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Recognizing the location of an individual in a home environment is crucial in order to enable various context-aware home applications such as elderly health monitoring and in home appliance automation. However, due to the limited number of dedicated Wi-Fi access points (APs), it is challenging to guarantee the reliable localization performance in a home environment by using the traditional Wi-Fi fingerprinting...
Waiting for service is a problem faced by people from different countries and cultures. The problem of waiting in a queue can bring losses of quality of life and even economic problems. In this paper, we propose a mechanism for automatic detection of wait events via smartphones. This detection is done cooperatively by observing data collected from the user's smartphone's wifi and accelerometer sensors,...
Mobile Crowd Sensing and Computing (MCSC) is a replacement of static sensing infrastructure by user's mobile sensor-enhanced devices. MCSC collects user's local knowledge such as local information, ambient, and traffic conditions using sensor-enabled devices. The collected information is further aggregated and transferred to the cloud for detailed analysis. In this paper, we propose a Smartphone-based...
Recognizing the occupants movement and locations within a home is a basic functionality, underlying a variety of smart-home services, including energy management, ambient environment control, and assistive-living services for seniors and people with disabilities. The outdoor-localization variant of the problem is effectively addressed with the use of GPS; however, GPS does not work well inside buildings,...
Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile Crowdsensing (MCS), citizens participate in the sensing process contributing data with their mobile devices such as smartphones, tablets and wearables. To be effective, MCS systems require a large number...
People counting (detection) in public transport setting provides highly valuable information for transport lines planning in respect of their density, routes, timetables and vehicle occupancy. The real-time information on current number of passengers at given point enables the city councils together with the carriers to make significant improvements in line planning and resource use efficiency. Thus...
This paper discusses the design and development efforts made to collect data using an opportunistic crowdsensing mobile application. Relevant issues are underlined, and solutions proposed within the CHIST-ERA Macaco project for the specifics of collecting fine-grained content and context data are highlighted. Global statistics on the data gathered for over a year of collection show its quality: Macaco...
Indoor Positioning is a crucial topic to provide autonomous services to people based on their location. Nowadays dominating positioning systems, like GPS (Global Positioning System), are designed for outdoor use not applicable for indoor scenarios as they depend on a direct line of sight to reference stations. Recent progress in wearable computing peaked in the promising development of SmartWatches...
This paper proposes a critical survey of crowd analysis techniques using visual and non-visual sensors. Automatic crowd understanding has a massive impact on several applications including surveillance and security, situation awareness, crowd management, public space design, intelligent and virtual environments. In case of emergency, it enables practical safety applications by identifying crowd situational...
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