Data Set Used
—We deployed 72 sensors of 10 modalities in 15 wireless and wired networked sensor systems in the environment, in objects, and on the body to create a sensor-rich environment for the machine recognition of human activities. We acquired data from 12 subjects performing morning activities, yielding over 25 hours of sensor data. We report the number of… (More)
Publicly available data sets are increasingly becoming an important research tool in context recognition. However, due to the diversity and complexity of the domain it is difficult to provide standard recordings that cover the majority of possible applications and research questions. In this paper we describe a novel data set hat combines a number of… (More)
This paper presents design, implementation, and evaluation of AmbientSense, a real-time ambient sound recognition system on a smartphone. AmbientSense continuously recognizes user context by analyzing ambient sounds sampled from a smartphone's microphone. The phone provides a user with realtime feedback on recognised context. AmbientSense is implemented as… (More)
We aim at activity and context recognition in opportunistic sensor setups. The system ought to make use of sensor modalities that just happen to be available, rather than to rely on specific sensor deployment. In order to assess opportunistic activity recognition methods, we collected a large-scale dataset of complex activities in a highly sensor rich… (More)
Upcoming ambient intelligence environments will boast ever larger number of sensor nodes readily available on body, in objects, and in the user's surroundings. We envision " Pervasive Apps " , user-centric activity-aware pervasive computing applications. They use available sensors for activity recognition. They are downloadable from application… (More)
We present RoomSense, a new method for indoor positioning using smartphones on two resolution levels: rooms and within-rooms positions. Our technique is based on active sound fingerprinting and needs no infrastructure. Rooms and within-rooms positions are characterized by impulse response measurements. Using acoustic features of the impulse response and… (More)
Situation Assessment and decision making in monitoring and surveillance scenarios are evolving from centralized models to high-level, reasoning oriented, net-centric models, according to new information fusion paradigms proposed by recent research.