Activity recognition on streaming sensor data
نویسندگان
چکیده
منابع مشابه
Activity recognition on streaming sensor data
Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a script...
متن کاملHuman Activity Recognition via Cellphone Sensor Data
The purpose of this project is to identify human activities while using cell phones via mobile sensor data. We collect 2085 data samples, which includes 3-axis acceleration, angular velocity and orientation sensor data, from 4 volunteers using the MATLAB Mobile package. After cleaning, interpolating, and FFT, we get 135 raw features, and we further reduce the feature number to 21 via feature se...
متن کاملActivity Recognition Based on Array Sensor
This paper introduces activity recognition based on our proposed array sensor. The array sensor consists of an antenna array on the receiver side and decomposes received signals into eigenvectors and eigenvalues. It exploits these components depending on its applications, such as activity recognition. When an event occurs, the propagation environment changes, and thus the eigenvector and eigenv...
متن کاملFuzzy Data Envelopment Analysis for Classification of Streaming Data
The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...
متن کاملTowards improving feature extraction and classification for activity recognition on streaming data
An Activity Recognition system on streaming data must analyze the drift in the sensing values and, at any significant change detected, decide if there is a change in the activity performed by the person. The performances of such system depend on both the Feature Extraction (FE) and the classification stages in the context of streaming data. In the context of streaming and high imbalanced data, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Pervasive and Mobile Computing
سال: 2014
ISSN: 1574-1192
DOI: 10.1016/j.pmcj.2012.07.003