Sensafety: Crowdsourcing the Urban Sense of Safety

Today, community initiatives to improve the urban quality of life can be conducted in a more focused way because local authorities and urban planners are able to reveal urban hotspots through the investigation of location-annotated crime and accident data. However, urban areas, which according to well-recorded incident data are characterized by a high level of public safety, but which are generally perceived by citizens as unsafe, remain undiscovered and therefore untreated. This work presents Sensafety, a citizen-centric crowdsourcing approach that enables users by means of a mobile application to report their personal feeling of safety anytime and at any site. Sensafety’s goal is to reveal a comprehensive and complete picture of the perceived safety in urban environments in order to identify blind spots that have not been further investigated due to lack of data. To encourage citizens to participate and contribute, Sensafety’s mobile application offers different ways to explore and experience the collected data depending on the user’s location. This paper gives a detailed description of Sensafety’s integrated concept and outlines the major technical and non-technical findings

A Collaborative Mobile Crowdsensing System for Smart Cities

Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System

GNL: GeoFencing Based Smart Outdoor Navigation and Localization

Navigation is a technique used by humans to construct a plan to help them travel within a place using instruments or maps. Navigation in the modern age is done using various electronic systems which provide a real-time map of the place and the step-by-step directions to the desired destination. The technology widely used today is GPS i.e. Global Positioning System. Outdoor navigation using Google maps, here maps or safari is a common go-to for the users but the problem is the map provided by these companies just has an overview of the place and not the detailed information. The GNL approach which authors have used in this paper focuses on the navigation and localization of the gated environment so that the person living and visiting the area will get familiar with the area and understand the area very well. The web app that authors have designed can be used for the College Campus, Fairs, open museums, etc. Comparative analysis of the web app-based approach is done with an existing one. The Presented approach will not only help you in navigation but also provide you with information about the POI (Point of Interests) of those visiting places. The Geofence mechanism will help users to navigate and get information about the area. The aim is to give the user the maximum information about the place with secured transfer of information and better localization. The authors have tested the approach on the real testbed in the gated society and it provides good results for what it promises

Integrating Augmented Interactive Geo visualizations and Open Government

Es gibt große Hoffnungen zivilgesellschaftliches Engagement im Rahmen von Open Government Initiativen neu zu gestalten. Das Ziel ist es, Bürgerbeteiligung mittels offener Interaktionen und Zugang zu Daten zu stärken und einen Schwerpunkt auf Transparenz, Partizipation und Kollaboration zu legen. Vor diesem Hintergrund formuliert und untersucht diese Arbeit einen Ansatz zur Förderung von bürgerschaftlichem Engagement mittels erweiterten und interaktiven Geo-visualisierungen (AIGs). AIGs nutzen Raum und Zeit als Integratoren, um Bürgern Kontextualisierung, Visualisierung und verschiedene Möglichkeiten zum Engagement zu bieten. Die Hauptforschungsfrage dieser Arbeit untersucht die Effekte von AIGs auf bürgerschaftliches Engagement, während vier Leitfragen Vorbedingungen und Herausforderungen untersuchen. Zusammenfassend werden ein Design Space für AIGs konzeptualisiert, potentielle Rollen der Zielgruppe beschrieben, Best Practices für die Publikation von räumlichen offenen Daten formuliert und es wurden drei AIG Prototypen für einzelne Bürgerbeteiligungsverfahren und Stufen entwickelt und evaluiert.High hopes are pinned to reshaping civic engagement in Open Government Initiatives that seek to open up governmental processes and data by using modern information and communication technologies. The aim is to facilitate citizen engagement through open interactions and access to data by emphasizing transparency, participation, and collaboration. This thesis formulates and evaluates an approach to facilitate citizen engagement with Augmented Interactive Geo-visualizations (AIGs). AIGs use space and time as integrators that allow citizens to contextualize, visualize and engage in different ways. The central research question of this thesis investigates the effects of AIGs on citizen engagement while four guiding questions look at pre-requisits and challenges. In summary, a design space for AIGs is conceptualized, potential roles of the target audience are described, best practices for publishing geospatial Open Data established, and three AIG prototypes have been developed and evaluated for specific instances and levels of citizen engagement

