Being embedded in the physical world, sensor networks present a wide range of bugs and misbehavior qualitatively different from those in most distributed systems. Unfortunately, due to resource constraints, programmers must investigate these bugs with only limited visibility into the application. This paper presents the design and evaluation of Sympathy, a tool for detecting and debugging failures in sensor networks. Sympathy has selected metrics that enable efficient failure detection, and includes an algorithm that root-causes failures and localizes their sources in order to reduce overall failure notifications and point the user to a small number of probable causes. We describe Sympathy and evaluate its performance through fault injection and by debugging an active application, ESS, in simulation and deployment. We show that for a broad class of data gathering applications, it is possible to detect and diagnose failures by collecting and analyzing a minimal set of metrics at a centralized sink. We have found that there is a tradeoff between notification latency and detection accuracy; that additional metrics traffic does not always improve notification latency; and that Sympathy's process of failure localization reduces primary failure notifications by at least 50% in most cases.

This tutorial presents a detailed study of sensor faults that occur in deployed sensor networks and a systematic approach to model these faults. We begin by reviewing the fault detection literature for sensor networks. We draw from current literature, our own experience, and data collected from scientific deployments to develop a set of commonly used features useful in detecting and diagnosing sensor faults. We use this feature set to systematically define commonly observed faults, and provide examples of each of these faults from sensor data collected at recent deployments.

Objective Self-management of risk behaviors is a cornerstone of future population health interventions. Using mobile phones for routine self-monitoring and feedback is a cost-efficient strategy for self-management and ecological momentary interventions (EMI). However, mobile health applications need to be designed to be highly attractive and acceptable to a broad range of user groups. To inform the design of an adaptable mobile health application we aimed to identify the dimensions and range of user preferences for application features by different user groups. Methods Five focus group interviews were conducted: two (n = 9; n = 20) with people living with HIV (PLH) and three with young mothers (n = 6; n = 8; n = 10). Thematic analyses were conducted on the focus group sessions’ notes and transcripts. Results Both groups considered customization of reminders and prompts as necessary, and goal setting, motivational messaging, problem solving, and feedback as attractive. For PLH, automated and location-based reminders for medication adherence and sharing data with healthcare providers were both acceptable and attractive features. Privacy protection and invasiveness were the primary concerns, particularly around location tracking, illegal drug use, and sexual partner information. Concerns were ameliorated by use scenario or purpose, monetary incentives, and password protection. Privacy was not a major concern to mothers who considered passwords burdensome. Mothers’ preferences focused on customization that supports mood, exercise and eating patterns, and especially using the mobile phone camera to photograph food to increase self-accountability. Conclusions Individualization emerged as the key feature and design principle to reduce user burden and increase attractiveness and acceptability. Mobile phone EMI uniquely enables individualization, context-aware and real-time feedback, and tailored intervention delivery.

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Use of improved (biomass) cookstoves (ICs) has been widely proposed as a Black Carbon (BC) mitigation measure with significant climate and health benefits. ICs encompass a range of technologies, including natural draft (ND) stoves, which feature structural modifications to enhance air flow, and forced draft (FD) stoves, which additionally employ an external fan to force air into the combustion chamber. We present here, under Project Surya, the first real-time in situ Black Carbon (BC) concentration measurements from five commercial ICs and a traditional (mud) cookstove for comparison. These experiments reveal four significant findings about the tested stoves. First, FD stoves emerge as the superior IC technology, reducing plume zone BC concentration by a factor of 4 (compared to 1.5 for ND). Indoor cooking-time BC concentrations, which varied from 50 to 1000 μg m(-3) for the traditional mud cookstove, were reduced to 5-100 μg m(-3) by the top-performing FD stove. Second, BC reductions from IC models in the same technology category vary significantly: for example, some ND models occasionally emit more BC than a traditional cookstove. Within the ND class, only microgasification stoves were effective in reducing BC. Third, BC concentration varies significantly for repeated cooking cycles with same stove (standard deviation up to 50% of mean concentration) even in a standardized setup, highlighting inherent uncertainties in cookstove performance. Fourth, use of mixed fuel (reflective of local practices) increases plume zone BC concentration (compared to hardwood) by a factor of 2 to 3 across ICs.

This paper examines inter-method reliability and validity of daily self-reports by smartphone application compared to 14-day recall web-surveys repeated over 6 weeks with people living with HIV (PLH). A participatory sensing framework guided participant-centered design prioritizing external validity of methods for potential applications in both research and self-management interventions. Inter-method reliability correlations were consistent with prior research for physical and mental health quality-of-life (r = 0.26–0.61), antiretroviral adherence (r = 0.70–0.73), and substance use (r = 0.65–0.92) but not for detailed sexual encounter surveys (r = 0.15–0.61). Concordant and discordant pairwise comparisons show potential trends in reporting biases, for example, lower recall reports of unprotected sex or alcohol use, and rounding up errors for frequent events. Event-based reporting likely compensated for modest response rates to daily time-based prompts, particularly for sexual and drug use behaviors that may not occur daily. Recommendations are discussed for future continuous assessment designs and analyses.

BACKGROUND Self-monitoring by mobile phone applications offers new opportunities to engage patients in self-management. Self-monitoring has not been examined thoroughly as a self-directed intervention strategy for self-management of multiple behaviors and states by people living with HIV (PLH). METHODS PLH (n=50), primarily African-American and Latino, were recruited from two AIDS services organizations and randomly assigned to daily smartphone (n=34) or bi-weekly web-survey only (n=16) self-monitoring for six weeks. Smartphone self-monitoring included responding to brief surveys on medication adherence, mental health, substance use, and sexual risk behaviors, and brief text diaries on stressful events. Qualitative analyses examine bi-weekly, open-ended user-experience interviews regarding perceived benefits and barriers of self-monitoring, and to elaborate a theoretical model for potential efficacy of self-monitoring to support self-management for multiple domains. RESULTS Self-monitoring functions include reflection for self-awareness, cues to action (reminders), reinforcements from self-tracking, and their potential effects on risk perceptions, motivations, skills, and behavioral activation states. Participants also reported therapeutic benefits related to self-expression for catharsis, non-judgmental disclosure, and in-the-moment support. About one-third of participants reported that surveys were too long, frequent, or tedious. Some smartphone group participants suggested that daily self-monitoring was more beneficial than bi-weekly due to frequency and in-the-moment availability. About twice as many daily self-monitoring group participants reported increased awareness and behavior change support from self-monitoring compared to bi-weekly web-survey only participants. CONCLUSION Self-monitoring is a potentially efficacious disruptive innovation for supporting self-management by PLH and for complementing other interventions, but more research is needed to confirm efficacy, adoption and sustainability.

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