Optimal Sensor Deployment According to a New Approach for Target Tracking in Smart Homes

• Published in: Ingénierie et recherche biomédicale Vol. 41; no. 6; pp. 321 - 330
• Main Authors: Gholizadeh-Tayyar, S., Bachouch, R.B., Fousseret, Y., Parmantier, Y., Ramdani, N.
• Format: Journal Article
• Language: English
• Published: Elsevier Masson SAS 01.12.2020; Elsevier Masson
• Subjects: Computer Science; Robotics
• ISSN: 1959-0318
• DOI: 10.1016/j.irbm.2020.06.009

•A new model that optimizes the sensor deployment using a target tracking approach.•Deployment of sensors according to the layout of the Region of Interest.•Satisfaction of a reliability level in the sensor network.•A user interface to monitor the location, energy consumption and well-being of people in AALs. Ambient Assisted Living (AAL) aims to ease the activities of daily lives for elderly or disabled people living in smart homes. In these systems, the assisting services are provided by use of the sensors that detect the location of inhabitants. Even though the cost and performance efficiencies of sensor networks depend directly on the number of the deployed sensors as well as the approaches that are employed to track the location of inhabitants, these factors are separately considered in research studies. In this paper, we propose an approach to track a target in smart homes. We present a new Integer Linear Programming (ILP) model that i. optimizes the number of the deployed sensors according to our proposed target tracking approach, ii. determines the placement of sensors in the network while considering the layout of the Region of Interest (RoI), iii. proposes appropriate settings for the sensors' field of view and their orientation, and, iv. deploys sensors according to the satisfaction of a reliability level in the network. In order to validate the proposed model and show its applicability, we use two sets of data, including real data gathered from a living lab and randomly generated data, as well as a test scenario. We also present a user interface that employs the concepts, which are presented in this research. The interface helps to easily monitor the location, energy consumption and well-being factors of a target in an AAL environment.