The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Mobile phones, sensors, patients, hospitals, researchers, providers and organizations are nowadays, generating huge amounts of healthcare data. The real challenge in healthcare systems is how to find, collect, analyze and manage information to make people's lives healthier and easier, by contributing not only to understand new diseases and therapies but also to predict outcomes at earlier stages and...
In this paper, we introduce a collaborative learning problem that is applicable in multi-agent data mining using heterogeneous computing resources in environments with limited control, resource failures, and communication bottlenecks. Specifically, we consider the scenario in which multiple agents collect noisy and overlapping information regarding an entity, such as a network attribute, which might...
This paper studies the problem of human activity recognition. Traditionally, the data collected by the accelerometer is preprocessed with a fixed time window, and features for human activity recognition model are extracted in this framework. However, some human activities are quasi-periodic, which means that classification accuracy can be improved if adaptive time window is adopted instead. As human...
Internet of Things (IoT) is extension of current internet to provide communication, connection, and inter-networking between various devices or physical objects also known as “Things.” In this paper we have reported an effective use of IoT for Environmental Condition Monitoring and Controlling in Homes. We also provide fault detection and correction in any devices connected to this system automatically...
Pollution detection and monitoring is very crucial task in todays world. To create better and safer environment for human being, animals, plants we need to monitor and control the pollution. This study proposes air pollution and monitoring model which detects pollution in air on the basis of data mining algorithm. The sensor grid is used to detect the sensor values from different gas sensors. Microcontroller...
The task of determining informative sensors and clustering the sensor measurements according to their information content is considered. To this end, the standard canonical correlation analysis (CCA) framework is equipped with norm-one and norm-two regularization terms to estimate the unknown number of field sources and identify informative groups of sensors. Coordinate descent techniques are combined...
It is well known from physiological studies that the level of human attention for adult individuals rapidly decreases after five to twenty minutes [1]. Attention retention for a surveillance operator represents a crucial aspect in Video Surveillance applications and could have a significant impact in identifying relevance, especially in crowded situations. In this field, advanced mechanisms for selection...
The internet of thing in environmental protecion provide a full range of monitor way to control environment from source. It becomes an important big data source. And how to manage and apply big data is a crucial problem. In this paper, we focul on the featurs, framework of management of big data of IoT in environmental protection. And outline the characteristics, areas and challenges of applicatin...
Smart and energy efficient (office) buildings do not only have to implement smart sensors and actuators, they should also be able to be optimized to be as energy efficient as possible based on the behavior of the user. This paper focuses on knowledge extraction of a smart building and automatic rule creation based on that knowledge. We are using different methods to analyze this data, create the appropriate...
With the proliferation of Internet of Things (IoT) devices such as smartphones, sensors, cameras, and RFIDs, it is possible to collect massive amount of data for localization and tracking of people within commercial buildings. Enabled by such occupancy monitoring capabilities, there are extensive opportunities for improving the energy consumption of buildings via smart HVAC control. In this respect,...
The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a dialysis machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemodialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat-to-beat...
Over the past few years, wireless sensor networks (WSN) have emerged as one of the most exciting fields in Computer Science research. A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomenon and processing them. The main aim of deploying applications based on WSNs is to make use...
This paper presents the multitemporal adaptive processing (MAP3) framework for the treatment of multitemporal synthetic aperture radar (SAR) images. The framework is organized in three major activities dealing with calibration, adaptability, and representation. The processing chain has been designed looking at the simplicity, i.e., the minimization of the operations needed to obtain the products,...
Wireless Sensor Network (WSN) is an emerging area of research in the field of communication. With the explosive growth of its applications, WSN goes through various challenges. One of the important challenges is to maintain both coverage and connectivity in WSN. In this paper, we address the issue of maintaining sensing coverage and network connectivity in WSN by keeping a minimal number of sensor...
Reality mining in behavioral studies is one of the highly researched topics in computational science. The reason behind this great deal of experimentation is the particularly dynamic and potentially latent nature of human behavior. In this work, we have showcased our efforts in analyzing the associations between the smartphone usage and the mental state of the person during depression, stress and...
We present an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. Sensors embedded in the environment capture behavior and activity patterns. Changes in patterns are detected as potential signs of changing health. We first present results of a preliminary study investigating 22 features extracted from in-home sensor data. A 1-D alert algorithm...
In this work, an "analytical data model of mosquito vector" was developed to perform analytical computation to the character of the dengue vectors. Our goal is to investigate a way to understand how the temporal trend of collected dataset correlates with the incidence dengue as identified by national health authorities. Based upon the mosquito-vector big data collections, we investigate...
Participatory sensor networks (PSNs) regards smartphone users as consumers as well as active producers of data. A sensing layer represents a type of data, coming from a given source of data, such as web services, traditional wireless sensor networks, and PSNs. In this work, we show the usefulness and potential of having sensing layers in PSNs. We also show how we can formalize the concept of sensing...
Synthetic Decision Support System is combined with online analytical processing, data mining, model libraries, databases and knowledge bases. It will become one of the key technologies of data management services of Internet of Things, and it will establish the foundation for the smart city. This paper researches on the sequential pattern mining for decision support, implements the Prefix Span algorithm,...
Current smartphones are integrated with rich sensors, which provides a good opportunity for the smartphone sensor data mining. By mining these data, we are able to analyze the user's behaviors. This paper describes HARLib, a human activity recognition library on the Android operating system. We use accelerometer built-in smartphone to recognize the user's activities, including walking, running, sitting,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.