A Hidden Markov Model for Indoor Trajectory Tracking of Elderly People

Abstract

Tracking of elderly people is indispensable to assist them as fast as possible. In this paper, we propose a new trajectory tracking technique to localize elderly people in real time in indoor environments. A mobility model is constructed, based on the hidden Markov models, to estimate the trajectory followed by each person. However, mobility models can not be used as standalone tracking techniques due to accumulation of error with time. For that reason, the proposed mobility model is combined with measurements from the network. Here, we use the power of the WiFi signals received from surrounding Access Points installed in the building. The combination between the mobility model and the measurements result in tracking of elderly people. Real experiments are realized to evaluate the performance of the proposed approach.

An Adaptive User Tracking Algorithm Using Irregular Data Frames for Passive Fingerprint Positioning

“…The authors of [ 5 , 6 ] applied HMM to solve the tracking problem and achieved almost 90% accuracy when comparing the proximity results to the ground truth labeled for each site. They determined the probability parameters of HMM based on the fingerprint saved in the radio map.…”

Application of optimization algorithm for virtual reference tag assisted localization and tracking of RFID

“…In the indoor tracking setting, shifting entities are tracked using the Hidden Markov Model (HMM) technique 17 . For monitoring shifting targets, it makes use of the gadget's free tracking concept.…”

“…16 In the indoor tracking setting, shifting entities are tracked using the Hidden Markov Model (HMM) technique. 17 For monitoring shifting targets, it makes use of the gadget's free tracking concept. A tracking technique relying on the linear correlation of tilt and variance of transmitted signal intensity is presented by 18 to track the indoor shifting entities.…”

The Supportive Smart Home System: Implications and Solutions for Service Providers

“…Research has also considered cloud processing in such systems that could provide support back to the individual or supply their family and caregivers with information related to well-being, thus providing more advanced functions and services to support aging-in-place [14], [16], [26]- [28]. Many research projects have explored such possibilities where some projects focused on (1) daily cognitive evaluations through homebased sensing [6], [11], [15], [29], (2) detection of overnight wandering in Dementia patients using a multi-sensor system [8]- [10], (3) the challenges accompanied by cloud processing and data analytics in smart home systems [16], [26], [27], (4) the security and reliability aspects of smart home systems [14], (5) real-time location tracking in indoor environments using Wi-Fi and a wearable sensor [30], (6) monitoring of user activity and rate of activity using RF-ID technology [31], (7) deployment of in-home robots to provide human-level social engagement and support for elderly with dementia [28], and (8) determining electrodermal activity as means for emotion-sensing using a wearable Printed Circuit Board (PCB) [32].…”