A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> Abstract For the improvement of reliability, safety and efficiency advanced methods of supervision, fault-detection and fault diagnosis become increasingly important for many technical processes. This holds especially for safety related processes like aircraft, trains, automobiles, power plants and chemical plants. The classical approaches are limit or trend checking of some measurable output variables. Because they do not give a deeper insight and usually do not allow a fault diagnosis, model-based methods of fault-detection were developed by using input and output signals and applying dynamic process models. These methods are based, e.g., on parameter estimation, parity equations or state observers. Also signal model approaches were developed. The goal is to generate several symptoms indicating the difference between nominal and faulty status. Based on different symptoms fault diagnosis procedures follow, determining the fault by applying classification or inference methods. This contribution gives a short introduction into the field and shows some applications for an actuator, a passenger car and a combustion engine. <s> BIB001 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> RF-based localization systems have been deeply investigated due to their flexibility and limited costs. These systems, when designed to support the independent life, are generally mission critical and they should be designed to be dependable. In this paper, we present a method to provide human localization systems with concurrent fault detection. We focus on two possible sources of faults: natural hardware (e.g., empty battery, faulty components) and human-made (e.g., device not worn). The adopted strategy relies on two independent measurement systems and on a fault detection apparatus. We present an implemented case-study, were the collected data are temporally annotated, processed, compared and, in case of anomalies, the system activates a notification, eventually to trigger an intervention. <s> BIB002 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> Thanks to the large diffusion of small wearable devices there are several systems designed for indoor localization. Among the proposed solutions, RF-based systems have been deeply investigated due to their flexibility and limited costs. When these systems are employed as assistive tools, they should be dependable, recognizing autonomously when they are affected by a fault. In this paper, we present a method to provide multiuser localization with concurrent fault detection. We focus on two possible sources of faults: natural hardware (e.g., empty battery, faulty components) and human-made (e.g., device not worn). The presented methodology relies on two independent measurement systems and on a model based fault detection apparatus, checking for discrepancies in the behavior of the subsystems. This method is implemented to provide dependable localization in fragile people (such as elderly or people with small impairments) dwellings. We present examples of simulations in a large environment, and an implemented case-study. The collected data confirm the validity of the approach. <s> BIB003 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> Life expectancy has continuously increased in most countries over the last decades and will probably continue to increase in the future. This leads to new challenges relative to the autonomy and the independence of elderly. The development of Smart Homes is a direction to face these challenges and to enable people to live longer in a safe and comfortable environment. Making a home smart consists in placing sensors, actuators and a controller in the house in order to take into account the behavior of their inhabitants and to act on their environment to improve their safety, health and comfort. Most of these approaches are based on the real-time indoor Location Tracking of the inhabitants. In this thesis, a whole new approach for model-based Location Tracking of an a priori unknown number of inhabitants is proposed. This approach is based on Discrete Event Systems paradigms, theory and tools. The usage of Finite Automata (FA) to model the detectable motion of the inhabitants as well as different methods to create such FA models have been developed. Based on these models, algorithms to perform efficient Location Tracking are defined. Finally, several approaches aiming at evaluating the relevance of the instrumentation of a Smart Home with the objective of Location Tracking are proposed. The approach has also been fully implemented and tested. Throughout the thesis, the different contributions are illustrated on case studies. <s> BIB004 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> Abstract In this paper, a passive method for robust fault detection and isolation is elaborated in the context of set-membership approach. The basic idea behind the proposed method is to compute a feasible set containing the states of a nonlinear system states using an interval constraints propagation method. A consistency test is performed using the q-relaxed intersection technique which consists in tolerating a given number q of outliers from m measurements. The robust feasible set, compatible with m-q observations, is then obtained and faulty sets are used for the isolation procedure. An application, within the framework of robot/human localization, is given to verify the efficiency of the method. <s> BIB005 </s> A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living <s> Model-Based Fault Detection <s> In this paper, we propose a discrete event system approach for location tracking of a single indoor inhabitant in Smart Home. We first construct the discrete event system model for the dynamics of the inhabitant and define the motions from one zone to another zone in the house as the events of the model. The model size is then linear with the number of the zone which is an advantage compared with the previous work. We adopt the state tree in Graph Theory to describe the observations of these events. Each branch from the root node to the terminal node represents an observable event or the occurrence of a disturbance. We then use the state estimation knowledge of discrete event systems to construct an observer to implement location tracking. Our results are optimal. Finally, we propose an reset procedure to deal with transient sensor faults. <s> BIB006
The following researchers have used model-based fault detection based on localization systems. An indoor human localization (IHL) system with fault detection focusing on hardware as well as human-made single faults was presented by Veronese et al. BIB002 . The IHL system consists of three main components; an RF-based localization subsystem, an off-the-shelf modular wireless home automation subsystem and a fault detection subsystem. The types of sensors chosen for home automation were contact sensors and passive infrared (PIR) sensors. A model-based fault detection approach was applied based on the concept proposed by Isermann BIB001 which states that a fault can be detected using the dependencies between different measured signals. The activation of the home automation sensors and its features were used to estimate the resident's location. Also, the position of the resident is estimated independently with the localization subsystem. The fault detection subsystem compares the two estimated location areas, and flag a fault whenever there is no intersection between the two areas. Experimental work was done, where 19 fixed LAURA anchors and 7 Z-wave devices were fixed across the rooms of the university building. Two fault scenarios were considered; forgotten worn device and blinded PIR motion detector. The results showed that the faults could be detected using the proposed approach. As a continuation of the work, multi-user simulation was conducted using three virtual users trajectories, the faults could be detected in the presence of multiple users with specificity and sensitivity above 90% BIB003 . Danancher proposed model-based location tracking of single as well as multiple inhabitants in smart homes BIB004 . He treated the location tracking of inhabitants as a problem of discrete event system modeling. Finite automata was used to model the observable motion of inhabitant, where each state represents a zone in the apartment, each event represents the rising or falling edge of binary sensor, and each transition is the observable location change. A case study was presented for an apartment equipped with motion detectors and door barrier sensors. The impact of sensor faults on the performance of location tracking was discussed. The applicability of three model-based fault detection and isolation (FDI) approaches; diagnoser, template and residual approaches, were investigated for fault-tolerant location tracking. An adaptation to the residual-based approach was applied to a case study of tracking a single inhabitant. Three fault scenarios were considered; spurious activation of a motion sensor, failure of power supply of door barrier sensor and a failure of motion detector sensor. The approach could not detect nor isolate faulty sensors in the proposed faulty scenarios. The author concluded that the industrial FDI approaches are not suitable for sensor faults in smart home and that a new FDI approach designed specifically for smart homes should be developed. Another discrete event system approach for location tracking was proposed by Wu et al. BIB006 . The motion of the resident is modeled using an automaton model and the observations of motion events from sensor signals are described using the state tree of Graph theory. An Observer is then used to estimate the location of the inhabitant. Dealing with transient sensor faults is performed by adding a reset procedure to the state tree and the observer so that they return to the initial state whenever blocking occurs due to missing or disordering of a sensor event. This ensures that the location tracking returns to output correct estimation results after deviating due to the transient sensor fault. However, false location estimation still occurs. A scenario of the motion of inhabitant in the presence of a missing sensor event was presented. Amri et al. have proposed fault detection approach for indoor localization based on set-membership fault detection using the q-relaxed intersection method BIB005 . The random walk model is used as the mobility model of the resident. The PIR sensor activation leads to the activation of a box representing its coverage area. At one second time step, the measurement boxes are observed and the predicted boxes are deduced using the mobility model. The q-intersection method deduces the location zone of the resident using these boxes. Outlier detection takes place by comparing the solution set obtained and the measurements. Experiments were conducted in a living lab equipped with PIR sensors.