Dynamic Bayesian Approach for decision-making in Ego-Things

by   Divya Kanapram, et al.

This paper presents a novel approach to detect abnormalities in dynamic systems based on multisensory data and feature selection. The proposed method produces multiple inference models by considering several features of the observed data. This work facilitates the obtainment of the most precise features for predicting future instances and detecting abnormalities. Growing neural gas (GNG) is employed for clustering multisensory data into a set of nodes that provide a semantic interpretation of data and define local linear models for prediction purposes. Our method uses a Markov Jump particle filter (MJPF) for state estimation and abnormality detection. The proposed method can be used for selecting the optimal set features to be shared in networking operations such that state prediction, decision-making, and abnormality detection processes are favored. This work is evaluated by using a real dataset consisting of a moving vehicle performing some tasks in a controlled environment.



There are no comments yet.


page 4

page 5


Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles

The advancements in connected and autonomous vehicles in these times dem...

Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform

Real-world problems such as landmine detection require multiple sources ...

A concise method for feature selection via normalized frequencies

Feature selection is an important part of building a machine learning mo...

Automation of Feature Engineering for IoT Analytics

This paper presents an approach for automation of interpretable feature ...

Time-Critical Dynamic Decision Making

Recent interests in dynamic decision modeling have led to the developmen...

A practical approach to detection of distributed denial-of-service attacks using a hybrid detection method

This paper presents a hybrid method for the detection of distributed den...

Explaining machine-learned particle-flow reconstruction

The particle-flow (PF) algorithm is used in general-purpose particle det...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.