e-mission: an open source, extensible platform for human mobility systems

Transportation is the single largest source of carbon emissions in the US. Decarbonizing it is challenging because it depends on individual behaviors, which in turn, depend on local land use planning. The interdisciplinary field of Computational Mobility, focusing on collecting, analysing and influencing human travel behavior, can frame solutions to this challenge.Innovation flows in interdisciplinary fields are bi-directional. The flow to the domain is focused on building a strong foundation for methodological improvements. As the improvements are deployed, they result in use-inspired computational research. This temporal dependency results in our initial focus on the modularity, accuracy and reproducibility of e-mission, an extensible platform for instrumenting human mobility. This open source platform has a modular architecture that supports power efficient duty cycling using virtual sensors, a read-only data model and a pipeline with novel algorithm adaptations for smartphone sensing.We also perform the first empirical evaluations of smartphone-based platforms in this domain. The architectural evaluation is based on three real world deployments: a classic travel diary, a crowdsourcing initiative, and a behavioral study. The accuracy evaluation is based on an novel procedure that uses artificial trips and multiple parallel phones to mitigate concerns over privacy, context sensitive power consumption and inherent sensing error. Data collected from three artifical timelines was used to evaluate the trajectory, segmentation and classification accuracies vs. power for various configurations.On computational side, challenges derived from the deployments can contribute to ongoing CS research in privacy, trustworthiness, incentivization and decision making. On the mobility side, this enables methodological innovations such as Agile Urban Planning for prototyping infrastructure changes

Machine Learning Technologies and Their Applications for Science and Engineering Domains Workshop -- Summary Report

The fields of machine learning and big data analytics have made significant advances in recent years, which has created an environment where cross-fertilization of methods and collaborations can achieve previously unattainable outcomes. The Comprehensive Digital Transformation (CDT) Machine Learning and Big Data Analytics team planned a workshop at NASA Langley in August 2016 to unite leading experts the field of machine learning and NASA scientists and engineers. The primary goal for this workshop was to assess the state-of-the-art in this field, introduce these leading experts to the aerospace and science subject matter experts, and develop opportunities for collaboration. The workshop was held over a three day-period with lectures from 15 leading experts followed by significant interactive discussions. This report provides an overview of the 15 invited lectures and a summary of the key discussion topics that arose during both formal and informal discussion sections. Four key workshop themes were identified after the closure of the workshop and are also highlighted in the report. Furthermore, several workshop attendees provided their feedback on how they are already utilizing machine learning algorithms to advance their research, new methods they learned about during the workshop, and collaboration opportunities they identified during the workshop

Data and the city – accessibility and openness. a cybersalon paper on open data

This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data

A Comprehensive Review of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impact

The unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 by the World Health Organization (WHO), has placed numerous governments around the world in a precarious position. The impact of the COVID-19 outbreak, earlier witnessed by the citizens of China alone, has now become a matter of grave concern for virtually every country in the world. The scarcity of resources to endure the COVID-19 outbreak combined with the fear of overburdened healthcare systems has forced a majority of these countries into a state of partial or complete lockdown. The number of laboratory-confirmed coronavirus cases has been increasing at an alarming rate throughout the world, with reportedly more than 3 million confirmed cases as of 30 April 2020. Adding to these woes, numerous false reports, misinformation, and unsolicited fears in regards to coronavirus, are being circulated regularly since the outbreak of the COVID-19. In response to such acts, we draw on various reliable sources to present a detailed review of all the major aspects associated with the COVID-19 pandemic. In addition to the direct health implications associated with the outbreak of COVID-19, this study highlights its impact on the global economy. In drawing things to a close, we explore the use of technologies such as the Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), blockchain, Artificial Intelligence (AI), and 5G, among others, to help mitigate the impact of COVID-19 outbreak.This work was supported by the Qatar National Research Fund (a member of the Qatar Foundation) under Grant NPRP10-1205-160012