Imagined communities: Reflections on the origin and spread of nationalism

The theory of affordances

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.

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A survey of mobile phone sensing

Named Data Networking (NDN) is one of five projects funded by the U.S. National Science Foundation under its Future Internet Architecture Program. NDN has its roots in an earlier project, Content-Centric Networking (CCN), which Van Jacobson first publicly presented in 2006. The NDN project investigates Jacobson's proposed evolution from today's host-centric network architecture (IP) to a data-centric network architecture (NDN). This conceptually simple shift has far-reaching implications for how we design, develop, deploy, and use networks and applications. We describe the motivation and vision of this new architecture, and its basic components and operations. We also provide a snapshot of its current design, development status, and research challenges. More information about the project, including prototype implementations, publications, and annual reports, is available on named-data.net.

/pdf/named-data-networking-4kzv69blab.pdf

Named data networking

An emerging category of devices at the edge of the Internet are consumer-centric mobile sensing and computing devices, such as smartphones, music players, and in-vehicle sensors. These devices will fuel the evolution of the Internet of Things as they feed sensor data to the Internet at a societal scale. In this article, we examine a category of applications that we term mobile crowdsensing, where individuals with sensing and computing devices collectively share data and extract information to measure and map phenomena of common interest. We present a brief overview of existing mobile crowdsensing applications, explain their unique characteristics, illustrate various research challenges, and discuss possible solutions. Finally, we argue the need for a unified architecture and envision the requirements it must satisfy.

Mobile crowdsensing: current state and future challenges

PEIR, the Personal Environmental Impact Report, is a participatory sensing application that uses location data sampled from everyday mobile phones to calculate personalized estimates of environmental impact and exposure. It is an example of an important class of emerging mobile systems that combine the distributed processing capacity of the web with the personal reach of mobile technology. This paper documents and evaluates the running PEIR system, which includes mobile handset based GPS location data collection, and server-side processing stages such as HMM-based activity classification (to determine transportation mode); automatic location data segmentation into "trips''; lookup of traffic, weather, and other context data needed by the models; and environmental impact and exposure calculation using efficient implementations of established models. Additionally, we describe the user interface components of PEIR and present usage statistics from a two month snapshot of system use. The paper also outlines new algorithmic components developed based on experience with the system and undergoing testing for integration into PEIR, including: new map-matching and GSM-augmented activity classification techniques, and a selective hiding mechanism that generates believable proxy traces for times a user does not want their real location revealed.

/pdf/peir-the-personal-environmental-impact-report-as-a-platform-2mkiit1ya7.pdf

PEIR, the personal environmental impact report, as a platform for participatory sensing systems research

Participatory sensing technologies could improve our lives and our communities, but at what cost to our privacy?

https://dl.acm.org/doi/pdf/10.1145/1592761.1592778

Four billion little brothers?: privacy, mobile phones, and ubiquitous data collection

/pdf/four-billion-little-brothers-privacy-mobile-phones-and-andarwubrf.pdf

Four Billion Little Brothers? Privacy, mobile phones, and ubiquitous data collection

Bicycling is an affordable, environmentally friendly alternative transportation mode to motorized travel. A common task performed by bikers is to find good routes in an area, where the quality of a route is based on safety, efficiency, and enjoyment. Finding routes involves trial and error as well as exchanging information between members of a bike community. Biketastic is a platform that enriches this experimentation and route sharing process making it both easier and more effective. Using a mobile phone application and online map visualization, bikers are able to document and share routes, ride statistics, sensed information to infer route roughness and noisiness, and media that documents ride experience. Biketastic was designed to ensure the link between information gathering, visualization, and bicycling practices. In this paper, we present architecture and algorithms for route data inferences and visualization. We evaluate the system based on feedback from bicyclists provided during a two-week pilot.

http://dmrussell.net/CHI2010/docs/p1817.pdf

Biketastic: sensing and mapping for better biking

As information systems transform our world, computer scientists design affordances that influence the uses and impacts of these technological objects. This article describes how the practices of de...

Katie Shilton

Papers

PEIR, the personal environmental impact report, as a platform for participatory sensing systems research

Four billion little brothers?: privacy, mobile phones, and ubiquitous data collection

Four Billion Little Brothers? Privacy, mobile phones, and ubiquitous data collection

Biketastic: sensing and mapping for better biking

Values Levers: Building Ethics into Design