Discussion on Challenges and Issues in Multi sensor Fusion Approach for Fall Detection

This article discusses about the few challenges and problem of the Multi sensor Fusion which are occur in the fall detection. This article is also discussing the solution of the problems while introduce the challenges of the multi sensor fusion and the various approaches are also describes in this article which is the good way to fall detection. In the aging society the situation of the emergency is linked with serious concerns of the falls. According to the ICT the recent development is also included for proposing the significant numbers of the solutions which is used for tracking the movement of the body as well as for detecting the falls by utilizing the different technologies of the sensors.

In this manner the fall detection is facilitating for the prevention of the few cases. For the method of the fall detection the various number of reviews is using for the technologies which have in the literature of the research article and research paper. This article is also discusses about the general approach by considering the combination of the information which are used for assessing the falls in the source of the several sensors. The fall detection of the data can be reducing by applying the various approaches which are discuss in this article.

The major objective of this research paper is evaluating the details of the techniques of the fall detection according to its subfield which is openly considered as the uses of the fusion of the multi sensor which is based upon the methods for determining the falls to assessing it. The crucial differences of the multi fusion one and approach of the single sensor is also highlighted in this paper. The classification which is used in the various system is also discussed is also describes in this articles which can provides the huge information for solving the challenges related to the approach of the multisession (Gregory Koshmak, 2016).

Reference of Challenges and Issues in Multi sensor Fusion Approach for Fall Detection