1. Open Data-Kit Sensors

2. Objectives Modular Framework for adding new sensors
Abstract discovery, communication channels, data buffers
Isolation between apps and sensor-specific code
Apps should work even with buggy sensor code
Understand the modularity vs. performance tradeoff
Ease sensor integration with applications by allowing sensor functionality to be downloaded from app store as opposed to OS/framework changes

3. Framework Requirements
Make it easy to create drivers
Make it easy to use/re-use external drivers in apps
Ease of deployment of new sensors/drivers shielding end-user from the details
Make it easy to upgrade
Make it hard for bad sensor drivers to affect framework negatively
Sensors should be easy to discover through streamlined UI
Easy to manage communication channel workings such as dropped connections

4. ODK Sensors Architecture
Three apps
User-Application App: User-facing; Communicates with sensors through the unified framework API
ODK Sensors Framework App: Manages low-level, channel specific communication, and abstractions to isolate sensor code
Sensor Driver Apps: Sensor driver

5. ODK Sensors Architecture

6. Three Driver Architectures
V1: Drivers in the
framework
Not flexible
V2: Each sensor driver is
an app
Use Binder to
communicate
Implement Generic
Sensor Interface
Sensor App needs to be stateless
V3: Each sensor driver is an app
Communicate via broadcasts asynchronously
Non-blocking nature shields apps from buggy drivers

7. Energy-Efficient GPS Sensing with Cloud Offloading

8. GPS Basics GPS Receiver needs the following info for trilateration
Precise time T
Set of visible satellites at time T
Distances of receiver from each of the visible satellites at time T (pseudoranges)
Almanac: Coarse orbit and status information of all satellites
Ephemeris: Precise orbit information only about the satellite transmitting

9. Calculating PseudoRange
C/A code repeats every millisecond
Can use this to calculate ToF if clocks are synchronized and stationary
Doppler Effect
Code Phase Change

10. A-GPS: Coarse-Time Navigation
Get Ephemeris data from servers
Also provide Doppler shift and code phase change guesses
Does not require precise timestamp (HOW)
Use time difference as another variable in the Minimization
Use nearby landmark (cell tower) to estimate time diff to nearest millisecond

11. CO-GPS Problem without landmarks: Shadow Locations
Solution 1: Angle of Arrival
Solution 2: Elevation Database

12. Solution Use WWVB for accurate time synchronization
Test case: .407mJ energy consumption
A-GPS fix: 1J for the first fix