.png){kind=icon}
.png){kind=icon}
Return
Development of a Smart IoT Charger for Wearable Cigarette Smoking Monitor
.png){kind=icon}
PRE
AI
M
V
P
N
E
DOI：10.1109/southeastcon42311.2019.9020337.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Wearable sensors have been proven effective for the objective detection of smoking events and individual puffs. For a precise analysis of the smoking habit of a person, these sensing methods need to be thoroughly applied for weeks or months. However, the limitation of sensor battery longevity, concern for sensors' timestamp drift or parameter calibration, and the restricted sensor data evaluation process limit this long-term application and force subjects, participating in the smoking study, for frequent returns to lab facilities. Also, sensor data analysis reports such as the statistics of daily cigarette consumption are not instantly available to smokers. Addressing these limitations, a smart IoT charger based on a Raspberry Pi (RPi) is presented in this paper, which can serve to a) recharge the sensor battery b) update the sensor timestamp c) exchange control commands d) extract data from the sensor system and, e) instant upload of sensor data to a cloud server to store and process sensor signals. To validate the proposed system, two volunteer smokers applied the wrist inertial sensor of a wearable sensor system for five consecutive days and used the proposed RPi charger daily. The difference in charging current provided by the smart charger and the commercial wall charger was found to be less than 0.1%. For sensor files of similar to 100KB size, the average file transfer rates and upload rates were found to be 3.25 MBps and 1.04 MBps, respectively, which was satisfactory for the current application. This smart charger approach is also envisioned to become a personalized tool to assist clinical smoking intervention methods by providing a method to learn daily consumption statistics.
Keywords:
Box
cigarette smoking
IoT
Raspberry Pi
smart charger
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
0
Papers:
19
Citations:
0
Organization
Cited Papers