Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents

Download

index.pdf

Date

2014-06-01

Author

Tunca, Can
Alemdar, Hande
Ertan, Halil
Incel, Ozlem Durmaz
Ersoy, Cem

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

231
views

115
downloads

Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

Subject Keywords

Electrical and Electronic Engineering, Analytical Chemistry, Atomic and Molecular Physics, and Optics, Biochemistry

URI

https://hdl.handle.net/11511/40862

Journal

SENSORS

DOI

https://doi.org/10.3390/s140609692

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Performance evaluation of similarity measures for dense multimodal stereovision Yaman, Mustafa; Kalkan, Sinan (SPIE-Intl Soc Optical Eng, 2016-05-01) Multimodal imaging systems have recently been drawing attention in fields such as medical imaging, remote sensing, and video surveillance systems. In such systems, estimating depth has become possible due to the promising progress of multimodal matching techniques. We perform a systematic performance evaluation of similarity measures frequently used in the literature for dense multimodal stereovision. The evaluated measures include mutual information (MI), sum of squared distances, normalized cross-correlat...
Collaborative mobile target imaging in ultra-wideband wireless radar sensor networks Arık, Muharrem; Akan, Özgür Barış; Department of Electrical and Electronics Engineering (2008) Wireless sensor networks (WSN) have thus far been used for detection and tracking of static and mobile targets for surveillance and security applications. However, detection and tracking do not suffice for a complete satisfaction of these applications and an accurate target classification. To address this need, among various target classification methods, imaging of target yields the most valuable information. Nevertheless, imaging of mobile targets moving over an area requires networked and collaborative d...
Multilevel Object Tracking in Wireless Multimedia Sensor Networks for Surveillance Applications Using Graph-Based Big Data Kucukkececi, Cihan; Yazıcı, Adnan (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01) Wireless Multimedia Sensor Networks (WMSN), for object tracking, have been used as an emerging technology in different application areas, such as health care, surveillance, and traffic control. In surveillance applications, sensor nodes produce data almost in real-time while tracking the objects in a critical area or monitoring border activities. The generated data is generally treated as big data and stored in NoSQL databases. In this paper, we present a new object tracking approach for surveillance applic...
Fault-tolerant topology control in heterogeneous wireless sensor networks Bağcı, Hakkı; Yazıcı, Adnan; Körpeoğlu, İbrahim; Department of Computer Engineering (2013) Wireless sensor networks have come into prominence for monitoring and tracking operations in many application areas including environmental monitoring, battlefield surveillance, healthcare solutions, vehicle traffic monitoring, smart home systems and many other industrial applications. A long network life time and fault-tolerant operation are two essential requirements for wireless sensor network applications. In order to satisfy these requirements, heterogeneous architectures can be employed in wireless se...
Electromagnetic Target Classification using time frequency analysis and neural networks Sayan, Gönül; Leblebicioğlu, Mehmet Kemal (Wiley, 1999-04-01) This paper demonstrates the feasibility and advantages of using a self-organizing map (SOM)-type neural network classifier for electromagnetic target recognition. The classifier is supported by a novel feature extraction unit in which the Wigner distribution (WD), a time-frequency representation, is utilized for the extraction of natural-resonance-related energy feature vectors from scattered fields. The proposed target classification technique is tested for a set of canonical targets, displaying an excelle...

Citation Formats

C. Tunca, H. Alemdar, H. Ertan, O. D. Incel, and C. Ersoy, “Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents,” SENSORS, pp. 9692–9719, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40862.