Temporary Screen Timeout Extension Based on User Intentions

This publication describes techniques to provide a temporary screen timeout extension for displays on electronic devices. The timeout extension is prompted based on a Screen Manager detecting activity that indicates a user may desire to keep the screen active. The Screen Manager may give the user an option to extend the screen timeout past the default timeout setting, or it may extend the timeout automatically. The default timeout setting does not change when the temporary screen timeout extension is chosen. The extension allows the user to continue to use the device periodically without needing regular inputs to the device in order to keep the screen on and unlocked. The temporary timeout extension will cause less disruption to the user when using applications on the device that do not require the user to constantly interact with the device (e.g., regularly provide input to the device keeping the screen active)

Turning off or dimming a device screen based on user attention

Device screens are often set to turn off and/or dim automatically if no user interaction is detected for a specified amount of time. Turning off or dimming the screen saves power and prolongs the amount of time the device can operate without needing to recharge the battery. However, such timeout-based actions can result in false positives or negatives. With user permission, this disclosure utilizes contextual input of a user’s gaze and attention for management of the automatic turn off or dimming of the device screen. The techniques are applied to reduce the false positives and negatives and ensure that the screen stays on longer if the user is still engaged with the device and turns off or dims before the timeout if the user has stopped using the screen

Utilizing Gaze Detection to Enhance Voice-Based Accessibility Services

For users that use voice as their primary mode of input, operating a computing device can be difficult due to potential false positives (e.g., unintended voice commands by the user, background noise such as a radio). Voice commands can also be difficult to decipher, resulting in the voice-based accessibility service needing additional, clarifying user input to disambiguate the auditory commands. This publication describes techniques and procedures for utilizing gaze detection to enhance voice-based accessibility services on a computing device, such as a smartphone or computer. The computing device utilizes camera image input and a machine-learned model to produce an estimated x-y coordinate of where the user is gazing on a display of the computing device. Utilizing the machine-learned model, if the computing device determines that the user is looking at the computing device’s display (i.e., giving the device attention), then auditory commands are accepted; otherwise, if the user is not giving the device attention, then auditory commands can be ignored. Additionally, the techniques and procedures can assist in disambiguation (e.g., similar sounding commands, identically titled functions). Finally, the techniques and procedures can be used as an alternative means for controlling the scrolling of the display of the device

High-Resolution Building and Road Detection from Sentinel-2

Mapping buildings and roads automatically with remote sensing typically requires high-resolution imagery, which is expensive to obtain and often sparsely available. In this work we demonstrate how multiple 10 m resolution Sentinel-2 images can be used to generate 50 cm resolution building and road segmentation masks. This is done by training a `student' model with access to Sentinel-2 images to reproduce the predictions of a `teacher' model which has access to corresponding high-resolution imagery. While the predictions do not have all the fine detail of the teacher model, we find that we are able to retain much of the performance: for building segmentation we achieve 78.3% mIoU, compared to the high-resolution teacher model accuracy of 85.3% mIoU. We also describe a related method for counting individual buildings in a Sentinel-2 patch which achieves R^2 = 0.91 against true counts. This work opens up new possibilities for using freely available Sentinel-2 imagery for a range of tasks that previously could only be done with high-resolution satellite imagery

Socio-spatial equity analysis of relative wealth index and emergency obstetric care accessibility in urban Nigeria

Background: Better geographical accessibility to comprehensive emergency obstetric care (CEmOC) facilities can significantly improve pregnancy outcomes. However, with other factors, such as affordability critical for care access, it is important to explore accessibility across groups. We assessed CEmOC geographical accessibility by wealth status in the 15 most-populated Nigerian cities. Methods: We mapped city boundaries, verified and geocoded functional CEmOC facilities, and assembled population distribution for women of childbearing age and Meta’s Relative Wealth Index (RWI). We used the Google Maps Platform’s internal Directions Application Programming Interface to obtain driving times to public and private facilities. City-level median travel time (MTT) and number of CEmOC facilities reachable within 60 min were summarised for peak and non-peak hours per wealth quintile. The correlation between RWI and MTT to the nearest public CEmOC was calculated. Results: We show that MTT to the nearest public CEmOC facility is lowest in the wealthiest 20% in all cities, with the largest difference in MTT between the wealthiest 20% and least wealthy 20% seen in Onitsha (26 vs 81 min) and the smallest in Warri (20 vs 30 min). Similarly, the average number of public CEmOC facilities reachable within 60 min varies (11 among the wealthiest 20% and six among the least wealthy in Kano). In five cities, zero facilities are reachable under 60 min for the least wealthy 20%. Those who live in the suburbs particularly have poor accessibility to CEmOC facilities. Conclusions: Our findings show that the least wealthy mostly have poor accessibility to care. Interventions addressing CEmOC geographical accessibility targeting poor people are needed to address inequities in urban settings

A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations

Travel time estimation accounting for on-the-ground realities between the location where a need for emergency obstetric care (EmOC) arises and the health facility capable of providing EmOC is essential for improving pregnancy outcomes. Current understanding of travel time to care is inadequate in many urban areas of Africa, where short distances obscure long travel times and travel times can vary by time of day and road conditions. Here, we describe a database of travel times to comprehensive EmOC facilities in the 15 most populated extended urban areas of Nigeria. The travel times from cells of approximately 0.6 × 0.6 km to facilities were derived from Google Maps Platform’s internal Directions Application Programming Interface, which incorporates traffic considerations to provide closer-to-reality travel time estimates. Computations were done to the first, second and third nearest public or private facilities. Travel time for eight traffic scenarios (including peak and non-peak periods) and number of facilities within specific time thresholds were estimated. The database offers a plethora of opportunities for research and planning towards improving EmOC accessibility

Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: insights from Spring 2020

Background Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease. Methods We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google. We used a pre-post comparison and two linear mixed-effects models to first assess the relationship between implementation of national policies and observed changes in mobility, and then to assess the relationship between changes in mobility and rates of COVID-19 infections in subsequent weeks. Results Compared to a pre-COVID baseline, Spain saw the largest decrease in aggregate population mobility (~70%), as measured by the time spent away from residence, while Sweden saw the smallest decrease (~20%). The largest declines in mobility were associated with mandatory stay-at-home orders, followed by mandatory workplace closures, school closures, and non-mandatory workplace closures. While mandatory shelter-in-place orders were associated with 16.7% less mobility (95% CI: -23.7% to -9.7%), non-mandatory orders were only associated with an 8.4% decrease (95% CI: -14.9% to -1.8%). Large-gathering bans were associated with the smallest change in mobility compared with other policy types. Changes in mobility were in turn associated with changes in COVID-19 case growth. For example, a 10% decrease in time spent away from places of residence was associated with 11.8% (95% CI: 3.8%, 19.1%) fewer new COVID-19 cases. Discussion This comprehensive evaluation across Europe suggests that mandatory stay-at-home orders and workplace closures had the largest impacts on population mobility and subsequent COVID-19 cases at the onset of the pandemic. With a better understanding of policies’ relative performance, countries can more effectively invest in, and target, early nonpharmacological interventions

Impacts of Social Distancing Policies on Mobility and COVID-19 Case Growth in the US

Social distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth 2 to 4 weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth 2 weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.Comment: Co-first Authors: GAW, SV, VE, and AF contributed equally. Corresponding Author: Dr. Evgeniy Gabrilovich, [email protected] 32 pages (including supplemental material), 4 figures in the main text, additional figures in the supplemental materia