ContextPhone: a prototyping platform for context-aware mobile applications

By Mika Raento, Antti Oulasvirta, Renaud Petit, Hannu (TT) Toivonen. IEEE pervasive computing, 2005

572 citations recorded by the source corpus.

Smart phones are a particularly tempting platform for building context-aware applications because they're programmable and often use well-known operating systems. There's a gap, however, between the operating systems' functionality and the features that application developers need. To fill this gap, we've designed and developed ContextPhone, a software platform consisting of four interconnected modules provided as a set of open source C++ libraries and source code components. ContextPhone runs on off-the-shelf mobile phones using Symbian OS and the Nokia Series 60 Smartphone platform. ContextPhone was developed using an iterative, human-centered design strategy. It thus helps developers more easily create applications that integrate into both existing technologies and users' everyday lives.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/4685c97b1234d7d2361cf85eb45332cb4d3a2c65

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Citations in the corpus

Smartphones (2009, unknown): “During the past three years, we have developed a software environment called ContextPhone (Raento et al. 2005) that is suitable for certain research practices and used extensively for ﬁeld studies by our research group and by several others in HCI.”
Habits make smartphone use more pervasive (2011, methodology): “ger1 [16] was used for data collection, allowing recording of sensor data, communication transactions, including the contents and transaction logs of all SMS and voice Fig.”
Inferring friendship network structure by using mobile phone data (2009, methodology): “The Reality Mining study followed 94 subjects using mobile phones preinstalled with several pieces of software that recorded and sent the researcher data about call logs, Bluetooth devices in proximity of approximately five meters, cell tower IDs, application usage, and phone status (6, 7).”
MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones (2007, background): “Automatic tracing typically records usage information passively without requiring user intervention (from the infrastructure [34] or directly from the device [28]).”
AWARE: Mobile Context Instrumentation Framework (2015, background): “ContextPhone (Raento et al., 2005) emphasizes context as an understandable resource to the user.”
Measuring Large-Scale Social Networks with High Resolution (2014, methodology): “A large number of solutions for sensor-driven human data collection have been developed, ranging from dedicated software to complete platforms, notably ContextPhone [20], SocioXensor [21], MyExpe-rience [22], Anonysense [23], CenceMe [24], Cityware [25], Darwin phones [26], Vita [27], and Context-To”