Search results for "Multi-sensor data fusion"

A Context-Aware System for Ambient Assisted Living

2017

In the near future, the world's population will be characterized by an increasing average age, and consequently, the number of people requiring for a special household assistance will dramatically rise. In this scenario, smart homes will significantly help users to increase their quality of life, while maintaining a great level of autonomy. This paper presents a system for Ambient Assisted Living (AAL) capable of understanding context and user's behavior by exploiting data gathered by a pervasive sensor network. The knowledge inferred by adopting a Bayesian knowledge extraction approach is exploited to disambiguate the collected observations, making the AAL system able to detect and predict…

An Ambient Intelligence System for Assisted Living

2017

Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is ab…

Multisensor Data Fusion in Pervasive Artificial Intelligence Systems

Intelligent systems designed to manage smart environments exploit numerous sensing and actuating devices, pervasively deployed so as to remain invisible to users and subtly learn their preferences and satisfy their needs. Nowadays, such systems are constantly evolving and becoming ever more complex, so it is increasingly difficult to develop them successfully. A possible solution to this problem might lie in delegating certain decisions to the machines themselves, making them more autonomous and able to self-configure and self-manage. This work presents a multi-tier architecture for a complete pervasive system capable of understanding the state of the surrounding environment, as well as usi…

Context-awareness for multi-sensor data fusion in smart environments

2016

Multi-sensor data fusion is extensively used to merge data collected by heterogeneous sensors deployed in smart environments. However, data coming from sensors are often noisy and inaccurate, and thus probabilistic techniques, such as Dynamic Bayesian Networks, are often adopted to explicitly model the noise and uncertainty of data. This work proposes to improve the accuracy of probabilistic inference systems by including context information, and proves the suitability of such an approach in the application scenario of user activity recognition in a smart home environment. However, the selection of the most convenient set of context information to be considered is not a trivial task. To thi…

Automatic defect localization in VLSI circuits: A fusion approach based on the Dempster-Shafer theory

2017

Defect localization in Very Large Integration Cir-cuits (VLSI) requires to use multi-sensor information such aselectrical waveforms, emission microscopy images and frequencymapping in order to detect, localize and identify the failure. Eachsensor provides a specific kind of feature modeling the evidence.Thus, the defect localization in VLSI can be summarized asa problem of data fusion with heterogeneous and impreciseinformation. This study illustrates how to reproduce the humandecision for modeling and fusing the different multi-sensorfeatures by using the Demspter-Shafer theory. We propose notonly an automatic decision rule for mass functions computingbut also confidence intervals to quantif…