It is a interesting topic of tracking a 3D object and estimating its 3-D motion in a multi-sensor observation environment. The motion with constant translation velocity and constant rotation rate is assumed and tracked by two separate cameras. Hence the problem considered here also involves a track-to-track fusion system in which twosensors are tracking the same target. Due to the nonlinear nat...

In this letter, a novel data fusion method, called the single sensor data fusion filter (SSDFF) was proposed. It differed from the existed multi sensor fusion algorithms. In the proposed SSDFF, a new process model using polynomial predictive filter by expanding the dimension of the state, was firstly constructed. Then the local estimation results based on the original model and the proposed mod...

A data fusion method based on navigation observations from multiple sensors with asynchronous sampling rates is presented aiming at the accomplishment of an optimal navigation result. Firstly, the observation estimations of navigation sensors at the same designated time are obtained through the fitting or interpolation algorithms based on the multi-sensors’ measurements at different times, whic...

Abstract Now a day, things are communicating using the Internet, In context of smart city all interconnected and they transferring data to each other. Smart subapplications like parking, pollution, traffic, transportation some examples. By internet, we can combine with communication, big challenge in multi-sensory environment fetch meaning full from sensors. There many methods used analyse mine...

We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary se...

In Smart Home, understanding the environment and what is going on is the basis of all adapted services. Unfortunately, inferring situations and activity recognition directly from raw data is way too complex to be applied. Firstly, we present a layered architecture we are building to process raw data into abstract situations and activities. Secondly, data fusion tools using the belief functions ...

Continuous technological progress facilitates the development of embedded vehicle classification systems. These systems typically have a lower availability of resources than on customary personal computers. They consist of several components such as sensor data acquisition and preprocessing, feature extraction and feature-/decision-based data fusion. Besides visual, Lidarand Radar-based informa...