Related papers: Predicting Floor-Level for 911 Calls with Neural N…

Respiratory auscultation is crucial for early detection of pediatric pneumonia, a condition that can quickly worsen without timely intervention. In areas with limited physician access, effective auscultation is challenging. We present a…

This study tackles on a new problem of estimating human-error potential on a shop floor on the basis of wearable sensors. Unlike existing studies that utilize biometric sensing technology to estimate people's internal state such as fatigue…

Emergency vehicles in service have right-of-way over all other vehicles. Hence, all other vehicles are supposed to take proper actions to yield emergency vehicles with active sirens. As this task requires the cooperation between ears and…

New computational devices, in particular wearable devices, offer the unique property of always being available and thus to be able to constantly update the user with information, such as by notifications. While research has been done in…

A noise map facilitates the monitoring of environmental noise pollution in urban areas. However, state-of-the-art techniques for rendering noise maps in urban areas are expensive and rarely updated, as they rely on population and traffic…

We present the first real-time sleep staging system that uses deep learning without the need for servers in a smartphone application for a wearable EEG. We employ real-time adaptation of a single channel Electroencephalography (EEG) to…

We propose an automated lowest floor elevation (LFE) estimation algorithm based on computer vision techniques to leverage the latent information in street view images. Flood depth-damage models use a combination of LFE and flood depth for…

Potholes are fatal and can cause severe damage to vehicles as well as can cause deadly accidents. In South Asian countries, pavement distresses are the primary cause due to poor subgrade conditions, lack of subsurface drainage, and…

We propose a new warning system based on smartphones that evaluates the risk of motor vehicle for vulnerable pedestrian (VP). The acoustic sensors are embedded in roadside to receive vehicles sounds and they are classified into heavy…

With the rapid development of indoor location-based services (LBSs), the demand for accurate localization keeps growing as well. To meet this demand, we propose an indoor localization algorithm based on graph convolutional network (GCN). We…

One of the key technologies for future large-scale location-aware services covering a complex of multi-story buildings --- e.g., a big shopping mall and a university campus --- is a scalable indoor localization technique. In this paper, we…

Natural disasters affect structural health of buildings, thus directly impacting public safety. Continuous structural monitoring can be achieved by deploying an internet of things (IoT) network of distributed sensors in buildings to capture…

Falling, especially in the elderly, is a critical issue to care for and surveil. There have been many studies focusing on fall detection. However, from our survey, there is still no research indicating the prior-fall activities, which we…

Predicting the price of a house remains a challenging issue that needs to be addressed. Research has attempted to establish a model with different methods and algorithms to predict the housing price, from the traditional hedonic model to a…

The localization speed and accuracy in the indoor scenario can greatly impact the Quality of Experience of the user. While many individual machine learning models can achieve comparable positioning performance, their prediction mechanisms…

This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood.…

We present and analyze a minimalist model for the vertical transport of people in a tall building by elevators. We focus on start-of-day operation in which people arrive at the ground floor of the building at a fixed rate. When an elevator…

Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are…

In essence, successful grasp boils down to correct responses to multiple contact events between fingertips and objects. In most scenarios, tactile sensing is adequate to distinguish contact events. Due to the nature of high dimensionality…

Mobile ground robots operating on unstructured terrain must predict which areas of the environment they are able to pass in order to plan feasible paths. We address traversability estimation as a heightmap classification problem: we build a…