Team 7: Sunoco Hotdog Eye Home Mid-Semester Presentation Hong, Keetaek Baek, Jinwook Lee, David

Status Update ► Concept  Home monitoring system that notifies via SMS ► Status Update of Implementation  Done with basic implementation  Now working on calibration and fault-tolerance ► Status Update of Testing and Experimentation  Tested sensor sensitivity  Tested normal operation  Tested some fault-injected test scenarios

Experimentation Plan ► Test Setup  2 sensor Tmotes, 1 server Tmote, 1 PC, 1 SMS-enabled mobile phone, Internet service, SMS gateway ► Metrics  Delivery time = End time – Start time  Start time = Sensor detects smoke  End time = Cellphone receives SMS  Binary ► 0 – Not detected (SMS doesn’t arrive within 2 min)‏ ► 1 – Detected (SMS arrives within 2 min)‏ ► Workload  Up to two problems detected simultaneously

Experimentation Plan ► Parameters  Location (humidity, lighting, pressure, etc.), size of fire, distance, radio reception, Internet connection ► Test run  Perform in same location  Simulate same fire size  Keep Internet connection connected  Keep number and nature of problems constant  Vary distance from sensor the problem occurs ► Experiment  Number of test runs 50 simulations  Average Number of Messages: 1 per simulation  Min time 0 seconds, Max time 2 minutes

Initial Data ► Initial Data for the Smoke Sensor  Due to poor sensor sensitivity, we allowed a very large range of analog values to be “problems”  Distance (d) was 10 cm from sensor  System successfully notified user under normal operation - 15 out of 15 times  System successfully notified user upon reconnection after being disconnected from the Internet - 15 out of 15 times

Initial Data ► Distance Detected  0 Success  5 Success  10 Success  20 Success  30 Fail  40 Fail  50 Fail ► This means that  Sensor sends analog values to Tmote  Tmote communication is working  Mainframe’s error-handling (exception, queue) working  Sensor calibration is the only big thing left

Looking Forward ► Things we’ve learned  Low-priced sensors are fishy  Some datasheets are not documented well  Other software in the system can be buggy ► We plan to  Calibrate the sensor to minimize false negatives  Improve error handling  Finish strong!

Questions or Suggestions? “Come with me if you want to live”