SmokingOpp: Detecting the smoking 'opportunity' context using mobile sensors

Soujanya Chatterjee, Alexander Moreno, Steven Lloyd Lizotte, Sayma Akther, Emre Ertin, Christopher P. Fagundes, Cho Lam, James M. Rehg, Neng Wan, David W. Wetter, Santosh Kumar

Research output: Contribution to journalArticlepeer-review


Context plays a key role in impulsive adverse behaviors such as fights, suicide attempts, binge-drinking, and smoking lapse. Several contexts dissuade such behaviors, but some may trigger adverse impulsive behaviors. We define these latter contexts as 'opportunity' contexts, as their passive detection from sensors can be used to deliver context-sensitive interventions. In this paper, we define the general concept of 'opportunity' contexts and apply it to the case of smoking cessation. We operationalize the smoking 'opportunity' context, using self-reported smoking allowance and cigarette availability. We show its clinical utility by establishing its association with smoking occurrences using Granger causality. Next, we mine several informative features from GPS traces, including the novel location context of smoking spots, to develop the SmokingOpp model for automatically detecting the smoking 'opportunity' context. Finally, we train and evaluate the SmokingOpp model using 15 million GPS points and 3,432 self-reports from 90 newly abstinent smokers in a smoking cessation study.

Original languageEnglish (US)
Article number3380987
JournalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Issue number1
StatePublished - Mar 18 2020
Externally publishedYes


  • Context
  • GPS traces
  • Intervention
  • Mobile Health
  • Smoking Cessation

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Networks and Communications


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