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With the provision of smart buildings and location awareness, energy use in buildings and in transport systems is rapidly becoming part of our lifelong contextual footprint - the idea that each of us, throughout our lifetimes, will lay down a digital trail that reflects our patterns of interaction with services, the contexts within which we choose to use them, and ultimately our reactions to them. | |||
C-AWARE aims to build services to improve users' awareness of their personal energy consumption, carbon footprint and modify their energy demand. | |||
Two main areas we are addressing is building energy monitoring and carbon footprints of employee's commute with sub-projects Joule and Carbon Commute respectively. | |||
For more information, please see the main [http://www.cl.cam.ac.uk/research/srg/netos/c-aware/ C-Aware] project page. | |||
Any enquiries or comments should be directed to Ian Leslie (ian.leslie@cl.cam.ac.uk). | |||
== | ==[[Joule]]== | ||
[[Joule]] is a collection of scripts and an HTML Web App to record and visualise the energy use of a collection of sensors, currently the sensors within the William Gates Building at The University of Cambridge. It provides a tool to explore a tree of sensors, drill down to interesting areas based on geography or energy use such as lighting or server power, and plot charts over a range of time, helping to identify both short and long term patterns. | |||
* | [[Joule | More info...]] | ||
* | |||
==[[Carbon Commute]]== | |||
[[Carbon Commute]] is a system to record and estimate a user’s carbon footprint during their travel to work, whilst respecting their privacy and giving them increased control over the data recording from this activity. It involves an mobile phone application that records a users’ location data and uploads it to a server application. Each user is assigned their own personal container data locker, isolated and controlled by themselves, which runs runs applications within itself and allows user control of the access to their data. | |||
The [[Carbon Commute]] system has 3 main parts; a mobile phone application, one or more installs of the “locker” personal container software, and applications that run within locker. In our implementation we used an iPhone for the mobile platform, and ran lockers on servers hosted by the university computer service. | |||
[[Carbon Commute | More info...]] | |||
==People== | |||
* [http://www.cl.cam.ac.uk/~iml1/ Ian Leslie] | |||
* [http://www.cl.cam.ac.uk/~smh22/ Steven Hand] | |||
* [http://www.cl.cam.ac.uk/~avsm2/ Anil Madhavapeddy] | |||
* [http://www.cl.cam.ac.uk/~jac22/ Jon Crowcroft] | |||
* [http://elsmorian.com/ Chris Elsmore] | |||
Latest revision as of 13:28, 20 March 2013
With the provision of smart buildings and location awareness, energy use in buildings and in transport systems is rapidly becoming part of our lifelong contextual footprint - the idea that each of us, throughout our lifetimes, will lay down a digital trail that reflects our patterns of interaction with services, the contexts within which we choose to use them, and ultimately our reactions to them.
C-AWARE aims to build services to improve users' awareness of their personal energy consumption, carbon footprint and modify their energy demand.
Two main areas we are addressing is building energy monitoring and carbon footprints of employee's commute with sub-projects Joule and Carbon Commute respectively.
For more information, please see the main C-Aware project page.
Any enquiries or comments should be directed to Ian Leslie (ian.leslie@cl.cam.ac.uk).
Joule
Joule is a collection of scripts and an HTML Web App to record and visualise the energy use of a collection of sensors, currently the sensors within the William Gates Building at The University of Cambridge. It provides a tool to explore a tree of sensors, drill down to interesting areas based on geography or energy use such as lighting or server power, and plot charts over a range of time, helping to identify both short and long term patterns.
Carbon Commute
Carbon Commute is a system to record and estimate a user’s carbon footprint during their travel to work, whilst respecting their privacy and giving them increased control over the data recording from this activity. It involves an mobile phone application that records a users’ location data and uploads it to a server application. Each user is assigned their own personal container data locker, isolated and controlled by themselves, which runs runs applications within itself and allows user control of the access to their data.
The Carbon Commute system has 3 main parts; a mobile phone application, one or more installs of the “locker” personal container software, and applications that run within locker. In our implementation we used an iPhone for the mobile platform, and ran lockers on servers hosted by the university computer service.
