twitter for their work

Mapping Crisis: Participation, Datafication, and Humanitarianism in the Age of Digital Mapping

This book brings together critical perspectives on the role that mapping people, knowledges and data now plays in humanitarian work, both in cartographic terms and through data visualisations. Since the rise of Google Earth in 2005, there has been an explosion in the use of mapping tools to quantify and assess the needs of the poor, including those affected by climate change and the wider neo-liberal agenda. Yet, while there has been a huge upsurge in the data produced around these issues, the representation of people remains questionable. Some have argued that representation has diminished in humanitarian crises as people are increasingly reduced to data points. In turn, this data becomes ever more difficult to analyse without vast computing power, leading to a dependency on the old colonial powers to refine the data of the poor, before selling it back to them. These issues are not entirely new, and questions around representation, participation and humanitarianism can be traced back beyond the speeches of Truman, but the digital age throws these issues back to the fore, as machine learning, algorithms and big data centres take over the process of mapping the subjugated and subaltern. This book questions whether, as we map crises, it is the map itself that is in crisis

Mapping Crisis

The digital age has thrown questions of representation, participation and humanitarianism back to the fore, as machine learning, algorithms and big data centres take over the process of mapping the subjugated and subaltern. Since the rise of Google Earth in 2005, there has been an explosion in the use of mapping tools to quantify and assess the needs of those in crisis, including those affected by climate change and the wider neo-liberal agenda. Yet, while there has been a huge upsurge in the data produced around these issues, the representation of people remains questionable. Some have argued that representation has diminished in humanitarian crises as people are increasingly reduced to data points. In turn, this data has become ever more difficult to analyse without vast computing power, leading to a dependency on the old colonial powers to refine the data collected from people in crisis, before selling it back to them. This book brings together critical perspectives on the role that mapping people, knowledges and data now plays in humanitarian work, both in cartographic terms and through data visualisations, and questions whether, as we map crises, it is the map itself that is in crisis