Today is a double celebration for us: the official (and initial) release of the Funf Open Sensing Framework open sourced codebase, and at the same time, the launch of the Funf Journal app on on the Android market!
The Funf Open Sensing Framework is an extensible sensing and data processing framework for mobile devices. The core concept is to provide an open source, reusable set of functionalities, enabling the collection, uploading, and configuration of a wide range of data types. This application is being developed by the Human Dynamics research group at the MIT Media Lab, and leverages our experience in developing and deploying social and behavioral sensing applications for mobile devices.
Funf Journal is an Android application for researchers, self-trackers, and anyone interested in collecting and exploring information related to the mobile device, its environment, and its user's behavior. It is built using the Funf framework and makes use of many of its built-in features.
Why Are We Doing This? (Read: Motivation)
As truly ubiquitous wearable computers, today’s mobile phones are quickly becoming the primary source for social, behavioral, and environmental sensing and data collection. Phone-based sensor data is used for enabling a broad range of research projects and application domains: research in areas of health and wellness, environmental sensing, sociological and psychological investigations, support for disaster and crisis response, as well as event triggers that can be used for building richer and more personalized mobile experiences, are just a few examples for uses of this kind of data.
Google’s Android platform has allowed researchers and developers to do more things with mobile devices than ever before. However, there is still a great gap between having API calls for accessing on-phone sensors and information, to having a "deployable" system or an end user application that fully utilizes this access. There are many additional components that need to exist for enabling this, which we had already built and deployed in the field during a 15 month long living laboratory deployment during 2010-11. Such additional components include, for example, specialized mechanisms for privacy preserving data collection (e.g. hashing human readable text so that its useful for scientific analysis but does not expose the original information), delay tolerant communication with a backend server (data collected locally when server not available, and uploaded in background whenever users connect to the network), “smart” data collection that maximizes battery life, ability to remotely configure the data collection settings, option to push software updates remotely, encrypting data files on the SD card for added protection, and so on.
Rather than having different developers and research teams re-invent the wheel, we are aiming to share the tools and experience we have already gained through our past deployments, and turn our system into an open source framework for researchers, developers, and end-users. We hope to foster a community around these ideas, where new development efforts would go towards extending a common platform rather than creating redundant functionality.
Remember, this is just the first release of both the app and the framework. This means both are still in beta stage, and there are bound to be quirks and kinks - so your feedback (and patience) are greatly appreciated. We also have a lot in store as far as features and capabilities, and you'll be seeing more of these in upcoming versions, so stay tuned. We are planning to release early and often, and we are looking forward to your comments and suggestions!