The goal of project CLEO is to develop devices and services to encourage and enable participatory sensing and citizen scientists. A core technology developed in the project is to make location sensing energy efficient, so devices can be small, light, sample more frequently, and low cost. The approach is called Cloud-Offloaded GPS (or CO-GPS). A second service is a web-based sensor data management service called CLEO Data Portal for uploading and sharing geo-tagged sensor data.
- Mobile Location Sensing Tutorial at ACM MobiSys 2013, June 25th, 2013, Taipei.
- Jie Liu to give a keynote address at Com.Geo 2013 on mobile location sensing.
- MIT Technology Review's blog on Cloud-Offloaded GPS.
- Download CLEON Reference Design
- Download LEAP API Examples
- Download GPS Data Traces
CLEON is a sensor node that collects raw GPS samples and stores it to an SD card.
We will soon release the reference design of the hardware and our collaborators at Purdue University have created firmware for it.
LEAP Web Services:
The Low Energy Assisted Positioning (LEAP) web service is deployed on Windows Azure at https://msr-leap.cloudapp.net/LEAP.svc. The internal architecture of the service is shown in the figure below.
To use the service, the user must request an ID from Microsoft Research. The GPS samples in the data file must be organized as defined for LEAP's headers in GpsSignalDataHeader.cs class in the CO-GPS tool kit. Once requests are successfully queued in the system, a request ID will be returned to the client, who can use the ID to request the results later.
This video shows an example of using LEAP web service. We will soon release a sample app that uses the LEAP web service for location resolution.
CLEO Data Portal:
In the CLEO project, we are also developing a cloud-based data portal to organize temporal/spatial tagged sensor data. The portal supports a RESTful API for mobile devices to upload sensor data, and an OData API for query the online data.
- jie liu, Bodhi Priyantha, Ted Hart, Heitor Ramos, Antonio A.F. Loureiro, and Qiang Wang, Energy Efficient GPS Sensing with Cloud Offloading, in 10th ACM Conference on Embedded Networked Sensor Systems (SenSys 2012), ACM, November 2012
- Heitor S. Ramos, Tao Zhang, Jie Liu, Bodhi Priyantha, and Aman Kansal, LEAP: A Low Energy Assisted GPS for Trajectory-Based Services, in 13th ACM International Conference on Ubiquitous Computing (UbiComp), ACM, 17 September 2011