A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Fault-Tolerant Location Tracking <s> In the context of a constantly increasing aging population with cognitive deficiencies, insuring the autonomy of the elders at home becomes a priority. The DOMUS laboratory is addressing this issue by conceiving a smart home which can both assist people and preserve their quality of life. Obviously, the ability to monitor properly the occupant's activities and thus provide the pertinent assistance depends highly on location information inside the smart home. This paper proposes a solution to localize the occupant thanks to Bayesian filtering and a set of anonymous sensors disseminated throughout the house. The localization system is designed for a single person inside the house. It could however be used in conjunction with other localization systems in case more people are present. Our solution is functional in real conditions. We conceived an experiment to estimate precisely its accuracy and evaluate its robustness. The experiment consists of a scenario of daily routine meant to maximize the occupant's motion in meaningful activities. It was performed by 14 subjects, one subject at a time. The results are satisfactory: the system's accuracy exceeds 85% and is independent of the occupant's profile. The system works in real time and behaves well in presence of noise. <s> BIB001 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Fault-Tolerant Location Tracking <s> In this paper, we present a novel probabilistic technique, based on the Bayes filter, able to estimate the user location, even with unreliable sensor data coming only from fixed sensors in the monitored environment. Our approach has been extensively tested in a home-like environment, as well as in a real home, and achieves very good results. We present results on two datasets, representative of real life conditions, collected during the testing phase. We detect the patient location with subroom accuracy, an improvement over the state of the art for localization using only environmental sensors. The main drawback is that it is only suitable for applications where a single person is present in the environment, like as with other approaches that do not use any mobile device. For this reason, we introduced the “telehomecare” term, therefore differentiating from generic telemedicine applications, where many people can be in the same environment at the same time. <s> BIB002 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Fault-Tolerant Location Tracking <s> User location is crucial context information for future smart homes where many location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently make conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses the design of such a ULD system for context-aware services in future smart homes stressing the following challenges: (i) users’ privacy; (ii) device-/tag-free; and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies, such as the Internet of Things, embedded systems, intelligent devices and machine-to-machine communication, are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors for the home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of inexpensive sensors, as well as a context broker with a fuzzy-based decision-maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation. <s> BIB003
A fault-tolerant location tracking system was presented by Rahal, Pigot and Mabilleau, which aims to localize single inhabitant using the already installed sensors in smart home BIB001 . The authors aimed to provide a reliable location tracking system that can estimate the location of inhabitant accurately despite the false trigger of sensors that may occur due to various factors. The adopted approach is based on sensor fusion, in which particle filters approach is used to estimate the new inhabitant's location using the last known position and the last sensor event. To evaluate the system, experiments were conducted in the DOMUS apartment, where non-intrusive unobtrusive sensors (infrared (IR) presence sensors, tactile carpets, smart light switches, contact sensors and pressure detectors) are installed. A daily routine scenario was performed by 14 subjects, one subject each time, and the results showed an accuracy in location tracking above 85%. The system performance was also investigated with respect to the inhabitant's profile, sensor configuration, inhabitant's dynamics and in the presence of noise. The results showed that the accuracy of the system is profile-independent. The accuracy of localization when using only infrared sensors is similar to using all the sensors. However, the IR sensors are more prone to false triggers, thus, the authors recommended the usage of at least one other type with IR sensors. The system accuracy remained at 84% when 2.5% and 5% noise were applied to the collected data. A similar system was proposed by Ballardini et al. that is based on estimating the resident location in the presence of false positive or false negative sensor readings via Bayes filtering BIB002 . The system uses a probabilistic model of the sensors and a motion model of the inhabitant. The proposed approach was tested on two noisy datasets that use PIR sensors (observed frequent false triggering of a motion sensor when no person is moving, and trigger of atrium's motion sensor when motion occurs in the dining room), producing 5% and 9% error rates in localization. A fuzzy set-based approach for localization tolerating sensor failures was proposed by Ahvar et al. BIB003 . The approach relies on using several functionally redundant sensors at specific nodes. The system is composed of sensor nodes and context broker based on the fuzzy set theory. The apartment is divided into zones and equipped with various types of ambient sensors. The sensors send context information, then the membership values for each zone is computed. The highest value indicates the user location. A case study was presented and simulated using the DPWsim simulator with different sensor error rates. However, the system was not verified using a real dataset.